Simulation of PM<Subscript>10</Subscript> concentration patterns for a 2010 traffic scenario in Bologna,Italy

Three state of the art traffic–emission–dispersion models dealing with particulate matter have been tested and validated over the Bologna metropolitan area with 2001 data and a future scenario has been developed in order to estimate expected PM concentrations in 2010. The modelling system is composed by a traffic model (VISUM) evaluating vehicle fluxes as a function of mobility demand and road network in the area, an emission model (Trefic) estimating pollutants emitted in atmosphere as a function of vehicle fluxes amount and composition and of environmental conditions and a dispersion model (ADMS) evaluating PM concentrations on the area, given the meteorological variables. The three models compose a cascade sequence and results of the previous one feed the next one. PM concentrations computed by the model suite for the town of Bologna, in northern Italy, for the reference period (January 2001) have been compared with air quality stations measurements suggesting the modelling system being especially suitable for evaluating traffic induced PM. Qualitative and quantitative changes in the circulating vehicle fleet have been supposed in order to obtain a realistic scenario for year 2010. Forecasted concentrations have been then compared with limits fixed by current EU legislation for particulate matter.     

Is PM10 mass measurement a reliable index for air quality assessment? An environmental study in a geographical area of north-eastern Italy

The aim of this study was to measure the concentration of some metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Ti) in PM(10) samples collected in one urban and one industrial site and to assess that PM(10) total mass measurement may be not sufficient as air quality index due to its complex composition. Metals were determined by inductively coupled plasma-atomic emission spectroscopy (ICP-AES) and differential pulsed anodic stripping voltammetry (DPASV). The measured concentrations were used to calculate the content of metals in the PM(10) total mass, and to estimate the enrichment factors and the correlations between PM(10), metal concentrations and meteorological data for the two sites. The mean PM10 concentration during the sampling period in the urban site exceeded the annual European Union (EU) standard (40 microg/m(3)) and, for some sampling days, the daily EU standard (50 microg/m(3)) was also exceeded. In opposite, both EU standards were never exceeded in the industrial site. The overall metal content was nearly double in the industrial site compared to the urban one, and the mean Ni concentration exceeded the EU annual limit value (10 ng/m(3)). The metals with the highest enrichment factor were Cd, Cu, Ni and Pb for both sites, suggesting a dominant anthropogenic source for these metals. Metal concentrations were very low and typical of rural background during Christmas holidays, when factories were closed. PM(10) total mass measurement is not a sufficient air quality index since the metal content of PM(10) is not related to its total mass, especially in sites with industrial activities. This measurement should be associated with the analysis of toxic metals.     

三维变分在PM2.5重污染数值模拟中的应用研究

为了探讨三维变分法(3DVAR)对成渝城市群冬季PM2.5重污染模拟的改善效果,采用3DVAR对成渝城市群2017年12月至2018年1月的空气质量数值模拟结果进行资料同化,对比评估嵌套网格空气质量预报模式(NAQPMS)原始数据与同化再分析数据的准确率,并分析成渝重污染特征。研究结果显示,3DVAR在PM2.5、PM10和NO2的同化实验中均取得较好的改善效果,成渝地区检验站点各污染物相关系数(r)的平均提升比例依次为44%、90%和332%,r改善的站点占检验站点总数的比例分别为98%、100%和82%;检验站点均方根误差(RMSE)的平均下降比例分别为15%、37%和31%,RMSE改善的站点占检验站点总数的比例为65%、98%和84%。与原始模拟结果相比,同化结果能够更准确地反映成渝地区冬季重污染期间的PM2.5和PM10空间分布特征。     

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。     

PM source apportionment and trace metallic aerosol affinities during atmospheric pollution episodes: a case study from Puertollano, Spain

Source apportionment study was performed, applying principal component analysis to the results of 221 chemical analyses of PM10 and PM2.5 samples collected daily from the industrial (but low traffic) Spanish town of Puertollano over a 14-month period during 2004-2005. Results reveal compositional variations attributable to different mixtures of natural and anthropogenic materials, mainly soil and rock dust (crustal), marine salt (only in PM10), petrochemical refinery emissions, and particles attributed to the combustion of local coal, which is unusually rich in Pb and Sb. During the study period there were 34 pollution episodes when PM10 exceeded 50 tg m(-3), mostly due to winter air temperature inversions, regional atmospheric stagnation, or African dust incursions (North African, NAF days: usually in summer). Whereas the crustal component during NAF episodes averaged 52% with a PM2.5/PM10 ratio of 0.54, this dropped to 29% and a PM2.5/PM10 of 0.67 during non-NAF days when anthropogenic materials predominated. Abnormally enhanced concentrations of pathfinder metallic trace elements provide additional evidence for source apportionment: thus aerosols with raised levels of Pb and Sb are associated with local coal combustion, Ni and V can be linked to petrochemical PM emissions, and Ti, Mn, Rb, and Ce are particularly characteristic of crustal dust incursions.     

