diff --git a/.veda/ui b/.veda/ui index 0470861d4..b174470f0 160000 --- a/.veda/ui +++ b/.veda/ui @@ -1 +1 @@ -Subproject commit 0470861d42ba8d75ff274a678258ccc215642215 +Subproject commit b174470f068e445e5e7d15604e1ae3a27e1ced64 diff --git a/overrides/home/arrow-link.tsx b/common/arrow-link.tsx similarity index 90% rename from overrides/home/arrow-link.tsx rename to common/arrow-link.tsx index d082b289c..13ad04ad5 100644 --- a/overrides/home/arrow-link.tsx +++ b/common/arrow-link.tsx @@ -2,7 +2,7 @@ import React from "$veda-ui/react"; import styled from "$veda-ui/styled-components"; import { glsp, themeVal } from "$veda-ui/@devseed-ui/theme-provider"; import { CollecticonArrowRight } from "$veda-ui/@devseed-ui/collecticons"; -import { AccessibilityLink } from "../common/styles"; +import { AccessibilityLink } from "../overrides/common/styles"; const ArrowLinkCmp = styled(AccessibilityLink)` display: flex; diff --git a/common/constants.js b/common/constants.js new file mode 100644 index 000000000..d7a72b00f --- /dev/null +++ b/common/constants.js @@ -0,0 +1,290 @@ +import featureEmissions from "./media/refinery.png"; +import featureSources from "./media/swamp.png"; +import featureMethane from "./media/plume.png"; + + + +import { DATASETS_PATH } from "$veda-ui-scripts/utils/routes"; +import { Actions } from "$veda-ui-scripts/components/common/browse-controls/use-browse-controls"; + + +export const focusAreaDatasets = [ + { + "title": "Gridded Anthropogenic Greenhouse Gas Emissions", + "desc": "Emission estimates from human activities including the energy, agriculture, waste, and industry sectors.", + "img": { + "src": featureEmissions, + "alt": "image of oil refinery." + }, + "link": { + "url": `${DATASETS_PATH}?${Actions.TAXONOMY}=${encodeURIComponent(JSON.stringify({ Topics: "anthropogenic-emissions" }))}`, + "text": "View more" + }, + "footer": { + "links": [{ + "title": "Check out relevant datasets", + "url": `${DATASETS_PATH}?${Actions.TAXONOMY}=${encodeURIComponent(JSON.stringify({ Topics: "anthropogenic-emissions" }))}` + }] + } + }, + { + "title": "Natural Greenhouse Gas Sources and Sinks", + "desc": "Naturally-occurring greenhouse gas fluxes from land, ocean, and atmosphere.", + "img": { + "src": featureSources, + "alt": "image of green wetlands." + }, + "link": { + "url": `${DATASETS_PATH}?${Actions.TAXONOMY}=${encodeURIComponent(JSON.stringify({ Topics: "natural-emissions-and-sinks" }))}`, + "text": "View more" + }, + "footer": { + "links": [{ + "title": "Check out relevant datasets", + "url": `${DATASETS_PATH}?${Actions.TAXONOMY}=${encodeURIComponent(JSON.stringify({ Topics: "natural-emissions-and-sinks" }))}` + }] + } + }, + { + "title": "New Observations for Tracking Large Emission Events", + "desc": "Identify and quantify large methane leak events leveraging aircraft and space-based data.", + "img": { + "src": featureMethane, + "alt": "image of colorful polygon against satellite view of landscape surface." + }, + "link": { + "url": `${DATASETS_PATH}?${Actions.TAXONOMY}=${encodeURIComponent(JSON.stringify({ Topics: "large-emission-events" }))}`, + "text": "View more" + }, + "footer": { + "links": [{ + "title": "Check out relevant datasets", + "url": `${DATASETS_PATH}?${Actions.TAXONOMY}=${encodeURIComponent(JSON.stringify({ Topics: "large-emission-events" }))}` + }] + } + } +]; + +// Make sure these are in the same order +const focusAreaStoriesLinks = [ + "/stories/us-methane-sources", "/stories/tracking-greenhouse-gas-cycles", "/stories/discovering-large-methane-emissions" +] + +export const focusAreasStories = focusAreaDatasets.map((area, index) => { + const { footer, ...areaSansFooter } = area; + return { + ...areaSansFooter, + link: { + ...areaSansFooter.link, + url: focusAreaStoriesLinks[index], + } + } +}); + + +export const dataEngagements = [ + { + "title": "Data Catalog", + "desc": "Detailed dataset information for insight into greenhouse gas sources, sinks, emissions, and large events.", + "img": { + "src": new URL('./media/data_catalog.png', import.meta.url).href, + "alt": "image of oil refinery" + }, + "link": { + "url": "/data-catalog", + "text": "View more" + }, + "footer": null + }, + { + "title": "Interactive Map", + "desc": "The exploration and analysis environment can be used to visually examine data on a customizable map and create a time series of basic statistics.", + "img": { + "src": new URL('./media/interactive_map.png', import.meta.url).href, + "alt": "image of green wetlands" + }, + "link": { + "url": "/exploration", + "text": "View more" + }, + "footer": null + }, + { + "title": "JupyterHub", + "desc": "With JupyterHub, users can analyze cloud archives of Earth science data using an interactive environment. Log in or request access here.", + "img": { + "src": new URL('./media/jupyter_hub.png', import.meta.url).href, + "alt": "image of colorful polygon against satellite landscape surface in brown" + }, + "link": { + "url": "https://hub.ghg.center", + "text": "View more" + }, + "footer": null + } +]; + +export const customInterfaces = [ + { + "title": "EMIT Methane Plume Viewer", + "desc": "Detailed information for methane plumes identified using EMIT.", + "img": { + "src": new URL('./media/emit.jpg', import.meta.url).href, + "alt": "view of colored shape overlaid on satellite landscape image with boxes of information containing plume details" + }, + "link": { + "url": "/data-catalog/emit-ch4plume-v1", + "text": "See more" + }, + "footer": null + }, + { + "title": "NOAA Concentration Viewer", + "desc": "Measurements of carbon dioxide and methane concentrations from ground stations throughout the US and worldwide.", + "img": { + "src": new URL('./media/co2.jpg', import.meta.url).href, + "alt": "map showing Mauna Loa location of station with a time series of data below the map" + }, + "link": { + "url": "/data-catalog/noaa-gggrn-co2-concentrations", + "text": "See more" + }, + "footer": { + "links": [ + { + "title": "Carbon Dioxide", + "url": "/data-catalog/noaa-gggrn-co2-concentrations" + }, + { + "title": "Methane", + "url": "/data-catalog/noaa-gggrn-ch4-concentrations" + } + ] + } + }, + { + "title": "NIST Tower Data Viewer", + "desc": "Measurements of carbon dioxide and methane concentrations from urban tower instruments.", + "img": { + "src": new URL('./media/nist-co2-nwb.jpg', import.meta.url).href, + "alt": "map showing Northwest Baltimore, MD location of station with a time series of data below the map" + }, + "link": { + "url": "/data-catalog/noaa-gggrn-ch4-concentrations", + "text": "See more" + }, + "footer": { + "links": [ + { + "title": "Indianapolis Flux Experiment (INFLUX)", + "url": "/data-catalog/influx-testbed-ghg-concentrations" + }, + { + "title": "Los Angeles Megacity Carbon Project", + "url": "/data-catalog/lam-testbed-ghg-concentrations" + }, + { + "title": "Northeast Corridor (NEC) Urban Test Bed", + "url": "/data-catalog/nec-testbed-ghg-concentrations" + } + ] + } + }, +] + +export const cities = [ + { + "title": "Baltimore, A Nexus for Government and Academic Emissions Research", + "desc": "Scientists from U.S. government agencies and regional universities have come together for cooperative research projects, helping to expand environmental monitoring capabilities and improve resident wellbeing across the Baltimore metropolitan region in line with the city’s ambitious climate action plans.", + "img": { + "src": new URL('../stories/media/baltimore_banner.png', import.meta.url).href, + "alt": "Baltimore" + }, + "link": { + "url": "/stories/baltimore", + "text": "See More" + }, + "footer": null + }, + { + "title": "New York City Researchers Take to the Street to Investigate Emissions", + "desc": "Researchers are working with the New York State Energy Research & Development Authority to improve emissions estimates by combining measurements from a network of sensors across NYC with data collected by satellites and aircraft, to pinpoint unidentified or incorrectly cataloged sources of GHGs and study interactions with other air pollutants.", + "img": { + "src": new URL('../stories/media/newyork_banner.png', import.meta.url).href, + "alt": "New York" + }, + "link": { + "url": "/stories/newyork", + "text": "See More" + }, + "footer": null + }, + { + "title": "Scientists Use Low-Cost Sensor Network to Track San Francisco Area Emissions", + "desc": "Cities have implemented a variety of measures to meet greenhouse gas emissions goals, including expanding renewable energy use and incentivizing residents to drive electric cars. But a challenge for city leaders is measuring if policies are working. One solution is a network of low-cost sensors, scientists say.", + "img": { + "src": new URL('../stories/media/sanfran_banner.png', import.meta.url).href, + "alt": "San Francisco" + }, + "link": { + "url": "/stories/sanfrancisco", + "text": "See More" + }, + "footer": null + }, + { + "title": "Satellite Data to Help Measure Impact of Los Angeles Climate Solutions", + "desc": "From its vantage point on the International Space Station, NASA’s Orbiting Carbon Observatory-3 provides measurements of carbon dioxide concentrations over many of the world’s cities. Scientists are using the data to examine the impact of efforts to reduce emissions in Los Angeles.", + "img": { + "src": new URL('../stories/media/losangeles_banner.png', import.meta.url).href, + "alt": "Los Angeles" + }, + "link": { + "url": "/stories/losangeles", + "text": "See More" + }, + "footer": null + } +]; + +export const keyUrbanDatasets = [ + { + "title": "Carbon Dioxide Emissions Estimates Available at Neighborhood Scale", + "desc": "Carbon dioxide emissions data are now available at a granular level, from city blocks to entire counties across the contiguous U.S. The latest dataset from the Vulcan Project, called Vulcan 4.0, helps researchers to analyze annual CO₂ emissions at fine scales and helps urban decision-makers to develop localized carbon management strategies.", + "img": { + "src": new URL('../stories/media/urban-1.jpeg', import.meta.url).href, + "alt": "magnifying glass with CO₂ written in text with background of smoke coming out of factories." + }, + "link": { + "url": "/stories/vulcan", + "text": "View more" + }, + "footer": null + }, + { + "title": "Nationwide Dataset Connects Greenhouse Gases and Air Quality", + "desc": "The GReenhouse gas And Air Pollutants Emissions System (GRA²PES), from NOAA and NIST, combines information on greenhouse gas and air quality pollutant sources into a single national database, offering innovative geospatial detail and new benefits for both climate and public health solutions.", + "img": { + "src": new URL('../stories/media/gra2pes.png', import.meta.url).href, + "alt": "Comparison of CO₂ and NOₓ emission from GRA2PES dataset" + }, + "link": { + "url": "/stories/gra2pes", + "text": "View more" + }, + "footer": null + }, + { + "title": "Innovative Urban Testbeds to Advance Emissions Estimates", + "desc": "NIST’s Urban GHG Measurements Testbed System uses ground-based observing networks in Los Angeles, Indianapolis, and the Baltimore/Washington, D.C. region, together with aircraft and satellite data, to diagnose accuracy of local emissions estimates and advance transformative monitoring and measurement methods for the future.", + "img": { + "src": new URL('../stories/media/US_INC_banner.jpg', import.meta.url).href, + "alt": "image from INFLUX project" + }, + "link": { + "url": "/stories/urban-testbed", + "text": "View more" + }, + "footer": null + } +]; diff --git a/common/keypoints.tsx b/common/keypoints.tsx new file mode 100644 index 000000000..f618187c4 --- /dev/null +++ b/common/keypoints.tsx @@ -0,0 +1,90 @@ +import React from "$veda-ui/react"; +import SmartLink from '$veda-ui-scripts/components/common/smart-link'; + +import { + Card, + CardHeader, + CardBody, + CardFooter, + CardMedia, + CardGroup, +} from '$veda-ui/@trussworks/react-uswds'; + +import { + CollecticonArrowRight +} from '$veda-ui/@devseed-ui/collecticons'; + +import "./styles.scss" + + +type Data = { + title: string; + desc: string; + img: { + src: string; + alt: string; + }; + link: { + url: string; + text: string; + }; + footer: { + links: [{ + title: string; + url: string; + }]; + } | null; +}; + +interface KeypointsProps { + data: Data[], + cardType?: string, + overlay?: boolean, +} + +export default function Keypoints({ + data, + cardType = "classic", + overlay = false, +}: KeypointsProps) { + return ( + + + {data.map(datum => ( + + + {datum.img.alt} + +
+
+ +

{datum.title}

+ + +

{datum.desc}

+ + + { + datum.footer?.links?.[0] && datum.footer?.links?.map(link => ( + + {link.title} + + )) + } + +
+
+ {!datum.footer?.links && } + + + ))} + + ); +} diff --git a/common/media/co2.jpg b/common/media/co2.jpg new file mode 100644 index 000000000..9a6f2a2a3 Binary files /dev/null and b/common/media/co2.jpg differ diff --git a/common/media/data_catalog.png b/common/media/data_catalog.png new file mode 100644 index 000000000..75febe57d Binary files /dev/null and b/common/media/data_catalog.png differ diff --git a/common/media/emit.jpg b/common/media/emit.jpg new file mode 100644 index 000000000..634cb361b Binary files /dev/null and b/common/media/emit.jpg differ diff --git a/common/media/interactive_map.png b/common/media/interactive_map.png new file mode 100644 index 000000000..be6be2f86 Binary files /dev/null and b/common/media/interactive_map.png differ diff --git a/common/media/jupyter_hub.png b/common/media/jupyter_hub.png new file mode 100644 index 000000000..f405cf25f Binary files /dev/null and b/common/media/jupyter_hub.png differ diff --git a/common/media/nist-co2-nwb.jpg b/common/media/nist-co2-nwb.jpg new file mode 100644 index 000000000..156f7078c Binary files /dev/null and b/common/media/nist-co2-nwb.jpg differ diff --git a/common/media/plume.png b/common/media/plume.png new file mode 100644 index 000000000..49c969523 Binary files /dev/null and b/common/media/plume.png differ diff --git a/common/media/refinery.png b/common/media/refinery.png new file mode 100644 index 000000000..b6803bbf4 Binary files /dev/null and b/common/media/refinery.png differ diff --git a/common/media/swamp.png b/common/media/swamp.png new file mode 100644 index 000000000..f141a2173 Binary files /dev/null and b/common/media/swamp.png differ diff --git a/common/styled-components.tsx b/common/styled-components.tsx new file mode 100644 index 000000000..71bd1b7c2 --- /dev/null +++ b/common/styled-components.tsx @@ -0,0 +1,20 @@ +import styled from "$veda-ui/styled-components"; + + +const Title = styled.h2` + margin: 48px 0 24px 0; + font-size: calc(2rem + var(--base-text-increment,0rem)); + &:before { + content: ''; + display: block; + width: 2rem; + height: 0.25rem; + border-radius: 0.25rem; + background: #082a64; + margin-bottom: 0.75rem; + } +` + +export { + Title, +} diff --git a/common/styles.scss b/common/styles.scss new file mode 100644 index 000000000..0bfba9e5b --- /dev/null +++ b/common/styles.scss @@ -0,0 +1,39 @@ +.blocklink { + &:focus { outline: none; } + &:focus-visible { outline: 1px solid var(--veda-color-link);} + @supports not selector(:focus-visible) { + &:focus { + outline: 1px solid var(--veda-color-link); + } + } +} + +.hug-reset-container { + grid-column: 1 / -1; +} + +.card-shadow__hover { + box-shadow: 0 0 2px 0 rgba(44,62,80,0.08),0 6px 6px 0 rgba(44,62,80,0.08); + transition: all 0.24s ease-in-out 0s; + &:hover { + transform: translate(0, 0.125rem); + } +} + +.card-image__blend { + mix-blend-mode: multiply; +} + +.veda-color--link { + color: var(--veda-color-link); +} +.veda-color--base { + color: var(--veda-color-base); +} + +// font-size: 20px (1.25rem) will be deprecated with USWDS design system +// but we need a temporary style class for the consistency across the pages + +.font-size-md-deprecated { + font-size: calc(1rem + var(--base-text-increment, 0rem)); +} diff --git a/custom-pages/common/styles.ts b/custom-pages/common/styles.ts new file mode 100644 index 000000000..ef21b6dd2 --- /dev/null +++ b/custom-pages/common/styles.ts @@ -0,0 +1,30 @@ +import { NavLink } from "$veda-ui/react-router-dom"; +import styled, { css } from "$veda-ui/styled-components"; + +const MouseEventStyle = css` + &:hover { + cursor: pointer; + } + &:focus { + outline: 3px solid #1565EF; + } + &:active { + color: black; + } +` + +export const AccessibilityLink = styled(NavLink)` + text-decoration: underline; + ${MouseEventStyle} +`; + +export const AccessibilityMenuItem = styled(NavLink)` + text-decoration: none; + ${MouseEventStyle} + &:hover { + text-decoration: underline; + } + &:active { + text-decoration: underline; + } +`; diff --git a/custom-pages/data-toolkit/component.tsx b/custom-pages/data-toolkit/component.tsx new file mode 100644 index 000000000..592f37ffb --- /dev/null +++ b/custom-pages/data-toolkit/component.tsx @@ -0,0 +1,81 @@ +import React from "$veda-ui/react"; +import { Link } from "$veda-ui/react-router-dom"; +import '$veda-ui/@trussworks/react-uswds/lib/index.css' + +import { + Grid, + GridContainer, +} from '$veda-ui/@trussworks/react-uswds'; + +import { + CollecticonTextBlock, + CollecticonEnvelope, + CollecticonSpeechBalloon, +} from '$veda-ui/@devseed-ui/collecticons'; + +import Keypoints from "../../common/keypoints"; +import { dataEngagements, focusAreaDatasets, customInterfaces } from "../../common/constants"; + +import { SUBSCRIPTION_URL } from "../../constants"; +import { Title } from "../../common/styled-components"; + +import '../../common/styles.scss'; + + +export default function Component() { + return ( +
+ +
+ Engage with Data +

+ Access the catalog of datasets, visualize the data on a map, and conduct analysis with JupyterHub. +

+ +
+
+ Featured Data Tools +

+ View and explore greenhouse gas emissions data with customized data visualization tools. +

+ +
+
+ Core Science Focus Areas +

+ The U.S. Greenhouse Gas Center is organized around three core focus areas. Sign up to join a focus area group. +

