长春市空气质量污染特征分析与防治对策

为探讨2003－2007年长春市污染新特征,了解大气污染物变化趋势,对市区内客车厂等6个环境空气质量国控点位监测数据进行了归纳计算,并采用API评价方法,得到了PM₁₀、SO₂和NO₂ 3种污染物年均值变化曲线和各种污染类型天数,同时查明了大气污染物的来源。结果表明：2003－2007年间长春市大气污染主要呈现波动略上升的总体特征,据此从气象条件和城市能源消耗等角度分析成因,并提出加深节能减排工作等一系列大气污染防治对策与建议。     

北京地区三级以上污染日的气象影响因子初步分析

依据2001—2007年北京市环境保护局公布的SO₂、NO₂和PM₁₀日平均空气质量等级大于或等于三级以上的污染日作为样本,统计分析了污染日3种污染物指数与同期南郊观象台（近郊区）的地面和探空气象要素的相关关系。同时采用Hysplit-4后向轨迹分析方法,对出现四级以上污染的重污染日污染源进行了初步探讨。结果表明：风向是造成上述3种污染物出现重污染的主要原因之一;污染日存在两重或多重逆温层,而且逆温层较低较厚,垂直对流和水平扩散作用较弱,湿沉降作用较小,因此污染物不易扩散和输送,堆积在近地面,造成重污染。北京西南、东南部地区以及沙尘暴过程内蒙古、河北北部是造成重污染天气的主要输送源地。研究结果可为北京重污染过程的预警预测及其综合防治提供科学依据。     

2010年民勤沙地近地面沙尘气溶胶浓度特征

为了更好地研究沙尘气溶胶起沙和输送特征,2010年4—5月,在民勤周边沙地利用EZ LIDAR ALS300&ALS450型激光雷达和 GRIMM 180型颗粒物采样器进行了大气气溶胶的外场连续观测,取得了晴天、浮尘、扬沙和沙尘暴天气条件下沙尘气溶胶总后向散射垂直剖面图和PM₁₀、PM_2.5、PM_1.0质量浓度采样资料,其中包含“0424”特强沙尘暴过程资料。结果表明：春季民勤近地层大气中沙尘气溶胶浓度较高,且随气象要素的变化很大;在整个观测期内,PM₁₀、PM_2.5、PM_1.0的平均质量浓度分别为202.3、57.4 μg/m³、16.7 μg/m³。在不同天气条件下,PM₁₀、PM_2.5、PM_1.0质量浓度的变化有很好的相关性,但变化趋势有所不同。在沙尘暴天气条件下,PM₁₀的日平均质量浓度高达2469.1μg/m³,是背景天气条件下PM10日平均质量浓度的100多倍,是浮尘天气条件下PM10日平均质量浓度的8倍,是扬沙天气条件下PM₁₀日平均质量浓度的2倍。PM_2.5在沙尘暴天气下日平均质量浓度为460.3 μg/m³,是背景天气条件下PM_2.5日平均质量浓度的45倍,是浮尘天气条件下PM_2.5日平均质量浓度的6倍,是扬沙天气条件下PM_2.5日平均质量浓度的1.4倍。PM_1.0在沙尘暴天气条件下的日平均浓度为92.7 μg/m³,是背景天气条件下PM_1.0日平均浓度的13倍,是浮尘天气条件下PM_1.0日平均浓度的7倍,是扬沙天气条件下PM_1.0日平均浓度的1.3倍。可见,风速增大时沙尘粒子浓度的增加对粒子粒径是有选择的,小粒子比重随沙尘浓度增加而相对减小,大粒子比重随沙尘浓度增加而相对增多;通过对“0424”特强沙尘暴过程的研究表明,一次沙尘暴过程往往包括沙尘暴、扬沙和浮尘天气中的两种类型;通过对激光雷达数据分析发现,在强沙尘暴发生过程当中,民勤沙地发生了非常严重的风蚀起沙现象。     

