Exposure to air pollution is the largest environmental health risk in India, where the coal-fed thermal power plants (TPPs) are identified as the single largest air pollution source. The key to an efficient air quality management plan is strict compliance of the TPPs with emission norms. Yet, in-situ measurements are lacking, and the bottom-up emission inventory is not periodically updated in India. Here we adopt a top-down approach to estimate NO₂ emission from nine TPPs within 300 km of the megacity Delhi using TROPOspheric Monitoring Instrument (TROPOMI) data. We first estimate the NO₂ lifetime for each TPP using an e-folding decay length along the wind direction and combine it with the NO₂ columnar molecular density to estimate the NO₂ emission. Our estimates show a correlation coefficient of 0.88, and a root mean square error of 4.15 kt/year with the ECLIPSE V5 bottom-up inventory. NO₂ emission in these TPPs varied in the range of 8.0–30.6 kt/year with considerable seasonal variability. Using this data, we report a decrease in NO₂ emission in the range 41%–290% during the COVID-19 lockdown period relative to the same period in the previous year. As India launched the National Clean Air Program to control air pollution, our method would be highly useful in tracking the emission compliance of the TPPs across the country.

暴露于空气污染是印度最大的环境健康风险，其中燃煤热电厂 (TPP) 被确定为最大的单一空气污染源。有效的空气质量管理计划的关键是严格遵守 TPP 的排放标准。然而，缺乏现场测量，而且印度没有定期更新自下而上的排放清单。在这里，我们采用自上而下的方法，使用对流层监测仪器 (TROPOMI) 数据估算德里特大城市 300 公里范围内 9 个 TPP 的NO ₂排放。我们首先使用沿风向的 e 折叠衰减长度估计每个 TPP的 NO ₂寿命，并将其与 NO ₂柱状分子密度结合以估计 NO ₂排放。我们的估计表明 ECLIPSE V5 自下而上库存的相关系数为 0.88，均方根误差为 4.15 kt/年。这些 TPP 中的NO ₂排放量在 8.0-30.6 kt/年的范围内变化，具有相当大的季节性变化。使用这些数据，我们报告说，在 COVID-19 锁定期内，与上一年同期相比，NO ₂排放量减少了 41%–290%。随着印度启动了控制空气污染的国家清洁空气计划，我们的方法对于跟踪全国 TPP 的排放合规性非常有用。