Emissions of gaseous and particulate pollutants in a port and harbour region in India

Ports can generate large quantity of pollutants in the atmosphere due to various activities like loading and unloading,transportation, and construction operations. Determination of the character and quantity of emissions from individual sources is an essential step in any project to control and minimize the emissions.In this study a detailed emission inventory of total suspendedparticulate matter (TSP), particulate matter less than 10 m(PM₁₀), sulfur dioxide (SO₂) and nitrogen oxides (NO_x) for a port and harbour project near Mumbai is compiled. Results show that the total annual average contributions of TSP and PM₁₀ from all the port activitieswere 872 and 221 t yr^-1, respectively. Annual average emissions of gaseous pollutants SO₂ and NO_xwere 56 and 397 t yr^-1, respectively, calculatedby using emission factors for different port activities. The maximum TSP emission (419 t yr ^-1) was from paved roads, while the least (0.4 t yr^-1) was from bulk handling activity. The maximum PM₁₀ emission (123 t yr^-1) was from unpaved roads and minimum (0.2 t yr^-1) from bulk handling operations. Similarly the ratio of TSP and PM₁₀ emission was highest (5.18) from paved roads and least (2.17) from bulk handling operations. Regression relation was derivedfrom existing emission data of TSP and PM₁₀ from variousport activities. Good correlation was observed between TSP andPM₁₀ having regression coefficient >0.8.     

Suspended Particulate Matter Distribution in Rural-Industrial Satna and in Urban-Industrial South Delhi

An air quality sampling program was designed and implemented to collect the baseline concentrations of respirable suspended particulates (RSP = PM₁₀), non-respirable suspended particulates (NRSP) and fine suspended particulates (FSP = PM_2.5). Over a three-week period, a 24-h average concentrations were calculated from the samples collected at an industrial site in Southern Delhi and compared to datasets collected in Satna by Envirotech Limited, Okhla, Delhi in order to establish the characteristic difference in emission patterns. PM_2.5, PM₁₀, and total suspended particulates (TSP) concentrations at Satna were 20.5 ± 6.0, 102.1 ± 41.1, and 387.6 ± 222.4 μg m⁻³ and at Delhi were 126.7 ± 28.6, 268.6 ± 39.1, and 687.7 ± 117.4 μg m⁻³. Values at Delhi were well above the standard limit for 24-h PM_2.5 United States National Ambient Air Quality Standards (USNAAQS; 65 μg m⁻³), while values at Satna were under the standard limit. Results were compared with various worldwide studies. These comparisons suggest an immediate need for the promulgation of new PM_2.5 standards. The position of PM₁₀ in Delhi is drastic and needs an immediate attention. PM₁₀ levels at Delhi were also well above the standard limit for 24-h PM₁₀ National Ambient Air Quality Standards (NAAQS; 150 μg m⁻³), while levels at Satna remained under the standard limit. PM_2.5/PM₁₀ values were also calculated to determine PM_2.5 contribution. At Satna, PM_2.5 contribution to PM₁₀ was only 20% compared to 47% in Delhi. TSP values at Delhi were well above, while TSP values at Satna were under, the standard limit for 24-h TSP NAAQS (500 μg m⁻³). At Satna, the PM₁₀ contribution to TSP was only 26% compared to 39% in Delhi. The correlation between PM₁₀, PM_2.5, and TSP were also calculated in order to gain an insight to their sources. Both in Satna and in Delhi, none of the sources was dominant a varied pattern of emissions was obtained, showing the presence of heterogeneous emission density and that nonrespirable suspended particulate (NRSP) formed the greatest part of the particulate load.     

Study of temporal variation in ambient air quality during Diwali festival in India