+ +
+ + + Learn More and Share Your Ideas + + + + + + For the latest updates and information about the US GHG Center or to join a focus area group, subscribe to our email updates list. + + + + + + + + Read more about the US GHG Center news, trainings, and workshop opportunities on the News and Events page. + + + + + + + + Do you have a US GHG Center portal suggestion or question? Reach the team using the "Contact Us" button at the top or bottom of every page. + + + + +
+ ) +}; diff --git a/custom-pages/data-toolkit/index.mdx b/custom-pages/data-toolkit/index.mdx new file mode 100644 index 000000000..b1579aed2 --- /dev/null +++ b/custom-pages/data-toolkit/index.mdx @@ -0,0 +1,11 @@ +--- +mainNavItem: + navTitle: Data Toolkit +title: Accessing and Exploring Data +description: " + Everything needed to better understand and use the U.S. Greenhouse Gas Center datasets, including data descriptions, data visualization and open source tools for those interested in utilizing the data for research. +" +--- +import Cmp from './component.tsx'; + + diff --git a/custom-pages/learn/AnchorScroll.tsx b/custom-pages/news-and-events/AnchorScroll.tsx similarity index 100% rename from custom-pages/learn/AnchorScroll.tsx rename to custom-pages/news-and-events/AnchorScroll.tsx diff --git a/custom-pages/learn/AnchorSrollMenu.tsx b/custom-pages/news-and-events/AnchorSrollMenu.tsx similarity index 100% rename from custom-pages/learn/AnchorSrollMenu.tsx rename to custom-pages/news-and-events/AnchorSrollMenu.tsx diff --git a/custom-pages/learn/component.tsx b/custom-pages/news-and-events/component.tsx similarity index 100% rename from custom-pages/learn/component.tsx rename to custom-pages/news-and-events/component.tsx diff --git a/custom-pages/learn/how-to-edit-content-on-learn-page.md b/custom-pages/news-and-events/how-to-edit-content-on-learn-page.md similarity index 91% rename from custom-pages/learn/how-to-edit-content-on-learn-page.md rename to custom-pages/news-and-events/how-to-edit-content-on-learn-page.md index 3d94f6fc4..903919418 100644 --- a/custom-pages/learn/how-to-edit-content-on-learn-page.md +++ b/custom-pages/news-and-events/how-to-edit-content-on-learn-page.md @@ -2,7 +2,7 @@ ### News Item -1. Open 'learn-page-content.js' file in the same directory. +1. Open 'news-page-content.js' file in the same directory. 2. Add an item to 'NEWS_ITEMS' by copying already existing items in the array. 3. Place necessary images in `./media/news` folder. (Let's say this image has a file name 'image-name.png') 4. Edit the field as needed. Please follow the pattern like below. @@ -23,7 +23,7 @@ ### Event Item -1. Open 'learn-page-content.js' file in the same directory. +1. Open 'news-page-content.js' file in the same directory. 2. Add an item to 'EVENT_ITEMS' by copying already existing items in the array. 3. Place necessary images in `./media/events` folder. (Let's say this image has a file name 'image-name.png') 4. Edit the field as needed. Please follow the pattern like below. Note that startDate and endDate should follow 'yyyy-mm-dd' format. If it is a oneday event, put the same date for both. diff --git a/custom-pages/learn/index.mdx b/custom-pages/news-and-events/index.mdx similarity index 95% rename from custom-pages/learn/index.mdx rename to custom-pages/news-and-events/index.mdx index e5316b90f..85478c7aa 100644 --- a/custom-pages/learn/index.mdx +++ b/custom-pages/news-and-events/index.mdx @@ -1,14 +1,14 @@ --- mainNavItem: - navTitle: Learn -title: Learn + navTitle: News & Events +title: News & Events description: " US GHG Center News, Events, and Training Opportunities. " --- import { EventsComponent } from './component' -import { NEWS_ITEMS, EVENT_ITEMS, NEWSLETTER_ITEMS, TUTORIAL_ITEMS } from './learn-page-content' +import { NEWS_ITEMS, EVENT_ITEMS, NEWSLETTER_ITEMS, TUTORIAL_ITEMS } from './news-page-content' import AnchorScroll from './AnchorScroll' import { SUBSCRIPTION_URL } from "../../constants"; @@ -57,12 +57,12 @@ Lorem ipsum dolor sit amet, consectetur adipiscing elit. Quisque vel nunc mauris - +{/* ## Tutorial Videos - + */} {/* @@ -97,7 +97,7 @@ Lorem ipsum dolor sit amet, consectetur adipiscing elit. Quisque vel nunc mauris Investigate US GHG Center demonstrations and presentations and explore opportunities to get involved. **Presentations** - - [Stakeholder Meeting Nov. 28](https://www.youtube.com/playlist?list=PLiuUQ9asub3RDzYAZ3N7_6wIIgmvDpZq_) + - [Stakeholder Meeting Nov. 28, 2023](https://www.youtube.com/playlist?list=PLiuUQ9asub3RDzYAZ3N7_6wIIgmvDpZq_) - [Part 1](https://www.youtube.com/watch?v=MPWow413i-o&list=PLiuUQ9asub3RDzYAZ3N7_6wIIgmvDpZq_&index=1&pp=iAQB) (Introductions and Science) - [Part 2](https://www.youtube.com/watch?v=CrnBY4iYVeA&list=PLiuUQ9asub3RDzYAZ3N7_6wIIgmvDpZq_&index=2&t=136s&pp=iAQB) (Website overview; Focus area details; National Strategy) - [COP28 State Department Announcement](https://www.youtube.com/watch?v=cw8ku_qfAao) diff --git a/custom-pages/learn/media/events/AMS24_Logo.png b/custom-pages/news-and-events/media/events/AMS24_Logo.png similarity index 100% rename from custom-pages/learn/media/events/AMS24_Logo.png rename to 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b/custom-pages/news-and-events/media/events/GHGC_Stakeholder_Forum_Announcement_Image.png similarity index 100% rename from custom-pages/learn/media/events/GHGC_Stakeholder_Forum_Announcement_Image.png rename to custom-pages/news-and-events/media/events/GHGC_Stakeholder_Forum_Announcement_Image.png diff --git a/custom-pages/learn/media/events/cms.png b/custom-pages/news-and-events/media/events/cms.png similarity index 100% rename from custom-pages/learn/media/events/cms.png rename to custom-pages/news-and-events/media/events/cms.png diff --git a/custom-pages/learn/media/events/stakeholder-forum.png b/custom-pages/news-and-events/media/events/stakeholder-forum.png similarity index 100% rename from custom-pages/learn/media/events/stakeholder-forum.png rename to custom-pages/news-and-events/media/events/stakeholder-forum.png diff --git a/custom-pages/learn/media/events/summer-school.png b/custom-pages/news-and-events/media/events/summer-school.png similarity index 100% rename from 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100% rename from custom-pages/learn/media/tutorials/tutorial_intro_video.png rename to custom-pages/news-and-events/media/tutorials/tutorial_intro_video.png diff --git a/custom-pages/learn/learn-page-content.js b/custom-pages/news-and-events/news-page-content.js similarity index 98% rename from custom-pages/learn/learn-page-content.js rename to custom-pages/news-and-events/news-page-content.js index 37952e6de..7dee964dc 100644 --- a/custom-pages/learn/learn-page-content.js +++ b/custom-pages/news-and-events/news-page-content.js @@ -61,7 +61,7 @@ export const NEWS_ITEMS = [ src: new URL('./media/news/nspires.jpg', import.meta.url).href, alt: 'NASA ROSES A.58' }, - description: 'Minority Serving Institutions (MSIs) are invited to propose for a ground-based GHG remote sensing instrument (EM27/Sun) to measure CO2 and CH4. NASA will provide one instrument and up to five years of funding for installation and operation. Read more at NASA NSPIRES A.58 ROSES call.' + description: 'Minority Serving Institutions (MSIs) are invited to propose for a ground-based GHG remote sensing instrument (EM27/Sun) to measure CO₂ and CH₄. NASA will provide one instrument and up to five years of funding for installation and operation. Read more at NASA NSPIRES A.58 ROSES call.' }, { name: 'US GHG Center announced at COP28', diff --git a/custom-pages/topics/component.tsx b/custom-pages/topics/component.tsx new file mode 100644 index 000000000..7bc7b948a --- /dev/null +++ b/custom-pages/topics/component.tsx @@ -0,0 +1,89 @@ +import React from "$veda-ui/react"; +import { Link } from '$veda-ui/react-router-dom'; +import { + Card, + CardHeader, + CardBody, + CardMedia, + CardGroup, + Grid, + GridContainer, +} from '$veda-ui/@trussworks/react-uswds'; + +import { + CollecticonTextBlock, + CollecticonEnvelope, + CollecticonSpeechBalloon, +} from '$veda-ui/@devseed-ui/collecticons'; + +import { focusAreasStories } from "../../common/constants"; +import { Title } from "../../common/styled-components"; + +import Keypoints from "../../common/keypoints"; + +import { SUBSCRIPTION_URL } from "../../constants"; + +import '../../common/styles.scss'; +import './topics.scss'; + +export default function HomeComponent() { + return ( +
+ + Content Collections by Topic + + + + distant view of hazy cityscape. + + + +

Urban Emissions

+ + +

+ Cities and metropolitan regions, where most of the world's population live, are responsible for approximately 70% of greenhouse gas emissions. Researchers are making rapid advances in urban emissions measurement and modeling to provide robust, accurate, and reliable emissions estimates at fine scales. The U.S. Greenhouse Gas Center offers an introduction to new urban-relevant datasets and highlights innovative emissions research in cities across the country. +

+ + + + + +
+ Core Science Focus Areas +

The US GHG Center targets three greenhouse gas areas of study, as shown below. For the latest, subscribe to our email newsletter.

