基于地基观测及源清单的2017—2019年德州市秋冬季大气污染防治效果评估
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摘要
为评估污染减排措施实施效果,基于地基观测及排放清单数据,运用WRF中尺度气象模型和CAMx空气质量模型,对德州市2017—2019年秋冬季大气污染攻坚实施效果进行了评估.结果表明,2017—2018年秋冬季,德州市ρ(PM2. 5)同比下降31. 7%,高于京津冀及周边地区平均水平(25. 6%),大气污染攻坚措施成效显著; 2018—2019年秋冬季,德州市ρ(PM2. 5)同比增加8. 5%,高于京津冀及周边地区平均水平(4. 2%),这与不利气象条件及排放量同比减少有关.观测结果显示,2018—2019秋冬季,德州市PM2. 5中无机组分、一次排放示踪物以及SO_2和CO等气态前体物浓度较上一年度呈下降趋势,ρ(SOA)(SOA为二次有机气溶胶)、ρ(NH4+)同比有大幅增长,增幅分别为53. 8%和19. 1%,这与大气中VOCs(挥发性有机物,增加46. 5%)及大气氧化性(增加6. 4%)的增加密切相关,表明德州市复合型大气污染加剧,PM2. 5防控难度加大.综合气象和减排评估结果可知,2017—2018年秋冬季,气象条件(13. 4%)和长效措施(9. 4%)是德州市PM2. 5改善的两个主要因素; 2018—2019年秋冬季,长效措施减排效果较为有限,减排主要来自预警应急(5. 0%)和区域减排(5. 2%),若仅考虑不利气象条件的影响,将导致同比约19. 9%的反弹.因此,持续深入推进长效减排措施,降低污染物排放水平,是德州市实现空气质量改善的根本途径.
In order to evaluate the effect of emission reduction measures,the effect of air pollution control in autumn and winter from 2017 to 2019 in Dezhou City was evaluated with ground-based observation and emission inventory data,the WRF mesoscale meteorological model and the CAMx air quality model. The results showed that during the winter period from 2017 to 2018,PM2. 5 mass concentration in Dezhou City decreased by 31. 7% compared with that of the previous year,which was higher than the average level of Jing-Jin-Ji and its surrounding areas( 25. 6%),suggesting the extraordinary effect of the prevention and control. During the winter period from 2018 to2019,PM2. 5 of Dezhou City increased by 8. 5% over the last year,which was higher than the average level of Jing-Jin-Ji and its surrounding areas( 4. 2%). This was related to the unfavorable weather condition and the loose of pollutant emissions. The ground-based observation showed that the concentration of inorganic components,primary emission tracer of PM2. 5 as well as SO_2,CO and other gaseous precursors in Dezhou City all decreased in 2018-2019 while SOA and NH4+showed substantial increase of 53. 8% and 19. 1%,respectively,which may be closely related to the increase in volatile organic compounds( increased by 46. 5%) and atmospheric oxidation( increased by 6.4%). This result indicated that the air pollution in Dezhou City became more complex and the prevention and control of PM2. 5 will be more difficulties. Based on the comprehensiveanalysis of meteorological and emission reduction assessments,meteorology( 13. 4%) and long-term emission reduction( 9. 4%) are two main factors for the improvement in Dezhou City during the winter precaution from 2017 to 2018. During the winter period from 2018 to 2019,the effect of long-term emission reduction was not as important as emergency pre-warning and response( 5. 0%) and regional emission reduction( 5. 2%). The unfavorable effects of meteorology conditions would result in approximately 19.9% rebound when other factors were not taken into account. Continuously promoting long-term emission reduction policies and reducing pollutant emission are the fundamental way to achieve air quality improvement.
In order to evaluate the effect of emission reduction measures,the effect of air pollution control in autumn and winter from 2017 to 2019 in Dezhou City was evaluated with ground-based observation and emission inventory data,the WRF mesoscale meteorological model and the CAMx air quality model. The results showed that during the winter period from 2017 to 2018,PM2. 5 mass concentration in Dezhou City decreased by 31. 7% compared with that of the previous year,which was higher than the average level of Jing-Jin-Ji and its surrounding areas( 25. 6%),suggesting the extraordinary effect of the prevention and control. During the winter period from 2018 to2019,PM2. 5 of Dezhou City increased by 8. 5% over the last year,which was higher than the average level of Jing-Jin-Ji and its surrounding areas( 4. 2%). This was related to the unfavorable weather condition and the loose of pollutant emissions. The ground-based observation showed that the concentration of inorganic components,primary emission tracer of PM2. 5 as well as SO_2,CO and other gaseous precursors in Dezhou City all decreased in 2018-2019 while SOA and NH4+showed substantial increase of 53. 8% and 19. 1%,respectively,which may be closely related to the increase in volatile organic compounds( increased by 46. 5%) and atmospheric oxidation( increased by 6.4%). This result indicated that the air pollution in Dezhou City became more complex and the prevention and control of PM2. 5 will be more difficulties. Based on the comprehensiveanalysis of meteorological and emission reduction assessments,meteorology( 13. 4%) and long-term emission reduction( 9. 4%) are two main factors for the improvement in Dezhou City during the winter precaution from 2017 to 2018. During the winter period from 2018 to 2019,the effect of long-term emission reduction was not as important as emergency pre-warning and response( 5. 0%) and regional emission reduction( 5. 2%). The unfavorable effects of meteorology conditions would result in approximately 19.9% rebound when other factors were not taken into account. Continuously promoting long-term emission reduction policies and reducing pollutant emission are the fundamental way to achieve air quality improvement.
