Evaluation and optimization of an urban PM2.5 monitoring network

The objective of this study was to evaluate the PM(2.5) monitoring network established in the Greater Cincinnati and Northern Kentucky metropolitan area for measuring the 24 h integrated PM(2.5) concentration, as well as-at selected sites-hourly PM(2.5) concentration and 24 h integrated PM(2.5) speciation. The data collected during three years at 13 measurement sites were analyzed for spatial and temporal variations. It was found that both daily and hourly concentrations of PM(2.5) have low spatial variation due to a regional influence of secondary ammonium sulfate. In contrast, the trace element concentrations had high spatial variation. Seasonal variation accounted for most of the total temporal variation (60%), while yearly, monthly, weekly and daily variations were lower. The variance components and cluster analyses were applied to optimize the number of sites for measuring the 24 h PM(2.5) concentration. It was found that the 13-site network may be optimized by reducing the number of sites to 8, which would result in a relative precision reduction of 9% and a relative cost reduction of 36%. At the same time, the data suggest that the spatial resolution of speciation monitors and real-time PM(2.5) mass monitors should be increased to better represent spatial and temporal variations of the markers of local air pollution sources.     

Evaluation of the Impact of Long-range Transport and Aerosol Concentration Temporal Variations at the Eastern Coast of the Baltic Sea

Ambient particles vary greatly in their ability to affect visibility, climate and human health. The fine fraction of aerosol is responsible for greater and wider effects on human health; thus, investigation of this fraction is very important. Continuous measurements of PM2.5 (particulate matter below 2.5 μm in size) concentrations at the Preila monitoring station started in 2003. During a period of 2 years, the episodes of high daily and semi-hourly concentrations of PM2.5 were measured. These episodes did not depend on the season or time of day. The substantial role of long-range transport of pollutants to these increases in concentration was shown using chemical and statistical analysis. It was found that most of the severe episodes occurred when air masses came from a specific site besides it was established that air masses of different origin were characterized by different mixing layer depth. Lower mixing depth was observed in air masses characterized by higher observed concentrations at the measuring site and vice versa. PM2.5 concentrations showed diurnal and seasonal variations whose pattern reflected the regional origin of the aerosol. The regional pollution level was evaluated by the statistical analysis of PM2.5 concentrations. The background annual average of PM2.5 mass concentration for the eastern coast of the Baltic Sea was 15.1 ± 0.8 μg m⁻³.     

基于后向轨迹模式的区域大气污染及传输特征分析

选取南京市2017年PM2.5逐时观测数据,分析其颗粒物污染特征,并利用聚类分析、潜在源贡献因子法和GDAS气象数据,分析不同高度、季节下南京市主要气流输送路径及PM2.5污染的主要潜在源区。结果表明：南京市PM2.5污染冬季最严重,夏季最轻,逐时PM2.5浓度变化范围夏季小于冬季;夏季气流轨迹主要来自东南方向,秋冬春等季节以偏西和西北路径为主,且随着高度的增加,气流输送速度逐渐加快;冬季对南京市PM2.5污染的贡献最为显著,低层PM2.5污染贡献源区主要集中在近地区域,且贡献率较高,随着高度的增加,贡献源区由研究区域向四周辐散,贡献范围广,贡献率降低。     

2015—2017年江苏省秋、冬季空气质量状况

采用2015—2017年秋、冬季江苏省环境空气质量监测数据,从空气质量优良(达标)率、首要污染物、主要污染物浓度分析空气质量现状及特点。结果表明,江苏省秋、冬季空气质量优良(达标)率在60%左右,其中沿海地区空气质量达标率最高(71.1%),西北地区达标率最差(52.2%)。污染日的首要污染物主要为PM 2.5,占比高达91.5%。ρ(PM2.5)/ρ(PM 10)存在地区差异,江苏西北地区扬尘源贡献较大,江苏南部地区的二次颗粒物贡献更明显。ρ(NO2)/ρ(SO2)逐年持续升高,表明大气污染类型从燃煤性污染转变为复合型污染。     

