Atmospheric methane growth reached an exceptionally high rate of 15.1 ± 0.4 parts per billion per year in 2020 despite a probable decrease in anthropogenic methane emissions during COVID-19 lockdowns1. Here we quantify changes in methane sources and in its atmospheric sink in 2020 compared with 2019. We find that, globally, total anthropogenic emissions decreased by 1.2 ± 0.1 teragrams of methane per year (Tg CH4 yr-1), fire emissions decreased by 6.5 ± 0.1 Tg CH4 yr-1 and wetland emissions increased by 6.0 ± 2.3 Tg CH4 yr-1. Tropospheric OH concentration decreased by 1.6 ± 0.2 per cent relative to 2019, mainly as a result of lower anthropogenic nitrogen oxide (NOx) emissions and associated lower free tropospheric ozone during pandemic lockdowns2. From atmospheric inversions, we also infer that global net emissions increased by 6.9 ± 2.1 Tg CH4 yr-1 in 2020 relative to 2019, and global methane removal from reaction with OH decreased by 7.5 ± 0.8 Tg CH4 yr-1. Therefore, we attribute the methane growth rate anomaly in 2020 relative to 2019 to lower OH sink (53 ± 10 per cent) and higher natural emissions (47 ± 16 per cent), mostly from wetlands. In line with previous findings3,4, our results imply that wetland methane emissions are sensitive to a warmer and wetter climate and could act as a positive feedback mechanism in the future. Our study also suggests that nitrogen oxide emission trends need to be taken into account when implementing the global anthropogenic methane emissions reduction pledge5. 

https://www.nature.com/articles/s41586-022-05447-w.pdf

Wetland emission and atmospheric sink changes explain methane growth in 2020.

ADVERTISEMENT RETURN TO ISSUEEditorialNEXTGlobal Endeavors to Address the Health Effects of Urban Air PollutionLing JinLing JinDepartment of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong KongDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong KongMore by Ling JinView Biographyhttps://orcid.org/0000-0003-1267-7396, Joshua S. ApteJoshua S. ApteDepartment of Civil and Environmental Engineering, University of California, Berkeley, California 94720, United StatesSchool of Public Health, University of California, Berkeley, California 94720, United StatesMore by Joshua S. ApteView Biographyhttps://orcid.org/0000-0002-2796-3478, Shelly L. MillerShelly L. MillerDepartment of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, United StatesMore by Shelly L. MillerView Biographyhttps://orcid.org/0000-0002-1967-7551, Shu TaoShu TaoCollege of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, ChinaSchool of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, ChinaMore by Shu TaoView Biographyhttps://orcid.org/0000-0002-7374-7063, Shuxiao WangShuxiao WangState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, ChinaState Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, ChinaMore by Shuxiao WangView Biographyhttps://orcid.org/0000-0001-9727-1963, Guibin JiangGuibin JiangState Key Laboratory of Environment Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, ChinaMore by Guibin JiangView Biographyhttps://orcid.org/0000-0002-6335-3917, and Xiangdong Li*Xiangdong LiDepartment of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong*Email: [email protected]More by Xiangdong LiView Biographyhttps://orcid.org/0000-0002-4044-2888Cite this: Environ. Sci. Technol. 2022, 56, 11, 6793–6798Publication Date (Web):June 7, 2022Publication History Published online7 June 2022Published inissue 7 June 2022https://doi.org/10.1021/acs.est.2c02627Copyright © Published 2022 by American Chemical SocietyRIGHTS & PERMISSIONSArticle Views1509Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (5 MB) Get e-AlertsSUBJECTS:Air pollution,Atmospheric chemistry,Environmental chemistry,Environmental pollution,Particulate matter Get e-Alerts 

Global Endeavors to Address the Health Effects of Urban Air Pollution.

Atmospheric methane mixing ratio rose by 15 ppbv between 2019 and 2020, the fastest growth rate on record. We conduct a global inverse analysis of 2019–2020 Greenhouse Gases Observing Satellite observations of atmospheric methane to analyze the combination of sources and sinks driving this surge. The imbalance between sources and sinks of atmospheric methane increased by 31 Tg a−1 from 2019 to 2020, representing a 36 Tg a−1 forcing (direct changes in methane emissions and OH concentrations) on the methane budget away from steady state. 86% of the forcing in the base inversion is from increasing emissions (82 ± 18% in the nine-member inversion ensemble), and only 14% is from decrease in tropospheric OH. Half of the increase in emissions is from Africa (15 Tg a−1) and appears to be driven by wetland inundation. There is also a large relative increase in emissions from Canada and Alaska (4.8 Tg a−1, 24%) that could be driven by temperature sensitivity of boreal wetland emissions.

Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations

https://doi.org/10.1016/j.scitotenv.2022.157142

Climate change and COVID-19: Interdisciplinary perspectives from two global crises

Abstract. Carbon dioxide (CO2) and air pollutants such as carbon monoxide (CO) are co-emitted by many combustion sources. Previous efforts have combined satellite-based observations of multiple tracers to calculate their emission ratio (ER) for inferring combustion efficiency at regional to city scale. Very few studies have focused on burning efficiency at the sub-city scale or related it to emission sectors using space-based observations. Several factors are important for deriving spatially-resolved ERs from asynchronous satellite measurements including 1) variations in meteorological conditions induced by different overpass times, 2) differences in vertical sensitivity of the retrievals (i.e., averaging kernel profiles), and 3) interferences from the biosphere and biomass burning. In this study, we extended an established emission estimate approach to arrive at spatially-resolved ERs based on retrieved column-averaged CO2 (XCO2) from the Snapshot Area Mapping (SAM) mode of the Orbiting Carbon Observatory-3 (OCO-3) and column-averaged CO from the TROPOspheric Monitoring Instrument (TROPOMI). To evaluate the influence of the confounding factors listed above and further explain the intra-urban variations in ERs, we leveraged a Lagrangian atmospheric transport model and an urban land cover classification dataset and reported ERCO from the sounding level to the overpass- and city- levels. We found that the difference in the overpass times and averaging kernels between OCO and TROPOMI strongly affect the estimated spatially-resolved ERCO. Specifically, a time difference of > 3 hours typically led to dramatic changes in the wind direction and shape of urban plumes and thereby making the calculation of accurate sounding-specific ERCO difficult. After removing those cases from consideration and applying a simple plume shift method when necessary, we discovered significant contrasts in combustion efficiencies between 1) two megacities versus two industry-oriented cities and 2) different regions within a city, based on six to seven nearly-coincident overpasses per city. Results suggest that the combustion efficiency for heavy industry in Los Angeles is slightly lower than its overall city-wide value (< 10 ppb-CO / ppm-CO2). In contrast, ERs related to the heavy industry in Shanghai are found to be much higher than Shanghai’s city-mean and more aligned with city-means of the two industry-oriented Chinese cities (approaching 20 ppb-CO / ppm-CO2). Although investigations based on a larger number of satellite overpasses are needed, our first analysis provides guidance for estimating intra-city gradients in combustion efficiency from future missions, such as those that will map column CO2 and CO concentration simultaneously with high spatiotemporal resolutions.


/pdf/towards-sector-based-attribution-using-intra-city-variations-3hq1kbe5.pdf

Towards sector-based attribution using intra-city variations in satellite-based emission ratios between CO2 and CO

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.

https://www.pnas.org/content/pnas/118/46/e2109481118.full.pdf

Bart E Croes

Papers

Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change.