| Nitrogen dioxide (NO2) is one of the constituents of troposphere. It is an important atmospheric trace gas and one of the main pollutants in atmosphere. It is an important precursors of ozone and other photochemical smog. It has great influence on respiration. NO2 density is an important indicator of atmospheric environmental monitoring. Time-series monthly GOME, GOME-2 and SCIAMACHY satellite remote sensing data were used, and the monthly average NO2 column densities from 1996 to 2012 in Hebei Province were extracted using ArcGIS software. The spatial and temporal change of monthly average and annual average NO2 column densities of 11 prefecture-level cities in Hebei Province were analyzed. In combination with precipitation and temperature data, as well as total population, GDP and total energy consumption data, influence factors of spatiotemporal distribution of tropospheric NO2 column densities in Hebei Province were analyzed. NO2 column densities were divided into low-value area (<10×1015molec/cm2), medium-value area (10-20×1015molec/cm2) and high-value area (>20×1015molec/cm2) to make study. The main conclusions were as follows:(1) The annual and seasonal changes of spatial distribution of NO2 column densities in eleven prefecture-level cities of Heibei Province from 1996 to 2012 were analyzed. The spatial distribution of NO2 in Hebei Province was extremely uneven with high NO2 in the southeast and low NO2 in the northwest. Areas with high NO2 values expanded each year. High NO2 values were distributed in Hebei plain in the southeast, including Shijiazhuang, Xingtai, Handan and Langfang cities, while low NO2 values were located in Yanshan Mountains, Taihang Mountains and Bashang Plateau. The change of NO2 spatial distribution was minimum in summer, and maximum in winter.(2) The interannual changes of NO2 column densities in Hebei Province presented a trend of increase from 1996 to 2012, except during the 2008 Beijing Olympic Games period. The highest NO2 column density appeared in 2011, which was 23.61×1015molec/cm2, the lowest NO2 column density appeared in 1996, which was 6.72×1015molec/cm2, and the average annual growth rate from 1996 to 2012 was 6.87%. The highest annual average NO2 column density appeared in Langfang city, followed by Shijiazhuang city, and the lowest appeared in Chengde city. The area with high NO2 column densities was getting greater, and the area with medium and low NO2 column densities was getting smaller, especially the area with medium NO2 values.(3) NO2 column densities in autumn and winter were significantly higher than those in spring and summer. The highest NO2 value appeared in winter and the lowest appeared in summer. The highest average NO2 column densities in winter appeared in Shijiazhuang and Hengshui cities, and NO2 seasonal differences were relatively great. The NO2 seasonal change trends were similar in Zhangjiakou and Chengde cities, and there was no significant seasonal change.(4) The ground-based NO2 daily change in 2014 in Hebei Province were analyzed. NO2 daily change curve had single peak and single valley in Shijiazhuang and Handan cities with higher economic levels and dense population. NO2 daily change curve had two peaks and two valleys in Zhangjiakou city with low economic level and sparse population. NO2 daily change at night was significantly higher than that in the day.(5) The ground-based NO2 column densities were positively correlated to those from OMI data from December 2013 to December 2015. The coorelationship coefficients were higher in eleven prefecture-level cities, except Qinhuangdao and Tangshan cities.(6) Natural and socio-economic factors had impact on tropospheric NO2 column densities in Hebei Province. NO2 column densities were significantly correlated with temperature, the correlation coefficient was 0.69, and the correlation coefficient with precipiation was 0.53. In addition, NO2 column densities were higher over urban and cropland while lower over grassland and forestland. The socio-economic factors were population density, vehicle ownership, total energy consumption, etc. |
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