+ +
+ + + Learn More and Share Your Ideas + + + + + + For the latest updates and information about the US GHG Center or to join a focus area group, subscribe to our email updates list. + + + + + + + + Read more about the US GHG Center news, trainings, and workshop opportunities on the News and Events page. + + + + + + + + Do you have a US GHG Center portal suggestion or question? Reach the team using the "Contact Us" button at the top or bottom of every page. + + + + + +
+ ); +} diff --git a/custom-pages/topics/index.mdx b/custom-pages/topics/index.mdx new file mode 100644 index 000000000..8dda90bfd --- /dev/null +++ b/custom-pages/topics/index.mdx @@ -0,0 +1,11 @@ +--- +mainNavItem: + navTitle: Topics +title: Topics +description: " + Explore thematic content collections and core science focus areas. +" +--- +import Cmp from './component'; + + diff --git a/custom-pages/topics/media/1-maia-los-angeles-1041.png b/custom-pages/topics/media/1-maia-los-angeles-1041.png new file mode 100644 index 000000000..09a48197e Binary files /dev/null and b/custom-pages/topics/media/1-maia-los-angeles-1041.png differ diff --git a/custom-pages/topics/topics.scss b/custom-pages/topics/topics.scss new file mode 100644 index 000000000..207564191 --- /dev/null +++ b/custom-pages/topics/topics.scss @@ -0,0 +1,13 @@ +// Overriding card flag style to have wider image +.usa-card--flag .usa-card__media { + @media (width >= 70em) { + width: 35rem; + margin: auto; + } +} + +.usa-card--flag .usa-card__header, .usa-card--flag .usa-card__body, .usa-card--flag .usa-card__footer { + @media (width >= 70em) { + margin-left: 35rem; + } +} diff --git a/datasets/eccodarwin-co2flux-monthgrid-v5.data.mdx b/datasets/eccodarwin-co2flux-monthgrid-v5.data.mdx index a2812f27b..87a4b99fc 100644 --- a/datasets/eccodarwin-co2flux-monthgrid-v5.data.mdx +++ b/datasets/eccodarwin-co2flux-monthgrid-v5.data.mdx @@ -16,7 +16,7 @@ usage: label: Browse and download the data title: Data Browser media: - src: ::file ./eccodarwin--dataset-cover.jpg + src: ::file ./media/eccodarwin--dataset-cover.jpg alt: Static rendering of oceanic currents with arrow indicators for cycle direction and strength author: name: NASA's Science Visualization Studio (SVS) @@ -93,7 +93,7 @@ layers: temporalResolution: Monthly unit: mmol m²/s media: - src: ::file ./eccodarwin-co2flux-monthgrid-v5.thumbnail.co2.png + src: ::file ./media/eccodarwin-co2flux-monthgrid-v5.thumbnail.co2.png alt: Rendered Air-Sea CO₂ Flux --- @@ -108,7 +108,7 @@ layers: **Data Type:** Research
**Data Latency:** Updated annually
- Due to its immense size, the ocean’s carbon reservoir is roughly 20 times larger than the combined atmosphere and land reservoirs. The eventual fate of our atmospheric carbon emissions will be primarily in the oceans, as the ocean has absorbed roughly 40% of fossil fuel carbon dioxide (CO₂) since the beginning of the industrial era. How do we understand the details of how the ocean takes up carbon? It isn't easy — the ocean is vast, deep, and continually in motion. Even with ocean-observing satellites that orbit Earth 24/7, data from below the ocean surface is sparse. Data-driven estimates of how much carbon dioxide the ocean is absorbing (the so-called “ocean carbon sink”) have improved substantially in recent years. However, computational ocean models that include biogeochemistry continue to play a critical role as they allow us to fill critical gaps in data and understand the individual processes that control ocean carbon storage. The ideal scenario is a combination of the above two methods, where data are ingested and then used to improve a model's fit to the observed ocean, also known as “data assimilation”. While the physical oceanographic community has made great progress in developing data assimilation systems, for example, the Estimating the Circulation and Climate of the Ocean (ECCO) consortium, the biogeochemical community has generally lagged behind. The ECCO-Darwin model represents an important technological step forward as it is the first global ocean biogeochemistry model that (1) ingests both physical and biogeochemical observations into the model in a realistic manner and (2) considers how the nature of the ocean carbon sink has changed over multiple decades. As the ECCO ocean circulation estimates become more accurate and lengthen in time, ECCO-Darwin will become an ever more accurate and useful tool for climate-related ocean carbon cycle and mitigation studies. This dataset contains global monthly averages of CO2 flux between the ocean and the air from version 5 of the ECCO-Darwin model. The data are available at ~1/3° horizontal resolution at the equator (~18 km at high latitudes) from January 2020 through December 2022. + Due to its immense size, the ocean’s carbon reservoir is roughly 20 times larger than the combined atmosphere and land reservoirs. The eventual fate of our atmospheric carbon emissions will be primarily in the oceans, as the ocean has absorbed roughly 40% of fossil fuel carbon dioxide (CO₂) since the beginning of the industrial era. How do we understand the details of how the ocean takes up carbon? It isn't easy — the ocean is vast, deep, and continually in motion. Even with ocean-observing satellites that orbit Earth 24/7, data from below the ocean surface is sparse. Data-driven estimates of how much carbon dioxide the ocean is absorbing (the so-called “ocean carbon sink”) have improved substantially in recent years. However, computational ocean models that include biogeochemistry continue to play a critical role as they allow us to fill critical gaps in data and understand the individual processes that control ocean carbon storage. The ideal scenario is a combination of the above two methods, where data are ingested and then used to improve a model's fit to the observed ocean, also known as “data assimilation”. While the physical oceanographic community has made great progress in developing data assimilation systems, for example, the Estimating the Circulation and Climate of the Ocean (ECCO) consortium, the biogeochemical community has generally lagged behind. The ECCO-Darwin model represents an important technological step forward as it is the first global ocean biogeochemistry model that (1) ingests both physical and biogeochemical observations into the model in a realistic manner and (2) considers how the nature of the ocean carbon sink has changed over multiple decades. As the ECCO ocean circulation estimates become more accurate and lengthen in time, ECCO-Darwin will become an ever more accurate and useful tool for climate-related ocean carbon cycle and mitigation studies. This dataset contains global monthly averages of CO₂ flux between the ocean and the air from version 5 of the ECCO-Darwin model. The data are available at ~1/3° horizontal resolution at the equator (~18 km at high latitudes) from January 2020 through December 2022. @@ -129,7 +129,7 @@ layers: The data assimilation techniques used for the physical and biogeochemical components of the ECCO-Darwin model are both linearized least squares minimization approaches. For ocean physics, ocean-ice state estimates from the ECCO LLC270 model were fit to observations including sea level anomalies, ocean bottom pressure anomalies, sea surface temperature, sea ice concentration, and ocean temperature and salinity profiles using an adjoint method. For ocean biogeochemistry, the MIT Darwin Project ecosystem model used a low-dimensional Green’s function optimization to adjust initial conditions and biogeochemical parameters. Using the paired ocean physics and biogeochemistry, air-sea CO₂ flux was calculated using the [Wanninkhof (1992)](https://doi.org/10.1029/92JC00188) parameterization for determining gas exchange across the air-sea interface. ## Key Publications - Carroll, D., Menemenlis, D., Adkins, J. F., Bowman, K. W., Brix, H., Dutkiewicz, S., Fenty, I., Gierach, M. M., Hill, C., Jahn, O., Landschützer, P., Lauderdale, J. M., Liu, J., Manizza, M., Naviaux, J. D., Rödenbeck, C., Schimel, D. S., Van der Stocken, T., & Zhang, H. (2020). The ECCO-Darwin Data-Assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multidecadal Surface Ocean pCO2 and Air-Sea CO2 Flux. *Journal of Advances in Modeling Earth Systems, 12*(10), e2019MS001888. [https://doi.org/10.1029/2019MS001888](https://doi.org/10.1029/2019MS001888) + Carroll, D., Menemenlis, D., Adkins, J. F., Bowman, K. W., Brix, H., Dutkiewicz, S., Fenty, I., Gierach, M. M., Hill, C., Jahn, O., Landschützer, P., Lauderdale, J. M., Liu, J., Manizza, M., Naviaux, J. D., Rödenbeck, C., Schimel, D. S., Van der Stocken, T., & Zhang, H. (2020). The ECCO-Darwin Data-Assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multidecadal Surface Ocean pCO₂ and Air-Sea CO₂ Flux. *Journal of Advances in Modeling Earth Systems, 12*(10), e2019MS001888. [https://doi.org/10.1029/2019MS001888](https://doi.org/10.1029/2019MS001888) ## Other Relevant Publications Brix, H., Menemenlis, D., Hill, C., Dutkiewicz, S., Jahn, O., Wang, D., & Zhang, H. (2015). Using Green's functions to initialize and adjust a global, eddying ocean biogeochemistry general circulation model. *Ocean Modelling, 95*, 114. [https://doi.org/10.1016/j.ocemod.2015.07.008](https://doi.org/10.1016/j.ocemod.2015.07.008) @@ -141,7 +141,7 @@ layers: Carroll, D., Menemenlis, D., Dutkiewicz, S., Lauderdale, J. M., Adkins, J. F., Bowman, K. W., et al. (2022). Attribution of space-time variability in global-ocean dissolved inorganic carbon. *Global Biogeochemical Cycles, 36*, e2021GB007162. https://doi.org/10.1029/2021GB007162 ## Learn More - - See a video animation of ECCO-Darwin CO2 flux data in the [Tracking Greenhouse Gas Cycles Data Insight](https://earth.gov/ghgcenter/stories/tracking-greenhouse-gas-cycles) + - See a video animation of ECCO-Darwin CO₂ flux data in the Tracking Greenhouse Gas Cycles Data Insight - Check out the [ECCO-Darwin Story Map](https://www.ecco-group.org/storymaps.htm?id=45) ## Acknowledgment diff --git a/datasets/emit-ch4plume-v1.data.mdx b/datasets/emit-ch4plume-v1.data.mdx index 9a8179888..eceb369de 100644 --- a/datasets/emit-ch4plume-v1.data.mdx +++ b/datasets/emit-ch4plume-v1.data.mdx @@ -16,7 +16,7 @@ usage: label: Download data from NASA Distributed Active Archive Center title: Data Browser media: - src: ::file ./emit-plume--cover.jpg + src: ::file ./media/emit-plume--cover.jpg alt: emission from industry author: name: Chris Leboutillier @@ -154,7 +154,7 @@ layers: ## Learn More - EMIT data are available through the NASA LP DAAC and [additional information is available](https://lpdaac.usgs.gov/data/get-started-data/collection-overview/missions/emit-overview/#emit-metadata) - The Jet Propulsion Lab (JPL) contains [VISIONS - The EMIT open data portal](https://earth.jpl.nasa.gov/emit/data/data-portal/coverage-and-forecasts/) - - See how EMIT contributes to new technologies to detect and quantify large methane release events in the [Discovering Large Methane Emission Events with Remote Measurement Data Insight](https://earth.gov/ghgcenter/stories/discovering-large-methane-emissions) + - See how EMIT contributes to new technologies to detect and quantify large methane release events in the Discovering Large Methane Emission Events with Remote Measurement Data Insight ## Acknowledgment We would like to acknowledge the contributions of the entire EMIT engineering and science teams and the ISS team for enabling the EMIT mission. We thank NASA’s Earth Science Division with special thanks to Dr. Jack Kaye for continued support of the greenhouse gas application. diff --git a/datasets/epa-ch4emission-yeargrid-v2express.data.mdx b/datasets/epa-ch4emission-yeargrid-v2express.data.mdx index d4539c5a4..9414a7276 100644 --- a/datasets/epa-ch4emission-yeargrid-v2express.data.mdx +++ b/datasets/epa-ch4emission-yeargrid-v2express.data.mdx @@ -16,7 +16,7 @@ usage: label: Browse and download the data title: Data Browser media: - src: ::file ./epa-annual--cover.jpg + src: ::file ./media/epa-annual--cover.jpg alt: Total Gridded Methane Emissions from the U.S. Inventory of Greenhouse Gas Emissions and Sinks author: name: EPA @@ -117,7 +117,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.total.methane.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.total.methane.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Total Methane (annual) - id: total-agriculture stacCol: epa-ch4emission-yeargrid-v2express @@ -192,7 +192,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.total.agriculture.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.total.agriculture.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Total Agriculture (annual) - id: enteric-fermentation stacCol: epa-ch4emission-yeargrid-v2express @@ -267,7 +267,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.enteric.fermentation.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.enteric.fermentation.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Agriculture - Enteric Fermentation (annual) - id: manure-management stacCol: epa-ch4emission-yeargrid-v2express @@ -342,7 +342,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.agriculture.manure.management.anual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.agriculture.manure.management.anual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Agriculture - Manure Management (annual) - id: rice-cultivation-l stacCol: epa-ch4emission-yeargrid-v2express @@ -417,7 +417,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.agriculture.rice.cultivation.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.agriculture.rice.cultivation.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Agriculture - Rice Cultivation (annual) - id: field-burning-l stacCol: epa-ch4emission-yeargrid-v2express @@ -492,7 +492,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.agriculture.field.burning.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.agriculture.field.burning.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Agriculture - Field Burning (annual) - id: total-natural-gas stacCol: epa-ch4emission-yeargrid-v2express @@ -567,7 +567,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.total.natural.gas.systems.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.total.natural.gas.systems.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Total Natural Gas Systems (annual) - id: exploration-ngs-l stacCol: epa-ch4emission-yeargrid-v2express @@ -642,7 +642,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.exploration.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.exploration.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Natural Gas - Exploration (annual) - id: production-ngs-l stacCol: epa-ch4emission-yeargrid-v2express @@ -717,7 +717,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.production.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.production.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Natural Gas - Production (annual) - id: 1B2b-transmission-storage-ngs stacCol: epa-ch4emission-yeargrid-v2express @@ -792,7 +792,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.transmission.and.storage.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.transmission.and.storage.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Natural Gas - Transmission and Storage (annual) - id: 1B2b-processing-ngs stacCol: epa-ch4emission-yeargrid-v2express @@ -867,7 +867,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.processing.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.processing.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Natural Gas - Processing (annual) - id: 1B2b-distribution-ngs stacCol: epa-ch4emission-yeargrid-v2express @@ -942,7 +942,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.distribution.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.distribution.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Natural Gas - Distribution (annual) - id: post-meter-ng stacCol: epa-ch4emission-yeargrid-v2express @@ -1017,7 +1017,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.post-meter.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.natural.gas.post-meter.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Natural Gas - Post-Meter (annual) - id: total-petroleum stacCol: epa-ch4emission-yeargrid-v2express @@ -1092,7 +1092,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.total.petroleum.systems.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.total.petroleum.systems.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Total Petroleum Systems (annual) - id: 1B2a-exploration-ps stacCol: epa-ch4emission-yeargrid-v2express @@ -1167,7 +1167,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.petroleum.exploration.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.petroleum.exploration.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Petroleum - Exploration (annual) - id: 1B2a-production-ps stacCol: epa-ch4emission-yeargrid-v2express @@ -1242,7 +1242,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.petroleum.production.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.petroleum.production.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Petroleum - Production (annual) - id: 1B2a-transport-ps stacCol: epa-ch4emission-yeargrid-v2express @@ -1317,7 +1317,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.petroleum.transportation.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.petroleum.transportation.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Petroleum - Transportation (annual) - id: 1B2a-refining-ps stacCol: epa-ch4emission-yeargrid-v2express @@ -1392,7 +1392,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.petroleum.refining.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.petroleum.refining.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Petroleum - Refining (annual) - id: total-waste stacCol: epa-ch4emission-yeargrid-v2express @@ -1467,7 +1467,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.total.waste.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.total.waste.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Total Waste (annual) - id: 5A1-msw-landfill-waste stacCol: epa-ch4emission-yeargrid-v2express @@ -1542,7 +1542,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.waste.municipal.landfills.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.waste.municipal.landfills.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Waste - Municipal Solid Waste (MSW) Landfills (annual) - id: 5A1-industrial-landfill-waste stacCol: epa-ch4emission-yeargrid-v2express @@ -1617,7 +1617,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.waste.industrial.landfills.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.waste.industrial.landfills.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Waste - Industrial Landfills (annual) - id: 5A1-dwtd-waste stacCol: epa-ch4emission-yeargrid-v2express @@ -1692,7 +1692,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.waste.domestic.wastewater.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.waste.domestic.wastewater.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Waste - Domestic Wastewater Treatment & Discharge (annual) - id: 5A1-iwtd-waste stacCol: epa-ch4emission-yeargrid-v2express @@ -1767,7 +1767,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.waste.industrial.wastewater.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.waste.industrial.wastewater.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Waste - Industrial Wastewater Treatment & Discharge (annual) - id: 5A1-composting-waste stacCol: epa-ch4emission-yeargrid-v2express @@ -1842,7 +1842,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.composting.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.composting.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Waste - Composting (annual) - id: total-coal-mines stacCol: epa-ch4emission-yeargrid-v2express @@ -1917,7 +1917,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.total.coal.mines.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.total.coal.mines.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Total Coal Mines (annual) - id: 1B1a-underground-coal stacCol: epa-ch4emission-yeargrid-v2express @@ -1992,7 +1992,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.coal.mining.underground.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.coal.mining.underground.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Coal Mining - Underground Mining (annual) - id: 1B1a-abn-underground-coal stacCol: epa-ch4emission-yeargrid-v2express @@ -2067,7 +2067,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.coal.mining.abandoned.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.coal.mining.abandoned.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Coal Mining - Abandoned Underground Mines (annual) - id: 1B1a-surface-coal stacCol: epa-ch4emission-yeargrid-v2express @@ -2142,7 +2142,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.coal.mining.surface.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.coal.mining.surface.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Coal Mining - Surface Mining (annual) - id: total-other stacCol: epa-ch4emission-yeargrid-v2express @@ -2217,7 +2217,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.total.other.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.total.other.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Total Other (annual) - id: 1A-stationary-combustion-other stacCol: epa-ch4emission-yeargrid-v2express @@ -2292,7 +2292,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.other.stationary.combustion.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.other.stationary.combustion.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Other - Stationary combustion (annual) - id: 1A-mobile-combustion-othe stacCol: epa-ch4emission-yeargrid-v2express @@ -2367,7 +2367,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.other.mobile.combustion.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.other.mobile.combustion.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Other - Mobile combustion (annual) - id: 1A-abn-ong-other stacCol: epa-ch4emission-yeargrid-v2express @@ -2442,7 +2442,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.other.abandoned.oil.gas.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.other.abandoned.oil.gas.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Other - Abandoned Oil and Gas Wells (annual) - id: 1A-petro-production-other stacCol: epa-ch4emission-yeargrid-v2express @@ -2517,7 +2517,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.other.petrochemical.production.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.other.petrochemical.production.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Other - Petrochemical Production (annual) - id: 1A-ferroalloy-production-other stacCol: epa-ch4emission-yeargrid-v2express @@ -2590,7 +2590,7 @@ layers: - "#721E17" - "#521A13" media: - src: ::file ./epa-ch4emission-yeargrid-v2express.thumbnails.other.ferroalloy.production.annual.png + src: ::file ./media/epa-ch4emission-yeargrid-v2express.thumbnails.other.ferroalloy.production.annual.png alt: U.S. Gridded Anthropogenic Methane Emissions Inventory - Other - Ferroalloy Production (annual) --- @@ -2604,9 +2604,9 @@ layers: **Data type:** Research (v2 express extension)
**Data Latency:** N/A - The gridded EPA U.S. anthropogenic methane greenhouse gas inventory (gridded GHGI) includes spatially disaggregated (0.1 deg x 0.1 deg or approximately 10 x 10 km resolution) maps of annual anthropogenic methane emissions for the contiguous United States (CONUS), consistent with national annual U.S. anthropogenic methane emissions reported in the U.S. EPA [Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks) (U.S. GHGI). This dataset contains methane emissions provided as fluxes, in units of molecules of methane per square cm per second, for over 25 individual emission source categories, including those from agriculture, petroleum and natural gas systems, coal mining, and waste. The data have been converted from their original NetCDF format to Cloud-Optimized GeoTIFF (COG) and scaled to Megagrams of CH4 per km2 per year (Mg/km²/yr) for use in the US GHG Center, thereby enabling user exploration of spatial anthropogenic methane emissions and their trends. + The gridded EPA U.S. anthropogenic methane greenhouse gas inventory (gridded GHGI) includes spatially disaggregated (0.1 deg x 0.1 deg or approximately 10 x 10 km resolution) maps of annual anthropogenic methane emissions for the contiguous United States (CONUS), consistent with national annual U.S. anthropogenic methane emissions reported in the U.S. EPA [Inventory of U.S. Greenhouse Gas Emissions and Sinks](https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks) (U.S. GHGI). This dataset contains methane emissions provided as fluxes, in units of molecules of methane per square cm per second, for over 25 individual emission source categories, including those from agriculture, petroleum and natural gas systems, coal mining, and waste. The data have been converted from their original NetCDF format to Cloud-Optimized GeoTIFF (COG) and scaled to Megagrams of CH₄ per km² per year (Mg/km²/yr) for use in the US GHG Center, thereby enabling user exploration of spatial anthropogenic methane emissions and their trends. - The gridded dataset, as included in the U.S. GHG Center Exploration Environment, currently includes 34 data layers. The first data layer includes annual 2012-2020 gridded methane emissions fluxes from all anthropogenic sources of methane in the U.S. GHGI (excluding Land Use, Land-Use Change and Forestry (LULUCF) sources, which are not included in the gridded GHGI). The next six data layers include annual 2012-2020 gridded methane fluxes from sources within the aggregate Agriculture, Natural Gas, Petroleum, Waste, Industry, and ‘Other’ source categories. The remaining 27 data layers include annual 2012-2020 gridded methane emissions fluxes from individual emission sectors within each of the aggregate categories. For more information, see the ‘information’ icon on each data layer or refer to the data interpretation notes available under “Learn More” below. + The gridded dataset, as included in the U.S. GHG Center Exploration Environment, currently includes 34 data layers. The first data layer includes annual 2012-2020 gridded methane emissions fluxes from all anthropogenic sources of methane in the U.S. GHGI (excluding Land Use, Land-Use Change and Forestry (LULUCF) sources, which are not included in the gridded GHGI). The next six data layers include annual 2012-2020 gridded methane fluxes from sources within the aggregate Agriculture, Natural Gas, Petroleum, Waste, Industry, and ‘Other’ source categories. The remaining 27 data layers include annual 2012-2020 gridded methane emissions fluxes from individual emission sectors within each of the aggregate categories. For more information, see the ‘information’ icon on each data layer or refer to the data interpretation notes available under “Learn More” below. ## Source Data Product Citation Gridded GHGI Version 2 & Express Extension **(this dataset in US GHG Center)**: diff --git a/datasets/gosat-based-ch4budget-yeargrid-v1.data.mdx b/datasets/gosat-based-ch4budget-yeargrid-v1.data.mdx index e654cf515..fda768b50 100644 --- a/datasets/gosat-based-ch4budget-yeargrid-v1.data.mdx +++ b/datasets/gosat-based-ch4budget-yeargrid-v1.data.mdx @@ -16,7 +16,7 @@ usage: label: Browse and download the data title: Data Browser media: - src: ::file ./oco2-mip-ch4budget-yeargrid-v1--cover.jpg + src: ::file ./media/oco2-mip-ch4budget-yeargrid-v1--cover.jpg alt: Dried/Burned trees author: name: Mark Landman @@ -97,7 +97,7 @@ layers: temporalResolution: Annual unit: Tg CH₄/yr media: - src: ::file ./gosat-based-ch4budget-yeargrid-v1.thumbnails.priori.total.png + src: ::file ./media/gosat-based-ch4budget-yeargrid-v1.thumbnails.priori.total.png alt: GOSAT-based Top-down Total and Natural Methane Emissions - Priori Total - id: post-total-id stacCol: gosat-based-ch4budget-yeargrid-v1 @@ -152,7 +152,7 @@ layers: temporalResolution: Annual unit: Tg CH₄/yr media: - src: ::file ./gosat-based-ch4budget-yeargrid-v1.thumbnails.posterior.total.png + src: ::file ./media/gosat-based-ch4budget-yeargrid-v1.thumbnails.posterior.total.png alt: GOSAT-based Top-down Total and Natural Methane Emissions - Posterior Total - id: prior-wetland-id stacCol: gosat-based-ch4budget-yeargrid-v1 @@ -207,7 +207,7 @@ layers: temporalResolution: Annual unit: Tg CH₄/yr media: - src: ::file ./gosat-based-ch4budget-yeargrid-v1.thumbnails.priori.wetlands.png + src: ::file ./media/gosat-based-ch4budget-yeargrid-v1.thumbnails.priori.wetlands.png alt: GOSAT-based Top-down Total and Natural Methane Emissions - Priori Wetlands - id: post-wetland-id stacCol: gosat-based-ch4budget-yeargrid-v1 @@ -262,7 +262,7 @@ layers: temporalResolution: Annual unit: Tg CH₄/yr media: - src: ::file ./gosat-based-ch4budget-yeargrid-v1.thumbnails.posterior.wetlands.png + src: ::file ./media/gosat-based-ch4budget-yeargrid-v1.thumbnails.posterior.wetlands.png alt: GOSAT-based Top-down Total and Natural Methane Emissions - Posterior Wetlands - id: prior-wetland-uncertainty-id stacCol: gosat-based-ch4budget-yeargrid-v1 @@ -317,7 +317,7 @@ layers: temporalResolution: Annual unit: Tg CH₄/yr media: - src: ::file ./gosat-based-ch4budget-yeargrid-v1.thumbnails.priori.wetlands.uncertainty.png + src: ::file ./media/gosat-based-ch4budget-yeargrid-v1.thumbnails.priori.wetlands.uncertainty.png alt: GOSAT-based Top-down Total and Natural Methane Emissions - Priori Wetlands Uncertainty - id: post-wetland-uncertainty-id stacCol: gosat-based-ch4budget-yeargrid-v1 @@ -372,7 +372,7 @@ layers: temporalResolution: Annual unit: Tg CH₄/yr media: - src: ::file ./gosat-based-ch4budget-yeargrid-v1.thumbnails.posterior.wetlands.uncertainty.png + src: ::file ./media/gosat-based-ch4budget-yeargrid-v1.thumbnails.posterior.wetlands.uncertainty.png alt: GOSAT-based Top-down Total and Natural Methane Emissions - Posterior Wetlands Uncertainty --- @@ -424,7 +424,7 @@ layers: ## Learn More - Learn more about this dataset on the [CEOS website](https://ceos.org/gst/methane.html) - - Learn more about how ground based measurements, satellite measurements and models are used to estimate methane emissions from human-caused and natural sources such as wetlands in the [Tracking Greenhouse Gas Cycles Data Insight](https://earth.gov/ghgcenter/stories/tracking-greenhouse-gas-cycles) + - Learn more about how ground based measurements, satellite measurements and models are used to estimate methane emissions from human-caused and natural sources such as wetlands in the Tracking Greenhouse Gas Cycles Data Insight ## Acknowledgment Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. This research was motivated by Committee on Earth Observation Satellites (CEOS) activities related to quantifying greenhouse gas emissions. This research was supported by funding from NASA's Carbon Monitoring System (CMS) and National Institute of Advanced Industrial Science and Technology (AIST) programs. Additional funding from the National Natural Science Foundation of China (NSFC) was also provided. diff --git a/datasets/gra2pes-co2-monthgrid-v1.data.mdx b/datasets/gra2pes-co2-monthgrid-v1.data.mdx new file mode 100644 index 000000000..374d110be --- /dev/null +++ b/datasets/gra2pes-co2-monthgrid-v1.data.mdx @@ -0,0 +1,448 @@ +--- +id: gra2pes-ghg-monthgrid-v1 +name: GRA²PES Greenhouse Gas and Air Quality Species +description: Monthly, 0.036 degree resolution emissions of carbon dioxide (CO₂), carbon monoxide (CO), nitrogen oxide (NOₓ), sulfur dioxide (SO₂), and particulate matter (PM2.5) emissions for the year 2021 over the Contiguous United States from the Greenhouse gas And Air Pollutants Emissions System (GRA²PES) +usage: + - url: "https://us-ghg-center.github.io/ghgc-docs/cog_transformation/gra2pes-ghg-monthgrid-v1.html" + label: Notebook showing data transformation to COG for ingest to the US GHG Center + title: 'Data Transformation Notebook' + - url: "https://us-ghg-center.github.io/ghgc-docs/datausage.html" + label: Notebooks to read, visualize, and explore data statistics + title: 'Data Usage Notebooks' + - url: "https://hub.ghg.center/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FUS-GHG-Center%2Fghgc-docs&urlpath=lab%2Ftree%2Fghgc-docs%2Fuser_data_notebooks%2Fgra2pes-ghg-monthgrid-v1_User_Notebook.ipynb&branch=main" + label: Run example notebook + title: Interactive Session in the US GHG Center JupyterHub (requires account) + - url: https://dljsq618eotzp.cloudfront.net/browseui/index.html#gra2pes-ghg-monthgrid-v1/ + label: Browse and download the data + title: Data Browser +media: + src: ::file ./media/gra2pes--dataset-cover.png + alt: Emissions from industrial area + author: + name: U.S. Greenhouse Gas Center + url: https://drive.google.com/file/d/1J3gDUaxWD4HiKAeoLEXGsK66CwL9jN8I/view?usp=share_link +taxonomy: + - name: Topics + values: + - Anthropogenic Emissions + - Urban + - name: Source + values: + - NIST + - NOAA + - name: Gas + values: + - CO₂ + - CO + - NOₓ + - SO₂ + - PM2.5 + - name: Product Type + values: + - Gridded Inventory +sourceExclusive: NIST +infoDescription: | + ::markdown + - Temporal Extent: January 2021 - December 2021 + - Temporal Resolution: Monthly + - Spatial Extent: Contiguous United States + - Spatial Resolution: 0.036 x 0.036 degrees + - Data Units: Metric tons per kilometer squared per month (tonne/km²/month) for carbon dioxide (ffCO₂), carbon monoxide (CO), nitrogen oxides (NOₓ), sulfur dioxide (SO₂), and particulate matter (PM2.5) + - Data Type: Research + - Data Latency: Updated ~annually +layers: + - id: co2 + stacCol: gra2pes-ghg-monthgrid-v1 + name: CO₂ Emissions + type: raster + description: Estimated monthly total CO₂ emissions across all sectors. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: co2 + colormap_name: spectral_r + rescale: + - 0 + - 100 + compare: + datasetId: gra2pes-ghg-monthgrid-v1 + layerId: nox + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/month + type: gradient + min: 0 + max: 100 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Monthly + unit: tonne CO₂/km²/month + media: + src: ::file ./media/gra2pes-ghg-monthgrid-v1.thumbnails.total.png + alt: Rendered CO₂ Emissions + - id: co + stacCol: gra2pes-ghg-monthgrid-v1 + name: CO Emissions + type: raster + description: Estimated monthly total carbon monoxide (CO) emissions across all sectors. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: co + colormap_name: spectral_r + rescale: + - 0 + - 2 + compare: + datasetId: gra2pes-ghg-monthgrid-v1 + layerId: co + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO/km²/month + type: gradient + min: 0 + max: 2 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Monthly + unit: tonne CO/km²/month + media: + src: ::file ./media/gra2pes-ghg-co-monthgrid-v1.thumbnails.total.png + alt: Rendered CO₂ Emissions + + - id: nox + stacCol: gra2pes-ghg-monthgrid-v1 + name: NOₓ Emissions + type: raster + description: Estimated monthly total nitrogen oxide (NOₓ) emissions across all sectors. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: nox + colormap_name: greens + rescale: + - 0 + - 2 + compare: + datasetId: gra2pes-ghg-monthgrid-v1 + layerId: nox + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne NOₓ/km²/month + type: gradient + min: 0 + max: 2 + stops: + - '#f7fcf5' + - '#c7e9c0' + - '#74c476' + - '#31a354' + - '#006d2c' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Monthly + unit: tonne NOₓ/km²/month + media: + src: ::file ./media/gra2pes-ghg-nox-monthgrid-v1.thumbnails.total.png + alt: Rendered CO₂ Emissions + + - id: so2 + stacCol: gra2pes-ghg-monthgrid-v1 + name: SO₂ Emissions + type: raster + description: Estimated monthly total sulfur dioxide (SO₂) emissions across all sectors. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: so2 + colormap_name: blues + rescale: + - 0 + - 0.5 + compare: + datasetId: gra2pes-ghg-monthgrid-v1 + layerId: so2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne SO₂/km²/month + type: gradient + min: 0 + max: 0.5 + stops: + - '#f7fbff' + - '#c6dbef' + - '#6baed6' + - '#3182bd' + - '#08519c' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Monthly + unit: tonne SO₂/km²/month + media: + src: ::file ./media/gra2pes-ghg-sox-monthgrid-v1.thumbnails.total.png + alt: Rendered CO₂ Emissions + + - id: pm25 + stacCol: gra2pes-ghg-monthgrid-v1 + name: Particulate Matter (PM2.5) + type: raster + description: Estimated monthly total emissions of fine particulate matter (PM2.5) across all sectors. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: pm25 + colormap_name: purples + rescale: + - 0 + - 0.2 + compare: + datasetId: gra2pes-ghg-monthgrid-v1 + layerId: pm25 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: PM2.5/km²/month + type: gradient + min: 0 + max: 0.2 + stops: + - '#fcfbfd' + - '#dadaeb' + - '#bcbddc' + - '#756bb1' + - '#54278f' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Monthly + unit: PM2.5/km²/month + media: + src: ::file ./media/gra2pes-ghg-pm25-monthgrid-v1.thumbnails.total.png + alt: Rendered CO₂ Emissions +--- + + + + **Temporal Extent:** January 2021 - December 2021
+ **Temporal Resolution:** Monthly
