Tang Tao, Cheng Tianhai, Zhu Hao, Ye Xiaotong, Fan Donghao, Li Xingyu, Tong Haoran
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100049, China.
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.
Sci Total Environ. 2024 Aug 15;938:173479. doi: 10.1016/j.scitotenv.2024.173479. Epub 2024 May 25.
Thermal power plants are significant contributors to nitrogen oxides (NOx), impacting global atmospheric conditions and human health. Satellite observations, known for their continuity and global coverage, have become an effective means of quantifying power plant emissions. Previous studies, often accumulating long temporal data into integrated plumes, resulted in substantial errors in annual emissions at the individual power plant level due to neglecting variations in emissions and diffusion conditions. This study presents, for the first time, the quantification of instantaneous NOx emissions based on single overpass observations from the Tropospheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite. By addressing the temporal variability of power plant emissions, it effectively reduces annual estimation errors. Comparative analysis between the Exponentially-Modified Gaussian (EMG) and Gaussian Plume Model (GPM) simulations demonstrates the capability of EMG to provide instantaneous emission estimates based on actual plumes, exhibiting closer proximity to actual monitoring values than GPM. Applying the EMG method, we quantify the instantaneous emission rates of six power plants in the United States. Comparing annual emission estimations at individual power plants with traditional integrated plume results, our method demonstrates a 63.7 % improvement in annual emission estimations. This study offers more detailed data on power plant emissions, providing a new avenue for better understanding the emission behavior of thermal power plants.
火力发电厂是氮氧化物(NOx)的重要排放源,对全球大气状况和人类健康产生影响。以连续性和全球覆盖范围著称的卫星观测,已成为量化发电厂排放的有效手段。以往的研究通常将长时间的数据累积成综合羽流,由于忽略了排放和扩散条件的变化,在单个发电厂层面的年度排放中产生了大量误差。本研究首次基于哨兵 - 5 号前体卫星上的对流层监测仪器(TROPOMI)的单次过境观测,对瞬时 NOx 排放进行了量化。通过解决发电厂排放的时间变异性问题,有效降低了年度估算误差。指数修正高斯(EMG)模型和高斯羽流模型(GPM)模拟之间的对比分析表明,EMG 能够基于实际羽流提供瞬时排放估算,与 GPM 相比,其估算值更接近实际监测值。应用 EMG 方法,我们对美国六家发电厂的瞬时排放率进行了量化。将单个发电厂的年度排放估算与传统综合羽流结果进行比较,我们的方法在年度排放估算方面显示出 63.7% 的改进。本研究提供了关于发电厂排放的更详细数据,为更好地理解火力发电厂的排放行为开辟了新途径。