The variation in air quality was assessed from the ambient concentrations of various air pollutants [total suspended particle (TSP), particulate matter ≤10 μm (PM₁₀), SO₂, and NO₂] for pre-Diwali, Diwali festival, post-Diwali, and foggy day (October, November, and December), Delhi (India), from 2002 to 2007. The extensive use of fireworks was found to be related to short-term variation in air quality. During the festival, TSP is almost of the same order as compared to the concentration at an industrial site in Delhi in all the years. However, the concentrations of PM₁₀, SO₂, and NO₂ increased two to six times during the Diwali period when compared to the data reported for an industrial site. Similar trend was observed when the concentrations of pollutants were compared with values obtained for a typical foggy day each year in December. The levels of these pollutants observed during Diwali were found to be higher due to adverse meteorological conditions, i.e., decrease in 24 h average mixing height, temperature, and wind speed. The trend analysis shows that TSP, PM₁₀, NO₂, and SO₂ concentration increased just before Diwali and reached to a maximum concentration on the day of the festival. The values gradually decreased after the festival. On Diwali day, 24-h values for TSP and PM₁₀ in all the years from 2002 to 2007 and for NO₂ in 2004 and 2007 were found to be higher than prescribed limits of National Ambient Air Quality Standards and exceptionally high (3.6 times) for PM₁₀ in 2007. These results indicate that fireworks during the Diwali festival affected the ambient air quality adversely due to emission and accumulation of TSP, PM₁₀, SO₂, and NO_2.     

Seasonal Variations of PM10 and TSP in Residential and Industrial Sites in an Urban Area of Kolkata, India

The objective of the study is to investigate seasonal and spatial variations of PM₁₀ (particulate matter with aerodynamic diameter less than or equal to 10 μm) and TSP (total suspended particulate matter) of an Indian Metropolis with high pollution and population density from November 2003 to November 2004. Ambient concentration measurements of PM₁₀ and TSP were carried out at two monitoring sites of an urban region of Kolkata. Monitoring sites have been selected based on the dominant activities of the area. Meteorological parameters such as wind speed, wind direction, rainfall, temperature and relative humidity were also collected simultaneously during the sampling period from Indian Meteorological Department, Kolkata. The 24 h average concentrations of PM₁₀ and TSP were found in the range 68.2–280.6 μg/m³ and 139.3–580.3 μg/m³ for residential (Kasba) area, while 62.4–401.2 μg/m³ and 125.7–732.1 μg/m³ for industrial (Cossipore) area, respectively. Winter concentrations of particulate pollutants were higher than other seasons, irrespective of the monitoring sites. It indicates a longer residence time of particulates in the atmosphere during winter due to low winds and low mixing height. Spread of air pollution sources and non-uniform mixing conditions in an urban area often result in spatial variation of pollutant concentrations. The higher particulate pollution at industrial area may be attributed due to resuspension of road dust, soil dust, automobile traffic and nearby industrial emissions. Particle size analysis result shows that PM₁₀ is about 52% of TSP at residential area and 54% at industrial area.     

Influence of Meteorological Parameters on Particulates and Atmospheric Pollutants at Taichung Harbor Sampling Site

Atmospheric aerosol particles and metallic concentrations, ionic species were monitored at the Experimental harbor of Taichung sampling site in this study. This work attempted to characterize metallic elements and ionic species associated with meteorological conditions variation on atmospheric particulate matter in TSP, PM_2.5, PM_2.5–10. The concentration distribution trend between TSP, PM_2.5, PM_2.5–10 particle concentration at the TH (Taichung harbor) sampling site were also displayed in this study. Besides, the meteorological conditions variation of metallic elements (Fe, Mg, Cr, Cu, Zn, Mn and Pb) and ions species (Cl⁻, NO₃ ⁻, SO₄ ²⁻, NH₄ ⁺, Mg²⁺, Ca²⁺ and Na⁺) concentrations attached with those particulate were also analyzed in this study. On non-parametric (Spearman) correlation analysis, the results indicated that the meteorological conditions have high correlation at largest particulate concentrations for TSP at TH sampling site in this study. In addition, the temperature and relative humidity of meteorological conditions that played a key role to affect particulate matter (PM) and have higher correlations then other meteorological conditions such as wind speed and atmospheric pressure. The parameter temperature and relative humidity also have high correlations with atmospheric pollutants compared with those of the other meteorological variables (wind speed, atmospheric pressure and prevalent wind direction). In addition, relative statistical equations between pollutants and meteorological variables were also characterized in this study.     