乌鲁木齐市2011年冬季PM2.5/PM10浓度特征分析

利用乌鲁木齐市PM2.5//PM10自动监测数据,分析PM2.5与PM10的浓度分布特征和时间变化规律。结果表明,按照《环境空气质量标准》(二次征求意见稿)的标准限值,乌鲁木齐市冬季PM2.5污染重于PM10。PM2.5浓度为0.164mg/m3,超过二级年标准限值的3.7倍,超标率为73.9%。PM2.5浓度日变化曲线昼高夜低,呈单峰型,峰值出现在13:00~14:00(北京时间)。PM10中PM2.5所占比例较高,PM2.5/PM10为0.79,相关分析和检验显示PM2.5与PM10的线性相关显著,相关系数为0.92。     

成渝地区一次区域重污染过程来源解析及减排效果研究

基于嵌套网格空气质量预报模式(NAQPMS)及耦合的污染来源追踪模块模拟2017年12月16日至2018年1月3日成渝地区一次区域重污染过程,定量解析成渝地区主要城市PM2.5来源,评估过程中应急减排的成效。结果表明,天气静稳和风向辐合是造成此次重污染过程的重要因素,污染峰值阶段,成渝地区多个城市PM2.5日均质量浓度超过150μg/m3,达到重度污染级别。污染过程中,成都市PM2.5本地排放的贡献率为42%,眉山和德阳贡献率将近30%;重庆市PM2.5本地排放的贡献率为60%,外来输送以湖北、湖南和其他地区为主,贡献率为24%,成都和重庆市的工业源和交通源的贡献最大。区域联防联控应急减排对成渝各城市空气质量改善效果显著,成渝地区PM2.5浓度降低率为5%~11%,对于未实施应急预警方案的地区(如眉山市)受周边城市减排影响,浓度降低可达6%。     

Estimation of the contributions of long range transported aerosol in East Asia to carbonaceous aerosol and PM concentrations in Seoul, Korea using highly time resolved measurements: a PSCF model approach

The contributions of long range transported aerosol in East Asia to carbonaceous aerosol and particulate matter (PM) concentrations in Seoul, Korea were estimated with potential source contribution function (PSCF) calculations. Carbonaceous aerosol (organic carbon (OC) and elemental carbon (EC)), PM(2.5), and PM(10) concentrations were measured from April 2007 to March 2008 in Seoul, Korea. The PSCF and concentration weighted trajectory (CWT) receptor models were used to identify the spatial source distributions of OC, EC, PM(2.5), and coarse particles. Heavily industrialized areas in Northeast China such as Harbin and Changchun and East China including the Pearl River Delta region, the Yangtze River Delta region, and the Beijing-Tianjin region were identified as high OC, EC and PM(2.5) source areas. The conditional PSCF analysis was introduced so as to distinguish the influence of aerosol transported from heavily polluted source areas on a receptor site from that transported from relatively clean areas. The source contributions estimated using the conditional PSCF analysis account for not only the aerosol concentrations of long range transported aerosols but also the number of transport days effective on the measurement site. Based on the proposed algorithm, the condition of airmass pathways was classified into two types: one condition where airmass passed over the source region (PS) and another condition where airmass did not pass over the source region (NPS). For most of the seasons during the measurement period, 249.5-366.2% higher OC, EC, PM(2.5), and coarse particle concentrations were observed at the measurement site under PS conditions than under NPS conditions. Seasonal variations in the concentrations of OC, EC, PM(2.5), and coarse particles under PS, NPS, and background aerosol conditions were quantified. The contributions of long range transported aerosols on the OC, EC, PM(2.5), and coarse particle concentrations during several Asian dust events were also estimated. We also investigated the performance of the PSCF results obtained from combining highly time resolved measurement data and backward trajectory calculations via comparison with those from data in low resolutions. Reduced tailing effects and the larger coverage over the area of interest were observed in the PSCF results obtained from using the highly time resolved data and trajectories.     