+ **Spatial Extent:** Contiguous United States
+ **Spatial Resolution:** 0.036 x 0.036 degrees
+ **Data Units:** Metric tons per kilometer squared per month (tonne/km²/month) for carbon dioxide (CO₂), carbon monoxide (CO), nitrogen oxides (NOₓ), sulfur dioxide (SO₂), and particulate matter (PM2.5)
+ **Data Type:** Research
+ **Data Latency:** Updated ~annually
+ + The Greenhouse gas And Air Pollutants Emissions System (GRA²PES) dataset at the GHG Center is an aggregated, regridded, monthly high-resolution (0.036 x 0.036°) data product with emissions of both greenhouse gases and air pollutants developed in a consistent framework. The dataset contains emissions over the contiguous United States covering major anthropogenic sectors, including energy, industrial fuel combustion and processes, commercial and residential combustion, oil and gas production, on-road and off-road transportation, etc. Carbon dioxide (CO₂) emissions are developed along with those of air pollutants including CO, NOₓ, SO₂, and PM2.5 with consistency in spatial and temporal distributions. Emissions by sectors are reported as column totals in units of metric tons per km² per month. Spatial-temporal surrogates are developed to distribute CO₂ emissions to grid cells to keep consistency between greenhouse gases and air quality species. The current version of GRA²PES is for 2021. Long-term emissions and more greenhouse gas species (e.g., methane) are under development and will be added in the future. + + GRA²PES is a collaborative research project, aiming to strengthen the community’s ability to consistently model and map greenhouse gas and air pollutant emissions and associated uncertainties across the contiguous United States. GRA²PES builds off of previously developed inventories such as the Fuel-based Oil and Gas (FOG) inventory (Gorchov Negron et al., 2018), and the Fuel-based Inventory of Vehicle Emissions (FIVE) (McDonald et al., 2014, McDonald et al., 2018a), the Volatile Chemical Products (VCPs) inventory (McDonald et al., 2018b). These inventories have been updated over time; VCPs in Coggon et al., 2021, FIVE in Harkins et al., 2021, FOG in Francoeur et al., 2021. A full anthropogenic air quality inventory, with near-real-time adjustments was also developed in He et al., 2024. These inventories that GRA²PES builds off of have been extensively evaluated in air quality modeling studies and compared to satellite, aircraft and ground observations in multiple years (McDonald et al., 2018a, Li et al., 2021, He et al., 2024, Zhu et al., 2024). + + + +
+ +
+ + + + ## Source Data Product Citation + The emissions data are deployed to the National Institute of Standards and Technology (NIST) data center with a DOI of https://doi.org/10.18434/mds2-3520. + + ## Version History + The current version is V1. + - August 2024, the first version of GRA²PES data with CO₂ and air pollutants is developed and deployed to the NIST data center. + + ## Dataset Accuracy + Quantifying emission uncertainties is difficult because of the complexity in data sources and emissions processing. Comprehensive evaluations are conducted to provide insights into the CO₂ emissions accuracy of GRA²PES. Through comparing GRA²PES with other commonly used climate inventories, ffCO₂ emissions agree within 1% of the ensembled average emission estimates at a national level. Higher discrepancies are found over state and urban levels. Model evaluation of the GRA²PES inventory suggests ~20% underestimation in ffCO₂ emissions against ¹⁴C-based ffCO₂ observations over Los Angeles, which is comparable to the uncertainties of other inventories. Details of emission evaluations of GRA²PES and associated uncertainties are discussed in Lyu et al. (to be submitted). + + ## Disclaimer + This dataset has been transformed from the original format (NetCDF) into Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) for display in the US GHG Center. Careful quality checks are used to ensure data transformation has been performed correctly. + + ## Scientific Details + The GHG Center provides a subset of the native GRA²PES data, which has been aggregated to monthly column totals and regridded. The native GRA²PES dataset has weekday-weekend and diurnal profiles applied by sources to allocate emissions from month to hour, at 4 km x 4 km spatial resolution. These data are reported in NetCDF format, with 20 vertical layers based on stack information where applicable, for 95 (excluding methane) species, and 18 sectors, as well as international emissions in the domain. Total emissions for all sectors combined are also provided. Please visit [NIST’s data center](https://doi.org/10.18434/mds2-3520) to access the native dataset and detailed documentation, including a listing of all 95 species, sectors and vertical layer descriptions. + + GRA²PES emissions are developed for both greenhouse gases and air pollutants under a consistent framework. For fuel combustion sources, fuel combustion and CO₂ emission factors at a state level are estimated, with facility-level information integrated. Emissions of electricity generation units are developed by matching point sources from different inventories. Air pollutant emissions derived from the national emissions inventory are used to develop spatial-temporal surrogates to distribute CO₂ emissions to 4 km x 4 km grid cells. A series of emission inventories that have been comprehensively evaluated based on field campaigns from oil and gas production, on-road vehicles, cooking and volatile chemical products are integrated into GRA²PES. + + **Table 1:** Species List (GHG Center data). For a full list of species included in the native dataset, please visit the [NIST data center](https://doi.org/10.18434/mds2-3520). + +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
SpeciesDescriptionUnit
CO₂Carbon Dioxidetonne CO₂/km²/month
COCarbon Monoxidetonne CO/km²/month
NOₓNitrogen Oxides (NOₓ)tonne NOₓ/km²/month
SO₂Sulfur Dioxide (SO₂)tonne SO₂/km²/month
PM2.5Total PM2.5 Emissionstonne PM2.5/km²/month
+
+
+ + ## Key Publications + Lyu, C., Harkins, C., Li, M., Mueller, K., McDonald, B. et al.: Developing the United States GReenhouse gas And Air Pollutants Emissions System (GRA²PES), *to be submitted*. + + Francoeur, C. B., McDonald, B. C., Gilman, J. B., Zarzana, K. J., Dix, B., Brown, S. S., de Gouw, J. A., Frost, G. J., Li, M., McKeen, S. A., Peischl, J., Pollack, I. B., Ryerson, T. B., Thompson, C., Warneke, C., & Trainer, M. (2021). Quantifying Methane and Ozone Precursor Emissions from Oil and Gas Production Regions across the Contiguous US. *Environmental Science & Technology, 55*(13), 9129-9139. [https://doi.org/10.1021/acs.est.0c07352](https://doi.org/10.1021/acs.est.0c07352) + + Gorchov Negron, A., McDonald, B. C., McKeen, S. A., Peischl, J., Ahmadov, R., de Gouw, J. A., Frost, G. J., Hastings, M. G., Pollack, I. B., Ryerson, T. B., Thompson, C., Warneke, C., & Trainer, M. (2018). Development of a fuel-based oil and gas inventory of nitrogen oxides emissions. *Environmental Science & Technology, 52*(17), 10175–10185. [https://doi.org/10.1021/acs.est.8b02245](https://doi.org/10.1021/acs.est.8b02245) + + McDonald, B. C., McKeen, S. A., Cui, Y. Y., Ahmadov, R., Kim, S.-W., Frost, G. J., Pollack, I. B., Peischl, J., Ryerson, T. B., Holloway, J. S., Graus, M., Warneke, C., Gilman, J. B., de Gouw, J. A., Kaiser, J., Keutsch, F. N., Hanisco, T. F., Wolfe, G. M., & Trainer, M. (2018a). Modeling Ozone in the Eastern U.S. using a Fuel-Based Mobile Source Emissions Inventory. *Environmental Science & Technology, 52*(13), 7360-7370. [https://doi.org/10.1021/acs.est.8b00778](https://doi.org/10.1021/acs.est.8b00778) + + McDonald, B. C., de Gouw, J. A., Gilman, J. B., Jathar, S. H., Akherati, A., Cappa, C. D., Jimenez, J. L., Lee-Taylor, J., Hayes, P. L., McKeen, S. A., Cui, Y. Y., Kim, S.-W., Gentner, D. R., Isaacman-VanWertz, G., Goldstein, A. H., Harley, R. A., Frost, G. J., Roberts, J. M., Ryerson, T. B., & Trainer, M. (2018b). Volatile chemical products emerging as largest petrochemical source of urban organic emissions. *Science, 359*(6377), 760-764. [https://doi.org/10.1126/science.aaq0524](https://doi.org/10.1126/science.aaq0524) + + ## Other Relevant Publications + Coggon, M. M., Gkatzelis, G. I., McDonald, B. C., Gilman, J. B., Schwantes, R. H., Abuhassan, N., Aikin, K. C., Arend, M. F., Berkoff, T. A., Brown, S. S., Campos, T. L., Dickerson, R. R., Gronoff, G., Hurley, J. F., Isaacman-VanWertz, G., Koss, A. R., Li, M., McKeen, S. A., Moshary, F., Peischl, J., Pospisilova, V., Ren, X., Wilson, A., Wu, Y., Trainer, M., & Warneke, C. (2021). Volatile chemical product emissions enhance ozone and modulate urban chemistry, *Proc Natl Acad Sci, 118*(32), e2026653118. [https://doi.org/10.1073/pnas.2026653118](https://doi.org/10.1073/pnas.2026653118) + + Coggon, M. M., Stockwell, C. E., Xu, L., Peischl, J., Gilman, J. B., Lamplugh, A., Bowman, H. J., Aikin, K., Harkins, C., Zhu, Q., Schwantes, R. H., He, J., Li, M., Seltzer, K., McDonald, B., & Warneke, C. (2024). Contribution of cooking emissions to the urban volatile organic compounds in Las Vegas, NV, *Atmospheric Chemistry Physics, 24*, 4289-4304. [https://doi.org/10.5194/acp-24-4289-2024](https://doi.org/10.5194/acp-24-4289-2024) + + Granier, C., Darras, S., Denier van der Gon, H., Doubalova, J., Elguindi, N., Galle, B., Gauss, M., Guevara, M., Jalkanen, J.-P., Kuenen, J., Liousse, C., Quack, B., Simpson, D., & Sindelarova, K. (2019). The Copernicus Atmosphere Monitoring Service global and regional emissions (April 2019 version). [https://doi.org/10.24380/d0bn-kx16](https://doi.org/10.24380/d0bn-kx16) + + Harkins, C., McDonald, B. C., Henze, D. K., & Wiedinmyer, C. (2021). A fuel-based method for updating mobile source emissions during the COVID-19 pandemic, *Environmental Research Letters, 16*, 065018. [https://doi.org/10.1088/1748-9326/ac0660](https://doi.org/10.1088/1748-9326/ac0660) + + He, J., Harkins, C., O'Dell, K., Li, M., Francoeur, C., Aikin, K., Anenberg, S., Baker, B., Brown, S. S., Coggon, M. M., Frost, G. J., Gilman, J. B., Kongdragunta, S., Lamplugh, A., Lyu, C., Moon, Z., Pierce, B., Schwantes, R.H., Stockwell, C.E., Warneke, C., Yang, K., & McDonald, B. C. (2024). COVID-19 perturbation on US air quality and human health impact assessment. *PNAS Nexus, 3*(1). [https://doi.org/10.1093/pnasnexus/pgad483](https://doi.org/10.1093/pnasnexus/pgad483) + + Li, M., McDonald, B. C., McKeen, S. A., Eskes, H., Levelt, P., Francoeur, C., Harkins, C., He, J., Barth, M., Henze, D. K., Bela, M. M., Trainer, M., de Gouw, J. A., & Frost, G. J. (2021). Assessment of Updated Fuel-Based Emissions Inventories Over the Contiguous United States Using TROPOMI NO2 Retrievals. *Journal of Geophysical Research: Atmospheres, 126*(24), e2021JD035484. [https://doi.org/10.1029/2021JD035484](https://doi.org/10.1029/2021JD035484) + + McDonald, B. C., McBride, Z. C., Martin, E. W., & Harley, R. A. (2014). High-resolution mapping of motor vehicle carbon dioxide emissions. *Journal of Geophysical Research: Atmospheres, 119*(9). [https://doi.org/10.1002/2013JD021219](https://doi.org/10.1002/2013JD021219) + + Zhu, Q., Schwantes, R. H., Coggon, M., Harkins, C., Schnell, J., He, J., Pye, H. O. T., Li, M., Baker, B., Moon, Z., Ahmadov, R., Pfannerstill, E. Y., Place, B., Wooldridge, P., Schulze, B. C., Arata, C., Bucholtz, A., Seinfeld, J. H., Warneke, C., Stockwell, C. E., Xu, L., Zuraski, K., Robinson, M. A., Neuman, J. A., Veres, P. R., Peischl, J., Brown, S. S., Goldstein, A. H., Cohen, R. C., & McDonald, B. C. (2024). A better representation of volatile organic compound chemistry in WRF-Chem and its impact on ozone over Los Angeles. *Atmos. Chem. Phys., 24*(9), 5265-5286. [https://doi.org/10.5194/acp-24-5265-2024](https://doi.org/10.5194/acp-24-5265-2024) + + ## Learn More + - Learn more about how GRA²PES combines GHG and air quality pollution sources into a single useful research database + + ## Acknowledgment + The National Oceanic and Atmospheric Administration's (NOAA's) Chemical Science Laboratory (CSL) and the National Institute of Standards and Technology's (NIST's) Greenhouse Gas (GHG) Measurement Program. + + ## License + [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/legalcode) (CC BY 4.0) + + ## Data Stewardship + - [Data Workflow](https://us-ghg-center.github.io/ghgc-docs/data_workflow/gra2pes-ghg-monthgrid-v1_Data_Flow.html) + - [Data Transformation Code](https://us-ghg-center.github.io/ghgc-docs/cog_transformation/gra2pes-ghg-monthgrid-v1.html) + - [US GHG Center Data Intake Processing and Verification Report](https://us-ghg-center.github.io/ghgc-docs/processing_and_verification_reports/gra2pes-ghg-monthgrid-v1_Processing%20and%20Verification%20Report.html) + + + diff --git a/datasets/influx-testbed-co2-and-ch4-concentrations.data.mdx b/datasets/influx-testbed-co2-and-ch4-concentrations.data.mdx new file mode 100644 index 000000000..1d4dcd82a --- /dev/null +++ b/datasets/influx-testbed-co2-and-ch4-concentrations.data.mdx @@ -0,0 +1,174 @@ +--- +id: influx-testbed-ghg-concentrations +name: Carbon Dioxide and Methane Concentrations from the Indianapolis Flux Experiment (INFLUX) +description: Atmospheric concentrations of carbon dioxide (CO₂) and methane (CH₄) collected at Indianapolis Flux Experiment (INFLUX) tower sites +usage: + - url: 'https://us-ghg-center.github.io/ghgc-docs/cog_transformation/influx-testbed-ghg-concentrations.html' + label: Notebook showing data transformation for ingest to the US GHG Center + title: 'Data Transformation Notebook' + - url: 'https://us-ghg-center.github.io/ghgc-docs/datausage.html' + label: Notebooks to read, visualize, and explore data statistics + title: 'Data Usage Notebooks' + - url: "https://hub.ghg.center/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FUS-GHG-Center%2Fghgc-docs&urlpath=lab%2Ftree%2Fghgc-docs%2Fuser_data_notebooks%2Finflux-testbed-ghg-concentrations_User_Notebook.ipynb&branch=main" + label: Run example notebook + title: Interactive Session in the US GHG Center JupyterHub (requires account) + - url: 'https://www.datacommons.psu.edu/download/meteorology/influx/influx-tower-data/wmo-x2019-scale/' + label: Browse and download data from Penn State + title: 'Data Browser' +media: + src: ::file ./media/nist-influx--dataset-cover.png + alt: Roadways in Indianapolis, Indiana near a tower station estimating local greenhouse gas emissions + author: + name: Pennsylvania State University + url: https://bpb-us-e1.wpmucdn.com/sites.psu.edu/dist/9/4276/files/2023/09/US_INC.png +taxonomy: + - name: Topics + values: + - GHG Concentrations + - Urban + - name: Source + values: + - Penn State + - NIST + - AEM/Earth Networks + - name: Product Type + values: + - Ground Measurements + - name: Gas + values: + - CO₂ + - CH₄ +infoDescription: | + ::markdown + - Temporal Extent: January 1, 2011 - December 31, 2023 + - Temporal Resolution: Hourly averages + - Spatial Extent: Indianapolis, Indiana, United States + - Spatial Resolution: Point location samples + - Data Units: Micromoles per mole of dry air (Parts CO₂ per million (ppm)); Nanomoles per mole of dry air (Parts CH₄ per billion (ppb)) + - Data Type: Research + - Data Latency: Updated ~annually +disableExplore: true +layers: + - id: influx-testbed-ghg-concentrations + stacCol: influx-testbed-ghg-concentrations + name: Methane Concentration (Air Sample) + type: vector + description: Discrete air sample measurements of methane (CH₄) + initialDatetime: newest + projection: + id: 'equirectangular' + zoomExtent: + - 0 + - 20 + sourceParams: + assets: influx-testbed-ghg-concentrations + colormap_name: plasma + rescale: + - 0 + - 1000 + nodata: 0 + compare: + datasetId: influx-testbed-ghg-concentrations + layerId: influx-testbed-ghg-concentrations + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: ppb + type: gradient + min: 0 + max: 1000 + stops: + - '#310597' + - '#4c02a1' + - '#6600a7' + - '#7e03a8' + - '#9511a1' + - '#aa2395' + - '#bc3587' + - '#cc4778' + - '#da5a6a' + - '#e66c5c' + - '#f0804e' + - '#f89540' + - '#fdac33' + - '#fdc527' + - '#f8df25' +--- + + + + **Temporal Extent:** January 1, 2011 - December 31, 2023 + **Temporal Resolution:** Hourly averages + **Spatial Extent:** Indianapolis, Indiana, United States + **Spatial Resolution:** Point location samples + **Data Units:** Micromoles per mole of dry air (Parts CO₂ per million (ppm)); Nanomoles per mole of dry air (Parts CH₄ per billion (ppb))
+ **Data Type:** Research
+ **Data Latency:** Updated ~annually + + NIST is engaged in research to improve measurement of greenhouse gas emissions in areas containing multiple emission sources and sinks, such as cities. NIST's objective is to develop measurement tools supporting independent means to diagnose the accuracy of greenhouse gas inventory data at urban and regional geospatial scales. NIST has established [three test beds in U.S. cities](https://www.nist.gov/greenhouse-gas-measurements/urban-test-beds) to develop and evaluate the performance of advanced measurement capabilities for emissions independent of their origin. Located in Indianapolis, Indiana, the Los Angeles air basin of California, and the U.S. Northeast corridor (beginning with the Baltimore/Washington D.C. region), the test beds have been selected for their varying meteorology, terrain and emissions characteristics. These test beds will serve as a means to independently diagnose the accuracy of emissions data obtained directly from emission or uptake sources. + + A variety of data are collected at the test bed locations including station measurements of various GHG and trace gas species, airborne observations, weather and surface fluxes, atmospheric profiling measurements including lidar measurements, and observations from rawinsondes. The interactive display below includes CO₂ and CH₄ concentration measurements from tower sites within the Indianapolis test bed location. This concentration data provides important continuous measurements of GHGs in the atmospheric boundary layer which can be used, along with associated weather models, to reveal how GHG concentrations and, more importantly, urban emissions of GHGs change over space and time. While only tower concentration data is shown in the GHG Center, the complete INFLUX urban test bed data collection can be accessed via the [Penn State INFLUX website](https://sites.psu.edu/influx/data/) and [PSU Data Commons](http://www.datacommons.psu.edu/commonswizard/SearchResults.aspx?searchType=Keyword&researcher=0&PennStateUnit=0&institution=0&keyword=influx&theme=0&condition=AND&smallX=0&smallY=0&bigX=0&bigY=0). + + + + +
+ +
+ + + + ## Source Data Product Citation + Miles, N. L., Richardson, S. J., Davis, K. J., and Haupt, B. J. (2017). In-situ tower atmospheric measurements of carbon dioxide, methane and carbon monoxide mole fraction for the Indianapolis Flux (INFLUX) project, Indianapolis, IN, USA. Data set. Available on-line [https://datacommons.psu.edu](https://datacommons.psu.edu) from The Pennsylvania State University Data Commons, University Park, Pennsylvania, USA. [https://doi.org/10.18113/D37G6P](https://doi.org/10.18113/D37G6P) + + ## Dataset Accuracy + Based on round-robin style testing and comparisons to NOAA flask measurements, we estimate the compatibility of the measurements better than 0.18 ppm CO₂, 1.0 ppb CH₄, and 6 ppb CO. In lieu of a full assessment of the total uncertainty as it changes in time, the instrument uncertainty is characterized by the standard deviation of the reference gas error for a 31-day period (including 15 days prior to the measurement day and 15 days following the measurement day). For more details, please see [Richardson, Miles, Davis et al. 2017](http://doi.org/10.1525/elementa.140). + + ## Disclaimer + This data is published for research academic and related non-commercial purposes consistent with NIST’s mandate to further the science and the promulgation of appropriate standards. + + Penn State reserves the right to make corrections to the data based on scientific grounds, e.g., recalibration of standard gases or discovery of operational issues not known at the time of the release. If the data are obtained for potential use in a publication or presentation, kindly inform Penn State personnel (co2data@meteo.psu.edu) of the nature of this work. + + ## Scientific Details + The Indianapolis urban test bed began in 2010 as the Indianapolis Flux Experiment, or INFLUX. INFLUX was designed to verify top-down methods for estimating fossil-fuel carbon dioxide (CO₂) emissions by combining upwind and downwind measurements of radiocarbon, or ¹⁴CO₂, with an existing high-resolution fossil-fuel CO₂ inventory, Hestia, being developed at Purdue University by Prof. Kevin Gurney (now at Northern Arizona University). The original two tower sites (01 and 02) were the sampling locations for automated whole air samples in NOAA/GML flasks analyzed for ¹⁴CO₂ ([Turnbull et al., 2012](https://amt.copernicus.org/articles/5/2321/2012/)). Additional flask sites and in-situ observations of CO₂, CH₄, and CO were added by NOAA/GML and Penn State University, respectively, and regular airborne sampling is conducted by Purdue’s Airborne Laboratory for Atmospheric Research ([ALAR](https://www.science.purdue.edu/shepson/research/ALARGreenhouseGas/)). The goals of this experiment are to link bottom-up (activity-based) and top-down (atmosphere-based) emissions estimates of GHG emissions, and many resulting [publications](https://sites.psu.edu/influx/publications/) have focused on that goal. + + The current INFLUX observation network includes nine in-situ tower-based, continuous measurements of CO₂, CO, and CH₄ (although not all species are measured at all sites), flask sampling of ¹⁴CO₂ and other trace gases, periodic aircraft sampling of greenhouse gases and two eddy-covariance flux towers. Only in-situ tower-based measurements of CO₂ and CH₄ concentrations are currently presented in the US GHG Center. Measurements are made with Picarro Inc. wavelength-scanned cavity ring down spectrometers at multiple levels. Hourly averages are reported here. + + ## Key Publications + Richardson, S. J., Miles, N. L., Davis, K. J., Lauvaux, T., Martins, D. K., Turnbull, J. C., et al. (2017). Tower measurement network of in-situ CO₂, CH₄, and CO in support of the Indianapolis FLUX (INFLUX) Experiment. *Elem Sci Anth, 5*(59). [https://doi.org/10.1525/elementa.140](https://doi.org/10.1525/elementa.140) + + ## Other Relevant Publications + Miles, N. L., Richardson, S. J., Lauvaux, T., Davis, K. J., Turnbull, J., Karion, A., Sweeney, C., Gurney, K. R., Patarasuk, R., Razlivanov, I., Cambaliza, M.O., & Shepson P. (2017). Quantification of urban atmospheric boundary layer greenhouse gas dry mole fraction enhancements: Results from the Indianapolis Flux Experiment (INFLUX). *Elem. Sci. Anth., 5*(27). [https://doi.org/10.1525/elementa.127](https://doi.org/10.1525/elementa.127) + + Davis, K. J., Deng, A., Lauvaux, T., Miles, N. L., Richardson, S. J., Sarmiento, D. P., Gurney, K. R., Hardesty, R. M., Bonin, T. A., Brewer, W. A., Lamb, B. K., Shepson, P. B., Harvey, R. M., Cambaliza, M. O., Sweeney, C., Turnbull, J. C., Whetstone, J., & Karion, A. (2017). The Indianapolis Flux Experiment (INFLUX): A test-bed for anthropogenic greenhouse gas emission measurement and monitoring. *Elem. Sci. Anth., 5*(21). [https://doi.org/10.1525/elementa.188](https://doi.org/10.1525/elementa.188) + + Turnbull, J., Sweeney, C., Karion, A., Newberger, T., Tans, P., Lehman, S., Davis, K. J., Miles N. L., Richardson, S. J., Lauvaux, T., Cambaliza, M. O., Shepson, P., Gurney, K., Patarasuk, R., & Zondervan, A. (2014). Towards quantification and source sector identification of fossil fuel CO₂ emissions from an urban area: Results from the INFLUX experiment. *J. Geophys. Res. Atmos, 120*(1), 292-312. [https://doi.org/10.1002/2014JD022555](https://doi.org/10.1002/2014JD022555) + + For a complete listing of related publications, please visit: [https://sites.psu.edu/influx/publications/](https://sites.psu.edu/influx/publications/) + + ## Learn More + - Check out the US GHG Center feature story on the NIST Urban GHG Measurements Test Bed System + - Learn more about INFLUX at the [Penn State website](https://sites.psu.edu/influx/) + - Learn more about the [Urban Test Bed System at NIST’s website](https://www.nist.gov/greenhouse-gas-measurements/urban-test-beds) + + ## Acknowledgment + This work was supported by the National Institutes of Standard and Technology (Award #70NANB19H128 and #70NANB23H188). + + ## License + [Creative Commons Attribution Non Commercial 4.0 International](https://creativecommons.org/licenses/by-nc/4.0/legalcode) (CC-BY-NC-4.0) + + This data is published for research academic and related non-commercial purposes consistent with NIST’s mandate to further the science and the promulgation of appropriate standards. + + ## Data Stewardship + - [Data Workflow](https://us-ghg-center.github.io/ghgc-docs/data_workflow/influx-testbed-ghg-concentrations_Data_Flow.html) + - [Data Transformation Code](https://us-ghg-center.github.io/ghgc-docs/cog_transformation/influx-testbed-ghg-concentrations.html) + - [US GHG Center Data Intake Processing and Verification Report](https://us-ghg-center.github.io/ghgc-docs/processing_and_verification_reports/influx-testbed-ghg-concentrations_Processing%20and%20Verification%20Report.html) + + + \ No newline at end of file diff --git a/datasets/lam-testbed-co2-and-ch4-concentrations.data.mdx b/datasets/lam-testbed-co2-and-ch4-concentrations.data.mdx new file mode 100644 index 000000000..458c82966 --- /dev/null +++ b/datasets/lam-testbed-co2-and-ch4-concentrations.data.mdx @@ -0,0 +1,175 @@ +--- +id: lam-testbed-ghg-concentrations +name: Carbon Dioxide and Methane Concentrations from the Los Angeles Megacity Carbon Project +description: Atmospheric concentrations of carbon dioxide (CO₂) and methane (CH₄) collected at NIST Urban Test Bed tower and rooftop sites in California’s South Coast Air Basin +usage: + - url: 'https://us-ghg-center.github.io/ghgc-docs/cog_transformation/lam-testbed-ghg-concentrations.html' + label: Notebook showing data transformation for ingest to the US GHG Center + title: 'Data Transformation Notebook' + - url: 'https://us-ghg-center.github.io/ghgc-docs/datausage.html' + label: Notebooks to read, visualize, and explore data statistics + title: 'Data Usage Notebooks' + - url: "https://hub.ghg.center/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FUS-GHG-Center%2Fghgc-docs&urlpath=lab%2Ftree%2Fghgc-docs%2Fuser_data_notebooks%2Flam-testbed-ghg-concentrations_User_Notebook.ipynb&branch=main" + label: Run example notebook + title: Interactive Session in the US GHG Center JupyterHub (requires account) + - url: 'https://doi.org/10.18434/mds2-2388' + label: Browse and download data from NIST + title: 'Data Browser' +media: + src: ::file ./media/nist-lam--dataset-cover.png + alt: Ground-based sensors, a satellite, and an aircraft collecting measurements of greenhouse gas emissions in the Los Angeles area + author: + name: NASA/JPL-Caltech + url: https://www.jpl.nasa.gov +taxonomy: + - name: Topics + values: + - GHG Concentrations + - Urban + - name: Source + values: + - NIST + - SIO + - NASA + - AEM/Earth Networks + - name: Product Type + values: + - Ground Measurements + - name: Gas + values: + - CO₂ + - CH₄ +infoDescription: | + ::markdown + - Temporal Extent: January 1, 2015 - December 31, 2023 + - Temporal Resolution: Hourly averages + - Spatial Extent:California’s South Coast Air Basin (includes urbanized portions of Los Angeles, Orange, Riverside, and San Bernardino counties) + - Spatial Resolution: Point location samples + - Data Units: Micromoles per mole of dry air (Parts CO₂ per million (ppm)); Nanomoles per mole of dry air (Parts CH₄ per billion (ppb)) + - Data Type: Research + - Data Latency: Updated ~annually +disableExplore: true +layers: + - id: lam-testbed-ghg-concentrations + stacCol: lam-testbed-ghg-concentrations + name: Methane Concentration (Air Sample) + type: vector + description: Discrete air sample measurements of methane (CH₄) + initialDatetime: newest + projection: + id: 'equirectangular' + zoomExtent: + - 0 + - 20 + sourceParams: + assets: lam-testbed-ghg-concentrations + colormap_name: plasma + rescale: + - 0 + - 1000 + nodata: 0 + compare: + datasetId: lam-testbed-ghg-concentrations + layerId: lam-testbed-ghg-concentrations + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: ppb + type: gradient + min: 0 + max: 1000 + stops: + - '#310597' + - '#4c02a1' + - '#6600a7' + - '#7e03a8' + - '#9511a1' + - '#aa2395' + - '#bc3587' + - '#cc4778' + - '#da5a6a' + - '#e66c5c' + - '#f0804e' + - '#f89540' + - '#fdac33' + - '#fdc527' + - '#f8df25' +--- + + + + **Temporal Extent:** January 1, 2015 - December 31, 2023 + **Temporal Resolution:** Hourly averages + **Spatial Extent:** California’s South Coast Air Basin (includes urbanized portions of Los Angeles, Orange, Riverside, and San Bernardino counties) + **Spatial Resolution:** Point location samples + **Data Units:** Micromoles per mole of dry air (Parts CO₂ per million (ppm)); Nanomoles per mole of dry air (Parts CH₄ per billion (ppb))
+ **Data Type:** Research
+ **Data Latency:** Updated ~annually + + NIST is engaged in research to improve measurement of greenhouse gas emissions in areas containing multiple emission sources and sinks, such as cities. NIST's objective is to develop measurement tools supporting independent means to diagnose the accuracy of greenhouse gas inventory data at urban and regional geospatial scales. NIST has established [three test beds in U.S. cities](https://www.nist.gov/greenhouse-gas-measurements/urban-test-beds) to develop and evaluate the performance of advanced measurement capabilities for emissions independent of their origin. Located in Indianapolis, Indiana, the Los Angeles air basin of California, and the U.S. Northeast corridor (beginning with the Baltimore/Washington D.C. region), the test beds have been selected for their varying meteorology, terrain and emissions characteristics. These test beds will serve as a means to independently diagnose the accuracy of emissions data obtained directly from emission or uptake sources. + + A variety of data are collected at the test bed locations including station measurements of various GHG and trace gas species, airborne observations, weather and surface fluxes, atmospheric profiling measurements including lidar measurements, and observations from rawinsondes. The interactive display below includes CO₂ and CH₄ concentration measurements from tower and rooftop sites within the Los Angeles Megacity test bed location. This concentration data provides important continuous measurements of GHGs in the atmospheric boundary layer which can be used, along with associated weather models, to reveal how GHG concentrations and, more importantly, urban emissions of GHGs change over space and time. While only tower and rooftop concentration data is shown in the GHG Center, the complete urban LAM test bed data collection can be accessed via NIST’s website: [https://www.nist.gov/greenhouse-gas-measurements/urban-test-beds](https://www.nist.gov/greenhouse-gas-measurements/urban-test-beds) + + + + + +
+ +
