大连市大气污染天气特征及污染成因模拟分析
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摘要
利用大连市2014～2015年地面观测资料、高空地面形势场和2015年12月NCEP/NCAR再分析资料,结合WRF-CMAQ数值模式,对大连市污染天气特征和污染过程的成因进行分析研究.结果表明:2014～2015年大连市共有大气污染日数145d,占20%,大气污染天气过程35个;发生大气污染时的高空形势场主要为槽后脊前的西北气流场,占63%,槽前西南气流场次之,占21%,槽区、脊区各占6%;地面形势场主要表现为风速较小的均压场(68%)和等压线密集风速较大的非均压场(32%)两种气压场.2015年12月出现的5次污染过程中,大气层结均为稳定层结,且近地面水平风速均值较小,对污染物垂直方向和水平方向上的扩散起到抑制作用,导致空气质量恶化;模拟结果发现大连市冬季污染过程中大气气溶胶的的主要成分是硝酸盐、铵盐和硫酸盐等细颗粒物,其中硝酸盐占比最大,且污染过程的增幅最为明显,说明机动车和燃煤排放已对大连市城市污染的形成产生重要影响.
Based on the observational data, upper air and ground surface synoptic field during 2014～2015, and NCEP/NCAR reanalysis data in December 2015, combined with WRF-CMAQ numerical model, the characteristics and the cause of the air pollution process in Dalian were analyzed. The results showed that there were 145 pollution days, accounting for 20%, and 35 pollution processes in Dalian from 2014 to 2015. The upper air circulations during air pollutions were mainly northwest air flow field after the trough(accounting for 63%), and the southwest air flow field before the trough(accounting for 21%). The ground surface synoptic field were mainly in two types, which are uniform pressure field with weak wind(accounting for 68%) and intensive isobars with high-speed wind. The atmospheric stratification was stable, with weak average horizontal wind during 5 air pollution processes in December 2015 in Dalian, which suppressed the dispersion of pollutant in the vertical and horizontal directions, leading to the deterioration of air quality. Results of the numerical model simulation showed that nitrate, ammonium and sulfate are the main components of aerosols during the pollution process. And the nitrate provided the first contribution and the most obvious increase during the pollution processes, which means the vehicle emission and coal-fired emission already had important impacts on the formation of urban pollution in Dalian.
Based on the observational data, upper air and ground surface synoptic field during 2014～2015, and NCEP/NCAR reanalysis data in December 2015, combined with WRF-CMAQ numerical model, the characteristics and the cause of the air pollution process in Dalian were analyzed. The results showed that there were 145 pollution days, accounting for 20%, and 35 pollution processes in Dalian from 2014 to 2015. The upper air circulations during air pollutions were mainly northwest air flow field after the trough(accounting for 63%), and the southwest air flow field before the trough(accounting for 21%). The ground surface synoptic field were mainly in two types, which are uniform pressure field with weak wind(accounting for 68%) and intensive isobars with high-speed wind. The atmospheric stratification was stable, with weak average horizontal wind during 5 air pollution processes in December 2015 in Dalian, which suppressed the dispersion of pollutant in the vertical and horizontal directions, leading to the deterioration of air quality. Results of the numerical model simulation showed that nitrate, ammonium and sulfate are the main components of aerosols during the pollution process. And the nitrate provided the first contribution and the most obvious increase during the pollution processes, which means the vehicle emission and coal-fired emission already had important impacts on the formation of urban pollution in Dalian.
引文
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[2]宋宇,唐孝炎,方晨,等.北京市能见度下降与颗粒物污染的关系[J].环境科学学报,2003,23(4):468-471.
[3]Wu D,Tie X X,Deng X J.Chemical characterizations of soluble aerosols in Southern China[J].Chemosphere,2006,64(5):749-757.
[4]GB3095-2012环境空气质量标准[S].
[5]HJ633-2012环境空气质量指数(AQI)技术规定(试行)[S].
[6]Weiss R E,Waggoner A P,Charlson R J,et al.Sulfate aerosol;Its geographical extent in the Midwestern and southern United States[J].Science,1977,195(4282):979-981.
