The Tempo-spatial Distribution Of Pollutants In China Based On Satellite Observation And Analysis Of Emission-reduction Measures

The air pollution in China is becoming more and more severe.NO₂ and SO₂ are the main polluted trace gases,then form secondary aerosol through further chemical reaction,which seriously threaten human health.The accuracy of the ground monitoring is high,but the sites are sparse and there are less data.The data of NO₂and SO₂ observed by satellite make up the shortage of the tempo-spatial of the ground monitoring sites,which is suitable for the study of long-time and large-scale.Therefore,firstly in this paper,the ground monitoring station data of Xuzhou in 2016 was used to analyze the variational characteristics of pollution gas NO₂ and SO₂.After that,we compared the difference of tropospheric NO₂ column concentrations observed by GOME-2 and OMI in 2016.At the same time,the MEIC emission inventory was preliminarily verified by calculating pollutant gas emissions from coal-fired units,and OMI satellite observation was analyzed with the MEIC and MarcoPolo emission inventory in 2012.Then,the tempo-spatial characteristics of the tropospheric NO₂ column concentration and the SO₂ planetary boundary layer?PBL?column concentrations from 2005 to 2016 were quantitatively analyzed.Finally,combined with the fossil energy consumption,we have accurately analysed the effectiveness of the implementation of related emission-reduction measures in China.The results showed that:?1?The diurnal variation of surface NO₂ mass concentration in urban and suburban areas of Xuzhou was bimodal and double-valley,but SO₂ was unimodal.There was a positive correlation between the satellite observation and the surface mass concentration.The correlation about NO₂ is higher than SO₂.There was good agreement for GOME-2 and OMI tropospheric NO₂ column concentration with high correlation coefficient?R²=0.9488?.In comparison,the tropospheric NO₂ column concentration observed by OMI could better characterize the surface NO_X emissions.?2?The pollution gas observed by OMI and the emission inventories included"bottom-up"?MEIC?and the"top-down"?MarcoPolo?were compared about the spatial distribution and the provincial scale.The results showed:for NO_X emission,the tropospheric NO₂ column concentration observed by OMI could better reflect the spatial pattern of NO_X emission,and it was consistent with the variational characteristics of NO_X emission at the provincial scale;for SO₂ emission,the current algorithm of retrieving SO₂ from satellite observation can only obtain the relative tempo-spatial distribution and variation of SO₂ column concentration.?3?The overall spatial distribution of tropospheric NO₂ column concentration and SO₂ PBL column concentrations was unbalanced in China and had significant regional characteristics,areas with high value were widely distributed.There were obvious differences between eastern and western regions.NO₂ and SO₂ pollution in northern part of Henan province was equivalent to those of Beijing-Tianjin-Hebei and Shandong,but it was not included in the key areas to joint prevention and control of"three districts,ten groups".The areas where NO_X emissions were dominated by anthropogenic sources in China were mainly concentrated in the eastern part and some areas of Xinjiang with the high population density and concentrated industrial.?4?The NO₂ column concentration from satellite observation and the statistical SO₂ emissions reflected that the emission targets of NO_X and SO₂ in the"11th Five-Year"and"12th Five-Year"plan have been completed.The variational characteristics of NO_X energy emission factor and SO₂ coal-fired emission factor in China was consistent with the introduced year of emission-reduction measures at all stages in China.The ratio of pollutant emissions to fossil energy consumption can eliminate the impact of economic activities on the fluctuation of pollutant emissions.By analyzing variations in fossil energy emission factors,the effectiveness of emission-reduction measures can be more accurately analysed.