山西省燃煤电厂二氧化硫减排对硫沉降的影响分析

采用ATMOS长距离传输模型,对2006—2007年山西省燃煤电厂通过关停小机组及增设脱硫设施所减少的SO₂排放量进行数值模拟,并基于地理信息系统,分析了整个模拟范围内的总S沉降和干/湿S沉降分布特点,探讨了关停小机组及增设脱硫设施减少SO₂排放量的效果。结果表明：2006—2007年间山西省燃煤电厂装机容量增加,但SO₂排放及其导致的S沉降量持续下降,表明二氧化硫减排效果非常明显。     

2003年辽西地区空气污染试预报检验

应用新一代大气扩散模型进行了辽西地区 2003年春季和夏季条件下的SO₂和TSP日均浓度试预报 ,同时引入平均相对误差的概念对浓度预报值进行了检验。结果表明 :SO₂预报结果好于TSP ,夏季预报结果好于春季     

本溪市大气环境质量区域评价

利用本溪市2002年TSP(总悬浮颗粒物 )和SO₂(二氧化硫 )大气环境监测资料、污染源排放清单资料和气象资料以及新一代大气扩散模型 ,进行了本溪市大气环境质量区域评价。结果表明 :本溪市低架源对地面浓度的贡献相对较大 ,高架源对地面浓度的贡献相对较小。     

AERMOD空气扩散模型在沈阳的应用和验证

根据2003年1～12月沈阳逐日大气环境监测数据、气象数据以及AERMOD模式系统建立并验证了空气扩散模型;同时,应用污染源排放清单管理工具软件建立了排放清单,其输出的数据格式满足AERMOD空气扩散模型的要求。验证结果表明:颗粒物的监测日平均值与模拟日平均值的相关性较好,81%的数值落在模拟值与监测值的2倍误差范围内,模拟值与监测值的相关系数为0.68;SO₂有72%的数值落在模拟值与监测值的2倍误差范围内,模拟值与监测值的相关系数为0.64。     

基于WRF/CMAQ的成都空气质量模拟与预报

本文是成都地区空气质量预报的一次模拟试验,文章通过污染源排放清单编制、不同模式下垫面资料使用、气象模式大气物理过程参数选取、以及成都地区空气质量实例模拟预报几个方面来开展工作。分析结果表明:使用新下垫面资料对SO₂、NO₂的模拟结果的统计结果均好于旧下垫面资料;选出了适合于成都地区的气象模式物理过程参数方案;受外地源影响较小的NO₂与PM₁₀的模拟预报效果比受外地源影响较大的SO₂模拟预报效果好;清单编制过程中对污染物排放的时间分配因子把握不精确造成了预报趋势与监测值趋势存在差异;对污染源排放量的低估是造成预报值普遍小于监测值的重要原因,同时未考虑外源的输入影响,以及用监测值的点均值来验证预报值的面均值,也是造成预报值与监测值存在明显差异的主要原因。      

不同水力负荷的垂直流湿地对生活污水处理效果研究

以沈阳浑南垂直流人工湿地模拟系统为研究对象,考察了湿地模拟系统对生活污水的处理效果,重点研究了不同水力负荷的影响。结果表明,垂直流湿地模拟系统对生活污水具有较好的处理效果,出水NH₄⁺-N、TP、COD_Cr和BOD₅均达到了《城镇污水处理厂污染物排放标准》（GB18918-2002）一级A 标准;水力负荷为0.156 t/m²•d时,是垂直流湿地模拟系统运行的最佳负荷。     

广州市区酸雨初探

本文通过对广州市区雨水酸度的分析,认为广州是酸性基础甚强的城市,酸雨出现的频率为60%左右,并有冬春强,夏秋弱的季节变化趋势。指出逆温和微风等稳定天气条件是产生酸性降水的有利天气条件。对水样的化学分析结果可见,广州酸雨中SO₄=为主要酸根,各类酸根的浓度变化受环境和人为因素的影响较大。阳离子浓度的强弱对市区酸雨起着重要的缓冲作用,在碱性污染源附近尤为明显。水化学分析结果表明局地污染源的作用是明显的,所以广州市区酸雨主要是由于本地大气污染所致。      

