From 93e553eb73968ea1da6d7eeb018046ea28b17310 Mon Sep 17 00:00:00 2001 From: Slesa Adhikari Date: Thu, 28 Sep 2023 16:57:13 -0500 Subject: [PATCH] Production release `1.0.0-beta.2` (#184) --- .env | 4 +- .veda/ui | 2 +- ...pa-ch4emission-yeargrid-v2express.data.mdx | 70 +++++----- overrides/about.mdx | 8 +- overrides/home/component.tsx | 7 +- overrides/home/keypoints.tsx | 8 +- package.json | 2 +- stories/blue-heron.jpeg | Bin 73161 -> 0 bytes stories/ch4_trend_all_gl.png | Bin 0 -> 58560 bytes ...vering-large-methane-emissions.stories.mdx | 17 +-- stories/ghgi.png | Bin 35707 -> 95021 bytes stories/global-mean-methane.png | Bin 30007 -> 0 bytes stories/intro-us-ghg-center.stories.mdx | 43 +++--- stories/lillies.jpeg | Bin 0 -> 85733 bytes ...tracking-greenhouse-gas-cycles.stories.mdx | 4 +- stories/us-methane-sources.stories.mdx | 129 ++++++++++-------- stories/water-lilies.jpeg | Bin 81945 -> 0 bytes 17 files changed, 156 insertions(+), 138 deletions(-) delete mode 100644 stories/blue-heron.jpeg create mode 100644 stories/ch4_trend_all_gl.png delete mode 100644 stories/global-mean-methane.png create mode 100644 stories/lillies.jpeg delete mode 100644 stories/water-lilies.jpeg diff --git a/.env b/.env index 5120d64d4..4c22e0601 100644 --- a/.env +++ b/.env @@ -5,7 +5,7 @@ APP_TITLE=U.S. Greenhouse Gas Center APP_DESCRIPTION='Exploring Greenhouse Gas Data; Driving Sustainable Strategies through Powerful Analysis' # Email to reach out when an error occurs or the users have questions. -APP_CONTACT_EMAIL=email@example.org +APP_CONTACT_EMAIL=veda@uah.edu # Endpoint for the Tiler server. No trailing slash. API_RASTER_ENDPOINT='https://ghg.center/api/raster' @@ -20,7 +20,7 @@ MAPBOX_STYLE_URL='mapbox://styles/covid-nasa/ckb01h6f10bn81iqg98ne0i2y' # PUBLIC_URL=http://example.com/mysite # Google form for feedback -GOOGLE_FORM = 'https://docs.google.com/forms/d/e/1FAIpQLSeZrDYP6W3fVOJBwncsLINTdhYsUl9XyoTjNvl7PLBQLV5A0Q/viewform' +GOOGLE_FORM = 'https://docs.google.com/forms/d/e/1FAIpQLSeVWCrnca08Gt_qoWYjTo6gnj1BEGL4NCUC9VEiQnXA02gzVQ/viewform' # Temporarily add hub link through env variables. # This does not scale for the different instances, but it's a quick fix for the diff --git a/.veda/ui b/.veda/ui index df3367d4b..45e6fce00 160000 --- a/.veda/ui +++ b/.veda/ui @@ -1 +1 @@ -Subproject commit df3367d4baf2496c2f07c3f29c2f119038273ca4 +Subproject commit 45e6fce00132001598bc6cf23ab46491c4d54e28 diff --git a/datasets/epa-ch4emission-yeargrid-v2express.data.mdx b/datasets/epa-ch4emission-yeargrid-v2express.data.mdx index 51f6fb4f9..89f93bd58 100644 --- a/datasets/epa-ch4emission-yeargrid-v2express.data.mdx +++ b/datasets/epa-ch4emission-yeargrid-v2express.data.mdx @@ -1,7 +1,7 @@ --- id: epa-ch4emission-yeargrid-v2express name: Gridded Anthropogenic Methane Emissions Inventory -description: Spatially disaggregated 0.1°x 0.1° annual maps of U.S. anthropogenic methane emissions, consistent with the U.S. Inventory of Greenhouse Gas Emissions and Sinks. This is the V2 Express Extension dataset +description: Spatially disaggregated 0.1°x 0.1° annual maps of U.S. anthropogenic methane emissions, consistent with the U.S. Inventory of Greenhouse Gas Emissions and Sinks. usage: - url: 'https://us-ghg-center.github.io/ghgc-docs/cog_transformation/epa-ch4emission-grid-v2express.html' label: Notebook showing data transformation to COG for ingest to the US GHG Center @@ -58,7 +58,7 @@ layers: layerId: total-methane mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -113,7 +113,7 @@ layers: layerId: total-agriculture mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -167,7 +167,7 @@ layers: layerId: enteric-fermentation mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -221,7 +221,7 @@ layers: layerId: manure-management mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -275,7 +275,7 @@ layers: layerId: rice-cultivation-l mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -329,7 +329,7 @@ layers: layerId: field-burning-l mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -383,7 +383,7 @@ layers: layerId: total-natural-gas mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -437,7 +437,7 @@ layers: layerId: exploration-ngs-l mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -491,7 +491,7 @@ layers: layerId: production-ngs-l mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -545,7 +545,7 @@ layers: layerId: 1B2b-transmission-storage-ngs mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -599,7 +599,7 @@ layers: layerId: 1B2b-processing-ngs mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -653,7 +653,7 @@ layers: layerId: 1B2b-distribution-ngs mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -707,7 +707,7 @@ layers: layerId: post-meter-ng mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -761,7 +761,7 @@ layers: layerId: total-petroleum mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -815,7 +815,7 @@ layers: layerId: 1B2a-exploration-ps mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -869,7 +869,7 @@ layers: layerId: 1B2a-production-ps mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -923,7 +923,7 @@ layers: layerId: 1B2a-transport-ps mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -977,7 +977,7 @@ layers: layerId: 1B2a-refining-ps mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1022,7 +1022,7 @@ layers: layerId: total-waste mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1076,7 +1076,7 @@ layers: layerId: 5A1-msw-landfill-waste mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1130,7 +1130,7 @@ layers: layerId: 5A1-industrial-landfill-waste mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1184,7 +1184,7 @@ layers: layerId: 5A1-dwtd-waste mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1238,7 +1238,7 @@ layers: layerId: 5A1-iwtd-waste mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1292,7 +1292,7 @@ layers: layerId: 5A1-composting-waste mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1346,7 +1346,7 @@ layers: layerId: total-coal-mines mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1400,7 +1400,7 @@ layers: layerId: 1B1a-underground-coal mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1454,7 +1454,7 @@ layers: layerId: 1B1a-abn-underground-coal mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1508,7 +1508,7 @@ layers: layerId: 1B1a-surface-coal mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1562,7 +1562,7 @@ layers: layerId: total-other mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1616,7 +1616,7 @@ layers: layerId: 1A-stationary-combustion-other mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1670,7 +1670,7 @@ layers: layerId: 1A-mobile-combustion-othe mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1724,7 +1724,7 @@ layers: layerId: 1A-abn-ong-other mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1778,7 +1778,7 @@ layers: layerId: 1A-petro-production-other mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true @@ -1832,7 +1832,7 @@ layers: layerId: 1A-ferroalloy-production-other mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { - if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`; + if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } analysis: exclude: true diff --git a/overrides/about.mdx b/overrides/about.mdx index c80b4b3d3..3f3d6dde5 100644 --- a/overrides/about.mdx +++ b/overrides/about.mdx @@ -5,9 +5,9 @@ description: Uniting Data and Technology to Empower Tomorrow's Climate Solutions - The U.S. Greenhouse Gas Center (US GHG Center) is a multi-agency effort consolidating greenhouse gas (GHG) information from observations and models into an authoritative product for decision-makers. EPA, NASA, NIST, and NOAA scientific experts together curated this catalog of authoritative 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 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 EPA, NASA, NIST, and NOAA worked together to curate this catalog 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 areas: + 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 @@ -17,7 +17,7 @@ description: Uniting Data and Technology to Empower Tomorrow's Climate Solutions 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. - [Contact us](https://docs.google.com/forms/d/e/1FAIpQLSeZrDYP6W3fVOJBwncsLINTdhYsUl9XyoTjNvl7PLBQLV5A0Q/viewform) to provide ideas and suggestions for future updates. + [Contact us](https://docs.google.com/forms/d/e/1FAIpQLSeVWCrnca08Gt_qoWYjTo6gnj1BEGL4NCUC9VEiQnXA02gzVQ/viewform) to provide ideas and suggestions for future updates. 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. @@ -79,7 +79,7 @@ description: Uniting Data and Technology to Empower Tomorrow's Climate Solutions 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/1FAIpQLSeZrDYP6W3fVOJBwncsLINTdhYsUl9XyoTjNvl7PLBQLV5A0Q/viewform). + 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). diff --git a/overrides/home/component.tsx b/overrides/home/component.tsx index 4caea2214..4ef0b2211 100644 --- a/overrides/home/component.tsx +++ b/overrides/home/component.tsx @@ -99,9 +99,10 @@ export default function HomeComponent() { one stop for data and analysis.

- This initial two-year demonstration phase creates a way to explore - and analyze U.S. government and other datasets. The US GHG Center - also encourages stakeholder feedback and ideas for future expansion. + This initial two-year demonstration phase creates a way to explore + and analyze U.S. government and other datasets, targeting three + greenhouse gas areas of study, as shown below. The US GHG Center + also encourages stakeholder feedback and ideas for future expansion.

Introduction to the US GHG Center diff --git a/overrides/home/keypoints.tsx b/overrides/home/keypoints.tsx index c5f87c5b3..116588bfb 100644 --- a/overrides/home/keypoints.tsx +++ b/overrides/home/keypoints.tsx @@ -40,8 +40,8 @@ export default function Keypoints() { QH zo-MQ-#XC8e{&?{SpM*L;qrs8+2l!#k4g8~QOU!KRfn9u$Tk8D=jlYA^^M0yMsBrcW zTtdh5w4^nhTeq!$lf}Oty4bxl*(Gf0wj_occzde`9z>%G`}$=DXkD-@-;N zQpsdTex55D53lQf4jps;%9#TF>dHuf>J1E)$O;#=L{QM&VBOr>*|K(VIa5$Ea-qLn zNf}h*D3|ZSN3Ndj{@sL81jWSd5C}$e!$Q1fzrAJKJ@^d~gP~+!8p0EXcOVlILCI{U z6D51mZj!4r118P&5vFWfdLHpGXvDoKK5|WyeF-B|=9|ysug67Uh!XoOKO(pEJtyP{ zu$o~TwmGpr9sbojM_G|jr1dLk8E)D-GC}c&6yaz%$1?|jJf1Xsxg7suljesf*R~a( zZf>Y7OCSFf3nb|rt0~4E^b{M=r6F`eC%yY(W?%cU8u4qjw05OLRzSo?W9+sKlxL-{ z1C?kVXV)EtDt0M!P|l^NHROaM(9qV~*C-`=0n5(c+B=aV;DfGn?Gc04mmhKV-ly@y zRZU-LZbfSB+dB)7*a>aw=0_l)yXiH-%Qn8hCW)s^y3?Ji!M8GVp~emsA~{tu7sQ+1 zXlpgl!=z_RaCAhn)dsH8KW#x&2t{X`r{k@0bL)CoHhMUaoXgaR;p@N)-!oXk0T|c% ztKc#)w$13>k&bt;@q>rK^}Tn)G|VBm{GICd0Vz)SEB#){UDbulTY!1rh+8EmBOsQ< 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There are other aircraft and satellite missions that have detected large emissions plumes, such as the TROPOspheric Monitoring Instrument (TROPOMI), PRISMA (PRecursore IperSpettrale della Missione Applicativa), and HISUI (Hyperspectral Imager Suite), which is on the International Space Station. A number of new missions are planned in the near term (Jacob et al., 2022), and the additional measurements of this expanding constellation will allow us to gain a comprehensive picture of large methane emissions in the United States and around the world. It will also provide information to policy and decision makers. Identifying large methane emissions also offers the potential for emission mitigation of this potent greenhouse gas. + These results from EMIT and AVIRIS-NG are offered as examples. There are other aircraft and satellite missions that have detected large emissions plumes, such as the TROPOspheric Monitoring Instrument (TROPOMI), PRISMA (PRecursore IperSpettrale della Missione Applicativa), and HISUI (Hyperspectral Imager Suite), which is on the International Space Station. A number of new missions are planned in the near term (Jacob et al., 2022), and the additional measurements of this expanding constellation will allow us to gain a comprehensive picture of large methane emissions in the United States and around the world. Identifying large methane emissions also offers the potential for emission mitigation of this potent greenhouse gas. Airborne instruments will remain important as they can observe smaller emissions that can not be observed with satellites. The JPL Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) program generates publicly available, airborne data that has been used for mapping methane across the western hemisphere. Methane observations from this platform provide high resolution observations over targeted areas, and will be incorporated into the US GHG Center’s available data and used to support calibration and validation of EMIT measurements. @@ -232,17 +232,18 @@ taxonomy: ## Resources / References - Saunois, M., Stavert, A. R., Poulter, B., Bousquet, P., Canadell, J. G., Jackson, R. B., Raymond, P. A., Dlugokencky, E. J., Houweling, S., Patra, P. K., Ciais, P., Arora, V. K., Bastviken, D., Bergamaschi, P., Blake, D. R., Brailsford, G., Bruhwiler, L., Carlson, K. M., ... Zhuang, Q. (2020). The Global Methane Budget 2000–2017. Earth System Science Data, 12, 1561–1623. [doi:10.5194/essd-12-1561-2020](https://doi.org/10.5194/essd-12-1561-2020) - - Myhre, G., Shindell, D., Bréon, F.