Impact of Diwali celebrations on urban air and noise quality in Delhi City,India

A study was conducted in the residential areas of Delhi, India, to assess the variation in ambient air quality and ambient noise levels during pre-Diwali month (DM), Diwali day (DD) and post-Diwali month during the period 2006 to 2008. The use of fireworks during DD showed 1.3 to 4.0 times increase in concentration of respirable particulate matter (PM₁₀) and 1.6 to 2.5 times increase in concentration of total suspended particulate matter (TSP) than the concentration during DM. There was a significant increase in sulfur dioxide (SO₂) concentration but the concentration of nitrogen dioxide (NO₂) did not show any considerable variation. Ambient noise level were 1.2 to 1.3 times higher than normal day. The study also showed a strong correlation between PM₁₀ and TSP (R ² ≥ 0.9) and SO₂ and NO₂ (R ² ≥ 0.9) on DD. The correlation between noise level and gaseous pollutant were moderate (R ² ≥ 0.5). The average concentration of the pollutants during DD was found higher in 2007 which could be due to adverse meteorological conditions. The statistical interpretation of data indicated that the celebration of Diwali festival affects the ambient air and noise quality. The study would provide public awareness about the health risks associated with the celebrations of Diwali festival so as to take proper precautions.     

江苏省工地和裸地扬尘遥感监测方法研究与结果分析

应用卫星遥感影像结合无人机现场核查数据,对2020年江苏省各设区市主城区工地和裸地2类扬尘源的时空分布变化和污染、管控情况开展了连续性监测,为生态环境监测部门业务化应用提供了思路和方法.研究结果显示,遥感解译精度优于95％,扬尘源数量、面积均呈上升趋势,至第4季度总数达1760个、总面积162.53 km2,总体管控情...     

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。     

杭州市大气污染物排放清单及特征

以杭州市区为研究区域,通过调查整合多套污染源数据库及其他统计资料,研究文献报道及模型计算的各种污染源排放因子,获得杭州市区各行业PM10、PM2.5、SO2、NOx、CO、VOCs、NH3等污染物的排放量,建立了杭州市区2010年1 km×1 km大气污染物排放清单。结果表明,2010年杭州市区PM10、PM2.5、SO2、NOx、CO、VOCs和NH3的排放总量分别为7.96×104、4.02×104、7.23×104、8.98×104、73.90×104、39.56×104、3.32×104t。从排放源的行业分布来看,机动车尾气排放是杭州市区大气污染物最重要排放源之一,对PM10、PM2.5、NOx、CO和VOCs的贡献分别达到14.4%、27.1%、40.3%、21.4%、31.1%。道路扬尘、电厂锅炉、工业炉窑、植被、畜禽养殖对不同污染物分别有着重要贡献,道路扬尘对PM10和PM2.5的贡献分别为44.6%和20.0%、电厂锅炉对SO2和NOx的贡献分别为37.0%和25.7%、工业炉窑对CO的贡献为41.5%、植被排放对VOCs的贡献为27.1%、畜禽养殖对NH3的贡献为76.5%。从空间分布来看,萧山区和余杭区对SO2、NH3和植被排放BVOC的贡献要显著高于主城区;而主城区机动车对PM2.5、NOx和VOCs的贡献分别达到36.3%、56.0%和47.4%,较市区范围内显著增加,表明机动车尾气排放已成为杭州主城区大气污染最重要的来源之一。     

Particulate matter concentration levels during intense haze event in an urban environment

This study assessed concentration levels of particulate matter (PM) in the ambient environment of Ilorin metropolis, Nigeria, during haze episodes. Meteorological data (wind speed and direction, rainfall data, sunshine data, relative humidity and temperature) were obtained. Aerocet 531S particle counter (MetOne Instruments, USA) was used to measure four mass concentration ranges of PM (PM_1.0, PM_2.5, PM₁₀ and the total suspended particles (TSP)) in 10 locations taking into consideration land use patterns. Surfer® version 8 (Golden Software LLC, USA) was used to model the spatial variation of particulate matter concentration levels using kriging interpolation griding method. Human exposure assessment was done using the total respiratory deposition dose (TRDD) estimates and statutory limit breach (SLB) approaches. The appearance of dominating weak southern atmospheric wind flow was observed as wind speed ranged from 0 to 6.811 m/s while solar radiation periods ranged from 0.3 to 3.5 h/day. The relative humidity of the metropolis ranged between 28 and 57%, while daily temperature was 15 to 36 °C. Highest concentration levels of PM measured were 73.4, 562.7, 7066.3 and 9907.8 μg/m³ for PM_1.0, PM_2.5, PM₁₀ and TSP, respectively. Very strong negative correlations existed between the PM concentration levels and microclimatic parameters. Spatial variation of the concentration level as modelled using Surfer® version 8 indicated that particulate concentration level increases from south to north. Concentration levels of PM for the 24-h averaging period were generally above the 24-h threshold limit value set by the regulatory agencies for all the locations.     