+ + + + ## Source Data Product Citation + Kim, J., Verhulst, K., Lueker, T., Salameh, P., Cox, A., Walker, S., Paplawsky, W., Prinzivalli, S., Fain, C., Stock, M., DiGangi, E., Biggs, B., Angel, B., Karion, A., Pongetti, T., Callahan, W., Weiss, R. F., Keeling, R. F., Miller, C. E. (2021), In Situ Carbon Dioxide, Methane, and Carbon Monoxide Mole Fractions from the Los Angeles Megacity Carbon Project, Revision 3, National Institute of Standards and Technology, [https://doi.org/10.18434/mds2-2388](https://doi.org/10.18434/mds2-2388) (Accessed 2024-05-17). + + ## Dataset Accuracy + Uncertainty estimates on each hourly observation are estimated using algorithms detailed in Karion et al., 2020 ([https://doi.org/10.5194/essd-12-699-2020](https://doi.org/10.5194/essd-12-699-2020)) and included in each data file. + + ## Disclaimer + This data is published for research academic and related non-commercial purposes consistent with NIST’s mandate to further the science and the promulgation of appropriate standards. + + ## Scientific Details + The Los Angeles Megacity Carbon Project (LA-MCP) was designed to demonstrate a scientifically robust measurement of multi-year emission trends for carbon dioxide (CO₂) and methane (CH₄) in a large urban environment (a “megacity”) and to attribute such trends to emissions from various sectors. Determination of greenhouse gas fluxes and uncertainties in urban areas is critical for evaluating mitigation strategies. The current LA surface observation network includes eleven in situ analyzers situated on tower- or rooftop/building- based platforms for continuous measurements of CO₂, CH₄ and CO (not all species are measured at all sites, and only CO₂ and CH₄ data are displayed in the GHG Center). + + Measurements are reported as dry air mole fractions on the NOAA/WMO X2007 (CO₂) and X2004A (CH₄) calibration scales, as reported by the WMO's CCL, NOAA/ESRL/GML. NOAA has recently released a new CO₂ scale, X2019. These data are reported on the X2007 scale. NIST plans to release all the data going back to 2015 under either a new version or an entirely separate release at a later date. + + The data from the in-situ towers and rooftops are currently being used in both forward and inverse modeling frameworks and the inverse model results have been used to estimate carbon fluxes for Southern California. The Hestia project ([https://hestia.rc.nau.edu/About.html](https://hestia.rc.nau.edu/About.html)) has produced bottom-up inventory estimates of fossil carbon emissions for a total of five counties in the South Coast Air Basin, including Los Angeles, with high space/time resolution. The Hestia data product also provides information on sectorally-resolved fossil carbon emissions. + + The LA Megacity project has also included flask sampling of ¹⁴CO₂ and other trace gases in the past. In addition, the California Laboratory for Atmospheric Remote Sensing (CLARS, [tmf.jpl.nasa.gov/clarsweather](https://tmf.jpl.nasa.gov/clarsweather/)) instrument on Mt. Wilson measures the slant column abundance of greenhouse gases by rastering across the LA basin roughly every 90 minutes. There have also been periodic aircraft sampling of greenhouse gases and meteorological conditions in the Los Angeles megacity during intensive campaigns. + + ## Key Publications + Verhulst, K. R., A. Karion, J. Kim, P. K. Salameh, R. F. Keeling, S. Newman, J. Miller, C. Sloop, T. Pongetti, P. Rao, C. Wong, F. M. Hopkins, V. Yadav, R. F. Weiss, R. M. Duren & C. E. Miller. (2017). Carbon dioxide and methane measurements from the Los Angeles Megacity Carbon Project - Part 1: calibration, urban enhancements, and uncertainty estimates. *Atmos. Chem. Phys., 17*(13), 8313-8341. [https://doi.org/10.5194/acp-17-8313-2017](https://doi.org/10.5194/acp-17-8313-2017) + + ## Other Relevant Publications + Yadav, V., Verhulst, K., Duren, R., Thorpe, A., Kim, J., Keeling, R., Weiss, R., Cusworth, D., Mountain, M., Miller, C., & Whetstone, J. (2023). A declining trend of methane emissions in the Los Angeles basin from 2015 to 2020. *Environmental Research Letters, 18*(3), 034004. [https://doi.org/10.1088/1748-9326/acb6a9](https://doi.org/10.1088/1748-9326/acb6a9) + + Yadav, V., Ghosh, S., Mueller, K., Karion, A., Roest, G., Gourdji, S. M., Lopez-Coto, I., Gurney, K. R., Parazoo, N., Verhulst, K. R., Kim, J., Prinzivalli, S., Fain, C., Nehrkorn, T., Mountain, M., Keeling, R. F., Weiss, R. F., Duren, R., Miller, C. E., & Whetstone, J. (2021). The Impact of COVID-19 on CO₂ Emissions in the Los Angeles and Washington DC/Baltimore Metropolitan Areas. *Geophysical Research Letters, 48*(11), e2021GL092744. [https://doi.org/10.1029/2021GL092744](https://doi.org/10.1029/2021GL092744) + + Yadav, V., Duren, R., Mueller, K., Verhulst, K. R., Nehrkorn, T., Kim, J., Weiss, R. F., Keeling, R., Sander, S., Fischer, M. L., Newman, S., Falk, M., Kuwayama, T., Hopkins, F., Rafiq, T., Whetstone, J., & Miller, C. (2019). Spatio-temporally Resolved Methane Fluxes From the Los Angeles Megacity. *JGR Atmospheres, 124*(9), 5131-5148. [https://doi.org/10.1029/2018JD030062](https://doi.org/10.1029/2018JD030062) + + Ware, J., Kort, E. A., Duren, R., Mueller, K. L., Verhulst, K., & Yadav, V. (2019). Detecting Urban Emissions Changes and Events With a Near-Real-Time-Capable Inversion System. *JGR Atmospheres, 124*(9), 5117-5130. [https://doi.org/10.1029/2018JD029224](https://doi.org/10.1029/2018JD029224) + + ## Learn More + - Check out the US GHG Center feature story on the NIST Urban GHG Measurements Test Bed System + - Learn more about the [Urban Test Bed System at NIST’s website](https://www.nist.gov/greenhouse-gas-measurements/urban-test-beds) + + ## Acknowledgment + NIST, AEM/Earth Networks, Inc., Scripps Institution of Oceanography, NASA/JPL, GCWerks, Inc. + + ## License + This data is published for research academic and related non-commercial purposes consistent with NIST’s mandate to further the science and the promulgation of appropriate standards. + + ## Data Stewardship + - [Data Workflow](https://us-ghg-center.github.io/ghgc-docs/data_workflow/lam-testbed-ghg-concentrations_Data_Flow.html) + - [Data Transformation Code](https://us-ghg-center.github.io/ghgc-docs/cog_transformation/lam-testbed-ghg-concentrations.html) + - [US GHG Center Data Intake Processing and Verification Report](https://us-ghg-center.github.io/ghgc-docs/processing_and_verification_reports/lam-testbed-ghg-concentrations_Processing%20and%20Verification%20Report.html) + + + \ No newline at end of file diff --git a/datasets/lpjwsl-wetlandch4-grid-v2.data.mdx b/datasets/lpjwsl-wetlandch4-grid-v2.data.mdx index 8cd33c80e..a31fc23e1 100644 --- a/datasets/lpjwsl-wetlandch4-grid-v2.data.mdx +++ b/datasets/lpjwsl-wetlandch4-grid-v2.data.mdx @@ -13,7 +13,7 @@ usage: label: Download data from NASA Distributed Active Archive Center title: Data Browser media: - src: ::file ./ch4-wetland--cover.jpeg + src: ::file ./media/ch4-wetland--cover.jpeg alt: svs visualiztion author: name: Mark SubbaRao (NASA/GSFC) @@ -384,8 +384,8 @@ layers: Zhang, Z., Zimmermann, N. E., Kaplan, J. O., & Poulter, B. (2016). Modeling spatiotemporal dynamics of global wetlands: comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties. *Biogeosciences, 13*(5), 1387–1408. [https://doi.org/10.5194/bg-13-1387-2016](https://doi.org/10.5194/bg-13-1387-2016) ## Learn More - - See a video of methane emissions from wetlands around the globe in the [Intro to the US GHG Center Data Insight](https://earth.gov/ghgcenter/stories/intro-us-ghg-center) - - See how wetlands in the tropics and in higher latitude areas differ in their contribution to global wetland methane emissions in the [Tracking Greenhouse Gas Cycles Data Insight](https://earth.gov/ghgcenter/stories/tracking-greenhouse-gas-cycles) + - See a video of methane emissions from wetlands around the globe in the Intro to the US GHG Center Data Insight + - See how wetlands in the tropics and in higher latitude areas differ in their contribution to global wetland methane emissions in the Tracking Greenhouse Gas Cycles Data Insight ## Acknowledgment The LPJ-EOSIM model is based on the development of the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM) [by researchers at institutions in Germany and Sweden](https://doi.org/10.1046/j.1365-2486.2003.00569.x) (Potsdam and Jena, Germany & Lund, Sweden). diff --git a/datasets/casagfed-carbonflux-monthgrid-v3.thumbnails.fire.png b/datasets/media/casagfed-carbonflux-monthgrid-v3.thumbnails.fire.png similarity index 100% rename from datasets/casagfed-carbonflux-monthgrid-v3.thumbnails.fire.png rename to datasets/media/casagfed-carbonflux-monthgrid-v3.thumbnails.fire.png diff --git a/datasets/casagfed-carbonflux-monthgrid-v3.thumbnails.fuel.png b/datasets/media/casagfed-carbonflux-monthgrid-v3.thumbnails.fuel.png similarity index 100% rename from datasets/casagfed-carbonflux-monthgrid-v3.thumbnails.fuel.png rename to datasets/media/casagfed-carbonflux-monthgrid-v3.thumbnails.fuel.png diff --git a/datasets/casagfed-carbonflux-monthgrid-v3.thumbnails.nee.png b/datasets/media/casagfed-carbonflux-monthgrid-v3.thumbnails.nee.png similarity index 100% rename from datasets/casagfed-carbonflux-monthgrid-v3.thumbnails.nee.png rename to 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a/datasets/media/vulcan-co2-yeargrid-v4.thumbnails.total.png b/datasets/media/vulcan-co2-yeargrid-v4.thumbnails.total.png new file mode 100644 index 000000000..038499461 Binary files /dev/null and b/datasets/media/vulcan-co2-yeargrid-v4.thumbnails.total.png differ diff --git a/datasets/micasa-carbonflux-daygrid-v1.data.mdx b/datasets/micasa-carbonflux-daygrid-v1.data.mdx index 40d0d69fb..b1fd10923 100644 --- a/datasets/micasa-carbonflux-daygrid-v1.data.mdx +++ b/datasets/micasa-carbonflux-daygrid-v1.data.mdx @@ -13,7 +13,7 @@ usage: label: Browse and download the data title: Data Browser media: - src: ::file ./geos-casa-gfed-cover.jpg + src: ::file ./media/geos-casa-gfed-cover.jpg alt: wildfire author: name: Marcus Kauffman @@ -809,7 +809,7 @@ layers: van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J., & Kasibhatla, P. S. (2017). Global fire emissions estimates during 1997–2016. *Earth System Science Data*, 9, 697–720. [https://doi.org/10.5194/essd-9-697-2017](https://doi.org/10.5194/essd-9-697-2017) ## Learn More - - Compare the difference in Net Ecosystem Exchange (NEE) between January and July 2011 in the [Tracking Greenhouse Gas Cycles Data Insight](https://earth.gov/ghgcenter/stories/tracking-greenhouse-gas-cycles). The NEE variable in the MiCASA dataset represents the balance in absorption of carbon by plants via photosynthesis against the release of carbon by plants during respiration. The comparison of NEE in January and July illustrates the difference between the winter and summer seasons. + - Compare the difference in Net Ecosystem Exchange (NEE) between January and July 2011 in the Tracking Greenhouse Gas Cycles Data Insight. The NEE variable in the MiCASA dataset represents the balance in absorption of carbon by plants via photosynthesis against the release of carbon by plants during respiration. The comparison of NEE in January and July illustrates the difference between the winter and summer seasons. ## Acknowledgment This dataset was produced as part of the [GEOS-Carb project](https://cce-datasharing.gsfc.nasa.gov/cmsprojects/list/h/0/) supported by NASA’s [Carbon Monitoring System (CMS) Program](https://carbon.nasa.gov/cms/). diff --git a/datasets/nec-testbed-co2-and-ch4-concentrations.data.mdx b/datasets/nec-testbed-co2-and-ch4-concentrations.data.mdx new file mode 100644 index 000000000..c17bbe5cf --- /dev/null +++ b/datasets/nec-testbed-co2-and-ch4-concentrations.data.mdx @@ -0,0 +1,166 @@ +--- +id: nec-testbed-ghg-concentrations +name: Carbon Dioxide and Methane Concentrations from the Northeast Corridor (NEC) Urban Test Bed +description: Atmospheric concentrations of carbon dioxide (CO₂) and methane (CH₄) collected at NIST Urban Test Bed tower sites in the Northeastern U.S. +usage: + - url: 'https://us-ghg-center.github.io/ghgc-docs/cog_transformation/nec-testbed-ghg-concentrations.html' + label: Notebook showing data transformation for ingest to the US GHG Center + title: 'Data Transformation Notebook' + - url: 'https://us-ghg-center.github.io/ghgc-docs/datausage.html' + label: Notebooks to read, visualize, and explore data statistics + title: 'Data Usage Notebooks' + - url: "https://hub.ghg.center/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FUS-GHG-Center%2Fghgc-docs&urlpath=lab%2Ftree%2Fghgc-docs%2Fuser_data_notebooks%2Fnec-testbed-ghg-concentrations_User_Notebook.ipynb&branch=main" + label: Run example notebook + title: Interactive Session in the US GHG Center JupyterHub (requires account) + - url: 'https://data.nist.gov/od/id/mds2-3012' + label: Browse and download data from NIST + title: 'Data Browser' +media: + src: ::file ./media/nist-nec--dataset-cover.jpg + alt: Smoke + author: + name: Chris Leboutillier + url: https://unsplash.com/photos/a-large-plume-of-smoke-coming-out-of-a-pipe-NmT8Nk8OJMg +taxonomy: + - name: Topics + values: + - GHG Concentrations + - Urban + - name: Source + values: + - NIST + - AEM/Earth Networks + - name: Product Type + values: + - Ground Measurements + - name: Gas + values: + - CO₂ + - CH₄ +infoDescription: | + ::markdown + - Temporal Extent: January 1, 2015 - December 31, 2022 + - Temporal Resolution: Hourly averages + - Spatial Extent: Northeastern United States (86.20 W, 70.49 W, 43.71 N, 35.20 N) + - Spatial Resolution: Point location samples + - Data Units: Micromoles per mole of dry air (Parts CO₂ per million (ppm)); Nanomoles per mole of dry air (Parts CH₄ per billion (ppb)) + - Data Type: Research + - Data Latency: Updated ~annually +disableExplore: true +layers: + - id: nec-testbed-ghg-concentrations + stacCol: nec-testbed-ghg-concentrations + name: Methane Concentration (Air Sample) + type: vector + description: Discrete air sample measurements of methane (CH₄) + initialDatetime: newest + projection: + id: 'equirectangular' + zoomExtent: + - 0 + - 20 + sourceParams: + assets: nec-testbed-ghg-concentrations + colormap_name: plasma + rescale: + - 0 + - 1000 + nodata: 0 + compare: + datasetId: nec-testbed-ghg-concentrations + layerId: nec-testbed-ghg-concentrations + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: ppb + type: gradient + min: 0 + max: 1000 + stops: + - '#310597' + - '#4c02a1' + - '#6600a7' + - '#7e03a8' + - '#9511a1' + - '#aa2395' + - '#bc3587' + - '#cc4778' + - '#da5a6a' + - '#e66c5c' + - '#f0804e' + - '#f89540' + - '#fdac33' + - '#fdc527' + - '#f8df25' +--- + + + + **Temporal Extent:** January 1, 2015 - December 31, 2022 + **Temporal Resolution:** Hourly averages + **Spatial Extent:** Northeastern United States (86.20 W, 70.49 W, 43.71 N, 35.20 N) + **Spatial Resolution:** Point location samples + **Data Units:** Micromoles per mole of dry air (Parts CO₂ per million (ppm)); Nanomoles per mole of dry air (Parts CH₄ per billion (ppb))
+ **Data Type:** Research
+ **Data Latency:** Updated ~annually + + NIST is engaged in research to improve measurement of greenhouse gas emissions in areas containing multiple emission sources and sinks, such as cities. NIST's objective is to develop measurement tools supporting independent means to increase the accuracy of greenhouse gas emissions data at urban and regional geospatial scales. NIST has established [three test beds in U.S. cities](https://www.nist.gov/greenhouse-gas-measurements/urban-test-beds) to develop and evaluate the performance of advanced measurement capabilities for emissions independent of their origin. Located in Indianapolis, Indiana, the Los Angeles air basin of California, and the U.S. Northeast corridor (beginning with the Baltimore/Washington D.C. region), the test beds have been selected for their varying meteorology, terrain and emissions characteristics. These test beds will serve as a means to independently diagnose the accuracy of emissions data obtained directly from emission or uptake sources. + + A variety of data are collected at the test bed locations including station measurements of various GHG and trace gas species, airborne observations, weather and surface fluxes, atmospheric profiling measurements including lidar measurements, and observations from rawinsondes. The interactive display below includes CO₂ and CH₄ concentration measurements from tower sites within the Northeast Corridor (NEC) test bed location. This concentration data provides important continuous measurements of GHGs in the atmospheric boundary layer which can be used, along with associated weather models, to reveal how GHG concentrations and, more importantly, urban emissions of GHGs change over space and time. While only tower concentration data is shown in the GHG Center, the complete NEC urban test bed data collection can be accessed via NIST’s website: [https://www.nist.gov/greenhouse-gas-measurements/urban-test-beds](https://www.nist.gov/greenhouse-gas-measurements/urban-test-beds) + + + +
+ +
+ + + + ## Source Data Product Citation + Karion, A., DiGangi, E., Prinzivalli, S., Draper, C., Baldelli, S., Fain, C., Biggs, B., Stock, M., Michalak, B., Salameh, P., Kim, J., Callahan, W., and Whetstone, J. (2023), Observations of carbon dioxide (CO₂), methane (CH₄), and carbon monoxide (CO) mole fractions from the NIST Northeast Corridor urban testbed, https://doi.org/10.18434/mds2-3012 (Accessed 2024-08-08). + + ## Dataset Accuracy + Uncertainty estimates on each hourly observation are estimated using algorithms detailed in Karion et al., 2020 ([https://doi.org/10.5194/essd-12-699-2020](https://doi.org/10.5194/essd-12-699-2020)) and included in each data file. + + ## Disclaimer + This data is published for research academic and related non-commercial purposes consistent with NIST’s mandate to further the science and the promulgation of appropriate standards. + + ## Scientific Details + The Northeast Corridor (NEC) Urban Test Bed Project was designed to demonstrate a scientifically robust measurement of total emissions and multi-year emission trends for carbon dioxide (CO₂) and methane (CH₄) in an urban environment and attribute these trends to emissions from various sectors. + + Continuous, in-situ measurements of CO₂, CH₄, and sometimes carbon monoxide (CO) dry air mole fractions (only CO₂ and CH₄ data are displayed in the GHG Center) are made from rooftops or towers in the Northeastern US region, including a dense network of towers in the Washington, DC and Baltimore, Maryland metro area. Most tower sites have measurements at multiple heights, but only measurements from the upper-most height are displayed in the GHG Center. + + Measurements are reported on the NOAA/WMO X2007 (CO₂) and X2004A (CH₄) calibration scales. The CO₂ data will be updated to the NOAA/WMO X2019 calibration scale at a future date. + + ## Key Publications + Karion, A., Callahan, W., Stock, M., Prinzivalli, S., Verhulst, K. R., Kim, J., Salameh, P. K., Lopez-Coto, I., & Whetstone, J. (2020). Greenhouse gas observations from the Northeast Corridor tower network. *Earth Syst. Sci. Data, 12*, 699–717. [https://doi.org/10.5194/essd-12-699-2020](https://doi.org/10.5194/essd-12-699-2020) + + ## Other Relevant Publications + Karion, A., Ghosh, S., Lopez-Coto, I., Mueller, K., Gourdji, S., Pitt, J., & Whetstone, J. (2023). Methane Emissions Show Recent Decline but Strong Seasonality in Two US Northeastern Cities. *Environmental Science & Technology, 57*(48), 19565-19574. [https://doi.org/10.1021/acs.est.3c05050](https://doi.org/10.1021/acs.est.3c05050) + + Yadav, V., Ghosh, S., Mueller, K., Karion, A., Roest, G., Gourdji, S. M., Lopez-Coto, I., Gurney, K. R., Parazoo, N., Verhulst, K. R., Kim, J., Prinzivalli, S., Fain, C., Nehrkorn, T., Mountain, M., Keeling, R. F., Weiss, R. F., Duren, R., Miller, C. E., & Whetstone, J. (2021). The Impact of COVID-19 on CO₂ Emissions in the Los Angeles and Washington DC/Baltimore Metropolitan Areas. *Geophysical Research Letters, 48*(11), e2021GL092744. [https://doi.org/10.1029/2021GL092744](https://doi.org/10.1029/2021GL092744) + + Gourdji, S. M., Karion, A., Lopez-Coto, I., Ghosh, S., Mueller, K. L., Zhou, Y., Williams, C. A., Baker, I. T., Haynes, K. D., & Whetstone, J. R. (2021). A Modified Vegetation Photosynthesis and Respiration Model (VPRM) for the Eastern USA and Canada, Evaluated With Comparison to Atmospheric Observations and Other Biospheric Models. *JGR Biogeosciences, 127*(1), e2021JG006290. [https://doi.org/10.1029/2021JG006290](https://doi.org/10.1029/2021JG006290) + + ## Learn More + - Check out the US GHG Center feature story on the NIST Urban GHG Measurements Test Bed System + - Learn more about the [Urban Test Bed System at NIST’s website](https://www.nist.gov/greenhouse-gas-measurements/urban-test-beds) + + ## Acknowledgment + NIST, AEM/Earth Networks, Inc., Scripps Institution of Oceanography, GCWerks, Inc. + + ## License + This data is published for research academic and related non-commercial purposes consistent with NIST’s mandate to further the science and the promulgation of appropriate standards. + + ## Data Stewardship + - [Data Workflow](https://us-ghg-center.github.io/ghgc-docs/data_workflow/nec-testbed-ghg-concentrations_Data_Flow.html) + - [Data Transformation Code](https://us-ghg-center.github.io/ghgc-docs/cog_transformation/nec-testbed-ghg-concentrations.html) + - [US GHG Center Data Intake Processing and Verification Report](https://us-ghg-center.github.io/ghgc-docs/processing_and_verification_reports/nec-testbed-ghg-concentrations_Processing%20and%20Verification%20Report.html) + + \ No newline at end of file diff --git a/datasets/noaa-cpfp-ch4-point.data.mdx b/datasets/noaa-cpfp-ch4-point.data.mdx index 6f3fff722..fc342b0fb 100644 --- a/datasets/noaa-cpfp-ch4-point.data.mdx +++ b/datasets/noaa-cpfp-ch4-point.data.mdx @@ -13,7 +13,7 @@ usage: label: Download data from NOAA title: 'Data Browser' media: - src: ::file ./noaa-air-samples--cover.png + src: ::file ./media/noaa-air-samples--cover.png alt: aa author: name: Columbia University @@ -102,7 +102,7 @@ layers: The Global Greenhouse Gas Reference Network (GGGRN) for the Carbon Cycle and Greenhouse Gases (CCGG) Group is part of NOAA'S Global Monitoring Laboratory (GML) in Boulder, CO. The Reference Network measures the atmospheric distribution and trends of the three main long-term drivers of climate change, carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N2O), as well as carbon monoxide (CO) and many other trace gases which help interpretation of the main GHGs. The Reference Network measurement program includes continuous in-situ measurements at 4 baseline observatories (global background sites) and 8 tall towers, as well as flask-air samples collected by volunteers at over 50 additional regional background sites and from small aircraft conducting regular vertical profiles. The air samples are returned to GML for analysis where measurements of about 55 trace gases are completed. - This dataset contains CH4 concentration measurements in units of parts per billion (ppb) made from surface in-situ and tower sites and from surface flask air samples. The surface in-situ and tower instrumentation measures CH4 continuously (hourly) while the flask air samples are non-continuous measurements (frequency varies by station). Due to the high data volume of hourly tower measurements, daily and monthly averages are generated for display in the US GHG Center. + This dataset contains CH₄ concentration measurements in units of parts per billion (ppb) made from surface in-situ and tower sites and from surface flask air samples. The surface in-situ and tower instrumentation measures CH₄ continuously (hourly) while the flask air samples are non-continuous measurements (frequency varies by station). Due to the high data volume of hourly tower measurements, daily and monthly averages are generated for display in the US GHG Center. NOAA's GGGRN maintains the World Meteorological Organization international calibration scales for CO₂, CH₄, CO, N2O, and SF6 in air. The measurements from the GGGRN serve as a comparison with measurements made by many other international laboratories, and with regional studies. They are widely used in modeling studies that infer space-time patterns of emissions and removals of greenhouse gases that are optimally consistent with the atmospheric observations, given wind patterns. These data serve as an early warning for climate "surprises". The measurements are also helpful for the ongoing evaluation of remote sensing technologies. @@ -121,11 +121,11 @@ layers: ## Source Data Product Citation K.W. Thoning, X. Lan, A.M. Crotwell, and J.W. Mund (2024). Atmospheric methane from quasi-continuous measurements at Barrow, Alaska and Mauna Loa, Hawaii, 1986-2023. National Oceanic and Atmospheric Administration (NOAA), Global Monitoring Laboratory (GML), Boulder, Colorado, USA. Version: 2024-02-12. [https://doi.org/10.15138/ve0c-be70](https://doi.org/10.15138/ve0c-be70) - A. Andrews, N. Miles, J. Kofler, M.E. Trudeau, P.S. Bakwin, M.L. Fischer, C. Sweeney, A.R. Desai, B. J. Viner, M. J. Parker, D. A. Jaffe, C. E. Miller, S. F. J. de Wekker, and J. B. Miller. Continuous measurements of CO2, CO, CH4 on tall towers starting in 1992. NOAA Global Monitoring Laboratory. Version: 2023-08-23. [https://doi.org/10.7289/V57W69F2](https://doi.org/10.7289/V57W69F2) + A. Andrews, N. Miles, J. Kofler, M.E. Trudeau, P.S. Bakwin, M.L. Fischer, C. Sweeney, A.R. Desai, B. J. Viner, M. J. Parker, D. A. Jaffe, C. E. Miller, S. F. J. de Wekker, and J. B. Miller. Continuous measurements of CO₂, CO, CH₄ on tall towers starting in 1992. NOAA Global Monitoring Laboratory. Version: 2023-08-23. [https://doi.org/10.7289/V57W69F2](https://doi.org/10.7289/V57W69F2) Lan, X., Mund, J.W., Crotwell, A.M., Crotwell, M.J., Moglia, E., Madronich, M., Neff, D., and Thoning, K.W. (2023). Atmospheric Methane Dry Air Mole Fractions from the NOAA GML Carbon Cycle Cooperative Global Air Sampling Network, 1983-2022. Version: 2023-08-28. [https://doi.org/10.15138/VNCZ-M766](https://doi.org/10.15138/VNCZ-M766) - Andrews, A., Crotwell, A., Crotwell, M., Handley, P., Higgs, J., Kofler, J., Lan, X., Legard, T., Madronich, M., McKain, K., Miller, J., Moglia, E., Mund, J., Neff, D., Newberger, T., Petron, G., Turnbull, J., Vimont, I., Wolter, S., & NOAA Global Monitoring Laboratory. (2023). NOAA Global Greenhouse Gas Reference Network Flask-Air PFP Sample Measurements of CH4 at Tall Tower and other Continental Sites, 2005-Present. NOAA GML. Version: 2023-08-23. [https://doi.org/10.15138/35JE-6D55](https://doi.org/10.15138/35JE-6D55) + Andrews, A., Crotwell, A., Crotwell, M., Handley, P., Higgs, J., Kofler, J., Lan, X., Legard, T., Madronich, M., McKain, K., Miller, J., Moglia, E., Mund, J., Neff, D., Newberger, T., Petron, G., Turnbull, J., Vimont, I., Wolter, S., & NOAA Global Monitoring Laboratory. (2023). NOAA Global Greenhouse Gas Reference Network Flask-Air PFP Sample Measurements of CH₄ at Tall Tower and other Continental Sites, 2005-Present. NOAA GML. Version: 2023-08-23. [https://doi.org/10.15138/35JE-6D55](https://doi.org/10.15138/35JE-6D55) The CH₄ data displayed in the web map viewer can be directly accessed here: - [Continuous Surface and Tower In-situ CH₄ Samples](https://gml.noaa.gov/dv/data/index.php?category=Greenhouse%252BGases&type=Insitu¶meter_name=Methane). Hourly tower data have been aggregated into daily and monthly averages for display in the US GHG Center. @@ -149,7 +149,7 @@ layers: For more information refer to the following dataset documentation and [sampling location information](https://gml.noaa.gov/dv/site/?program=ccgg): - [Continuous Surface In-situ CH₄ Measurements](https://gml.noaa.gov/aftp/data/greenhouse_gases/ch4/in-situ/surface/README_ch4_surface-insitu_ccgg.html) - [Continuous Tower CH₄ Measurements](https://gml.noaa.gov/aftp/data/greenhouse_gases/ch4/in-situ/tower/README_ch4_tower-insitu_ccgg.html) - - Non-continuous Surface [Flask](https://gml.noaa.gov/aftp/data/greenhouse_gases/ch4/flask/surface/README_ch4_surface-flask_ccgg.html) and [Programmable Flask Package (PFP)](https://gml.noaa.gov/aftp/data/greenhouse_gases/ch4/pfp/surface/README_ch4_surface-pfp_ccgg.html) CH4 Measurements + - Non-continuous Surface [Flask](https://gml.noaa.gov/aftp/data/greenhouse_gases/ch4/flask/surface/README_ch4_surface-flask_ccgg.html) and [Programmable Flask Package (PFP)](https://gml.noaa.gov/aftp/data/greenhouse_gases/ch4/pfp/surface/README_ch4_surface-pfp_ccgg.html) CH₄ Measurements ## Key Publications Lan, X., Nisbet, E.G., Dlugokencky, E.J., & Michel, S.E. (2021). What do we know about the global methane budget? Results from four decades of atmospheric CH₄ observations and the way forward. *Phil. Trans. R. Soc. A 379*:20200440. [https://doi.org/10.1098/rsta.2020.0440](https://doi.org/10.1098/rsta.2020.0440) @@ -185,7 +185,7 @@ layers: ## Learn More - [View current trends in CH4](https://gml.noaa.gov/ccgg/trends_ch4/) powered by NOAA data - - See how NOAA’s GHG observations have contributed to the understanding of GHG fluxes from human-caused and natural sources in the [Tracking Greenhouse Gas Cycles Data Insight](https://earth.gov/ghgcenter/stories/tracking-greenhouse-gas-cycles). + - See how NOAA’s GHG observations have contributed to the understanding of GHG fluxes from human-caused and natural sources in the Tracking Greenhouse Gas Cycles Data Insight - [Learn more about the Global Greenhouse Gas Reference Network (GGGRN)](https://gml.noaa.gov/ccgg/about.html) ## Acknowledgment diff --git a/datasets/noaa-cpfp-co2-point.data.mdx b/datasets/noaa-cpfp-co2-point.data.mdx index 9ac390abd..7649f00f0 100644 --- a/datasets/noaa-cpfp-co2-point.data.mdx +++ b/datasets/noaa-cpfp-co2-point.data.mdx @@ -13,7 +13,7 @@ usage: label: Download data from NOAA title: 'Data Browser' media: - src: ::file ./noaa-air-samples--cover.png + src: ::file ./media/noaa-air-samples--cover.png alt: aa author: name: Columbia University @@ -185,7 +185,7 @@ layers: ## Learn More - [View current trends in CO₂](https://gml.noaa.gov/ccgg/trends/) powered by NOAA data - - See NOAA’s observations of CO₂ at the Mauna Loa Observatory featured in the [Tracking Greenhouse Gas Cycles Data Insight](https://earth.gov/ghgcenter/stories/tracking-greenhouse-gas-cycles). The Mauna Loa CO₂ data provides the longest record of direct measurements of CO₂ in Earth’s atmosphere. + - See NOAA’s observations of CO₂ at the Mauna Loa Observatory featured in the Tracking Greenhouse Gas Cycles Data Insight - [Learn more about the Global Greenhouse Gas Reference Network (GGGRN)](https://gml.noaa.gov/ccgg/about.html) ## Acknowledgment diff --git a/datasets/oco2-mip-co2budget-yeargrid-v1.data.mdx b/datasets/oco2-mip-co2budget-yeargrid-v1.data.mdx index e441a9038..f0b10d06c 100644 --- a/datasets/oco2-mip-co2budget-yeargrid-v1.data.mdx +++ b/datasets/oco2-mip-co2budget-yeargrid-v1.data.mdx @@ -16,7 +16,7 @@ usage: label: Browse and download the data title: Data Browser media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1--cover.jpg + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1--cover.jpg alt: mean net emissions and removals of carbon dioxide author: name: NASA/JPL @@ -101,7 +101,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.biosphere.exchange.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.biosphere.exchange.png alt: OCO-2 MIP Top-down CO₂ Budgets - LNLGIS Net Biosphere Exchange (LNLGIS_NBE) - id: co2-emissions-lnlgis-nbe-std stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -158,7 +158,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.biosphere.exchange.uncertainty.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.biosphere.exchange.uncertainty.png alt: OCO-2 MIP Top-down CO₂ Budgets - Uncertainty - LNLGIS Net Biosphere Exchange (LNLGIS_NBE_std) - id: co2-emissions-lnlgis-nce stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -215,7 +215,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.net.carbon.exchange.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.net.carbon.exchange.png alt: OCO-2 MIP Top-down CO₂ Budgets - LNLGIS Net Carbon Exchange (LNLGIS_NCE) - id: co2-emissions-lnlgis-nce-std stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -272,7 +272,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.net.carbon.exchange.uncertainty.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.net.carbon.exchange.uncertainty.png alt: OCO-2 MIP Top-down CO₂ Budgets - Uncertainty - LNLGIS Net Carbon Exchange (LNLGIS_NCE_std) - id: co2-emissions-lnlgis-dc-loss stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -329,7 +329,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.net.land.carbon.stock.loss.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.net.land.carbon.stock.loss.png alt: OCO-2 MIP Top-down CO₂ Budgets - LNLGIS Net Land Carbon Stock Loss (LNLGIS_dC_loss) - id: co2-emissions-lnlgis-dc-loss-std stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -386,7 +386,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.net.land.carbon.stock.loss.uncertainty.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.net.land.carbon.stock.loss.uncertainty.png alt: OCO-2 MIP Top-down CO₂ Budgets - Uncertainty LNLGIS Net Land Carbon Stock Loss (LNLGIS_dC_loss_std) - id: co2-emissions-crop stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -443,7 +443,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.crop.co2.flux.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.crop.co2.flux.png alt: OCO-2 MIP Top-down CO₂ Budgets - Lateral Crop CO₂ Flux (Crop) - id: co2-emissions-crop-std stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -500,7 +500,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.crop.co2.flux.uncertainty.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.crop.co2.flux.uncertainty.png alt: OCO-2 MIP Top-down CO₂ Budgets - Uncertainty - Lateral Crop CO₂ Flux (Crop_std) - id: co2-emissions-ff stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -557,7 +557,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.fossil.fuel.cement.co2.emissions.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.fossil.fuel.cement.co2.emissions.png alt: OCO-2 MIP Top-down CO₂ Budgets - Fossil Fuel and Cement CO₂ Emissions (FF) - id: co2-emissions-ff-std stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -614,7 +614,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.fossil.fuel.cement.co2.emissions.uncertainty.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.fossil.fuel.cement.co2.emissions.uncertainty.png alt: OCO-2 MIP Top-down CO₂ Budgets - Uncertainty - Fossil Fuel and Cement CO₂ Emissions (FF_std) - id: co2-emissions-river stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -671,7 +671,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.river.co2.flux.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.river.co2.flux.png alt: OCO-2 MIP Top-down CO₂ Budgets - Lateral River CO₂ Flux (River) - id: co2-emissions-river-std stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -728,7 +728,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.river.co2.flux.uncertainty.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.river.co2.flux.uncertainty.png alt: OCO-2 MIP Top-down CO₂ Budgets - Uncertainty - Lateral River CO₂ Flux (River_std) - id: co2-emissions-wood stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -785,7 +785,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.wood.co2.flux.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.wood.co2.flux.png alt: OCO-2 MIP Top-down CO₂ Budgets - Lateral Wood CO₂ Flux (Wood) - id: co2-emissions-wood-std stacCol: oco2-mip-co2budget-yeargrid-v1 @@ -842,7 +842,7 @@ layers: temporalResolution: Annual unit: g CO₂/m²/yr media: - src: ::file ./oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.wood.co2.flux.uncertainty.png + src: ::file ./media/oco2-mip-co2budget-yeargrid-v1.thumbnails.lateral.wood.co2.flux.uncertainty.png alt: OCO-2 MIP Top-down CO₂ Budgets - Uncertainty - Lateral Wood CO₂ Flux (Wood_std) --- @@ -883,7 +883,7 @@ layers: Leveraging the OCO-2 MIP, the surface-atmosphere CO₂ fluxes are estimated from four standardized experiments of which one is included in the Center: - LNLGIS: both in situ CO₂ measurements from the National Oceanic and Atmospheric Administration (NOAA) Observation Package [ObsPack](https://gml.noaa.gov/ccgg/obspack/) and column-averaged CO₂ dry air mole fraction (XCO₂) retrievals from NASA’s Orbiting Carbon Observatory-2 (OCO-2) Land Nadir and Land Glint data - For the LNLGIS experiment, net carbon exchange (NCE) and ocean CO₂ fluxes are optimized to match the atmospheric CO₂ observations within their uncertainties. The net biosphere exchange (NBE) is calculated by subtracting bottom-up fossil fuel emission estimates from NCE. The net loss of land carbon is then estimated by accounting for “lateral” carbon fluxes from the terrestrial biosphere such as land-to-ocean transport of carbon by rivers and the import and export of harvested agricultural and wood products. Changes in terrestrial carbon stocks (ΔCloss) reflect the combined impact of direct anthropogenic activities and changes to managed ecosystems in response to rising atmospheric CO2 concentrations, climate change, and disturbances (i.e., droughts, floods, wildfires, severe weather). + For the LNLGIS experiment, net carbon exchange (NCE) and ocean CO₂ fluxes are optimized to match the atmospheric CO₂ observations within their uncertainties. The net biosphere exchange (NBE) is calculated by subtracting bottom-up fossil fuel emission estimates from NCE. The net loss of land carbon is then estimated by accounting for “lateral” carbon fluxes from the terrestrial biosphere such as land-to-ocean transport of carbon by rivers and the import and export of harvested agricultural and wood products. Changes in terrestrial carbon stocks (ΔCloss) reflect the combined impact of direct anthropogenic activities and changes to managed ecosystems in response to rising atmospheric CO₂ concentrations, climate change, and disturbances (i.e., droughts, floods, wildfires, severe weather). The US GHG Center explore view only highlights flux estimates from the LNLGIS experiment, but the full dataset with all layers and national totals can be accessed on the [CEOS website](https://ceos.org/gst/carbon-dioxide.html). In addition, the following Jupyter Notebook demonstrates how to read, visualize and explore statistics for the national (i.e. country level) CO₂ budget data: [OCO-2 MIP National CO₂ Budget Notebook](https://us-ghg-center.github.io/ghgc-docs/user_data_notebooks/oco2-mip-National-co2budget.html). @@ -912,7 +912,7 @@ layers: - Environmental Restoration and Conservation Agency of Japan - Korea Meteorological Administration - A full accounting of acknowledgements can be found in the “Acknowledgements” section of the Byrne et al. publication: [https://doi.org/10.5194/essd-15-963-2023](https://doi.org/10.5194/essd-15-963-2023). + A full accounting of acknowledgments can be found in the “Acknowledgements” section of the Byrne et al. publication: [https://doi.org/10.5194/essd-15-963-2023](https://doi.org/10.5194/essd-15-963-2023). ## License [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/legalcode) (CC BY 4.0) diff --git a/datasets/oco2geos-co2-daygrid-v10r.data.mdx b/datasets/oco2geos-co2-daygrid-v10r.data.mdx index 002387ad2..bfea4c86c 100644 --- a/datasets/oco2geos-co2-daygrid-v10r.data.mdx +++ b/datasets/oco2geos-co2-daygrid-v10r.data.mdx @@ -17,7 +17,7 @@ usage: title: Data Browser media: - src: ::file ./oco--dataset-cover.jpg + src: ::file ./media/oco--dataset-cover.jpg alt: Smoking Factory author: name: Johannes Plenio @@ -93,7 +93,7 @@ layers: temporalResolution: Daily unit: ppm media: - src: ::file ./oco2geos-co2-daygrid-v10r.thumbnails.daily.png + src: ::file ./media/oco2geos-co2-daygrid-v10r.thumbnails.daily.png alt: OCO-2 GEOS Column CO₂ Concentrations - Average Dry-Air Column CO₂ (XCO₂) --- @@ -123,7 +123,7 @@ layers: ## Disclaimer This datasethas been transformed from the original format (NetCDF) into Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) for display in the US GHG Center. Careful quality checks are used to ensure data transformation has been performed correctly. Apart from the data format, the OCO-2 GEOS Assimilated CO₂ Concentrations dataset is identical to the [OCO2_GEOS_L3CO2_DAY dataset available at GES DISC](https://doi.org/10.5067/Y9M4NM9MPCGH). - The full title of the dataset, [OCO-2 GEOS Level 3 daily, 0.5x0.625 assimilated CO2 V10r](https://doi.org/10.5067/Y9M4NM9MPCGH), has been shortened for display on the GHG Center website. The short name of the source dataset is [OCO2_GEOS_L3CO2_DAY](https://doi.org/10.5067/Y9M4NM9MPCGH), but it is referred to as oco2geos-co2-daygrid-v10r in the GHG Center system. + The full title of the dataset, [OCO-2 GEOS Level 3 daily, 0.5x0.625 assimilated CO₂ V10r](https://doi.org/10.5067/Y9M4NM9MPCGH), has been shortened for display on the GHG Center website. The short name of the source dataset is [OCO2_GEOS_L3CO2_DAY](https://doi.org/10.5067/Y9M4NM9MPCGH), but it is referred to as oco2geos-co2-daygrid-v10r in the GHG Center system. Users should understand that during Arctic and Antarctic nights and in cloudy conditions, there is no observational coverage from OCO-2. The data assimilation approach to gap filling ensures that when direct OCO-2 observations are unavailable, concentration estimates are informed by a combination of upwind OCO-2 observations, observations of land surface processes, and millions of meteorological observations that constrain atmospheric circulation. @@ -149,7 +149,7 @@ layers: Yuen, K. (n.d.). *Home*. Orbiting Carbon Observatory-2. [https://ocov2.jpl.nasa.gov/](https://ocov2.jpl.nasa.gov/) ## Learn More - - Learn more about how OCO-2 observations and measurements from other satellites contribute to GHG monitoring and models in the [Tracking