This site displays analyses from the Global Methane Assessment: Benefits and Costs of Mitigating Methane Emissions (United Nations Environment Programme and Climate and Clean Air Coalition, Nairobi, 2021). This Assessment is intended to support decision making regarding methane emissions by providing an in depth analysis of oppor tunities to reduce methane emissions from all sectors across all regions and an analysis of both the costs and the benefits to human health, crops and the economy of s uch reductions. Users of this site can either examine the mitigation potential within specific socio-economic sectors using the tab in the left column labeled 'Analyze d Mitigation' or enter the potential methane emissions reductions (or increases) associated with any action of interest, ranging from individual projects to national o r international action plans using the tab labeled 'Select Mitigation'. The tool then provides quantitative values for multiple impacts of those emissions reductions u sing the mean of the models that participated in the Assessment.
Methane Mitigation Potentials
The 'Analyzed Mitigation' tab provides values from studies of the oil and gas sector by the International Energy Agency (IEA), of multiple sectors by the Internatio nal Institute of Applied Systems Analysis (IIASA), the US EPA and a group of researchers: Harmsen et al., Env. Sci. Pol., 2019. Potentials are analyzed for 2020 by IEA assuming maximum application of existing technology, and for 2030 in the EPA, IIASA and Harmsen analyses accounting for estimated changes in baseline emissions and fo r the time required for technological transformations. Mitigation labeled '(avg)' represents averages across the available analyses. Note that the Harmsen analysis doe s not include negative cost measures, and that EPA anlayses are for measures costing less than $25,000 per tonne methane from their 2019 report.
Composition and Climate Models
Responses of the Earth system to methane changes are based upon a coordinated model study using the following models: the CESM2(WACCM6) model developed by the Natio nal Center for Atmospheric Research in Boulder, CO, USA; the GFDL AM4.1/ESM4.1 model developed by the National Oceanographic and Atmospheric Administration in Princeto n, NJ, USA; the GISS E2.1/E2.1-G model developed by the National Aeronautics and Space Administration in New York, NY, USA; the MIROC-CHASER model developed jointly by the Atmosphere and Ocean Research Institute, University of Tokyo, the National Institute for Environmental Studies, Tsukuba, the Japan Agency for Marine-Earth Science and Technology, Yokohama, and Nagoya University, Nagoya, Japan; and the UKESM1 model developed by the UK Meteorological Office, Exeter, UK and the UK academic communi ty. Impact evaluations use the multi-model mean of these models interpolated to the given emissions change. Analyses demonstrated that health and agriculture-related o zone changes scale approximately linearly with methane emissions changes, so that the interpolated results are highly accurate for current background atmospheric condi tions.
Impact Analyses
The impacts analyzed include the effects on climate change and ground-level ozone concentrations, and then via those environmental changes the resulting impacts on human health, agricultural crops and the economy. Human health impacts take place the same year as emissions change, whereas climate changes are reported for the avera ge over 1-3 decades after emissions changes. Agricultural impacts are largely driven by ozone change, and hence quasi-immediate, but the climate-related impacts occur more slowly (those are especially important for tropical wheat). For premature deaths, results are based upon the relationship between ozone exposure and health impact s determined from the American Cancer Society Cancer Prevention Study II that followed more than 660,000 people for 22 years and quantified the increased risk of heart disease, cerebrovascular disease, pneumonia and influenza, chronic obstructive pulmonary disease and lung cancer with increased ozone exposure. Those increased risks are combined with data on public health conditions and population distributions to evaluate worldwide health burdens. For agriculture, relative yield losses are based on field studies of the response to ozone and meta-analyses of both measured and modeled responses to climate change. These are then applied to 2010 crop distributions from the Food and Agricultural Organization to obtain tonnes yield changes. Additional information on impacts and associated uncertainties can be found in the benefit map captions.
NOTE: There is an issue with the legends and titles for one entry in the analyses. For the valuations, the left panel shows Value of avoided Lost Work hours due to heat exposure (millions $US) and the right shows Valuation of Increase in Crop Yields due to Climate and Ozone Response to Methane ($US). The caption should read The left map shows the monetized value of reduced risk of premature death due to respiratory plus cardiovascular illnesses caused by ozone in persons of age 30 and ol der. Valuation of reduced risk is based upon willingness to pay data, adjusted to local income levels all using 2018 USD. Uncertainties in these values stem from both the underlying exposure-response relationships and the ozone response to methane. These vary slightly from country to country, but the 95% confidence interval extends from ~60% lower to 75% higher than the best estimates shown here. The right map shows the valuation of the increases in yield of wheat, rice, maize and soybeans in res ponse to the input methane emissions changes. Values are based on the temperature, precipitation and ozone responses along with a small contribution from CO2 fertiliza tion to establish yield changes, which are then valued based on world commodity prices.
We thank our sponsors: the Climate and Clean Air Coalition and NASA. Visualization assistance from Cypress River Advisors is also gratefully acknowledged. Developme nt of this web tool benefited enormously from the work of volunteer Duke University undergraduates (Krista Stark, Jared Junkin, Maxwell Silverstein, Rithik Castelino, and Alex Glick) as well as graduate students working towards their degrees (Karl Seltzer, Muye Ru, Gray Li, and Longyi Yang). Suggestions and comments appreciated (send to drew.shindell@duke.edu).