-M., Collins, W., Fuglestvedt, J., Huang, J., Koch, D., Lamarque, J., Lee, D., Mendoza, B., Nakajima, T., Robock, A., Stephens, G., Takemura, T., & Zhang, H. (2013). Anthropogenic and natural radiative forcing. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Tech. Rep.). + Crippa, M., Guizzardi, D., Banja, M., Solazzo, E., Muntean, M., Schaaf, E., Pagani, F., Monforti-Ferrario, F., Olivier, J., Quadrelli, R., Risquez Martin, A., Taghavi-Moharamli, P., Grassi, G., Rossi, S., Jacome Felix Oom, D., Branco, A., San-Miguel-Ayanz, J. and Vignati, E., CO2 emissions of all world countries - 2022 Report, EUR 31182 EN, Publications Office of the European Union, Luxembourg, 2022, doi:10.2760/730164, JRC130363 Cusworth, D.H., Thorpe, A.K., Ayasse, A.K., Stepp, D., Heckler, J., Asner, G.P., Miller, C.E., Yadav, V., Chapman, J.W., Eastwood, M.L. and Green, R.O., 2022. Strong methane point sources contribute a disproportionate fraction of total emissions across multiple basins in the United States. Proceedings of the National Academy of Sciences, 119(38), p.e2202338119. - Crippa, M., Guizzardi, D., Banja, M., Solazzo, E., Muntean, M., Schaaf, E., Pagani, F., Monforti-Ferrario, F., Olivier, J., Quadrelli, R., Risquez Martin, A., Taghavi-Moharamli, P., Grassi, G., Rossi, S., Jacome Felix Oom, D., Branco, A., San-Miguel-Ayanz, J. and Vignati, E., CO₂ emissions of all world countries - 2022 Report, EUR 31182 EN, Publications Office of the European Union, Luxembourg, 2022, [doi:10.2760/730164](https://doi.org/10.2760/730164), JRC130363 + EPA. (2022). Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2020. (EPA 430-R-22-003). U.S. Environmental Protection Agency. https://www.epa.gov/system/files/documents/2022-04/us-ghg-inventory-2022-main-text.pdf - Jacob, D.J., Varon, D.J., Cusworth, D.H., Dennison, P.E., Frankenberg, C., Gautam, R., Guanter, L., Kelley, J., McKeever, J., Ott, L.E. and Poulter, B., 2022. Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane. Atmospheric Chemistry and Physics, 22(14), pp.9617-9646. [doi:10.5194/acp-22-9617-2022](https://doi.org/10.5194/acp-22-9617-2022) + Jacob, D.J., Varon, D.J., Cusworth, D.H., Dennison, P.E., Frankenberg, C., Gautam, R., Guanter, L., Kelley, J., McKeever, J., Ott, L.E. and Poulter, B., 2022. Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane. Atmospheric Chemistry and Physics, 22(14), pp.9617-9646. https://doi.org/10.5194/acp-22-9617-2022 + + Myhre, G., Shindell, D., Bréon, F.-M., Collins, W., Fuglestvedt, J., Huang, J., Koch, D., Lamarque, J., Lee, D., Mendoza, B., Nakajima, T., Robock, A., Stephens, G., Takemura, T., Zhang, H. (2013). Anthropogenic and natural radiative forcing. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Technical Report. + + Saunois, M., Stavert, A.R., Poulter, B., Bousquet, P., Canadell, J.G., Jackson, R.B., Raymond, P.A., Dlugokencky, E.J., Houweling, S., Patra, P.K., Ciais, P., Arora, V.K., Bastviken, D., Bergamaschi, D., Blake, D.R., Brailsford, G., Bruhwiler, L., Carlson, K.M., ... Zhuang Q. (2020). The Global Methane Budget 2000–2017. Earth System Science Data. 12, 1561–1623. - EPA. (2022). Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2020. (EPA 430-R-22-003). 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b/stories/intro-us-ghg-center.stories.mdx @@ -1,7 +1,7 @@ --- id: 'intro-us-ghg-center' name: Intro to the US GHG Center -description: The U.S. Greenhouse Gas Center (US GHG Center) is a multi-agency effort to compile greenhouse gas data from observations and models into trusted, authoritative greenhouse gas emissions and flux products for use in decision-making. +description: The U.S. Greenhouse Gas Center (US GHG Center) is a multi-agency effort to compile greenhouse gas data from observations and models into a collection of trusted greenhouse gas emissions and flux products. media: src: ::file ./intro-to-ghg-center--cover.png alt: Screenshot of the US GHG Center website homepage @@ -19,15 +19,13 @@ featured: true Elevated concentrations of GHGs, including methane and carbon dioxide, are warming the planet. This is leading to changes in Earth's climate that occur at a pace in a way that threatens human health, society, and the natural environment. These changes include warmer air and ocean temperatures, changes in precipitation patterns, retreating snow and ice, increasingly severe weather events, such as hurricanes of greater intensity, and sea level rise, among other impacts. - The Intergovernmental Panel on Climate Change (IPCC) states: "it is unequivocal that human influence has warmed the atmosphere, ocean and land" and that "widespread and rapid changes in the atmosphere, cryosphere, and biosphere have occurred." Link to IPCC AR6: [https://www.ipcc.ch/assessment-report/ar6/](https://www.ipcc.ch/assessment-report/ar6/). + The Intergovernmental Panel on Climate Change (IPCC) states: "it is unequivocal that human influence has warmed the atmosphere, ocean and land" and that "widespread and rapid changes in the atmosphere, cryosphere, and biosphere have occurred." Link to IPCC AR6: [https://www.ipcc.ch/assessment-report/ar6/](https://www.ipcc.ch/assessment-report/ar6/). The data shows trends and patterns in carbon dioxide (CO₂) and methane (CH₄) from anthropogenic (human-related) and natural sources that can be used to inform decisions. - The data shows trends and patterns in carbon dioxide (CO₂) and methane (CH₄) from anthropogenic (human-related) and natural sources that can be used to inform decisions. - - Federal agencies are working together to develop a Greenhouse Gas Monitoring and Information System (GHGMIS) for the U.S. that combines atmospheric- and activity-based approaches to increase confidence in setting, assessing, and meeting climate mitigation goals. This system uses these advanced capabilities, as well as the growth of GHG observational data and models, to provide enhanced emissions and uptake data products. + Federal agencies are working together to develop a Greenhouse Gas Monitoring and Information System (GHGMIS) for the U.S. that combines atmospheric- and activity-based approaches to increase confidence in setting, assessing, and meeting climate mitigation goals. This system uses these advanced capabilities, as well as the growth of GHG observational data and models, to provide enhanced emissions and uptake data products. The US GHG Center will disseminate this GHG data as well as supporting decision support tools, engaging with users, developing data quality criteria, and communicating data, capability, and expertise needs. - The Center works to inform mitigation efforts for a range of stakeholders and forms an interface between Federal and non-Federal activities to improve quantification of greenhouse gas exchange within the Earth system. + The US GHG Center works to inform mitigation efforts for a range of stakeholders and forms an interface between Federal and non-Federal activities to improve quantification of greenhouse gas exchange within the Earth system. @@ -51,7 +49,7 @@ featured: true - **EPA**: *Climate Change*: https://www.epa.gov/climate-change - **NASA**: *Global Climate Change*: https://climate.nasa.gov/ - **NIST**: *Climate*: https://www.nist.gov/climate - - **NOAA**: *Climate Change Impacts*: https://www.noaa.gov/education/resource-collections/climate/climate-change-impacts" (or billion $ disasters) + - **NOAA**: *Climate Change Impacts*: https://www.noaa.gov/education/resource-collections/climate/climate-change-impacts @@ -74,11 +72,11 @@ featured: true The U.S. Greenhouse Gas Center (US GHG Center) is a multi-agency effort to compile greenhouse gas data from observations and models into one environment containing trusted greenhouse gas emissions and flux products for use in research, decision-making, and other applications. - The US GHG Center is built on open source principles and techniques that allow users to access, analyze, visualize and apply data and products to their own usage. + The US GHG Center is built on open source principles and techniques that allow users to access, analyze, visualize, and apply data and products to their own usage. With this wealth of data pertaining to greenhouse gases, greenhouse gas emissions, and related ancillary information, the US GHG Center can be used to increase understanding of the types of GHG data and measurement platforms to facilitate wider and appropriate usage of GHG information. -
+ {/*
President Biden addressing the crowd at COP27. President Biden addressing the crowd at COP27. The image is licensed under https://creativecommons.org/licenses/by/2.0/legalcode -
+
*/} @@ -99,9 +97,9 @@ featured: true align="left" alt="logos for the four agencies: EPA, NASA, NIST, NOAA" /> - The U.S. Greenhouse Gas Center is coordinated by NASA in partnership with EPA, NIST and NOAA. These agencies are collaborating to prototype development of the center with the goal of accelerating the production and delivery of quality greenhouse gas (GHG) information, including a curated collection of GHG datasets, workflows and visualizations from the federal government and non-public sector, NASA, EPA, NOAA and NIST. + The US GHG Center is coordinated by NASA in partnership with EPA, NIST and NOAA. These agencies are collaborating to prototype development of the center with the goal of accelerating the production and delivery of quality greenhouse gas (GHG) information, including a curated collection of GHG datasets, workflows and visualizations from the federal government and non-public sector, NASA, EPA, NOAA and NIST. - The Center acts as an facilitator of collaboration with networks of interagency, intergovernmental and private sector partners to support setting, assessing, and meeting climate mitigation goals. + The Center acts as an facilitator of collaboration with networks of interagency, intergovernmental and private sector partners to support setting, assessing, and meeting climate mitigation goals. The US GHG Center is more than just a funnel for greenhouse gas datasets packaged into a user interface. The US GHG Center also includes and reports on various efforts to engage stakeholders, increase understanding with webinars and training events, inform communities, empower users with decision insights. @@ -116,9 +114,9 @@ featured: true The U.S. Government plans to use a phased approach in implementing the National Strategy, with Phase 1 taking advantage of, and integrating, mature research capabilities and existing data, and Phase 2 reflecting a more robust monitoring and information system based on well-defined requirements as well as planning and research and development efforts from Phase 1. - The US GHG Center supports both phases of the implementation of the National Strategy, following an iterative approach, which begins with input from NASA, NIST, NOAA, and EPA, and is expected to expand and include other agency and non-federal capabilities in the future. + The US GHG Center supports both phases of the implementation of the National Strategy, following an iterative approach, which begins with input from EPA, NASA, NIST, and NOAA, and is expected to expand and include other agency and non-federal capabilities in the future. - The U.S. Greenhouse Gas Center plans to coordinate with networks of international organizations — including the World Meteorological Organization, the Committee on Earth Observation Satellites, and the UN Environment’s International Methane Emissions Observatory — to accelerate development and dissemination of GHG MMRV decision support tools and data and establish criteria for thorough evaluation of the quality, accessibility, and transparency of new data and modeling products. + The U.S. Greenhouse Gas Center plans to coordinate with networks of international organizations — including the World Meteorological Organization, the Committee on Earth Observation Satellites, and the UN Environment’s International Methane Emissions Observatory — to accelerate development and dissemination of the measurement, monitoring, reporting, and verification of GHGs. It also will establish criteria for thorough evaluation of the quality, accessibility, and transparency of new data and modeling products. {/*
## What Datasets are in the US GHG Center and Why These? - The US GHG Center contains trusted, authoritative greenhouse gas emissions and flux products. + The US GHG Center contains trusted information on greenhouse gas emissions and flux products.