Greenhouse Gas Cycles Data Insight](https://earth.gov/ghgcenter/stories/tracking-greenhouse-gas-cycles) + - Learn more about how OCO-2 observations and measurements from other satellites contribute to GHG monitoring and models in the Tracking Greenhouse Gas Cycles Data Insight - Learn more about the [OCO-2 mission](https://ocov2.jpl.nasa.gov/) ## Acknowledgment diff --git a/datasets/odiac-ffco2-monthgrid-v2023.data.mdx b/datasets/odiac-ffco2-monthgrid-v2023.data.mdx index ebe47f51f..803d17271 100644 --- a/datasets/odiac-ffco2-monthgrid-v2023.data.mdx +++ b/datasets/odiac-ffco2-monthgrid-v2023.data.mdx @@ -16,7 +16,7 @@ usage: label: Browse and download the data title: Data Browser media: - src: ::file ./odiac--dataset-cover.jpg + src: ::file ./media/odiac--dataset-cover.jpg alt: White smoke coming from building author: name: Marcin Jozwiak @@ -109,7 +109,7 @@ layers: temporalResolution: Monthly unit: tonne C/km²/month media: - src: ::file ./odiac-ffco2-monthgrid-v2022.thumbnails.co2.png + src: ::file ./media/odiac-ffco2-monthgrid-v2022.thumbnails.co2.png alt: ODIAC Fossil Fuel CO₂ Emissions - Fossil Fuel CO₂ Emissions --- diff --git a/datasets/sedac-popdensity-yeargrid5yr-v4.11.data.mdx b/datasets/sedac-popdensity-yeargrid5yr-v4.11.data.mdx index cc1aa77fc..f21e567ee 100644 --- a/datasets/sedac-popdensity-yeargrid5yr-v4.11.data.mdx +++ b/datasets/sedac-popdensity-yeargrid5yr-v4.11.data.mdx @@ -16,7 +16,7 @@ usage: label: Browse and download the data title: Data Browser media: - src: ::file ./gpw-yearly--cover.jpg + src: ::file ./media/gpw-yearly--cover.jpg alt: aa author: name: Columbia University @@ -90,7 +90,7 @@ layers: temporalResolution: Annual unit: persons/km² media: - src: ::file ./sedac-popdensity-yeargrid5yr-v4.11.thumbnails.population.density.png + src: ::file ./media/sedac-popdensity-yeargrid5yr-v4.11.thumbnails.population.density.png alt: SEDAC Gridded World Population Density - Population Density --- diff --git a/datasets/tm54dvar-ch4flux-monthgrid-v1.data.mdx b/datasets/tm54dvar-ch4flux-monthgrid-v1.data.mdx index 4faaf81ff..5fea4f44e 100644 --- a/datasets/tm54dvar-ch4flux-monthgrid-v1.data.mdx +++ b/datasets/tm54dvar-ch4flux-monthgrid-v1.data.mdx @@ -17,7 +17,7 @@ usage: title: Data Browser media: - src: ::file ./tm5--dataset-cover.jpg + src: ::file ./media/tm5--dataset-cover.jpg alt: Landfill author: name: Katie Rodriguez @@ -102,7 +102,7 @@ layers: temporalResolution: Monthly unit: g CH₄/m²/year media: - src: ::file ./tm54dvar-ch4flux-monthgrid-v1.thumbnails.total.png + src: ::file ./media/tm54dvar-ch4flux-monthgrid-v1.thumbnails.total.png alt: TM5-4DVar Isotopic CH₄ Inverse Fluxes - Total CH₄ Emission - id: microbial-ch4 stacCol: tm54dvar-ch4flux-mask-monthgrid-v1 @@ -158,7 +158,7 @@ layers: temporalResolution: Monthly unit: g CH₄/m²/year media: - src: ::file ./tm54dvar-ch4flux-monthgrid-v1.thumbnails.microbial.png + src: ::file ./media/tm54dvar-ch4flux-monthgrid-v1.thumbnails.microbial.png alt: TM5-4DVar Isotopic CH₄ Inverse Fluxes - Microbial CH₄ Emission - id: fossil-ch4 stacCol: tm54dvar-ch4flux-mask-monthgrid-v1 @@ -214,7 +214,7 @@ layers: temporalResolution: Monthly unit: g CH₄/m²/year media: - src: ::file ./tm54dvar-ch4flux-monthgrid-v1.thumbnails.fossil.png + src: ::file ./media/tm54dvar-ch4flux-monthgrid-v1.thumbnails.fossil.png alt: TM5-4DVar Isotopic CH₄ Inverse Fluxes - Fossil CH₄ Emission - id: pyrogenic-ch4 stacCol: tm54dvar-ch4flux-mask-monthgrid-v1 @@ -270,7 +270,7 @@ layers: temporalResolution: Monthly unit: g CH₄/m²/year media: - src: ::file ./tm54dvar-ch4flux-monthgrid-v1.thumbnails.pyrogenic.png + src: ::file ./media/tm54dvar-ch4flux-monthgrid-v1.thumbnails.pyrogenic.png alt: TM5-4DVar Isotopic CH₄ Inverse Fluxes - Pyrogenic CH₄ Emission --- @@ -327,7 +327,7 @@ layers: ## Learn More - Learn more about methane isotopes on [NOAA’s website](https://research.noaa.gov/2021/06/17/new-analysis-shows-microbial-sources-fueling-rise-of-atmospheric-methane/) - - Learn about how different methane isotopes can help identify methane sources in the [Tracking Greenhouse Gas Cycles Data Insight](https://earth.gov/ghgcenter/stories/tracking-greenhouse-gas-cycles) + - Learn about how different methane isotopes can help identify methane sources in the Tracking Greenhouse Gas Cycles Data Insight ## Acknowledgment This work was supported by funding from the National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA). Measurements of atmospheric methane and ¹³C of methane were supported by several partner agencies and laboratories globally as described in [Basu et al. 2022](https://doi.org/10.5194/acp-22-15351-2022). diff --git a/datasets/vulcan-co2-yeargrid-v4.data.mdx b/datasets/vulcan-co2-yeargrid-v4.data.mdx new file mode 100644 index 000000000..3326c1eff --- /dev/null +++ b/datasets/vulcan-co2-yeargrid-v4.data.mdx @@ -0,0 +1,732 @@ +--- +id: vulcan-ffco2-yeargrid-v4 +name: Vulcan Fossil Fuel CO₂ Emissions +description: Annual (2010 - 2021), 1 km resolution estimates of carbon dioxide emissions from fossil fuel combustion over the contiguous United States, version 4.0 +usage: + - url: "https://us-ghg-center.github.io/ghgc-docs/cog_transformation/vulcan-ffco2-yeargrid-v4.html" + label: Notebook showing data transformation to COG for ingest to the US GHG Center + title: 'Data Transformation Notebook' + - url: "https://us-ghg-center.github.io/ghgc-docs/datausage.html" + label: Notebooks to read, visualize, and explore data statistics + title: 'Data Usage Notebooks' + - url: "https://hub.ghg.center/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FUS-GHG-Center%2Fghgc-docs&urlpath=lab%2Ftree%2Fghgc-docs%2Fuser_data_notebooks%2Fvulcan-ffco2-yeargrid-v4_User_Notebook.ipynb&branch=main" + label: Run example notebook + title: Interactive Session in the US GHG Center JupyterHub (requires account) + - url: https://dljsq618eotzp.cloudfront.net/browseui/index.html#vulcan-ffco2-yeargrid-v4/ + label: Browse and download the data + title: Data Browser +media: + src: ::file ./media/vulcan--dataset-cover.jpg + alt: FFCO2 emissions for the year 2010-2015 for the contiguous United States + author: + name: Dr. Kevin Gurney/NAU + url: https://vulcan.rc.nau.edu/Data.html +taxonomy: + - name: Topics + values: + - Anthropogenic Emissions + - Urban + - name: Source + values: + - NAU + - NASA + - NOAA + - NSF + - name: Gas + values: + - CO₂ + - name: Product Type + values: + - Hybrid Product +sourceExclusive: NSF +infoDescription: | + ::markdown + - Temporal Extent: 2010 - 2021 + - Temporal Resolution: Annual + - Spatial Extent: Contiguous United States + - Spatial Resolution: 1km x 1km + - Data Units: Metric tons of carbon dioxide per 1 km x 1 km grid cell per year (tonne CO₂/km²/year) + - Data Type: Research + - Data Latency: Updated annually +layers: + - id: vulcan-total-co2 + stacCol: vulcan-ffco2-yeargrid-v4 + name: Total Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual CO₂ emissions from fossil fuel combustion (ffCO₂) across all sectors. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: total-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-yeargrid-v4 + layerId: vulcan-total-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/vulcan-co2-yeargrid-v4.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions + + - id: vulcan-air-co2 + stacCol: vulcan-ffco2-yeargrid-v4 + name: Airport Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual ffCO₂ emissions from taxi, take-off, and landing up to 3000 ft. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: air-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-yeargrid-v4 + layerId: vulcan-air-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/vulcan-co2-yeargrid-v4.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions + - id: vulcan-cmt-co2 + stacCol: vulcan-ffco2-yeargrid-v4 + name: Cement Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual ffCO₂ emissions from cement production. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: cmt-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-yeargrid-v4 + layerId: vulcan-cmt-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/vulcan-co2-yeargrid-v4.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions + - id: vulcan-cmv-co2 + stacCol: vulcan-ffco2-yeargrid-v4 + name: Commercial Marine Vessel Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual ffCO₂ emissions from commercial marine vessels while maneuvering, hoteling, cruising and traveling within reduced speed zones at ports and shipping lanes. Includes only activity within 12 nautical miles (~22km) from the U.S. shoreline. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: cmv-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-yeargrid-v4 + layerId: vulcan-cmv-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/vulcan-co2-yeargrid-v4.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions + - id: vulcan-com-co2 + stacCol: vulcan-ffco2-yeargrid-v4 + name: Commercial Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual ffCO₂ emissions from Commercial buildings. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: com-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-yeargrid-v4 + layerId: vulcan-com-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/vulcan-co2-yeargrid-v4.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions + - id: vulcan-elc-co2 + stacCol: vulcan-ffco2-yeargrid-v4 + name: Power Plant Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual ffCO₂ emissions from power plants. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: elc-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-yeargrid-v4 + layerId: vulcan-elc-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/vulcan-co2-yeargrid-v4.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions + - id: vulcan-ind-co2 + stacCol: vulcan-ffco2-yeargrid-v4 + name: Industrial Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual ffCO₂ emissions from Industrial buildings. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: ind-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-yeargrid-v4 + layerId: vulcan-ind-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/vulcan-co2-yeargrid-v4.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions + - id: vulcan-nrd-co2 + stacCol: vulcan-ffco2-yeargrid-v4 + name: Nonroad Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual ffCO₂ emissions from off-road engines, equipment and vehicles including waterborne pleasure craft. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: nrd-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-yeargrid-v4 + layerId: vulcan-nrd-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/vulcan-co2-yeargrid-v4.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions + - id: vulcan-onr-co2 + stacCol: vulcan-ffco2-yeargrid-v4 + name: Onroad Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual ffCO₂ emissions from mobile vehicles on roads. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: onr-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-yeargrid-v4 + layerId: vulcan-onr-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/vulcan-co2-yeargrid-v4.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions + - id: vulcan-res-co2 + stacCol: vulcan-ffco2-yeargrid-v4 + name: Residential Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual ffCO₂ emissions from Residential buildings. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: res-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-elc-res-yeargrid-v4 + layerId: vulcan-elc-res-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/vulcan-co2-yeargrid-v4.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions + - id: vulcan-rrd-co2 + stacCol: vulcan-ffco2-yeargrid-v4 + name: Railroad Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual ffCO₂ emissions coming from railroads. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: rrd-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-yeargrid-v4 + layerId: vulcan-rrd-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + exclude: true + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/vulcan-co2-yeargrid-v4.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions +--- + + + + **Temporal Extent:** 2010 - 2021
+ **Temporal Resolution:** Annual
+ **Spatial Extent:** Contiguous United States
+ **Spatial Resolution:** 1 km x 1 km
+ **Data Units:** Metric tons of carbon dioxide per 1 km x 1 km grid cell per year (tonne CO₂/km²/year)
+ **Data Type:** Research
+ **Data Latency:** Updated annually
+ + The Vulcan version 4.0 data product represents total carbon dioxide (CO₂) emissions resulting from the combustion of fossil fuel (ff) for the contiguous United States and District of Columbia. Referred to as ffCO₂, the emissions from Vulcan are also categorized into 10 source sectors including; airports, cement production, commercial marine vessels, commercial, power plants, industrial, non-road, on-road, residential and railroads. Data are gridded annually on a 1-km grid for the years 2010 to 2021. These data are annual sums of hourly estimates. Shown is the estimated total annual ffCO₂ for the United States, as well as the estimated total annual ffCO₂ per sector. + + The Vulcan Project is a multiagency (NASA, NOAA, NSF) funded effort under the North American Carbon Program (NACP) to quantify North American fossil fuel carbon dioxide (ffCO₂) emissions at space and time scales much finer than has been achieved in the past. The purpose is to aid in quantification of the North American carbon budget, to support inverse estimation of carbon sources and sinks, and to support the demands posed by higher resolution ffCO₂ observations (in situ and remotely sensed). The detail and scope of the Vulcan ffCO₂ inventory has also made it a valuable tool for policymakers, demographers, social scientists and the public at large. + + + + +
+ +
+ + + + ## Source Data Product Citation + This data product will soon be available at the NASA Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC). Once available, the data product citation will be provided here. In the meantime, please refer to the [Gurney et al. 2020 publication](https://doi.org/10.1029/2020JD032974) for more information. + + ## Disclaimer + This dataset has been transformed from the original format (GeoTIFF) into Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) for display in the US GHG Center. Careful quality checks are used to ensure data transformation has been performed correctly. + + The Vulcan data product is an attempt to estimate fossil fuel CO₂ (ffCO₂) emissions at fine time and space scales. It should be considered a “climatology” of emissions rather than the “weather” of emissions. This means that the estimates represent “typical” emissions at a specific time and place (average conditions). Hence, it is not considered appropriate to use in comparison to short-term “campaign” style atmospheric measurements (e.g. 5 days of continuous monitoring at a specific location) without consideration of the mismatch between the measurement and the Vulcan estimation approach. + + ## Scientific Details + Vulcan covers 10 emission source sectors and is constructed from numerous public datasets that generate the emissions’ magnitude in addition to space and time distributions. The ffCO₂ emissions are estimated at a mixture of spatial and temporal resolutions (e.g., polygons, points, lines, annual, hourly) depending upon the characteristics of the incoming data sources and spatialization/temporalization techniques. Hence, some sources receive spatial and temporal “conditioning” (e.g., downscaling, interpolation, proxy surrogates) to arrive at the mix of spatial resolutions (point, polylines, polygons) and hourly resolution for each of the years spanning the 2010-2021 period. The emissions are typically gridded to spatial resolutions coarser than 0.5 km x 0.5 km. Please refer to the [Vulcan data derivation notes](https://drive.google.com/file/d/1NyIvUW-ABCkf5AUZezKSVma0F4TwAG2d/view?usp=drive_link) for further detail on the methods for estimating emissions in the largest sectors: electricity production, industrial, on-road, and residential/commercial emissions. Methods for the remaining sectors: airport, railroad, commercial marine vessels, non-road, and cement can be found in [Gurney et al., 2020](https://doi.org/10.1029/2020JD032974) which describes the previous version of Vulcan, [Vulcan v3.0](https://doi.org/10.3334/ORNLDAAC/1741). + + ## Key Publications + Gurney, K. R., Liang, J., Patarasuk, R., Song, Y., Huang, J., & Roest, G. (2020). The Vulcan Version 3.0 High-Resolution Fossil Fuel CO₂ Emissions for the United States. *Journal of Geophysical Research: Atmospheres, 125*(19), e2020JD032974. [https://doi.org/10.1029/2020JD032974](https://doi.org/10.1029/2020JD032974) + + ## Other Relevant Publications + Gurney, K. R., Mendoza, D. L., Zhou, Y., Fischer, M. L., Miller, C. C., Geethakumar, S., de la Rue du Can, S. (2009). High Resolution Fossil Fuel Combustion CO₂ Emission Fluxes for the United States. *Environmental Science & Technology, 43*(14), 5535-5541. [https://doi.org/10.1021/es900806c](https://doi.org/10.1021/es900806c) + + ## Learn More + - Learn more about how decision-makers and researchers can leverage Vulcan data + - Learn more about the Vulcan project at the [Vulcan website](https://vulcan.rc.nau.edu/About.html) + + ## Acknowledgment + The Vulcan team would like to thank the NAU High-Performance Computing team for access and use of the NAU HPC system (“Monsoon”). + + ## License + [Creative Commons Attribution Non Commercial No Derivatives 4.0 International](https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode) (CC-BY-NC-ND-4.0) + + This data product is made freely available to the public and the scientific community in the belief that its wide dissemination will lead to greater scientific understanding and policy insights. The availability of this data product does not constitute publication of the data product or permission to use the information contained in the data product for publication or any commercial use. Please refer to the [Vulcan data Terms of Use for further information](https://vulcan.rc.nau.edu/assets/files/Terms.of.Use.12.20.2018.pdf). + + ## Data Stewardship + - [Data Workflow](https://us-ghg-center.github.io/ghgc-docs/data_workflow/vulcan-ffco2-yeargrid-v4_Data_Flow.html) + - [Data Transformation Code](https://us-ghg-center.github.io/ghgc-docs/cog_transformation/vulcan-ffco2-yeargrid-v4.html) + - [US GHG Center Data Intake Processing and Verification Report](https://us-ghg-center.github.io/ghgc-docs/processing_and_verification_reports/vulcan-ffco2-yeargrid-v4_Processing%20and%20Verification%20Report.html) + + + diff --git a/datasets/vulcan-ffco2-elc-res-yeargrid-v4.data.mdx b/datasets/vulcan-ffco2-elc-res-yeargrid-v4.data.mdx new file mode 100644 index 000000000..5d545f944 --- /dev/null +++ b/datasets/vulcan-ffco2-elc-res-yeargrid-v4.data.mdx @@ -0,0 +1,174 @@ +--- +id: vulcan-ffco2-elc-res-yeargrid-v4 +name: Vulcan Fossil Fuel CO₂ Emissions, Version 4 +description: Annual (2010 - 2021), 1 km resolution estimates of carbon dioxide emissions from fossil fuels and cement production over the contiguous United States, version 4.0 +isHidden: true +usage: + - url: "https://us-ghg-center.github.io/ghgc-docs/cog_transformation/vulcan-ffco2-yeargrid-v4.html" + label: Notebook showing data transformation to COG for ingest to the US GHG Center + title: 'Data Transformation Notebook' + - url: "https://us-ghg-center.github.io/ghgc-docs/datausage.html" + label: Notebooks to read, visualize, and explore data statistics + title: 'Data Usage Notebooks' + - url: "https://hub.ghg.center/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FUS-GHG-Center%2Fghgc-docs&urlpath=lab%2Ftree%2Fghgc-docs%2Fuser_data_notebooks%2Fvulcan-ffco2-yeargrid-v4_User_Notebook.ipynb&branch=main" + label: Run example notebook + title: Interactive Session in the US GHG Center JupyterHub (requires account) + - url: https://dljsq618eotzp.cloudfront.net/browseui/index.html#vulcan-ffco2-yeargrid-v4/ + label: Browse and download the data + title: Data Browser +media: + src: ::file ./media/tm5--dataset-cover.jpg + alt: Static rendering of oceanic currents with arrow indicators for cycle direction and strength + author: + name: NASA's Science Visualization Studio (SVS) + url: https://svs.gsfc.nasa.gov/12629/ +taxonomy: + - name: Topics + values: + - Anthropogenic Emissions + - name: Source + values: + - NAU + - NASA + - NOAA + - NSF + - name: Gas + values: + - CO₂ + - name: Product Type + values: + - Model Output +infoDescription: | + ::markdown + - Temporal Extent: 2010 - 2021 + - Temporal Resolution: Annual + - Spatial Extent: Contiguous United States + - Spatial Resolution: 1km x 1km + - Data Units: Units are metric tonnes of CO₂ per 1 km x 1 km cell per year (tC/km²/year) + - Data Type: Research + - Data Latency: Updated annually +layers: + - id: vulcan-elc-res-co2 + stacCol: vulcan-ffco2-elc-res-yeargrid-v4 + name: Scope 2 Residential Fossil Fuel CO₂ Emissions + type: raster + description: Estimated total annual CO₂ emissions from fossil fuel combustion (ffCO₂) across all sectors. + initialDatetime: newest + projection: + id: "equirectangular" + zoomExtent: + - 0 + - 20 + sourceParams: + assets: elc-res-co2 + colormap_name: spectral_r + rescale: + - 0 + - 500 + compare: + datasetId: vulcan-ffco2-yeargrid-v4 + layerId: vulcan-total-co2 + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + } + legend: + unit: + label: tonne CO₂/km²/year + type: gradient + min: 0 + max: 500 + stops: + - '#5e4fa2' + - '#388eba' + - '#75c8a5' + - '#bfe5a0' + - '#f1f9a9' + - '#feeea2' + - '#fdbf6f' + - '#f67b4a' + - '#d8434e' + - '#9e0142' + analysis: + metrics: + - mean + sourceParams: + dst_crs: "+proj=cea" + info: + source: NASA + spatialExtent: Global + temporalResolution: Annual + unit: tonne CO₂/km²/year + + media: + src: ::file ./media/tm54dvar-ch4flux-monthgrid-v1.thumbnails.total.png + alt: Rendered Fossil Fuel CO₂ Emissions +--- + + + + **Temporal Extent:** 2021
+ **Temporal Resolution:** Annual
+ **Spatial Extent:** Contiguous United States
+ **Spatial Resolution:** 1km x 1km
+ **Data Units:** Metric tons of carbon dioxide per 1 km x 1 km grid cell per year (tonne CO₂/km²/year)
+ **Data Type:** Research
+ **Data Latency:** Updated annually
+ + The Vulcan version 4.0 data product represents total carbon dioxide (CO₂) emissions resulting from the combustion of fossil fuel (ff) for the contiguous United States and District of Columbia. Referred to as ffCO₂, the emissions from Vulcan are also categorized into 10 source sectors including; airports, cement production, commercial marine vessels, commercial, power plants, industrial, non-road, on-road, residential and railroads. Data are gridded annually on a 1-km grid for the years 2010 to 2021. These data are annual sums of hourly estimates. Shown is the estimated total annual ffCO₂ for the United States, as well as the estimated total annual ffCO₂ per sector. + + The Vulcan Project is a multiagency (NASA, DOE, NOAA, NIST) funded effort under the North American Carbon Program (NACP) to quantify North American fossil fuel carbon dioxide (ffCO₂) emissions at space and time scales much finer than has been achieved in the past. The purpose is to aid in quantification of the North American carbon budget, to support inverse estimation of carbon sources and sinks, and to support the demands posed by higher resolution ffCO₂ observations (in situ and remotely sensed). The detail and scope of the Vulcan ffCO₂ inventory has also made it a valuable tool for policymakers, demographers, social scientists and the public at large. + + + + + + ## Source Data Product Citation + Gurney, K.R., J. Liang, R. Patarasuk, Y. Song, J. Huang, and G. Roest. 2019. Vulcan: High-Resolution Annual Fossil Fuel CO₂ Emissions in USA, 2010-2015, Version 3. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1741 + + ## Dataset Accuracy + Uncertainty in the ffCO₂ emissions were accounted for within each sector and quantified as the 95% confidence interval bounds. High and low bounds for each sector were gridded in addition to the mean emissions estimates. More information on uncertainty bounds are available in the peer-reviewed paper (see section 2). + + The uncertainty of the Vulcan results are estimated by attempting to capture key input parameter variation. This is accomplished by completing a simulation with key input parameters (e.g. CO emission factor, CO₂ emission factor, CO emissions) set at their upper and lower range (an approximate 95% confidence interval). These two additional simulations estimated total annual domain ffCO₂ emissions as -14.0%/+16.6% of the central estimate for the example year of 2011. Two separate techniques are used to test the general quality of the Vulcan v3.0 ffCO₂ emissions estimate. The first is a comparison to other similar space/time-resolved ffCO₂ emission data products. Comparison to the ACES granular ffCO₂ estimate which only covers 13 Northeastern states was performed. In this comparison, total relative difference of 1.7% (ACES>Vulcan) was found, but much larger differences at the grid cell scale with a grid cell absolute median relative difference of 53.4%. Vulcan v3.0 results were also compared to the ODIAC global gridded ffCO₂ emissions data product which found a total relative difference of 6.9% (100.3 MtC/yr; Vulcan>ODIAC) in 2011. At the grid cell-scale a grid cell absolute median relative difference of 104.4% was observed. See Gurney et al. (2020) for more details. A second approach that compared the results presented here to atmospheric CO₂ inverse estimates was performed. At the whole contiguous US spatial scale and annual temporal scale, the 2010 Vulcan results were within 1.4% of an atmospheric 14CO₂ inversion effort (Basu et al., 2020). + + ## Disclaimer + This dataset has been transformed from the original format (GeoTIFF) into Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) for display in the US GHG Center. Careful quality checks are used to ensure data transformation has been performed correctly. + + The Vulcan data product is an attempt to estimate fossil fuel CO₂ (ffCO₂) emissions at fine time and space scales. It should be considered a “climatology” of emissions rather than the “weather” of emissions. This means that the estimates represent “typical” emissions at a specific time and place (average conditions). Hence, it is not considered appropriate to use in comparison to short-term “campaign” style atmospheric measurements (e.g. 5 days of continuous monitoring at a specific location) without consideration of the mismatch between the measurement and the Vulcan estimation approach. + + ## Scientific Details + Vulcan covers 10 emission source sectors and is constructed from numerous public datasets that generate the emissions’ magnitude in addition to space and time distributions. The ffCO₂ emissions are estimated at a mixture of spatial and temporal resolutions (e.g., polygons, points, lines, annual, hourly) depending upon the characteristics of the incoming data sources and spatialization/temporalization techniques. Hence, some sources receive spatial and temporal “conditioning” (e.g., downscaling, interpolation, proxy surrogates) to arrive at the mix of spatial resolutions (point, polylines, polygons) and hourly resolution for each of the years spanning the 2010-2021 period. The emissions are typically gridded to spatial resolutions coarser than 0.5km x 0.5 km and temporal resolutions coarser than hourly. Please refer to the [Vulcan data derivation notes](https://docs.google.com/document/d/1DCwFoMdDy8xGJ-zcdX8IkNwo6cEwFc7E7Xu47IgE2Ik/edit?usp=sharing) for further detail on the methods for estimating emissions in the largest sectors: electricity production, industrial, on-road, and residential/commercial emissions. Methods for the remaining sectors: airport, railroad, commercial marine vessels, non-road, and cement can be found in [Gurney et al., 2020](https://doi.org/10.1029/2020JD032974) which describes the previous version of Vulcan, [Vulcan v3.0](https://doi.org/10.3334/ORNLDAAC/1741). + + ## Key Publications + Gurney, K.R., J. Liang, R. Patarasuk, Y. Song, J. Huang, G. Roest (2020). The Vulcan Version 3.0 High-Resolution Fossil Fuel CO₂ Emissions for the United States. Journal of Geophysical Research: Atmospheres, 125(19), e2020JD032974. [https://doi.org/10.1029/2020JD032974](https://doi.org/10.1029/2020JD032974) + + User guide: https://daac.ornl.gov/daacdata/nacp/Vulcan_V3_Annual_Emissions/comp/Vulcan_V3_Annual_Emissions.pdf + + ReadMe: https://daac.ornl.gov/daacdata/nacp/Vulcan_V3_Annual_Emissions/comp/readme.Vulcan.1km.V3.0.annual.pdf + + ## Other Relevant Publications + Gurney, K. R., Mendoza, D. L., Zhou, Y., Fischer, M. L., Miller, C. C., Geethakumar, S., de la Rue du Can, S. (2009). High Resolution Fossil Fuel Combustion CO₂ Emission Fluxes for the United States. Environmental Science & Technology, 43(14), 5535-5541. [https://doi.org/10.1021/es900806c](https://doi.org/10.1021/es900806c) + + ## Learn More + - Link to Vulcan story (once available) + - Learn more about the Vulcan project at the [Vulcan website](https://vulcan.rc.nau.edu/About.html) + + ## Acknowledgment + The Vulcan data product represents many years of development by many people with support from NASA. If you use the Vulcan data product in your research, it is recommended that you contact Dr. Kevin Gurney to assure that the data product is being used in a way consistent with its strengths and weaknesses. In some instances, it is considered appropriate to include the Vulcan team in publications resulting from use of the Vulcan data product. At a minimum, the Vulcan team kindly requests that you cite the database DOI and peer-reviewed paper establishing the data product (citations below) and acknowledge the funding agencies that have supported the Vulcan development. + + The following is the correct acknowledgement: + “The Vulcan v3.0 data product was made possible through support from the National Aeronautics and Space Administration grant NNX14AJ20G and the NASA Carbon Monitoring System program, Understanding User Needs for Carbon Information project (subcontract 1491755).” + + Please cite both the dataset DOI (https://doi.org/10.3334/ORNLDAAC/1741) and the peer-reviewed publication: + Gurney, K.R., J. Liang, R. Patarasuk, Y. Song, J. Huang, G. Roest (2020). The Vulcan Version 3.0 High-Resolution Fossil Fuel CO₂ Emissions for the United States. Journal of Geophysical Research: Atmospheres, 125(19), e2020JD032974. [https://doi.org/10.1029/2020JD032974](https://doi.org/10.1029/2020JD032974) + + ## License + [Creative Commons Attribution Non Commercial 4.0 International](https://creativecommons.org/licenses/by-nc/4.0/legalcode) (CC-BY-NC-4.0) + + ## Data Stewardship + - [Data Workflow](https://us-ghg-center.github.io/ghgc-docs/data_workflow/vulcan-ffco2-yeargrid-v4_Data_Flow.html) + - [Data Transformation Code](https://us-ghg-center.github.io/ghgc-docs/cog_transformation/vulcan-ffco2-yeargrid-v4.html) + - [US GHG Center Data Intake Processing and Verification Report](https://us-ghg-center.github.io/ghgc-docs/processing_and_verification_reports/vulcan-ffco2-yeargrid-v4_Processing%20and%20Verification%20Report.html) + + + diff --git a/overrides/about.mdx b/overrides/about.mdx index 1611fc48e..8a720de1e 100644 --- a/overrides/about.mdx +++ b/overrides/about.mdx @@ -2,6 +2,7 @@ title: The U.S. Greenhouse Gas Center description: Uniting Data and Technology to Empower Tomorrow's Climate Solutions --- +import { PartnerHeader } from "./common/styles"; import { SUBSCRIPTION_URL } from "../constants"; @@ -9,19 +10,17 @@ import { SUBSCRIPTION_URL } from "../constants"; The U.S. Greenhouse Gas Center (US GHG Center) is a multi-agency effort consolidating greenhouse gas (GHG) information from observations and models. Scientific experts from NASA, EPA, NIST, and NOAA worked together to curate this catalog of GHG datasets and analysis tools. The goal is to better understand GHG fluxes and emissions from natural and human-caused sources. The US GHG Center helps researchers, climate change mitigation practitioners, policymakers, data service providers, and concerned citizens understand GHG datasets and put them to use. - The initial two-year demonstration phase targets three GHG areas of study: - 1. Human-caused GHG emissions - 2. Natural GHG sources and sinks, fluxes, and patterns - 3. Methane emission leaks from large events - - The US GHG Center is built on open source principles and techniques. It allows users to access, explore, analyze, and download data and products. The US GHG Center provides access to a curated and evolving list of foundational GHG data. This includes sources such as ground observations from NASA, NIST, and NOAA; data collected from space-borne (ex. EMIT and OCO-2/3) and airborne (ex. AVIRIS-NG) platforms, and model-derived data and analyses. The US GHG Center includes curated EPA regulatory and research datasets as well as research data from NASA, NIST, and NOAA. It features data insights to introduce topics and data, user support for open data exploration via Jupyter notebooks, and an analysis hub for authorized users to perform advanced cloud data analysis with computational resources. All code supporting the US GHG Center system is fully open sourced and available for examination. - Begin your journey by exploring the “Introduction to the US GHG Center”. + The initial two-year demonstration phase focused on three GHG areas of study: human-caused GHG emissions; natural GHG sources and sinks, fluxes, and patterns; and large methane emission leak events. + + The US GHG Center portal is built using open source principles and techniques allowing users to access, explore, analyze, and download data and products and learn about the latest information. It provides access to a curated and evolving list of foundational GHG data, including sources such as: ground observations from NASA, NIST, and NOAA; data collected from space-borne (ex. EMIT and OCO-2/3), airborne (ex. AVIRIS-NG), and ground-based platforms (ex. NIST tower data); and model-derived data and analyses. The US GHG Center includes curated EPA regulatory and research datasets as well as research data from NASA, NIST, and NOAA. + + The portal features stories that introduce themes, topics, data and discoveries. User support is within reach via data exploration, Jupyter notebooks, and an analysis hub for authorized users to perform advanced cloud data analysis with computational resources. All code supporting the US GHG Center system is fully open sourced and available for examination. - Numerous stakeholder engagement activities will help scope and prioritize the evolution of US GHG Center during its 2-year demonstration phase and its longer term implementation. + Begin your journey by exploring the “Introduction to the US GHG Center.” Additional demonstration videos show users how to explore and discover data. - [Contact us](https://docs.google.com/forms/d/e/1FAIpQLSeVWCrnca08Gt_qoWYjTo6gnj1BEGL4NCUC9VEiQnXA02gzVQ/viewform) to provide ideas and suggestions for future updates. + Numerous stakeholder engagement activities continue to help scope and prioritize the evolution of the US GHG Center during continued development and implementation. - The US GHG Center contains data on greenhouse gases, emissions, and related information - all consolidated to increase the understanding and the use of GHG datasets and measurement platforms. + Use the “Contact Us” button at the top right of every page to provide the team with ideas and suggestions for future updates. @@ -31,67 +30,74 @@ import { SUBSCRIPTION_URL } from "../constants"; ## Our Partners -The US GHG Center would not be possible without the collaboration of the partnering governmental agencies and other non-governmental entities. The initial partners are the NASA, EPA, NIST, and NOAA. +The US GHG Center would not be possible without the collaboration of the partnering U.S. governmental agencies and other non-governmental entities. The initial partners of this effort are NASA, EPA, NIST, and NOAA. {" "} - - NASA logo - - -**[NASA (National Aeronautics and Space Administration)](https://www.nasa.gov/)** - NASA is the lead agency for implementing the US GHG Center. NASA Headquarters guides the Center's development with scientific and technical implementation from NASA's Marshall Space Flight Center, Goddard Space Flight Center, and the Jet Propulsion Laboratory. NASA's leadership of the US GHG Center accelerates collaborative use of Earth science data and information for GHG monitoring, measurement, reporting, and decision support. NASA plays a crucial role in expanding our understanding of the universe and advancing technology for the benefit of humanity. - + + + NASA logo +