Temporal variations of airborne particles concentration in the Brussels environment

We report and analyze data on the PM10 fraction of airborne particles measured at five recording stations in the Brussels region from October 2002 till September 2003. These stations are representative of the various activity sectors of the Brussels urban area. The objective was the determination of the origin of the PM10 particles (particles up to 10 μm) that are recorded in that region in order to follow the EU directives concerning tolerance level of airborne particles concentration. In order to evaluate the impacts of local and external factors that inject solid particles in the atmosphere of Brussels we compared concentration data from working and not working (holidays) periods. Moreover, we also compared concentrations from periods of agricultural activity and rest in the Brabant provinces surrounding the Brussels region for various crop types. The results lead to the conclusion that the impact or urban traffic is rather limited while that of the agricultural activities is important. Moreover, there appears a clear-cut distinction between different types of crops.     

Evaluation of the urban/rural particle-bound PAH and PCB levels in the northern Spain (Cantabria region)

The aim of the present study was to evaluate the polycyclic aromatic hydrocarbon (PAH) and polychlorinated biphenyl (PCB) levels in PM(10) and PM(2.5), at one rural and three urban sites in the Cantabria region (northern Spain). From all of these pollutants, benzo(a)pyrene is regulated by the EU air quality directives; its target value (1?ng/m(3)) was not exceeded. The concentration values of the studied organic pollutants at the studied sites are in the range of those obtained at other European sites. A comparison between the rural-urban stations was developed: (a) PAH concentration values were lower in the rural site (except for fluorene). Therefore, the contribution of local sources to the urban levels of PAHs seems relevant. Results from the coefficient of divergence show that the urban PAH levels are influenced by different local emission sources. (b) PCB rural concentration values were higher than those found at urban sites. Because no local sources of PCBs were identified in the rural site, the contribution of more distant emission sources (about 40?km) to the PCB levels is considered to be the most important; the long-range transport of PCBs does not seem to be significant. Additionally, local PAH tracers were identified by a triangular diagram: higher molecular weight PAHs in Reinosa, naphthalene in Santander and anthracene/pyrene in Castro Urdiales. A preliminary PAH source apportionment study in the urban sites was conducted by means of diagnostic ratios. The ratios are similar to those reported in areas affected by traffic emissions; they also suggest an industrial emission source at Reinosa.     

宁波和温州地区夏季大气中不同粒径颗粒物特征分析

对宁波地区北仑和奉化站、温州地区乐清站3个监测点夏季TSP、PM10、PM2.5和PM1.0进行监测,测试分析各种粒径颗粒物浓度水平和粒径分布特征,并通过化学质量平衡(CMB)受体模型对颗粒物进行源解析。监测结果显示,夏季宁波、温州地区TSP和PM10日均浓度为0.049～0.134mg/m3和0.025～0.084mg/m3,均未超过我国环境空气质量二级标准;PM2.5日均浓度为0.007～0.069mg/m3,按美国2006年EPA最新标准限值0.035mg/m3衡量,奉化、乐清、北仑站的超标天数占总监测天数的比例分别为75%、40%和37.5%。粒径分布统计结果显示,3个监测站点PM10占TSP的比例为48.78%～86.96%;PM2.5占TSP的比例为33.33%～72.46%;奉化和乐清监测点PM10中PM2.5和PM1.0的比例平均值在50%以上。源解析结果显示,夏季TSP主要来源于土壤尘,其次是建筑尘和煤烟尘,其贡献率分别为40.70%～55.49%、9.62%～13.64%和5.85%～17.28%。     

Particulate matter levels in a South American megacity: the metropolitan area of Lima-Callao,Peru

The temporal and spatial trends in the variability of PM₁₀ and PM_2.5 from 2010 to 2015 in the metropolitan area of Lima-Callao, Peru, are studied and interpreted in this work. The mean annual concentrations of PM₁₀ and PM_2.5 have ranges (averages) of 133–45 μg m^?3 (84 μg m^?3) and 35–16 μg m^?3 (26 μg m^?3) for the monitoring sites under study. In general, the highest annual concentrations are observed in the eastern part of the city, which is a result of the pattern of persistent local winds entering from the coast in a south-southwest direction. Seasonal fluctuations in the particulate matter (PM) concentrations are observed; these can be explained by subsidence thermal inversion. There is also a daytime pattern that corresponds to the peak traffic of a total of 9 million trips a day. The PM_2.5 value is approximately 40% of the PM₁₀ value. This proportion can be explained by PM₁₀ re-suspension due to weather conditions. The long-term trends based on the Theil-Sen estimator reveal decreasing PM₁₀ concentrations on the order of ?4.3 and ?5.3% year^?1 at two stations. For the other stations, no significant trend is observed. The metropolitan area of Lima-Callao is ranked 12th and 16th in terms of PM₁₀ and PM_2.5, respectively, out of 39 megacities. The annual World Health Organization thresholds and national air quality standards are exceeded. A large fraction of the Lima population is exposed to PM concentrations that exceed protection thresholds. Hence, the development of pollution control and reduction measures is paramount.     