@@ -155,11 +153,10 @@ featured: true The initial 2-yr demonstration phase or the project targets three GHG areas of study in order to - Provide access to selected anthropogenic gas emission data products; - - Complement anthropogenic GHG inventories with estimates of natural GHG emissions, update and other fluxes of GHGs, as well as improved usability and visualizations. + - Complement anthropogenic GHG inventories with estimates of natural GHG emissions, updates and other fluxes of GHGs, as well as improved usability and visualizations. - Identify and quantify emissions from large methane (CH₄) leak events leveraging aircraft and space-borne instruments. - - The US GHG Center is not a comprehensive accounting of all GHG-relevant products and datasets produced by the U.S. Federal Government. Additional features and data sets will be added as additional information is available, with links throughout the site to additional resources. - - + + The US GHG Center is not a comprehensive accounting of all GHG-relevant products and datasets produced by the U.S. Federal Government. Additional features and data sets will be added as additional information is available, with links throughout the site to additional resources. @@ -176,7 +173,7 @@ featured: true - ## What can You Do in the US GHG Center with the Existing Data? + ## What Can You Do in the US GHG Center with the Existing Data? - **Discover** - Users can search the data catalog or learn more about the three demonstration areas - **Explore** - Visualize the relevant data from various data products, instruments and models @@ -220,7 +217,7 @@ featured: true ## What’s Coming Next? - Additions to to the US GHG Center will occur in the coming months, including some new features and capabilities that will improve data discovery, exploration and analysis. + Additions to the US GHG Center will occur in the coming months, including some new features and capabilities that will improve data discovery, exploration and analysis. - Improvements to Center design and function of the interface and tools - More and different kinds of data, such as data from airborne campaigns, new instruments, and other selected data products @@ -246,9 +243,9 @@ featured: true ## We Want Your Help! 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- In our atmosphere, greenhouse gases like carbon dioxide and methane act like a blanket. They keep heat in and warm the Earth. Carbon and methane ‘cycles’ or moves to and from the atmosphere. These cycles include emissions from human activities and natural sources, to the atmosphere, to ‘sinks’ like plants and oceans that absorb these chemical components. Understanding how these sources and sinks are changing is critically important for policymakers, local environmental managers, and scientists working to predict climate in coming decades. + In our atmosphere, greenhouse gases like carbon dioxide and methane act like a blanket. They keep heat in and warm the Earth. The elements carbon and methane ‘cycle’ or move to and from the atmosphere. These cycles include emissions from human activities and natural sources, to the atmosphere, to ‘sinks’ like plants and oceans that absorb these chemical components. Understanding and quantifying how these sources and sinks are changing is critically important for policymakers, local environmental managers, and scientists working to predict climate in the coming decades.
@@ -42,7 +42,7 @@ taxonomy: altDesc='Time series graph showing increase in atmospheric CO₂ over time as measured at Mauna Loa observatory in Hawaii' /> - NOAA’s observations at the Mauna Loa observatory in Hawaii have allowed scientists to track the build up of atmospheric concentrations of CO₂ in recent decades from all sources, natural and human-caused. It also records the imprint of the seasonal cycle of vegetation in the northern hemisphere. The Mauna Loa CO₂ data is the longest record and was started by C. David Keeling of the Scripps Institution of Oceanography in March 1958 at a NOAA facility [Keeling, 1976](https://onlinelibrary.wiley.com/doi/abs/10.1111/j.2153-3490.1976.tb00701.x). *Credit: NOAA GML* + NOAA’s observations at the Mauna Loa Observatory in Hawaii have allowed scientists to track the build up of atmospheric concentrations of CO₂ in recent decades from all sources, natural and human-caused. It also records the imprint of the seasonal cycle of vegetation in the northern hemisphere. The Mauna Loa CO₂ data is the longest record and was started by C. David Keeling of the Scripps Institution of Oceanography in March 1958 at a NOAA facility [Keeling, 1976](https://onlinelibrary.wiley.com/doi/abs/10.1111/j.2153-3490.1976.tb00701.x). *Credit: NOAA GML*
diff --git a/stories/us-methane-sources.stories.mdx b/stories/us-methane-sources.stories.mdx index 6edb6e90f..af088120b 100644 --- a/stories/us-methane-sources.stories.mdx +++ b/stories/us-methane-sources.stories.mdx @@ -1,7 +1,7 @@ --- id: "us-methane-sources" -name: US Methane Sources -description: "Mapping human-caused sources of methane across the U.S. provides insight into sources and emission trends. This geographic representation enables new comparisons between emission locations and includes methane estimates informed by atmospheric observations. The aim is improving national and state-level methane emission estimates." +name: Gridded Anthropogenic Greenhouse Gas Emissions +description: "Mapping human-caused sources of methane across the U.S. provides insight into source and emission trends. This geographic representation enables new comparisons between emission locations and includes methane estimates informed by atmospheric observations. The aim is to improve national and state-level methane emission estimates." media: src: ::file ./total-methane-2020.png alt: Map of total U.S. gridded methane emissions in the year 2020 @@ -20,20 +20,31 @@ taxonomy: - ## What is methane and why is it important? - Methane is the second most abundant greenhouse gas, behind carbon dioxide CO₂ and is a ‘potent’ greenhouse gas that traps heat in the atmosphere. It is responsible for about one third of all warming resulting from human emissions. Also, methane has a shorter lifetime than carbon dioxide, meaning it leaves the atmosphere much faster. These factors make reducing methane emissions one of the best opportunities for reducing near term global warming. +