广州市空气可吸入性颗粒物的污染水平

报告了中美合作“广州市大气污染对儿童肺功能影响研究”课题可吸入性颗粒物的两年监测结果。用安德森双道采样器、Ｔｅｆｌｏｎ膜采集细颗粒物（＜２５μｍ,ＰＭ２５）和粗颗粒物（２５≤＜１０μｍ,ＰＭ２５１０）,两者之和为ＰＭ１０,每季度采１５天,每天采一个２４小时样品。结果表明,广州市城区大气可吸入性颗粒物的污染相当严重,尤其是细颗粒物（ＰＭ２５）的污染,应引起公众和政府有关部门的重视。     

睢宁地区大气PM_(2.5)及气态污染物季节性变化特征

根据2014年全年实时在线观测数据,分析了徐州睢宁地区大气细颗粒物(PM_(2.5))和气态污染物(包括SO_2、CO、NO_x、O_3)质量浓度的季节性变化特征。结合后向轨迹模型,分析不同气团对该地区大气污染浓度的影响。PM_(2.5)与O_3值在夏季最低,呈显著相关,表明夏季PM_(2.5)主要受控于本地大气光化学活性。在冬季,除O_3外,PM_(2.5)、SO_2、CO、NO_x值最高,且大气颗粒物主要以细粒子为主。O_3在春季最高,并与远程传输的气团且经过我国东部污染源密集地区相对应。高浓度的PM_(2.5)主要与冬季缓慢移动的气团相对应,这可能将PM_(2.5)及其气态前体物传输至该地区进而加重大气污染程度。     

Overview of particulate exposures in the US trucking industry

As part of a large epidemiologic study of lung cancer, 55,000 subjects, we have conducted a nation-wide survey of particulate exposures in the US trucking industry. The goal is to differentiate the risks from various types of particulate exposures, such as traffic emissions and general air pollution. We hypothesize that exposures defined by job and work site characteristics can be linked with subjects using their personal job histories. This report covers exposures at 36 randomly chosen large truck freight terminals in the US. Measurements were made of PM2.5, elemental carbon (EC), and organic carbon (OC) upwind of the terminal (background) and in work areas, and by personal samples. Significant differences in exposure intensity, microg m(-3), were found for work locations and jobs relative to background levels (GM[GSD]) at terminal sites: PM2.5 9.8[2.34], EC 0.5[3.24], and OC 5.0[1.76]. Using EC as a marker for diesel particles, work locations varied significantly: office 0.3[3.7], dock area 0.7[2.89] and shop area 1.5[3.52]), as did job titles (non-smokers): clerk 0.1[9.98], dock worker 0.8[2.13], and mechanic 2.0[3.82]. Cigarette smoking contributed substantially to personal exposures, approximately doubling PM2.5 and OC, but having less of an effect on EC. Large differences were seen across the terminal sites due to differences in local regional air pollution levels from traffic and other sources. We conclude that it will be possible to estimate current exposures of the cohort using an exposure assignment matrix based on job title, work location, and terminal site. This distribution overlaps substantially with the general public's exposure to these sources.     

基于遥感数据的京津冀地区PM2.5时空分布特征

基于MODIS AOD遥感数据,采用多元线性回归模型对PM2.5地面监测数据进行模拟估算,同时加入降水量、相对湿度等气象因子以提高模型精度,结合GIS空间分析技术,得到2015—2016年京津冀地区空间连续的PM2.5浓度分布。结果表明:利用多元线性回归模型反演PM2.5浓度效果较好,R 2均在0.59~0.84之间。在时间上,京津冀地区PM2.5浓度呈现出夏季最低、秋季稍高、冬春两季最高的变化趋势;在空间上,2015年和2016年京津冀地区PM2.5浓度有明显的区域差异,均呈现出西北低、东南高的分布格局,大致与燕山山脉和太行山脉走向一致。     

宜都市PM2.5与O3季节性分布特征及潜在源区分析

为了解宜都市PM_2.5与O₃的污染特征及潜在来源,利用宜都市2020年3月至2022年2月在线监测数据及气象数据,对宜都市PM_2.5与O₃质量浓度变化特征、气象影响因素及潜在源区进行了分析,结果表明:宜都市PM_2.5质量浓度冬高夏低,日变化呈双峰特征,O₃质量浓度夏高冬低,日变化呈单峰特征。高湿、静稳的气象条件以及较强偏北风作用下的区域污染传输对PM_2.5污染有重要影响,高温以及中湿度对O₃污染过程有重要作用。春、夏、秋季偏南方向气流轨迹占主导,且携带较高的污染物浓度,冬季来自湖北东北及西南方向的气流占比较高且携带的PM_2.5浓度较高;宜都市PM_2.5、O₃的潜在源区具有季节性差异,总体来看,主要分布在河南南部、湖北东部及湖南的北部区域。     

