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arXiv · 2604.06661

Global near-real-time daily emissions of atmospheric pollutants from power plants

Tao Li·Lixing Wang·Biqing Zhu·Zhu Liu
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Abstract

The power sector is a major source of fossil fuel use and air pollutant emissions, making high-spatiotemporal-resolution emission accounting essential for effective mitigation policy and air quality management. Yet existing public inventories are often limited by low timeliness and coarse resolution. Here, we develop a global, plant-level, daily, multi-pollutant emission database for the power sector by integrating nearly 3 million hourly-to-daily near-real-time power generation records from 57 countries, representing about 81% of global fossil-fuel-based electricity generation, with fundamental information for more than 10,000 power plants worldwide, including location and installed capacity. The dataset substantially improves the timeliness and granularity of global power-sector emission estimates. From 2019 to 2025, emissions of most pollutants increased, with 2025 daily mean emissions reaching 0.274 kt/d for BC, 45.1 kt/d for CO, 0.418 kt/d for NH3, 52.2 kt/d for NOx, 3.01 kt/d for NMVOC, 0.418 kt/d for OC, 6.76 kt/d for PM10, 5.11 kt/d for PM2.5, and 78.5 kt/d for SO2. Compared with 2019, NMVOC showed the largest increase, whereas SO2 was the only pollutant to decline overall. Coal remained the dominant source of sulfur-, nitrogen-, and particulate-related emissions, while gas and biomass contributed more to carbonaceous species and reduced nitrogen. The dataset also captures pronounced seasonal, regional, and short-term variability. Against EDGAR for 2019-2022, our estimates agree well, with Pearson correlations of 0.92-0.99 and mean relative deviations of 8.8%-28.1%. This near-real-time, high-resolution dataset provides a strong foundation for air pollution control, carbon mitigation, emission monitoring, and satellite-based inversion.

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Tao Li, Lixing Wang, Biqing Zhu, Zhu Liu. 2026-04-08. Global near-real-time daily emissions of atmospheric pollutants from power plants. https://arxiv.org/abs/2604.06661

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