- Over the last two centuries, methane concentrations in the atmosphere have more than doubled. While some methane emissions come from natural sources, many sources are from human-related activities including agriculture, oil and natural gas systems, landfills, coal mining, stationary and mobile combustion, wastewater treatment, and certain industrial processes. Follow these links for more information on the importance of methane, global methane budget, and observed trends in global atmospheric concentrations. + A potent greenhouse gas, methane is responsible for about one third of all global warming that results from human activities. Methane also traps more heat than carbon dioxide and has a relatively shorter lifeline in our atmosphere. This makes finding and limiting methane emissions one of the best opportunities for reducing climate change. Locating and mapping U.S. sources of methane emissions can provide insights into emission trends and improve national and state-level estimates. Detailed maps also allow for more direct comparisons of methane emissions, thereby helping to improve the information used to track progress towards collective climate goals. + +
+ + + + + + ## Tracking and Mapping Methane + + Methane is the second most abundant greenhouse gas behind carbon dioxide (CO₂). Over the last two centuries, methane concentrations in the atmosphere have more than doubled, largely due to human-related activities. While there are natural sources of methane emissions, most methane comes from human activities in agriculture and water industries such as landfills, wastewater treatment, and other industrial processes. Additional human emissions of methane are coal mining, stationary and mobile combustion, and oil and natural gas systems. Because methane is a powerful GHG and has a relatively shorter lifetime in the atmosphere than CO₂, reducing methane emissions is one of the best opportunities for reducing near term global warming. + + Follow these links for more information on the [importance of methane](https://www.epa.gov/gmi/importance-methane), [global methane budget](https://www.globalcarbonproject.org/methanebudget/index.htm), and [observed trends](https://gml.noaa.gov/ccgg/trends_ch4/) in global atmospheric concentrations.
time series from 1984 to 2022 of global monthly mean atmospheric methane - Globally-averaged, monthly mean atmospheric methane abundance determined from marine surface sites, last updated Aug 05, 2023. + Globally-averaged, monthly mean atmospheric methane abundance determined from marine surface sites, last updated Sept 05, 2023.
@@ -49,32 +60,40 @@ taxonomy: Gas flaring during oil and gas production is a known source of methane emissions
- ### GHG Inventories are a fundamental tool for promoting international cooperation to address climate change + ## GHG Inventories - A Fundamental Tool Promoting International Climate Change Cooperation - The 1992 United Framework Convention on Climate Change is an international treaty that established a framework for international cooperation to achieve “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system” (Article 2). Towards this end, signatories to this U.N. framework (UNFCCC) are committed to developing and reporting “national inventories of anthropogenic emissions by sources and removals by sinks of all greenhouse gases” (Article 4). These inventories provide a scientific basis for tracking and planning emission mitigation efforts to achieve the long-term objective of the Convention. Inventory reporting is also a continued commitment under Article 13 of the 2015 U.N. Paris Agreement. + The [United Nations Framework Convention on Climate Change](https://www.google.com/url?q=https://unfccc.int/resource/docs/convkp/conveng.pdf&sa=D&source=docs&ust=1695419649511030&usg=AOvVaw2r_M3u40Dcb9U77HDrHNRx) (UNFCCC) is an international treaty that established a framework for international cooperation to achieve “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system” (Article 2). Towards this end, signatories to the UNFCCC are committed to developing and reporting “national inventories of anthropogenic emissions by sources and removals by sinks of all greenhouse gases” (Article 4). These inventories provide a scientific basis for tracking and planning emission mitigation efforts to achieve the long-term objective of the Convention. Inventory reporting is also a continued commitment under the 2015 U.N. Paris Agreement. - ### Creating GHG Inventories with a Consistent Methodology + ## Creating GHG Inventories with a Consistent Methodology - The Intergovernmental Panel on Climate Change (IPCC) assesses the scientific, technical, and socio-economic information relevant to understanding the scientific basis of risk of human-induced climate change, its potential impacts, and options for adaptation and mitigation (IPCC, 2021). To consistently create internationally acceptable inventories of greenhouse gases, the IPCC issues methodology reports. These methods are largely based on an approach that combines information on human activity data and factors that quantify the amount of emissions or removal per unit of activity. For example it has data on how much fuel is used by human activity as well as the amount of methane emissions released from using that fuel. + The Intergovernmental Panel on Climate Change (IPCC) issues GHG methodology reports to assist in the development of internationally consistent, transparent, accurate, complete, and comparable inventories of national GHG emissions and sinks ([2006, IPCC](https://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html)). These methods are largely based on an approach that uses human activity data (e.g., tons of fuel used), combined with factors that quantify the amount of GHGs emitted or removed per unit of activity (e.g., tons of CO₂ emitted per tons of fuel used).These methods can be more or less complex depending on the type of data available for a given emissions source or GHG. - These methods can be more or less complex depending on the type of data available for a given source or gas. Currently, national inventories reported to the UNFCCC are required to use methods consistent with the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (2006, IPCC), and its subsequent supplements and refinements, where appropriate. + Currently, national inventories reported to the UNFCCC are required to use methods consistent with the 2006 IPCC Guidelines for National Greenhouse Gas Inventories ([2006, IPCC](https://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html)), and its subsequent supplements and refinements, where appropriate.