克拉玛依市中心城区颗粒物中多环芳烃污染特征

在克拉玛依市中心城区布设4个采样点,在供暖期和非供暖期分别同步采集4个点位大气中不同粒径的颗粒物,采用HPLC进行分析并计算2个采样期内PM_(10)和PM_(2.5)中多环芳烃(PAHs)的浓度和种类。结果表明:中心城区供暖期PM_(10)中PAHs浓度为56.19 ng/m3,PM_(2.5)中PAHs浓度为48.85 ng/m3;中心城区非供暖期PM_(10)中PAHs浓度为18.86 ng/m~3,PM_(2.5)中PAHs浓度为14.53 ng/m~3。不同采样期PM_(10)和PM_(2.5)中PAHs浓度变化趋势相同,均为供暖期明显大于非供暖期。中心城区供暖期大气颗粒物吸附的PAHs以4环以下的组份为主,非供暖期则是5~6环的高环数组份偏多。分析结果表明克拉玛依市中心城区供暖期颗粒物中PAHs来源于燃煤排放叠加机动车排放,与中心城区集中供热锅炉关系密切;非供暖期则是以机动车排放污染为主。     

基于GIS的石家庄市PM10和PM2.5时空分布研究

利用2018年261个乡镇环境空气自动监测站监测数据,结合GIS空间分析技术,对石家庄市PM10和PM2.5的时空污染特征进行了研究。结果表明,石家庄地区PM10和PM2.5污染的空间分布整体表现为西北部山区好于东南部的平原地区,主城区好于周边县(市、区)的特征。采暖期PM10和PM2.5的污染程度明显重于非采暖期。PM2.5稳定性差于PM10,PM10和PM2.5的稳定性与污染程度具有一定的负相关性,表现出污染越轻的区域稳定性越差。两者的日均值浓度变化在时间序列上呈极强正相关,且污染越重的区域时间相关性越强。与日均值相关性不同,污染程度越轻的区域PM10和PM2.5年均值的线性相关性越强。     

Seasonal variability of endotoxin in ambient fine particulate matter

Endotoxin is a toxic, pro-inflammatory compound that has been detected in indoor air and dust in homes and occupational settings, and also in outdoor air. Data on the outdoor sampling of endotoxin are limited. Currently, little is known about the seasonal variation and influence of temperature on outdoor endotoxin levels. In the present study, we report endotoxin levels in fine fraction particulate matter with a 50% aerodynamic cutoff diameter of 2.5 microm (PM2.5) and describe the seasonal variation of endotoxin in Munich, Germany. In 1999-2000, PM2.5 was collected at forty outdoor monitoring sites across Munich. Approximately four samples were collected at each site for a total of 158 samples. Endotoxin concentrations in the PM2.5 samples were determined using the kinetic chromogenic Limulus Amebocyte Lysate (LAL) assay. The geometric mean endotoxin concentration was 1.07 EU mg PM2.5(-1) (95% C.I.: 0.915-1.251) or 0.015 EU m(-3) of sampled air (95% C.I.: 0.013-0.018). Munich endotoxin levels were significantly related to ambient temperature (p < 0.0001) and percent relative humidity (p < 0.0001). Sampling periods with higher average temperatures yielded higher levels of endotoxin in PM2.5 (r = 0.641), whereas decreases in percent relative humidity were associated with increased endotoxin levels in PM2.5 (r = -0.388). Endotoxin levels were significantly higher during the warmer seasons of spring [means ratio (MR): 2.5-2.7] and summer (MR: 2.1-3.0) than during winter. Although temperature and relative humidity do not explain all of the variability in endotoxin levels, their effects were significant in our data set. Temperature effects and seasonal variation of endotoxin should be considered in future studies of outdoor endotoxin.     