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%。     

Differences between weekend and weekday ozone levels over rural and urban sites in Southern Italy

Air quality data from a network of 11 monitoring stations in the Apulia region of southern Italy during the summer of 2005 reveal a high frequency of ozone law limit violations. Since ozone is a secondary pollutant, air quality control strategies aimed at reducing ozone concentration are not immediate. Herein, we analyse weekly changes in concentration levels of ozone (O(3)), nitrogen oxides (NO(x)), carbon monoxide (CO), and volatile organic compounds (VOCs), and evaluate how the differences in primary emissions cause changes in the production of ozone. The comparison between weekend and weekday levels of O(3) and its precursors are direct evidence for the existence of the "ozone weekend effect." This effect was observed at all stations with a considerable variation in the overall ozone magnitude, including both traffic stations and non-traffic stations. Data from VOC measurements at traffic stations primarily indicated elevated levels of benzene, toluene, and xylenes (BTX); all of these substances showed an overall decrease over the weekend. A single station indicated levels of non-methane hydrocarbon (NMHC) and PM10, both of which did not demonstrate any weekly cycle. Analysis of weekly and diurnal cycles of O(3), NO(x), CO, NMHC, and PM10 indicates that higher weekend ozone levels result from a reduction in the emission of nitrogen oxides on weekends in VOC-sensitive regimes. This indicates that a reduction in VOC and NO(x) levels would be more effective than NO(x) reduction alone. Our results underscore the need for improved and more efficient VOC measurements.     

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。     

Relationship between different size classes of particulate matter and meteorology in three European cities

Evidence on the correlation between particle mass and (ultrafine) particle number concentrations is limited. Winter- and spring-time measurements of urban background air pollution were performed in Amsterdam (The Netherlands), Erfurt (Germany) and Helsinki (Finland), within the framework of the EU funded ULTRA study. Daily average concentrations of ambient particulate matter with a 50% cut off of 2.5 microm (PM2.5), total particle number concentrations and particle number concentrations in different size classes were collected at fixed monitoring sites. The aim of this paper is to assess differences in particle concentrations in several size classes across cities, the correlation between different particle fractions and to assess the differential impact of meteorological factors on their concentrations. The medians of ultrafine particle number concentrations were similar across the three cities (range 15.1 x 10(3)-18.3 x 10(3) counts cm(-3)). Within the ultrafine particle fraction, the sub fraction (10-30 nm) made a higher contribution to particle number concentrations in Erfurt than in Helsinki and Amsterdam. Larger differences across the cities were found for PM2.5(range 11-17 microg m(-3)). PM2.5 and ultrafine particle concentrations were weakly (Amsterdam, Helsinki) to moderately (Erfurt) correlated. The inconsistent correlation for PM2.5 and ultrafine particle concentrations between the three cities was partly explained by the larger impact of more local sources from the city on ultrafine particle concentrations than on PM2.5, suggesting that the upwind or downwind location of the measuring site in regard to potential particle sources has to be considered. Also, relationship with wind direction and meteorological data differed, suggesting that particle number and particle mass are two separate indicators of airborne particulate matter. Both decreased with increasing wind speed, but ultrafine particle number counts consistently decreased with increasing relative humidity, whereas PM2.5 increased with increasing barometric pressure. Within the ultrafine particle mode, nucleation mode (10-30 nm) and Aitken mode (30-100 nm) had distinctly different relationships with accumulation mode particles and weather conditions. Since the composition of these particle fractions also differs, it is of interest to test in future epidemiological studies whether they have different health effects.     

乌鲁木齐市冬季大气颗粒物PM_(10) 和PM_(2.5)污染水平及相关性研究

为研究乌鲁木齐市冬季采暖期间大气颗粒物污染特征,通过采样和在线监测二种手段分析了2015年1~2月大气颗粒物样品,采用重量法分析颗粒物质量浓度,并对其相关性进行分析。结果表明:依据《环境空气质量标准》(GB 3095-2012),采样期间乌鲁木齐市大气PM_(10) 和PM_(2.5)的日均质量浓度均超过了国家二级标准,颗粒物污染严重;PM_(10) 和PM_(2.5)存在显著相关性,PM_(2.5)和PM_(10) 浓度的比值均大于0.5,采暖期PM2.5对乌鲁木齐市大气颗粒物贡献显著。     