[7]Husar R B,Wilson W E.Haze and sulfur emission trends in the eastern United States[J].Environmental Science and Technology,1993,27(1):12-16.
[8]杨卫芬,银燕,魏玉香,等.霾天气下南京PM2.5中金属元素污染特征及来源分析[J].中国环境科学,2010,30(1):12-17.
[9]Ferman M A,Wolff G T,Kelly N A.The nature and source of haze in the Shenandoah Valley/Blue Ridge Mountains area[J].Air Pollut Control Assoc,1991,31(10):1074-1082.
[10]徐敬,丁国安,颜鹏,等.北京地区PM2.5的成分特征及来源分析[J].应用气象学报,2007,18(5):645-654.
[11]付桂琴,张迎新,谷永利,等.河北省霾日变化及成因[J].气象与环境学报,2014,30(1):51-56.
[12]王成祥,刘加珍.聊城市空气质量现状及污染原因分析[J].气象与环境学报,2016,32(1):108-112.
[13]Ziomas I C,Melas D,Zerefos C S,et al.Forecasting peak pollutant levels from meteorological variables[J].Atmospheric Environment,1995,29(24):3703-3711.
[14]谢付莹,王自发,王喜全.2008年奥运会期间北京地区PM10污染天气形势和气象条件特征研究[J].气候与环境研究,2010,15(5):584-594.
[15]任阵海,苏福庆,高庆先,等.边界层内大气排放物形成重污染背景解析[J].大气科学,2005,29(1):57-63.
[16]Tai A P K,Loretta J M,Daniel J J,et al.Correlations between fine particulate matter(PM2.5)and meteorological variables in the United States:Implications for the sensitivity of PM2.5 to climate change[J].Atmospheric Environment,2010,44(32):3976-3984.
[17]胡敏,刘尚,吴志军,等.北京夏季高温高湿和降水过程对大气颗粒物谱分布的影响[J].环境科学,2006,27(11):2293-2298.
[18]韩燕,徐虹,毕晓辉,等.降水对颗粒物的冲刷作用及其对雨水化学的影响[J].中国环境科学,2013,33(2):193-200.
[19]李芳,张承中.西安市大气颗粒物PM2.5与降水关系的探讨[J].中国环境监测,2013,29(6):22-28.
[20]Ding A,Wang T,Zhao M,et al.Simulation of sea-land breezes and a discussion of their implications on the transport of air pollution during a multi-day ozone episode in the Pearl River Delta of China[J].Atmospheric Environment,2004,38(39):6737-6750.
[21]Chen X L,Feng Y R,Li J N,et al.Numerical simulations on the effect of set-land breezes on atmospheric haze over the Pearl River Delta region[J].Environment Model Assessment,2009,14(3):351-363.
[22]李莉,陈长虹,黄成,等.长江三角洲地区大气O3和PM10的区域污染特征模拟[J].环境科学,2008,29(1):238-246.
[23]韩霄,张美根.2013年1月华北平原重霾成因模拟分析[J].气候与环境研究,2014,19(2):127-139.
[24]李丹.2006~2010年大连市区空气质量变化原因分析[J].辽宁师范大学学报,2011,34(4):524-527.
[25]阎守政,纪德钰,李丹,等.大连市区空气中颗粒物(PM10和PM2.5)污染原因分析[J].中国环境管理干部学院学报,2015,25(4):53-56.
[26]Zhang Q,Streets D G,Carmichael G R,et al.Asian emissions in2006for the NASA INTEX-B mission[J]Atmospheric Chemistry and Physics,2009,9(14):5131-5153.
[27]李锋,朱彬,安俊岭,等.2013年12月初长江三角洲及周边地区重雾霾污染的数值模拟[J].中国环境科学,2015,35(7):1965-1974.
[28]常明,刘晓环,刘明旭,等.非采暖期和采暖期青岛市及中国东部臭氧和细颗粒物模拟研究[J].中国海洋大学学报:自然科学版,2016,46(2):14-25.
[29]李红斌,傅瑜,张靖萱,等.一次大气污染过程的降水天气特征及相关分析[J].气象,2018,44(5):655-664.
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