A land use regression model for predicting ambient fine particulate matter across Los Angeles, CA

Land use regression (LUR) models have been used successfully for predicting local variation in traffic pollution, but few studies have explored this method for deriving fine particle exposure surfaces. The primary purpose of this method is to develop a LUR model for predicting fine particle or PM(2.5) mass over the five county metropolitan statistical area (MSA) of Los Angeles. PM(2.5) includes all particles with diameter less than or equal to 2.5 microns. In the Los Angeles MSA, 23 monitors of PM(2.5) were available in the year 2000. This study uses GIS to integrate data regarding land use, transportation and physical geography to derive a PM(2.5) dataset covering Los Angeles. Multiple linear regression was used to create the model for predicting the PM(2.5) surface. Our parsimonious model explained 69% of the variance in PM(2.5) with three predictors: (1) traffic density within 300 m, (2) industrial land area within 5000 m, and (3) government land area within 5000 m of the monitoring site. These results suggest the LUR method can refine exposure models for epidemiologic studies in a North American context.     

污染源减排对长三角区域冬季细颗粒物污染的敏感性研究

为了进一步精准有效地降低细颗粒物浓度,针对长三角区域细颗粒物PM2.5浓度,选取8个省级区域的5种污染物为减排目标,设定5个基准排放情景,采用CMAQ-DDM敏感性技术分别进行敏感性分析。结果表明,冬季长三角区域PM2.5污染受区域内的4个省级区域一次PM2.5排放影响最大,区域外的排放影响主要来自河南省和山东省的氨气和一次PM2.5。分别削减本地60%一次PM2.5的排放,安徽省PM2.5平均质量浓度下降了23. 24μg/m^3,江苏省下降了18. 32μg/m^3,上海市下降了15. 17μg/m^3,浙江省下降了9. 07μg/m3。综合各省(市)浓度响应曲线,最大排放因子均为本地一次PM2.5,削减20%左右存在敏感性最大值,削减60%之后浓度曲线趋于平缓,其他因子削减40%以后PM2.5浓度下降逐渐明显,对最后一位排放因子的响应则比较平缓。     

克拉玛依市大气PM2.5、PM10污染水平浅析

根据从2012年1月1日至2012年3月30日在同一个监测点取得的PM2.5和PM10监测数据,分析采暖期颗粒物污染水平特征。结果表明,PM2.5浓度和PM10浓度之间高度线性相关;克拉玛依市冬季空气环境中PM2.5是PM10中的主要组成成分;PM2.5浓度在一天内基本保持稳定,而PM10浓度在一天之中的变化幅度较大,峰值出现在中午上下班高峰期。     

秸秆焚烧对空气质量影响特征及判别方法的研究

利用南京空气自动监测数据及PM_(2.5)组分监测结果,分析了2011年夏收秸秆焚烧期间大气污染特征,并探寻快速判别秸秆焚烧影响的指标及方法。结果表明:秸秆焚烧期间PM_(2.5)污染特征显著,其组分中K~+、EC、OC等浓度相对偏高。基于离子组分及碳元素在线监测数据,可选取K~+作为快速判别指标,并根据K~+与PM_(2.5)的相关性,计算秸秆焚烧对PM_(2.5)的贡献。同时结合OC、EC浓度变化,综合判别秸秆焚烧对空气质量的影响程度。     

降雨对长三角区域PM2.5浓度的影响

利用WRF-CAMx模式分析首届中国国际进口博览会(简称进博会)期间一次降雨过程对长三角地区PM2.5浓度影响,结果表明,降雨量分布区域与因降雨造成的PM2.5浓度减少量分布区域并不完全一致,湿沉降量受降雨量、PM2.5浓度和风速等多个因素共同影响。数值模拟结果表明,降雨导致浓度下降幅度排前5位的组分分别是有机气溶胶、硫酸盐、硝酸盐、铵盐和细颗粒原生气溶胶,下降幅度分别为44. 28%、16. 55%、11. 55%、9. 53%和5. 23%。结合观测资料和数值模式模拟结果可知,首届进博会期间上海本地减排和周边区域协同控制作用使PM2.5日均质量浓度降低33. 23μg/m3,因降雨引起的湿沉降作用使上海市PM2.5质量浓度降低15. 88μg/m^3。