# **1. Introduction**

The World Meteorological Organization forecasts that the current greenhouse gas (GHG) emissions trend will increase global temperature 3-5 degrees C by 2100 (Reuters 2018). This would far overshoot the 2-degree limit pledged by the 2015 Paris Climate Accord (COP 21) and might have a catastrophic impact (Steffen et al. 2018; World Bank 2012). In response, several industrial nations pledged very steep emissions reductions at the Leaders’ Summit on Climate in April 2021. The response deepened at COP 26 in Glasgow with the introduction of the Global Methane Pledge, whose 122 current participating nations have joined a collective effort to reduce global methane (CH4) emissions at least 30 percent from 2020 levels by 2030. The Pledge highlights the particular importance of methane reduction: “Methane is a powerful but shortlived climate pollutant that accounts for about half of the net rise in global average temperature since the pre-industrial era. Rapidly reducing methane emissions from energy, agriculture and waste ... is regarded as the single most effective strategy to keep the goal of limiting warming to 1.5 ̊C within reach while yielding co-benefits including improving public health and agricultural productivity.”<sup>1</sup> The Global Methane Pledge is a laudable commitment by the international community, and broad-based participation will build political support for emissions reduction. At the same time, a rapid transition may be assisted by an evidence-based global effort that identifies the highestpriority CH4 emissions sites and mobilizes the latest technology to monitor their progress. This paper attempts to contribute with a multi-level approach. First, we perform a spatial analysis of global CH4 emissions to assess potential gains from priority site identification. Then we use the World Bank’s gridded database of satellite-measured methane concentrations at 5-km resolution to establish a template for tracking methane emissions reduction at priority sites. We demonstrate its potential effectiveness with case studies for large sources of methane emissions from energy, agriculture and waste. Then we extend the template to create and analyze emissions trend reports for 775 high-priority global sites.

The remainder of the paper is organized as follows. Section 2 analyzes the global distribution of methane emissions sources using “bottom-up” estimates from the Emissions Database for Global Atmospheric Research (EDGAR).<sup>2,3</sup> In Section 3, we use the results to identify high-priority sites where rapid reduction of methane emissions would accelerate the global transition. Section 4 develops a strategy for sampling satellite-measured CH4 concentrations in sites that account for 50% of global methane emissions. Section 5 introduces our monitoring approach with illustrative case studies for landfills (Spain), irrigated rice production (India) and oil production (Iraq). In Section 6, we extend our approach to 775 high-priority areas and use the results to analyze the distribution of emissions trends globally, by source sector, and by World Bank income group. Section 7 presents the priority-area reports in detailed tables, maps and an accompanying Excel file, while Section 8 summarizes and concludes the paper.

> 1 https://www.globalmethanepledge.org/#about

> 2 https://edgar.jrc.ec.europa.eu/

> 3 EDGAR’s “bottom-up” approach estimates emissions by combining sectoral activity data with broadly-calibrated emissions factors (Crippa et al. 2020; Solazzo et al. 2021).

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