A room of attendees at an opening session of UN COP15 - United Nations photo of a meeting during the U.N. Climate Change Conference in 2015 (COP15) + President Biden addressing the U.N. Climate Change Conference (COP27) in Egypt, November 2022.
+ + + ## Inventory of U.S. Greenhouse Gas Emissions and Sinks + + As a Party to the UNFCCC, the U.S. annually submits a national inventory of GHGs to the U.N. each year, called the [Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI)](https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks). The EPA has prepared this report since the early 1990s. The GHGI represents official U.S. Government data on national anthropogenic GHG emissions and uses IPCC Guidelines to calculate the annual time series of national emissions and sinks for seven GHGs (including methane), by source and economic sector. + + Separately through the [Greenhouse Gas Reporting Program (GHGRP)](https://www.epa.gov/ghgreporting), the EPA also collects annual GHG emissions data (including methane) from individual facilities and suppliers of certain fossil fuels and industrial gases that emit more than 25,000 metric tons or more of CO₂ equivalent per year. Unlike the national Inventory, the GHGRP does not provide full coverage of total annual anthropogenic U.S. GHG emissions, but is used in part to help develop the inventory. + +
Time series of Annual U.S. Anthropogenic GHG Emissions, by GHG
- - ### Inventory of U.S. Greenhouse Gas Emissions and Sinks - - As a Party to the UNFCCC, the U.S. submits a national inventory of anthropogenic sources and sinks of GHGs by April 15th each year, called the Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI). The EPA has prepared this report since the early 1990s. It uses IPCC Guidelines to calculate the annual time series of anthropogenic emissions and sinks by source, economic sector, and GHG (including methane). Separately through the Greenhouse Gas Reporting Program (GHGRP), the EPA also collects annual GHG emissions data (including methane) from individual facilities and suppliers of certain fossil fuels and industrial gases that emit more than 25,000 metric tons or more of CO₂ equivalent per year. The GHGRP does not provide full coverage of total annual anthropogenic U.S. GHG emissions, but both data sets are complementary to each other and the GHGRP data is included in the inventory data. -
- ### Using atmospheric observations to identify areas for improvement in national methane estimates + ## Identifying Areas for Improvement in US Methane Estimates with Atmospheric Observations - Over the last two decades there have been advancements in measuring human-caused methane emissions using instruments on satellites, aircraft, and mobile platforms. Also, scientists use inverse modeling. This is a mathematical technique to infer emissions from concentrations and it has revolutionized the ability to estimate methane emissions such as from biological activity, leaks, and other fugitive sources. However, a more localized spatial representation of inventory emissions is needed to determine the types of direct comparisons that can enable these local and regional estimates to inform inventory improvements (2019 IPCC Refinements). + There have been important advancements over the last two decades in measuring atmospheric methane using instruments on satellites, aircraft, and mobile platforms. These observations can help to identify potential areas for improvement in the national inventory. For example, scientists can now use inverse modeling to estimate methane emissions from atmospheric observations. This is a mathematical technique to infer emissions from observed concentrations, which has revolutionized the ability to estimate methane emissions from relatively more uncertain sources, such as biological activity, leaks, and other fugitive events. However, it remains difficult to directly compare singlar observation-based estimates to the total annual U.S. emissions reported in the GHGI. Therefore a more localized spatial representation of inventory emissions is needed to enable these types of comparisons (2019 IPCC Refinements).
Media example {/* NOAA CH₄ concentration map */}
@@ -115,24 +128,32 @@ taxonomy:
+ {/* visualization of total methane emissions from all sources shown on a map */} - EPA Gridded Express 2020 emission + EPA Gridded Express 2020 - Total Methane Emissions
## A Spatial U.S. Methane Emissions Dataset for Research - Showing U.S. methane emissions across a map, spatially, enables more direct comparisons between atmospheric observations and U.S. inventory estimates. This dataset currently includes maps of U.S. methane emissions from human activity from over 25 individual sources, at the 10 x 10 km scale, for the years 2012 through 2020. Compared to other ‘gridded’ emission products, this dataset is uniquely consistent with the U.S. GHGI, meaning that when summed, gridded methane estimates will equal total contiguous U.S. methane emissions in the U.S. GHGI. As discussed in a recent paper, this consistency is maintained by allocating U.S. GHGI methane emissions to each grid cell using, where available, the same activity data (e.g., animal counts, gas well locations and production volumes, etc.) that was used to calculate the national inventory estimates. This dataset was developed through a collaboration between researchers at the SRON Netherlands Institute for Space Research, Harvard University, Lawrence Berkeley National Lab (LBNL), and the EPA. + The gridded methane GHGI has been developed to enable more direct comparisons between atmospheric observations and U.S. inventory estimates. This dataset currently includes maps of U.S. methane emissions from human activity from over 25 individual sources, at the 10 x 10 km scale, for the years 2012 through 2020. In contrast to other ‘gridded’ emission products, this dataset is consistent with the U.S. GHGI, meaning that when summed, gridded methane estimates will equal the total methane emissions from the contiguous U.S. in the national GHGI. As discussed in a recent [paper](https://eartharxiv.org/repository/view/5623/), this consistency is maintained by allocating national GHGI methane emissions from each source category to each grid cell using, where available, the same activity data (e.g., animal counts, gas well locations and production volumes, etc.) that was used to calculate the original national inventory estimates. This dataset was developed in collaboration between researchers at the SRON