北京城区降水对PM2.5和PM10清除作用分析

基于北京市PM_2.5和PM₁₀质量浓度、组分浓度以及降水数据,利用数理统计、相关性分析等方法分别从降水总量、降水时长和降水前颗粒物浓度3个角度研究降水对PM_2.5、PM₁₀的清除作用,同时以一次典型降水过程为例,具体分析降水对颗粒物的影响。结果表明：降水总量的增加有助于促进PM_2.5、PM₁₀的清除,随着降水总量增加,PM_2.5、PM₁₀的平均清除率提高,有效清除的比例增加;连续降水可增强对大气颗粒物的湿清除作用,连续降水达3d可有效降低PM_2.5、PM₁₀浓度;降水对PM_2.5、PM₁₀浓度的清除率和大气颗粒物前一日的平均浓度有较好的正相关性。降水对大气颗粒物的清除可分为清除、回升和平稳3个阶段,各个阶段大气颗粒物的变化趋势不同。降水对于大气气溶胶化学组分和酸碱性的改变具有明显作用,对于大气颗粒物各种组分的清除效果不完全相同。对于大气中OC、NO₃^-、SO₄^2-和NH₄⁺去除率较高,且这4种组分主要以颗粒态形式被冲刷进入降水中,加剧了北京市降水酸化程度。     

Using Archive Data to Investigate Trends in the Sources and Composition of Urban PM10 Particulate Matter: Application to Edinburgh (U.K.) Between 1992 and 1997

By extending the method of Stedman (1998), daily dataof atmospheric concentrations of gravimetricPM₁₀, black smoke (BS) and sulphate aerosol (SA)from national networks were analysed to determine thetrends in time of the contribution of different sources of particulate matter to total PM₁₀ measured in central Edinburgh. Since BS is an indicator of combustion-related primary sources of particulate matter, the quantity obtained by subtraction of daily BS from daily PM₁₀ is indicative of the contribution to total PM₁₀ from other primary sources and from secondary aerosol. This PM₁₀-BS statistic was regressed on SA, since SA is an indicator of variation in secondary aerosol source. For Edinburgh, SA is a considerably better indicator of PM₁₀-BS during summer than winter (reflecting the much greater photochemical generation of secondary aerosol in summer) and there is evidence that the contribution of other secondary aerosol (presumably nitrate aerosol) has increased relative to SA between 1992 and 1997. The concentration of non-combustion primary particulate material (marine aerosol, suspended dust) to PM₁₀ in Edinburgh has not changed over this period but is about twice that calculated as the U.K. national average. The increasing input to PM₁₀ from secondary aerosol sources at regional rather than urban scale has important implications for ensuring local air quality compliance. The method should have general applicability to other locations.     

Industrial hygiene and toxicity studies in unorganized bone-based industrial units

A large variety of ornamental and decorative items are manufactured from bone waste by various unorganized sectors in India. An initial survey indicated that workers were exposed at various phases of final product. The subjects (12 industrial units) were tested for total suspended particulate matter (TSPM), particulate matter <10  $\upmu $ m (PM₁₀), and particulate matter <2.5  $\upmu $ m (PM_2.5). Prevalent levels of TSPM ranged between 2.90 and 5.89 mg m^???3. Respirable fractions of occupational dust as PM₁₀ and PM_2.5 were found in the range of 0.30?C2.08 and 0.26?C0.50 mg m^???3, respectively. Cytotoxicity study was conducted using hemolysis as a sensitive marker. In an in vitro study, rat RBCs were exposed to the concentration of 25?C1,000  $\upmu $ g/ml for 15?C120 min. A considerable variation was observed in the hemolytic activity of samples collected from different areas. At 500  $\upmu $ g/ml concentration, the hemolytic activity (12 h) was found to be in the range of 18?C25%. Due to limitation in sample mass of respirable fractions, only one concentration (100  $\upmu $ g/ml/2 h) was used for comparative study on hemolysis of RBCs caused by PM₁₀ and PM_2.5. Interestingly, the hemolytic activity was more at PM_2.5 than PM₁₀ and TSPM. These results suggest that the respirable particles are capable of reaching deep into the respiratory system. The finding is significant notably when there are no standards available in occupationally exposed populations. This is the first such study. Data could be of importance to policy makers and regulators.     

