东莞市一次空气污染过程成因分析

基于东莞市大气复合污染超级监测站的监测数据,选取2017年12月一次典型空气污染过程,对污染期间气象要素、大气颗粒物组分特征和污染物来源进行综合研究。结果表明,在污染期间,首要污染物为PM_2.5,日均值为86μg/m3,其主要化学组分依次是OC、NO_3^-和SO_4^2-,分别占PM_2.5的19.7%,16.1%和14.9%;在不利的气象条件下,本地污染排放和外源输入的一次污染物快速生成二次有机物、硝酸盐和硫酸盐,是造成该次空气污染的主要原因; PM_2.5污染主要来源为机动车尾气(27.7%)及二次无机源(19.0%)。     

Interpretation of roadside PM10 monitoring data from Sunderland,United Kingdom

Roadside PM₁₀ has been monitored by Partisol® at three sitesin Sunderland between August 1997 and February 1998. The sites chosen were an inner city kerbside site; a roadside site adjacentto a dual carriageway on the outskirts of Sunderland with an openaspect; and a rural site.The results indicate that there is a seasonal variation in the relationship between the sites in terms of monitored PM₁₀.In the winter there is a poor correlation between the sites whereas in the summer significant correlations are obtained. Of the sites monitored PM₁₀ is consistently highest at the inner city roadside site. During the summer, exceedances of theU.K. 50 g m^-3 standard (DETR, 2000) are associated with conditions suitable for the build-up of photochemical pollutionhowever during the winter period exceedances are recorded duringa variety of weather conditions.At the dual carriageway site PM_2.5 has also been recorded and contributions to measured PM₁₀ are 77% in summer and68% in winter. The results illustrate a number of inconsistencies between this study utilising the Partisol® andothers reporting results where PM₁₀ has been monitored by TEOM®.     

Characterisation of PM10, PM2.5 and Benzene Soluble Organic Fraction of Particulate Matter in an Urban Area of Kolkata, India

In this study, the relationship between inhalable particulate (PM₁₀), fine particulate (PM_2.5), coarse particles (PM_{2.5 – 10}) and meteorological parameters such as temperature, relative humidity, solar radiation, wind speed were statistically analyzed and modelled for urban area of Kolkata during winter months of 2003–2004. Ambient air quality was monitored with a sampling frequency of twenty-four hours at three monitoring sites located near traffic intersections and in an industrial area. The monitoring sites were located 3–5 m above ground near highly trafficked and congested areas. The 24 h average PM₁₀ and PM_2.5 samples were collected using Thermo-Andersen high volume samplers and exposed filter papers were extracted and analysed for benzene soluble organic fraction. The ratios between PM_2.5 and PM₁₀ were found to be in the range of 0.6 to 0.92 and the highest ratio was found in the most polluted urban site. Statistical analysis has shown a strong positive correlation between PM₁₀ and PM_2.5 and inverse correlation was observed between particulate matter (PM₁₀ and PM_2.5) and wind speed. Statistical analysis of air quality data shows that PM₁₀ and PM_2.5 are showing poor correlation with temperature, relative humidity and solar radiation. Regression equations for PM₁₀ and PM_2.5 and meteorological parameters were developed. The organic fraction of particulate matter soluble in benzene is an indication of poly aromatic hydrocarbon (PAH) concentration present in particulate matter. The relationship between the benzene soluble organic fraction (BSOF) of inhalable particulate (PM₁₀) and fine particulate (PM_2.5) were analysed for urban area of Kolkata. Significant positive correlation was observed between benzene soluble organic fraction of PM₁₀ (BSM10) and benzene soluble organic fraction of PM_2.5 (BSM2.5). Regression equations for BSM10 and BSM2.5 were developed.     

石家庄市大气颗粒物元素组分特征分析

为研究石家庄市大气颗粒物的污染特征及其来源,于2013年4—5月在主城6区分别采集TSP、PM10和PM2.5颗粒物样品,利用ICP-MS分析其中的22种元素浓度。结果表明,石家庄市城区Ca、Fe元素在各粒径颗粒物中含量都较高,PM2.5中的S、K含量较高,PM10和TSP中Mg、Al的浓度相对较高。颗粒物的主要来源为燃煤尘、道路尘和建筑尘,TSP、PM10和PM2.5具有较好的统计相关性和同源性。     

Distribution of PM2.5 and PM10-2.5 in PM10 Fraction in Ambient Air Due to Vehicular Pollution in Kolkata Megacity

This research paper aims at establishing baseline PM₁₀ and PM_2.5 concentration levels, which could be effectively used to develop and upgrade the standards in air pollution in developing countries. The relative contribution of fine fractions (PM_2.5) and coarser fractions (PM_10-2.5) to PM₁₀ fractions were investigates in a megacity which is overcrowded and congested due to lack of road network and deteriorated air quality because of vehicular pollution. The present study was carried out during the winter of 2002. The average 24h PM₁₀ concentration was 304 μg/m³, which is 3 times more than the Indian National Ambient Air Quality Standards (NAAQS) and higher PM₁₀ concentration was due to fine fraction (PM_2.5) released by vehicular exhaust. The 24h average PM_2.5 concentration was found 179 μg/m³, which is exceeded USEPA and EU standards of 65 and 50 μg/m³ respectively for the winter. India does not have any PM_2.5 standards. The 24 h average PM_10-2.5 concentrations were found 126 μg/m³. The PM_2.5 constituted more than 59% of PM₁₀ and whereas PM₁₀-PM_2.5 fractions constituted 41% of PM₁₀. The correlation between PM₁₀ and PM_2.5 was found higher as PM_2.5 comprised major proportion of PM₁₀ fractions contributed by vehicular emissions.     