NASA (National Aeronautics and Space Administration)

+ + + + NASA plays a crucial role in expanding our understanding of the universe and advancing technology for the benefit of humanity. As the lead agency for implementing the US GHG Center, the effort is shared among various NASA centers and coordinated by the project office at NASA Goddard Space Flight Center (GSFC). Technical development and implementation of the US GHG Center portal is carried out by a team at NASA’s Marshall Space Flight Center (MSFC), and scientists at the Jet Propulsion Laboratory produce many of the NASA datasets available from the portal (for example EMIT and various model datasets). NASA’s leadership of the US GHG Center accelerates collaborative use of Earth science data and information for GHG monitoring, measurement, reporting, and decision support. {" "} + epa logo - +

EPA (Environmental Protection Agency)

+ + -**[EPA (Environmental Protection Agency)](https://www.epa.gov/)** - The EPA is a vital agency committed to protecting human health and the environment. Through our collaboration with the EPA, we gain access to valuable resources, research, and regulatory information related to environmental issues, sustainability, and public health. By incorporating EPA's insights and guidelines into our content, we aim to raise awareness and encourage responsible practices that contribute to a healthier planet. + The EPA is a vital agency committed to protecting human health and the environment. The inclusion of EPA in the US GHG Center effort ensures portal users have access to valuable and relevant EPA resources, research, and regulatory information related to environmental issues, sustainability, and public health. By incorporating EPA's insights and guidelines into Center content, we aim to raise awareness and encourage responsible practices that contribute to a healthier planet. {" "} - - NIST logo - + + + NIST logo +