Monitoring long-term variation of aerosol composition: a dual particle-size approach applied to Hong Kong

The 1990's time series in Hong Kong for various components oftotal suspended particulate matter (TSP) and PM₁₀ have beenanalyzed in order to assess two distinct types of anthropogenicinput. The first of these relates to the immense reclamation andconstruction activities for new developments and airportconstruction. The concentrations of crustal components inPM₁₀ (= TSP – PM₁₀) were found to peak at the time ofthis maximum activity. A second type of anthropogenic input,ambient lead from petrol vehicles, has decreased in Hong Kongand now represents a regional background. Ambient bromine nowarises mainly from the seasalt source.     

Differences in the Spatial Distribution and Chemical Composition of PM10 Between the UK and Poland

The Fine Resolution Atmospheric Multi-pollutant Exchange Model was used to calculate the spatial distribution and chemical composition of PM₁₀ concentrations for two geographically remote countries in Europe—the UK and Poland—for the year 2007. These countries are diverse in terms of pollutant emissions as well as climate conditions. Information on the contribution of natural and anthropogenic as well as national and imported particles in total PM₁₀ concentrations in both countries is presented. The paper shows that the modelled national annual average PM₁₀ concentrations, calculated for the entire country area, are similar for the UK and Poland and close to 12 μg m^?3. Secondary inorganic aerosols dominate the total PM₁₀ concentrations in Poland. Primary particulate matter has the greatest contribution to total PM₁₀ in the UK, with large contribution of base cations. Anthropogenic sources predominate (81 %) in total PM₁₀ concentrations in Poland, whereas natural prevail in the UK—hence, the future reduction of PM₁₀ air concentrations by emissions reduction could be more difficult in the UK than in Poland.     

北京市建筑施工裸地的空间分布及扬尘效应

北京市作为中国典型的快速城市化大城市之一,大规模的城市建设使得城市内部存在大量的建筑施工裸地,工地扬尘效应造成了严重的大气颗粒物污染。以北京市平原区为研究区,首先利用高分辨率卫星数据反演了建筑施工裸地的空间分布格局,在此基础上,结合建筑施工裸地的扬尘排放因子,在空间上定量分析建筑施工裸地的扬尘效应。结果显示,2012年全市平原区建筑施工裸地总面积为140.77 km2,主要分布在城市核心区向外拓展的城乡过渡带。建筑施工裸地的扬尘效应分析中发现北京市平原区建筑施工裸地中TSP、PM10和PM2.5的排放量分别是31.53、16.66、9.16万吨,并且这些污染物的排放量在城市发展新区与功能拓展区中较高,生态涵养发展区较小。以北京市的建筑施工裸地为例,示范了以遥感为技术手段结合污染排放因子的城市内部典型面源污染的监测和污染排放定量化,为今后面源污染的快速准确监测开辟了新的研究思路。     

Source identification and apportionment of PM2.5 and PM2.5−10 in iron and steel scrap smelting factory environment using PMF,PCFA and UNMIX receptor models

To identify the potential sources responsible for the particulate matter emission from secondary iron and steel smelting factory environment, PM_2.5 and PM_2.5?10 particles were collected using the low-volume air samplers twice a week for a year. The samples were analyzed for the elemental and black carbon content using x-ray fluorescence spectrometer and optical transmissometer, respectively. The average mass concentrations were 216.26, 151.68, and 138. 62 μg/m³ for PM_2.5 and 331.36, 190.01, and 184.60 μg/m³ for PM_2.5?10 for the production, outside M1 and outside M2 sites, respectively. The same size resolved data set were used as input for the positive matrix factorization (PMF), principal component factor analysis (PCFA), and Unmix (UNMIX) receptor modeling in order to identify the possible sources of particulate matter and their contribution. The PMF resolved four sources with their respective contributions were metal processing (33 %), e-waste (33 %), diesel emission (22 %) and soil (12 %) for PM_2.5, and coking (50 %), soil (29 %), metal processing (16 %) and diesel combustion (5 %) for PM_2.5?10. PCFA identified soil, metal processing, Pb source, and diesel combustion contributing 45, 41, 9, and 5 %, respectively to PM_2.5 while metal processing, soil, coal combustion and open burning contributed 43, 38, 12, and 7 %, respectively to the PM_2.5?10. Also, UNMIX identified metal processing, soil, and diesel emission with 43, 42 and 15 % contributions, respectively for the fine fraction, and metal processing (71 %), soil (21 %) and unidentified source (1 %) for the coarse fraction. The study concluded that metal processing and e-waste are the major sources contributing to the fine fraction while coking and soil contributed to the coarse fraction within the factory environment. The application of PMF, PCFA and UNMIX receptor models improved the source identification and apportionment of particulate matter drive in the study area.     