2019—2021年徐州市大气细颗粒物化学组成特征及来源解析

徐州市地处四省交界,大气污染物来源复杂,颗粒物污染在气象条件不利时较为显著。通过地面观测数据、颗粒物组分连续观测、源解析及轨迹溯源等方法,对徐州市2019—2021年颗粒物变化特征进行了全面分析,以定量解析各类污染源的贡献,识别对颗粒物贡献显著的化学成分。结果表明：PM_2.5各组分质量占比中二次无机盐和有机碳相对较高,其中二次无机盐SNA(SO■、NO^-₃、NH⁺₄)占比达到59.1%～62.7%;水溶性离子总浓度逐年降低,但Mg²⁺和Ca²⁺浓度2021年分别同比增加2%和12.5%,说明扬尘污染存在反弹。秋冬季水溶性离子明显较高,Cl^-浓度明显高于其他季节,表明徐州市秋冬季受移动源、燃煤源和二次有机气溶胶共同影响。PM_2.5中OC与EC质量浓度比为4.88～8.40,说明徐州市颗粒物受多源影响,柴油、汽油机动车尾气排放以及燃煤排放对颗粒物贡献较大。后向轨迹分析表明,污染严重的1月污染物主...     

2021年沙尘天气影响下江苏省空气质量特征分析

对2021年影响江苏省的沙尘天气过程开展研究,分析受影响的时间、区域特征及环境空气质量特征。结果表明,影响江苏省的沙尘天气过程共计13次,全省累计受影响229 d。从时间分布看,沙尘天气过程多发生在1月、3—5月,2月、11月较少,6—10月和12月无沙尘天气过程。从区域分布看,苏北地区受沙尘天气过程影响较显著,受影响天数>20 d的城市均分布于此。受沙尘天气过程影响,且东北偏北风或东北风输送时,可吸入颗粒物(PM₁₀)和细颗粒物(PM_2.5)较易出现小时高值。沙尘过程造成PM₁₀日均质量浓度超标的天数占比为38.0%,造成PM_2.5日均质量浓度超标的天数占比仅为12.7%;扣除沙尘天气过程影响后,PM_2.5和PM₁₀年均质量浓度分别较扣除前下降1和6μg/m³,沙尘天气过程对PM₁₀质量浓度的影响大于对PM_2.5质量浓度的影响。受沙尘天气过程影响时,环境空气质量为轻度污染及以上级别占...     

Monitoring of Daily Integrated Exposure of Outdoor Workers to Respirable Particulate Matter in an Urban Region of India

It is more and more recognised that an estimation of the exposure of the population to air pollutants is more relevant than the ambient air quality, since it gives a better indication of health risk. Outdoor workers in an urban region are generally of low income status and are exposed to higher levels of both indoor and outdoor air pollution. Hence respondents from this population subgroup have been selected for this study. Outdoor workers are divided into two categories, viz. traffic constables and casual outdoor workers like watchmen, roadside shopkeepers etc. Most of the respondents are from the lower income group. Each respondent is monitored for a continuous 48-hour period. The sampling frequency is once a week.The study region is situated in the north-west part of the Greater Mumbai Municipal Corporation. It can be classified as industrial cum residential area. The daily integrated exposure of the outdoor workers consists of two major micro-environments, viz. occupational and indoor residential.A personal air sampler was used along with a cyclone to measure levels of Respirable Particulate Matter (RPM). The cyclone has a 50% removal efficiency for particle diameter of 5 m. Paired samples of PM10 (ambient) and RPM (personal) were collected to establish the correlation between them. The average 24-hour integrated exposure to RPM was 322 g/m3 and exceeded the corresponding PM10 level observed at the nearest Ambient Air Quality Monitoring Station by a factor of 2.25. The 90% confidence interval for this exposure is 283–368 g/m3. This study clearly demonstrates that the daily integrated exposure and therefore the health risk of outdoor workers in an urban area is significantly more serious than that indicated by ambient air quality data.     

Inorganic constituents of urban air pollution in the Lazio region (Central Italy)

A field study was carried out at six locations in the Lazio region (Central Italy) aimed at characterising atmospheric particulate matter (PM₁₀ and PM_2.5) from the point of view of the chemical composition and grain size distribution of the particles, the mixing properties of the atmosphere, the frequency and relevance of natural events. The combination of four different analytical techniques (ion chromatography, X-ray fluorescence and ICP for inorganic components, thermo-optical analysis for carbon compounds) yielded sound results in terms of characterisation of the air masses. During the first three months of the study (October-December 2004), many pollution events of natural (sea-salt or desert dust episodes) or anthropogenic nature were identified and characterised. More than 90% of the collected mass was identified by chemical analysis. The central role played by the mixing properties of the lower atmosphere when pollution events occurred was highlighted. The results show a major impact of primary anthropogenic pollutants on traffic stations and a homogeneous distribution of secondary pollutants over the regional area. An evaluation of the sources of PM and an identification of possible reliable tracers were obtained using a chemical fractionation procedure.     

石家庄市春节期间大气颗粒物有机碳和元素碳的变化特征

为研究石家庄市大气颗粒物的污染特征及其来源,于2013年2月6—19日春节期间在石家庄市采集大气颗粒物TSP、PM10、PM2.5样品,对其有机碳、元素碳进行分析测定。结果表明,石家庄TSP、PM10、PM2.5日平均质量浓度分别为389、330、245μg/m3,颗粒物污染严重;碳组分在颗粒物中占有较大比重,且随着粒径的减少,碳组分比重逐渐增加;存在不严重的次生有机碳污染;OC与EC的相关系数较高,说明两者有较为相似的污染源,主要为燃煤、机动车排放源。各种气象条件对PM2.5、OC、EC浓度和OC/EC的变化都有不同程度的影响。