基于热异常遥感的冀南城市群工业能耗及大气污染

选取冀南城市群为研究区，基于2012~2016年VⅡRS卫星数据热异常点产品，结合工业能源消耗量、工业废气排放量以及空气质量数据，利用统计分析和空间分析探讨热异常点辐射强度的变化规律及其与工业能源消耗、污染物排放之间的关系.结果表明，热异常点的辐射强度可以表征工业能源消耗量，并间接反映工业生产规模与污染排放水平.辐射强度越大，工业生产规模越大.辐射强度与工业SO₂排放量呈较高的正相关，与NO_x排放量呈中度线性相关.PM₁₀、SO₂及NO₂浓度与工业能源消耗和热异常点辐射强度灰色关联度均较高.工业生产活动产生的污染物中，颗粒物对大气污染的贡献最高，其次为SO₂.2012~2016年，邯郸、石家庄以及廊坊的工业生产空间分布呈逐年收缩聚集的趋势，保定和沧州的工业生产分别出现向南、向西迁移趋势.

Industrial pollution emissions based on thermal anomaly remote sensing monitoring:A case study of Southern Hebei urban agglomerations,China

The urban agglomerations of southern Hebei were selected as the study area. Statistical and spatial analysis methods were applied to a variety of datasets including VⅡRS thermal anomaly products from 2012~2016, industrial energy consumption, industrial exhaust emissions and air quality data. The variation law of radiation intensity of thermal anomaly was the main principle examined with the data on industrial energy consumption and pollution emissions. The fire radiative power of thermal anomalies can characterize industrial energy consumption and indirectly reflect industrial production scale and pollution emission levels. The greater the fire radiative power, the larger the scale of industrial production. Radiation intensity was highly correlated with industrial SO₂ emissions and moderately linear with NO_x emissions. The grey correlations between pollutant's concentration and industrial energy consumption, pollutant concentration and thermal anomaly radiation intensity were both higher. Among the pollutants produced by industrial production activities, particulate matter had the highest contribution to atmospheric pollution, followed by SO₂. In the 2012~2016 period, the spatial distribution of industrial production in Handan, Shijiazhuang and Langfang showed a trend toward shrinking year by year. The industrial production of Baoding and Cangzhou showed a trend of migration to the south and west.