基于Sentinel-5P卫星的中国NO2浓度遥感监测

NO₂是重要的痕量气体,对其监测有助于大气污染治理。本文基于Sentinel-5P大气污染监测卫星提供的对流层NO₂浓度数据和总NO₂浓度数据,借助谷歌地球引擎(google earth engine,GEE)分析了2018~2021年间中国大气NO₂浓度时空变化特征,使用OLS模型揭示了中国地区NO₂浓度的主要影响因子。结果表明:我国对流层NO₂浓度空间分布呈现东高西低的总体格局,东中部城市群对流层NO₂柱浓度水平明显呈现冬高夏低、春秋过渡的季节特征,西部大部分城市的四季变化不明显。北京、深圳、上海3所城市NO₂柱浓度分布呈现出较为显著的圈层结构。OLS模型结果表明,中国地区NO₂浓度变化受到社会经济和自然因素的共同影响,其中城市化程度是影响NO₂排放的重要因子。

Monitoring atmospheric NO2 concentrations in China based on Sentinel-5P satellite products

NO₂ is an important trace gas and its monitoring contributes to air pollution control. Based on the tropospheric vertical column and total vertical column of NO₂ provided by the Sentinel-5P air pollution monitoring satellite, we analyzed spatial-temporal characteristics of NO₂ in China during 2018~2021 by Google Earth Engine (GEE) and revealed the main drivers of NO₂ concentration using OLS model. Results showed that there were a spatial pattern with high in the east and low in the west regarding the tropospheric vertical column of NO₂ in China. A seasonal pattern with high in winter, low in summer and excessive in spring and autumn, was presented in the eastern and central city clusters and Urumqi city. The western cities, however, had less significant changes within seasons. The concentration distribution of tro NO₂ in Beijing, Shanghai and Shenzhen showed a significant circle structure. The OLS model results showed that the atmospheric NO₂ concentration in China was influenced collectively by socio-economic and natural factors, with the degree of urbanization being the critical factor driving NO₂ emissions.