Seasonal air quality profile of inorganic ionic composition of PM10 near Taj Mahal in Agra, India

Atmospheric aerosols and their impacts on the environment particularly on human health is an issue of significant public and governmental concern. Though studies on air quality related to total suspended particulate matter have done by various authors in India, yet respirable suspended particulate matter (PM₁₀) is not characterized so far particularly in a historical and world heritage city like Agra. This study presents seasonal variation in mass levels of PM₁₀ and its ionic composition. PM₁₀ samples were collected in the proximity of Taj Mahal and subjected to chemical analysis using ion chromatography technique. The preliminary findings reveal that the 24-h average of PM₁₀ mass level varies from 115 to 233, 155 to 321, and 33 to 178 μg/m³, respectively, in summer, winter, and rainy seasons indicating critical pollution situation. These values are very much higher than the National Ambient Air Quality Standards of 75 μg/m³ (prescribed by Central Pollution Control Board, India) in both of summer and winter seasons whereas quite near the permissible limits in rainy season. The equivalent ratios of NH₄ ⁺ to nonsea salt SO₄ ^2? and NO₃ ^? and ∑Cations to ∑Anios were found to be greater than unity indicating high source strength of ammonia and alkaline nature of aerosols. The study suggests the need for continuous and long-term systematical sampling and detailed physiochemical analysis of PM₁₀ and also to know the characteristics of PM in background areas for better understanding of the emission sources.     

Estimation of shipping emissions in Candarli Gulf, Turkey

Ships are significant air pollution sources as their high powered main engines often use heavy fuels. The major atmospheric components emitted are nitrogen oxides, particulate matter (PM), sulfur oxide gases, carbon oxides, and toxic air pollutants. Shipping emissions cause severe impacts on health and environment. These effects of emissions are emerged especially in territorial waters, inland seas, canals, straits, bays, and port regions. Candarli Gulf is one of the major industrial regions on the Aegean side of Turkey. The marine environment of the region is affected by emissions from ships calling to ten different ports. In this study, NO _x , SO₂, CO₂, hydrocarbons (HC), and PM emissions from 7,520 ships are estimated during the year of 2007. These emissions are classified regarding operation modes and types of ships. Annual shipping emissions are estimated as 631.2 t year^???1 for NO _x , 573.6 t year^???1 for SO₂, 33,848.9 t year^???1 for CO₂, 32.3 t year^???1 for HC, and 57.4 t year^???1 for PM.     

大同市大气颗粒物浓度与水溶性离子季度分布特征

为研究大同市大气颗粒物质量浓度与水溶性离子组成特征,于2013年2、7、9、12月,分别对大同市及其对照点庞泉沟国家大气背景点进行了PM2.5及PM10的采样,通过超声萃取-IC法测定了样品中的9种水溶性离子,结果表明,大同市大气颗粒物污染1、4季度重于2、3季度,PM2.5季度均值全年均未超标,PM10仅第1季度超标1.4倍,污染状况总体良好,PM2.5与PM10相关系数R为0.75,说明大同市颗粒物污染有较为相近的来源,且不同季节均以粗颗粒物为主;大同市PM2.5中水溶性离子浓度分布为SO2-4、NO-3、NH+4Cl-、Ca2+K+、Na+F-、Mg2+,PM10中Ca2+浓度仅次于SO2-4、NO-3,控制扬尘将有效降低PM10的浓度;PM2.5及PM10中的9种水溶性离子在不同季度的浓度与颗粒物浓度分布规律类似,1、4季度较高,2、3季度较低;由阴阳离子平衡计算结果可知,相关性方程的斜率K为1.045,表明大同市大气颗粒物中阳离子相对亏损,大气细粒子组分偏酸性。NO-3与SO2-4浓度比值均小于1,大同市以硫酸型污染为主,大气中的SO2-4主要来源于人类活动排放。