武汉市大气污染源排放清单及分布特征研究

以武汉市为研究区域,基于实地调查获得典型行业污染源活动水平,以大气污染物排放清单编制技术指南为参考,利用排放因子法建立2014年武汉市大气污染源排放清单,并结合经纬度、人口密度分布、土地利用类型、道路长度等数据将排放清单进行了3 km×3 km网格化处理.结果表明,2014年武汉市SO₂、NO_x、PM₁₀、PM_2.5、CO、BC、OC、VOCs和NH₃排放量分别为10.3、17.0、16.3、7.1、63.1、0.6、0.4、19.8和1.6万t.固定燃烧源为SO₂排放的主要来源,其贡献率约64%;移动源为NO_x的主要来源,其贡献率约51%;颗粒物排放主要来源于扬尘源和工艺过程源;CO和VOCs主要来源于工艺过程源,BC和OC排放均以移动源和生物质燃烧源为主,NH₃排放主要来自农业源.污染物排放主要集中在青山区至新洲区一带.     

Local and regional sources of fine and coarse particulate matter based on traffic and background monitoring

The aim of this study was to identify local and exogenous sources affecting particulate matter (PM) levels in five major cities of Northern Europe namely: London, Paris, Hamburg, Copenhagen and Stockholm. Besides local emissions, PM profile at urban and suburban areas of the European Union (EU) is also influenced by regional PM sources due to atmospheric transport, thus geographical city distribution is of a great importance. At each city, PM₁₀, PM_2.5, NO₂, SO₂, CO and O₃ air pollution data from two air pollution monitoring stations of the EU network were used. Different background characteristics of the selected two sampling sites at each city facilitated comparisons, providing a more exact analysis of PM sources. Four source apportionment methods: Pearson correlations among the levels of particulates and gaseous pollutants, characterisation of primal component analysis components, long-range transport analysis and extrapolation of PM size distribution ratios were applied. In general, fine (PM_2.5) and coarse (PM₁₀) particles were highly correlated, thus common sources are suggested. Combustion-originated gaseous pollutants (CO, NO₂, SO₂) were strongly associated to PM₁₀ and PM_2.5, primarily at areas severely affected by traffic. On the contrary, at background stations neighbouring important natural sources of particles or situated in suburban areas with rural background, natural emissions of aerosols were indicated. Series of daily PM_2.5/PM₁₀ ratios showed that minimum fraction values were detected during warm periods, due to higher volumes of airborne biogenic PM coarse, mainly at stations with important natural sources of particles in their vicinity. Hybrid single-particle Lagrangian integrated trajectory model was used, in order to extract 4-day backward air mass trajectories that arrived in the five cities which are under study during days with recorded PM₁₀ exceedances. At all five cities, a significantly large fraction of those trajectories were classified in short- and medium-range clusters, thus transportation of particulates along with slow moving air masses was identified. A finding that supports the assumption of long-range transport is that, at background stations, long-range transportation effects were stronger, in comparison to traffic stations, due to less local particle emissions. Short-range trajectories associated to PM transport in Stockholm, Copenhagen and Hamburg were mainly of a continental origin. All three cities were approached by slow moving air masses originated from Poland and the Czech Republic, whereas Copenhagen and Stockholm were also influenced by short-range trajectories from Germany and France and from Jutland Peninsula and Scandinavian Peninsula, respectively. London and Paris are located to the north-west part of Europe. Trajectories of short and medium length arrived to these two megacities mainly through France, Germany, UK and North Atlantic.     