引文
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[22] BOVE M C,BROTTO P,CASSOLA F,et al.An integrated PM2. 5source apportionment study:positive matrix factorisation vs. the chemical transport model CAMx[J]. Atmospheric Environment,2014,94:274-286.
[2] LIU X G,LI J,QU Y,et al.Formation and evolution mechanism of regional haze:a case study in the megacity Beijing,China[J].Atmospheric Chemistry and Physics,2013,13(9):4501-4514.
[3] ZHANG Yinglong,ZHU Bin,GAO Jinhui,et al. The source apportionment of primary PM2. 5in an aerosol pollution event over Beijing-Tianjin-Hebei Region using WRF-Chem,China[J].Aerosol and Air Quality Research,2017,17(12):2966-2980.
[4]徐伟召，朱雯斐，王甜甜，等．冬季德州市大气颗粒物消光与化学组成关系研究[J]．环境科学学报，2019,39(4):1057-1065.XU Weizhao,ZHU Wenfei,WANG Tiantian,et al. Relationship between the aerosol light extinction and chemical composition in winter of Dezhou City[J]. Acta Scientiae Circumstantiae,2019,39(4):1057-1065.
[5]刘文雯，段菁春，胡京南，等．基于环境监测数据的大气重污染应急减排措施效果评估[J]．环境科学研究，2019,32(5):734-741.LIU Wenwen,DUAN Jingchun,HU Jingnan,et al.Effect assessment of emergency measures for heavy air pollution based on environmental monitoring data[J]. Research of Environmental Sciences,2019,32(5):734-741.
[6]王浩，李轶，高健，等．APEC会议期间石家庄市大气污染特征及空气质量保障措施效果评估[J]．环境科学研究，2016,29(2):164-174.WANG Hao,LI Yi,GAO Jian,et al. Characteristics of air pollution and evaluation of the effects of air quality assurance measures in Shijiazhuang City during the 2014 APEC meeting[J]. Research of Environmental Sciences,2016,29(2):164-174.
[7]李荔，刘倩，李冰，等．南京青奥会期间管控措施空气质量改善效果评估[J]．环境科学研究，2016,29(2):175-182.LI Li,LIU Qian,LI Bing,et al. Assessment of air quality benefits from control measures during Nanjing Youth Olympic Games[J].Research of Environmental Sciences,2016,29(2):175-182.
[8] ODUM J R,HOFFMANN T,BOWMAN F,et al. Gasparticle partitioning and secondary organic aerosol yields[J].Environmental Science&Technology,1996,30(8):2580-2585.
[9] ZHANG Y X,SCHAUER J J,ZHANG Y H,et al.Characteristics of particulate carbon emissions from real-world Chinese coal combustion[J]. Environmental Science&Technology,2008,42(14):5068-5073.
[10] GAO S,NG N L,KEYWOOD M,et al. Particle phase acidity and oligomer formation in secondary organic aerosol[J]. Environmental Science&Technology,2004,38(24):6582-6589.
[11]吴晓璐．长三角地区大气污染物排放清单研究[D]．上海:复旦大学，2009.
[12]贺克斌，王书肖，张强，等．城市大气污染物排放清单编制技术手册[R]．北京:清华大学，2017.
[13] SHEN J,WANG X S,LI J F,et al.Evaluation and intercomparison of ozone simulations by Models-3CMAQ and CAMx over the Pearl River Delta[J]. Science China Chemistry,2011,54(11):1789-1800.
[14] CHANG J S,BROST R A,ISAKSEN I S A,et al. A threedimensional eulerian and acid deposition model-physical concepts and formulation[J].Journal of Geophysical Research:Atmospheres,1987,92(D12):14681-14700.
[15] NENES A,PANDIS S N,PILINIS C. ISORROPIA:a new thermodynamic equilibrium model for multiphase multicomponent inorganic aerosols[J]. Aquatic Geochemistry,1998,4(1):123-152.
[16] GUENTHER A,KARL T,HARLEY P,et al. Estimates of global terrestrial isoprene emissions using MEGAN(Model of Emissions of Gases and Aerosols from Nature)[J]. Atmospheric Chemistry&Physics,2006,6(11):3181-3210.
[17] SKAMAROCK W C.A description of the advanced research WRF version 3[J].Ncar Technical Notes,2006,113:7-25.
[18] LI X,WANG L,JI D,et al.Characterization of the size-segregated water-soluble inorganic ions in the Jing-Jin-Ji urban agglomeration:spatialtemporal variability,size distribution and sources[J].Atmospheric Environment,2013,77:250-259.
[19] ZHANG T,CAO J J,TIE X X,et al. Water-soluble ions in atmospheric aerosols measured in Xi'an,China:seasonal variations and sources[J].Atmospheric Research,2011,102(12):110-119.
[20] CHAN C K,YAO X. Air pollution in mega cities in China[J].Atmospheric Environment,2008,42(1):1-42.
[21] JAOUI M,KLEINDIENST T,OFFENBERG J H,et al. SOA formation from the atmospheric oxidation of 2-methyl-3-buten-2-ol and its implications for PM2. 5[J]. Atmospheric Chemistry and Physics Discussions,2011,11:24043-24083.
[22] BOVE M C,BROTTO P,CASSOLA F,et al.An integrated PM2. 5source apportionment study:positive matrix factorisation vs. the chemical transport model CAMx[J]. Atmospheric Environment,2014,94:274-286.
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