Netherlands Institute for Space Research, Harvard University, Lawrence Berkeley National Lab (LBNL), and the EPA. -
- ## Different emission sources have different spatial patterns + ## Different Emission Sources have Different Spatial Patterns @@ -141,7 +162,7 @@ taxonomy: center={[-98.5795, 39.8283]} zoom={4} datasetId='epa-ch4emission-yeargrid-v2express' - layerId='rice-cultivation-l' + layerId='total-agriculture' datetime='2020-01-01' > ## Emissions from Agriculture @@ -152,29 +173,29 @@ taxonomy: center={[-98.5795, 39.8283]} zoom={4} datasetId='epa-ch4emission-yeargrid-v2express' - layerId='production-ngs-l' + layerId='total-natural-gas' datetime='2020-01-01' > ## Emissions from Natural Gas and Petroleum - Methane emissions from natural gas and petroleum activities are primarily associated with activities in oil and gas production basins. Methane is also emitted from activities related to the transmission, storage, and distribution of natural gas and crude oil, with emissions largely distributed along pipelines or concentrated at storage sites, transport terminals, refineries, or in densely populated areas. + Methane emissions from natural gas and petroleum activities are primarily associated with activities in oil and gas production basins. Methane is also emitted from activities related to the transmission, storage, and distribution of natural gas and crude oil, with emissions largely distributed along pipelines or concentrated at storage sites, transport terminals, refineries, or in densely populated areas. (Map shows total methane emissions from natural gas systems.) ## Emissions from Coal Mining - Surface and underground coal mining activities and associated methane emissions are mainly centralized in Southwest Appalachia, as well as at mines located across other U.S. regions + Surface and underground coal mining activities and associated methane emissions are mainly centralized in Southwest Appalachia, as well as at mines located across other U.S. regions. ## Emissions from Waste Management @@ -185,7 +206,7 @@ taxonomy: center={[-98.5795, 39.8283]} zoom={4} datasetId='epa-ch4emission-yeargrid-v2express' - layerId='1B2a-transport-ps' + layerId='total-other' datetime='2020-01-01' > ## Emissions from Other Sources @@ -196,8 +217,8 @@ taxonomy: - ## The spatial patterns of some emission sources change overtime - While national total methane emissions in the U.S. GHGI declined between 2012 and 2020, the gridded dataset reveals that these trends are not the same across all regions or emission sources. + ## The Spatial Patterns of Some Emission Sources Change Overtime + While total national methane emissions in the U.S. GHGI declined between 2012 and 2020, the gridded dataset reveals that these trends are not the same across all regions or emission sources.
- The caption displays below the map. + Comparison of total yearly methane emissions from all sources between years 2012 and 2020
@@ -223,11 +244,11 @@ taxonomy: align="left" /> - The caption displays below the map. + Comparison of total yearly methane emissions from agriculture between years 2012 and 2020 - For example, total U.S. agriculture methane emissions fell between 2012 and 2020. However, emissions in some regions increased, largely depending on how animal populations and manure management systems changed in these locations. + For example, total U.S. agriculture methane emissions fell between 2012 and 2020. However, emissions in some regions increased, largely depending on how animal populations and manure management systems changed in specific locations. @@ -245,7 +266,7 @@ taxonomy: align="left" /> - The caption displays below the map. + Comparison of total yearly methane emissions from petroleum systems between years 2012 and 2020 @@ -260,7 +281,7 @@ taxonomy: align="left" /> - The caption displays below the map. + Comparison of total yearly methane emissions from coal mines between years 2012 and 2020 @@ -276,7 +297,7 @@ taxonomy:
flowering water lilies in a pond on a nice day ## Resources / References - Notebook link that contains a means to generate the images used in the data - - Users are directed to the following links for more information on U.S. methane emissions: + Users are directed to the following EPA links for more information on U.S. methane emissions: - - For U.S. National Methane Emissions → https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks - - For U.S. state-level methane emissions → https://www.epa.gov/ghgemissions/state-and-tribal-greenhouse-gas-data-and-resources - - For U.S. individual facility emissions → https://epa.gov/ghgreporting - - For the gridded methane emission research dataset → https://zenodo.org/record/7672124 + - [U.S. national methane emissions](https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks) + - [U.S. state-level methane emissions](https://www.epa.gov/ghgemissions/state-and-tribal-greenhouse-gas-data-and-resources) + - [U.S. individual facility emissions](https://www.epa.gov/ghgreporting) + - [The gridded methane emission research dataset from the EPA](https://zenodo.org/record/7672124) @@ -304,6 +323,6 @@ taxonomy: ## Disclaimers - This gridded methane emissions dataset is currently under peer-review and will be updated upon peer-review and final publication of the associated manuscript. Please see GHG Gridded dataset Landing Page and and links in the resources for additional details. + This gridded methane emissions dataset has been peer-reviewed as part of the associated manuscript, Maasakkers et al., 2023. Please see the Gridded Anthropogenic Methane Emissions Inventory dataset landing page and links in the resources for additional details. diff --git a/stories/water-lilies.jpeg b/stories/water-lilies.jpeg deleted file mode 100644 index 94a8f73bbb0e2e0c4c0a8751d9e0d4c435c9bd14..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 81945 zcmZU(18^o$(>8p^+1SR$wr$(CoosAplRLI;+_7!j*2Z==+Wq!<-uL^e{`#*|b*ksg zboJ?(n(1r0`|tYSeE^EAq>Lm03=9AO`!@i8w*X-P2yk#XSh)WScsTg~5&z%PKLPeX z_|NixrvFN?u<(d*u!#R;STG1kNN6Z%IA~}%6eM^gXo$r~q(OFbGtzzrz3`000~u0_-0E{|hK+NEmPkSg>yZxWAhK*#9~4i)YDF zE}c~JYwOivj-cFQiAC5J5sO3AiUoY28f<*S#=S*lR!i|OAOqcUDxE6eYs!8JQ7_F#82_luxKdgMTe-ZX(Ac^$|-WmQZ~6)a;A&(BhCBP-HpMVwSJxN z1TtB&l23Um(PNv}^$HObg*=0{ZBR{w{Vdu8+HRWSe+ih{+dUfK_FW2(nVvM(?pO%+ zZf+{1ZNcnIj49m;dB=QIn^j8~_RTkVT$tsfh-7%9rsl(T_?!(*gdlVD zY~12pn#zkvR<>Mb@Z=5iSd=Pr`q~Av$&IUI&heNL3&nn6Up}`O#w!>j+UvQF=dI9j z;C;DGhScOwD>ieK^Jl)n;W!#beyfx0m5gbgB3{obWfrjzYIx#*>GM} 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