PM2.5 co-benefits of climate change legislation part 1: California’s AB 32

The Scoping Plan for compliance with California Assembly Bill 32 (Global Warming Solutions Act of 2006; AB 32) proposes a substantial reduction in 2020 greenhouse gas (GHG) emissions from all economic sectors through energy efficiency, renewable energy, and other technological measures. Most of the AB 32 Scoping Plan measures will simultaneously reduce emissions of traditional criteria pollutants along with GHGs leading to a co-benefit of improved air quality in California. The present study quantifies the airborne particulate matter (PM_2.5) co-benefits of AB 32 by comparing future air quality under a Business as Usual (BAU) scenario (without AB 32) to AB 32 implementation by sector. AB 32 measures were divided into five levels defined by sector as follows: 1) industrial sources, 2) electric utility and natural gas sources, 3) agricultural sources, 4) on-road mobile sources and 5) other mobile sources. Air quality throughout California was simulated using the UCD source-oriented air quality model during 12 days of severe air pollution and over 108 days of typical meteorology representing an annual average period in the year 2030 (10 years after the AB 32 adoption deadline). The net effect of all AB 32 measures reduced statewide primary PM and NO_x emissions by ~1 % and ~15 %, respectively. Air quality simulations predict that these emissions reductions lower population-weighted PM_2.5 concentrations by ~6 % for California. The South Coast Air Basin (SoCAB) experienced the greatest reductions in PM_2.5 concentrations due to the AB 32 transportation measures while the San Joaquin Valley (SJV) experiences the smallest reductions or even slight increases in PM_2.5 concentrations due to the AB 32 measures that called for increased use of dairy biogas for electricity generation. The ~6 % reduction in PM_2.5 exposure associated with AB 32 predicted in the current study reduced air pollution mortality in California by 6.2 %, avoiding 880 (560–1100) premature deaths per year for the conditions in 2030. The monetary benefit from this avoided mortality was estimated at $5.4B/yr with a weighted average benefit per tonne of $35 k/tonne ($23 k/tonne–$45 k/tonne) of PM, NO_x, SO_x, and NH₃ emissions reduction.     

Relative influence of air pollutants and weather conditions on solar radiation – Part 1: Relationship of air pollutants with weather conditions

Summary Air pollution measurements from January 1999 to December 2003 were studied in 14 sites covering most of Egypt, with the aim of understanding the governing processes pollutants phase interaction. The nature of the contributing sources has been investigated, and some attempts have been made to indicate the role played by neighboring regions in determining the air quality at these sites. The seasonal variability of particulate matter (PM₁₀) and some gaseous pollutants (e.g., SO₂, NO₂, CO and O₃) were analyzed. Their relationships with meteorology were also examined. The results reveal that levels of major air pollutants were not significantly different at the rural and background sites during any season. On contrary the high atmospheric loading for PM₁₀, CO and SO₂ was frequently observed in winter at the urban sites. As expected, the prevailing winds were found to have an influence not only on air pollutants but also on the correlation between them.     

The fine and coarse particulate matter at four major Mediterranean cities: local and regional sources

Particulate air pollution is associated with adverse health effects to the population exposed. The aim of this paper is the identification of local and regional sources, affecting PM₁₀ and PM_2.5 levels in four large cities of southern Europe, namely: Lisbon, Madrid, Marseille, and Rome. Air pollution data from seven sampling sites of the European Union network were used. These stations were selected due to their ability of monitoring PM_2.5 concentrations and providing reliable series of data. Each station’s background was also taken into account. Pearson correlation coefficients and primal component analysis components were extracted separately for cold and warm periods in order to define the relationships among particle matters (PM_s) and gaseous pollutants (CO, NO₂, SO₂, and O₃) and evaluate the contributions of local sources. Possible seasonal variations of PM_2.5/PM₁₀ ratio daily values were also used as markers of PM sources, influencing particulate size distribution. Particle emissions were primarily attributed to traffic and secondarily to natural sources. Minimum daily values of PM_2.5/PM₁₀ ratio were observed during warm periods, particularly at suburban stations with rural background, due to dust resuspension and also due to the increase of biogenic coarse PM (pollen, dust, etc.). Hybrid Single-Particle Lagrangian Integrated Trajectory Model trajectory model was used in order to compute the 4-day backward trajectories of the air masses that affected the four cities which are under study during days with recorded PM₁₀ exceedances, within a 5-year period (2003–2007), at 300, 750, and 1,500 m above ground level (AGL). The trajectories were then divided to clusters with a K-means analysis. In all four cities, the influence of slow-moving air masses was associated with a large fraction of PM₁₀ exceedances and with high average and maximum daily mean PM₁₀ concentrations, principally at the 300 m AGL analysis. As far the issue of the increased PM₁₀ concentrations, the results were weaker in Marseille and particularly in Rome, probably due to their greater distance from Northwest Africa, in comparison to Madrid and Lisbon. Dust intrusions from the Sahara desert and transportation of Mediterranean/Atlantic sea spray, were characterized as primary regional sources of exogenous PM₁₀ in all four cities. Continental trajectories from the industrialized northern Italy affected PM₁₀ levels particularly in Marseille and Rome, due to their more eastern geographical position.     