NIST (National Institute of Standards and Technology)

+ + -**[NIST (National Institute of Standards and Technology)](https://www.nist.gov/)** - NIST contributes access to cutting-edge research, data, and standards on GHG that help ensure the accuracy and reliability of the US GHG Center content and services. NIST is an agency of the U.S. Department of Commerce that is dedicated to promoting innovation and industrial competitiveness by advancing measurement science, standards, and technology. + NIST is an agency of the U.S. Department of Commerce that is dedicated to promoting innovation and industrial competitiveness by advancing measurement science, standards, and technology. NIST contributes access to cutting-edge research, data, and standards on greenhouse gases that help ensure the accuracy and reliability of the US GHG Center content and services. {" "} + NOAA logo - +

NOAA (National Oceanic and Atmospheric Administration)

+ + -**[NOAA (National Oceanic and Atmospheric Administration)](https://www.noaa.gov/)** - NOAA focuses on public understanding and predicting changes in the Earth's environment and safeguarding its resources. NOAA provides accurate and up-to-date information on greenhouse gas monitoring and the research to increase understanding of greenhouse gas impacts on Earth's environment. As an agency within the U.S. Department of Commerce, NOAA data helps to empower users with the knowledge needed to make informed decisions about their lives and the environment. + As an agency within the U.S. Department of Commerce, NOAA data helps to empower users with the knowledge needed to make informed decisions about their lives and the environment. NOAA focuses on public understanding and predicting changes in the Earth's environment and safeguarding its resources. As a member of the US GHG Center, NOAA provides accurate and up-to-date information on greenhouse gas monitoring and the research to increase understanding of greenhouse gas impacts on Earth’s environment. ## Joining Forces for a Better Future - Through partnerships with other organizations, the US GHG Center provides a comprehensive platform that fosters learning, discovery, and positive change. Together, it strives to inspire curiosity, promote scientific literacy, and drive progress in various fields. The Center looks forward to expanding into a network of partners and continuing to build a community that values knowledge and innovation. - - If you are interested in exploring partnership opportunities with the US GHG Center, please [reach out to our team](https://docs.google.com/forms/d/e/1FAIpQLSeVWCrnca08Gt_qoWYjTo6gnj1BEGL4NCUC9VEiQnXA02gzVQ/viewform). + Through partnerships with other organizations, the US GHG Center portal provides a comprehensive platform that fosters learning, discovery, and positive change. Together, it strives to inspire curiosity, promote scientific literacy, and drive progress in various fields. The Center looks forward to expanding into a network of partners and continuing to build a community that values knowledge and innovation. + + If you are interested in exploring partnership opportunities with the US GHG Center, please reach out using the “Contact Us” button at the top right of every portal page. - To get GHG Center updates delivered to your mailbox, subscribe to the news and announcements list. + To get updates delivered to your mailbox, subscribe to the news and announcements list. diff --git a/overrides/common/styles.ts b/overrides/common/styles.ts index 0b9ba0365..8a73985b7 100644 --- a/overrides/common/styles.ts +++ b/overrides/common/styles.ts @@ -27,4 +27,17 @@ export const AccessibilityMenuItem = styled(NavLink)` &:active { text-decoration: underline; } -`; \ No newline at end of file +`; + +export const PartnerHeader = styled.div` + margin-bottom: 24px; + + a { + img { + margin-bottom: 32px; + } + p { + margin-top: 16px; + } + } +` diff --git a/overrides/components/home-hero/component.tsx b/overrides/components/home-hero/component.tsx index fc1a9f04c..a0d62bb3a 100644 --- a/overrides/components/home-hero/component.tsx +++ b/overrides/components/home-hero/component.tsx @@ -67,6 +67,7 @@ const PageHeroCover = styled(Figure)` } `; + export default function HomeHero(props) { const { isMediumUp } = useMediaQuery(); diff --git a/overrides/components/page-footer/component.tsx b/overrides/components/page-footer/component.tsx index bdc78b738..6c498e4a1 100644 --- a/overrides/components/page-footer/component.tsx +++ b/overrides/components/page-footer/component.tsx @@ -12,16 +12,10 @@ import { } from "$veda-ui/@devseed-ui/theme-provider"; import { Button } from "$veda-ui/@devseed-ui/button"; import { format } from "$veda-ui/date-fns"; -import { getString } from "veda"; import { Tip } from "$veda-ui-scripts/components/common/tip"; import { variableGlsp } from "$veda-ui-scripts/styles/variable-utils"; -import { - STORIES_PATH, - DATASETS_PATH, - ANALYSIS_PATH, - ABOUT_PATH, -} from "$veda-ui-scripts/utils/routes"; + import { useFeedbackModal } from "$veda-ui-scripts/components/common/layout-root"; import { useMediaQuery } from "$veda-ui-scripts/utils/use-media-query"; import { getLinkProps } from "$veda-ui-scripts/utils/url"; @@ -32,8 +26,6 @@ import { CollecticonExpandTopRight } from '$veda-ui/@devseed-ui/collecticons'; import { SUBSCRIPTION_URL } from "../../../constants"; -const PRESS_PATH = '/learn#press'; - const FooterInner = styled.div` display: flex; @@ -135,15 +127,7 @@ const MODALS_CONTENT = { headline: "Disclaimer", body: (

- This Exploration and Analysis environment is an interactive space - for users to visually examine data within a mapping environment - and to create time series of basic statistics for dataset layers. - The statistics calculation ensures correct representation of data - across latitudes (area weighting / equal area reprojection). - This environment is intended for quickly exploring spatial and temporal - patterns and not for use in rigorous scientific data analysis. - For complete documentation of the data shown, please visit the dataset - overview pages by clicking the (i) on each data layer. + This Exploration environment is an interactive space for users to visually examine data within a mapping environment and to create time series of basic statistics for selected dataset layers. The statistics calculation ensures correct representation of data across latitudes using area weighting and equal area reprojection. This environment is intended for quickly exploring spatial and temporal patterns and not for use in rigorous scientific data analysis. For complete documentation of the data shown, please visit the dataset overview pages by clicking the (i) on each data layer.

), }, @@ -245,30 +229,25 @@ export default function PageFooter(props) {