基于空气质量模拟的江苏省大气污染物排放清单比较研究

大气污染物排放清单是空气质量模拟和空气污染治理的重要依据.本研究比较分析了两套覆盖江苏省的2017年大气污染物排放清单，即分别由上海市环境科学研究院、江苏省环境科学研究院编制的"长三角清单"和"江苏省清单"，并结合区域空气质量模型CMAQ评估不同清单对长三角地区2017年1、4、7、10月的空气质量模拟的影响.清单比较结果表明，除二氧化硫（SO₂）以外，江苏省清单估算的各污染物排放量较长三角清单低.通过与观测数据比较，发现两套清单对SO₂、氮氧化物（NO_x）、臭氧（O₃）和细颗粒物（PM_2.5）的模型模拟性能均较好.江苏省清单与长三角清单两者的模拟结果空间分布接近，其中江苏省清单模拟的PM_2.5和O₃在长三角多数地区略低于长三角清单的模拟结果（1月O₃除外）.江苏省清单与长三角清单均能够用于空气质量模式模拟，可为江苏地区的细颗粒物和光化学烟雾污染的控制策略制定提供参考.     

Size-resolved characteristics of inorganic ionic species in atmospheric aerosols at a regional background site on the South African Highveld

Aerosols consist of organic and inorganic species, and the composition and concentration of these species depends on their sources, chemical transformation and sinks. In this study an assessment of major inorganic ions determined in three aerosol particle size ranges collected for 1 year at Welgegund in South Africa was conducted. SO₄^2? and ammonium (NH₄⁺) dominated the PM₁ size fraction, while SO₄^2? and nitrate (NO₃) dominated the PM_1–2.5 and PM_2.5–10 size fractions. SO₄^2? had the highest contribution in the two smaller size fractions, while NO₃^? had the highest contribution in the PM_2.5–10 size fraction. SO₄^2? and NO₃^? levels were attributed to the impacts of aged air masses passing over major anthropogenic source regions. Comparison of inorganic ion concentrations to levels thereof within a source region influencing Welgegund, indicated higher levels of most species within the source region. However, the comparative ratio of SO₄^2? was significantly lower due to SO₄^2? being formed distant from SO₂ emissions and submicron SO₄^2? having longer atmospheric residencies. The PM at Welgegund was determined to be acidic, mainly due to high concentrations of SO₄^2?. PM₁ and PM_1–2.5 fractions revealed a seasonal pattern, with higher inorganic ion concentrations measured from May to September. Higher concentrations were attributed to decreased wet removal, more pronounced inversion layers trapping pollutants, and increases in household combustion and wild fires during winter. Back trajectory analysis also revealed higher concentrations of inorganic ionic species corresponding to air mass movements over anthropogenic source regions.     

武汉市冬季灰霾期PM2.5中水溶性无机离子的特征

2018年1月,利用颗粒物采样器采集武汉市大气PM_2.5样品并进行水溶性无机离子（F^-、Cl^-、NO₃^-、SO₄^2-、Na⁺、NH₄⁺、K⁺、Mg²⁺、Ca²⁺）的分析.结果表明,NO₃^-、SO₄^2-、NH₄⁺是PM_2.5中最主要的3种水溶性无机离子,除Mg²⁺与Ca²⁺外,PM_2.5与WSⅡs （水溶性无机离子）之间的相关性显著,且移动源贡献占主导地位.阴阳离子平衡表明武汉市冬季灰霾期PM_2.5呈中性或弱酸性.通过混合单粒子拉格朗日综合轨迹模式模拟并采用分层聚类得出了4种主要的后向气流轨迹及相应的PM_2.5和水溶性离子浓度,结果表明区域传输对此次灰霾期影响较大.