Source apportionment of PM10 and PM(2.5) at Tocopilla, Chile (22 degrees 05' S, 70 degrees 12' W)

Tocopilla is located on the coast of Northern Chile, within an arid region that extends from 30 degrees S to the border with Perú. The major industrial activities are related to the copper mining industry. A measurement campaign was conducted during March and April 2006 to determine ambient PM10 and PM(2.5) concentrations in the city. The results showed significantly higher PM10 concentrations in the southern part of the city (117 microg/m3) compared with 79 and 80 (microg/m3) in the central and northern sites. By contrast, ambient PM2.5 concentrations had a more uniform spatial distribution across the city, around 20 (microg/m3). In order to conduct a source apportionment, daily PM10 and PM(2.5) samples were analyzed for elements by XRF. EPA's Positive Matrix Factorization software was used to interpret the results of the chemical compositions. The major source contributing to PM(2.5) at sites 1, 2 and 3, respectively are: (a) sulfates, with approximately 50% of PM2.5 concentrations at the three sites; (b) fugitive emissions from fertilizer storage and handling, with 16%, 21% and 10%; (c) Coal and residual oil combustion, with 15%, 15% and 4%; (d) Sea salt, 5%, 6% and 16%; (e) Copper ore processing, 4%, 5% and 15%; and (f) a mixed dust source with 11%, 7% and 4%. Results for PM10--at sites 1, 2 and 3, respectively--show that the major contributors are: (a) sea salt source with 36%, 32% and 36% of the PM10 concentration; (b) copper processing emissions mixed with airborne soil dust with 6.6%, 11.5% and 41%; (c) sulfates with 31%, 31% and 12%; (d) a mixed dust source with 16%, 12% and 10%, and (e) the fertilizer stockpile emissions, with 11%, 14% and 2% of the PM10 concentration. The high natural background of PM10 implies that major reductions in anthropogenic emissions of PM10 and SO2 would be required to attain ambient air quality standards for PM10; those reductions would curb down ambient PM(2.5) concentrations as well.     

Characterization of PM10 and PM2.5 and associated heavy metals at the crossroads and urban background site in Zabrze, Upper Silesia, Poland, during the smog episodes

The concentrations of seven heavy metals (Cd, Cr, Cu, Fe, Mn, Ni, and Pb) associated with PM10 and PM2.5 at the crossroads and the background sites have been studied in Zabrze, Poland, during smog episodes. Although the background level was unusually elevated due to both high particulate emission from the industrial and municipal sources and smog favorable meteorological conditions, significant increase of the concentration of PM2.5 and PM10 as well as associated heavy metals in the roadside air compared to the urban background has been documented. The average daily difference between the roadside and corresponding urban background aerosol concentration was equal to 39.5 μg m^???3 for PM10 and 41.2 μg m^???3 for PM2.5. The highest levels of the studied metals in Zabrze appeared for iron carried by PM10 particles: 1,706 (background) and 28,557 ng m^???3 (crossroads). The lowest concentration level (in PM10) has been found for cadmium: 7 and 77 ng m^???3 in the background and crossroads site, respectively. Also the concentrations of heavy metals carried by the fine particles (PM2.5) were very high in Zabrze during the smog episodes. Concentrations of all studied metals associated with PM10 increased at the roadside compared to the background about ten times (one order) while metals contained in PM2.5 showed two to three times elevated concentrations (except Fe—five times and Cr—no increase).     

Investigation of indoor environmental quality in Shanghai metro stations, China

A field study was carried out in Shanghai metro stations to gather and evaluate information about the real environment. The thermal environment and particulate matter levels were monitored in this study. The mean thermal sensation vote in metro stations was 0.91, and the mean thermal neutral temperature was 20.6°C. Although 92.1% of subjects voted that the thermal environment was acceptable, the condition of air quality in Shanghai metro stations was not good. The mean levels of PM1.0, PM2.5, and PM10 were 0.231 ± 0.152, 0.287 ± 0.177, and 0.366 ± 0.193 mg/m³, respectively. The contribution of PM1.0 to PM2.5 and PM2.5 to PM10 was up to 79% and 76%, respectively. This means that fine particles or ultrafine particles constituted the preponderant part of metro station particulate matter.     

库尔勒市大气颗粒物污染特征与影响因素分析

针对库尔勒市PM 10、PM 2.5年均浓度超标现象,基于市区3个环境监测站2013—2017年的逐时观测数据,分析PM 10、PM 2.5污染特征、成因及其主要影响因素。结果表明:①2013—2017年库尔勒市PM 10年均浓度变化较大且无明显趋势,PM 2.5年均浓度整体呈下降趋势;②季节尺度上,库尔勒市PM 10在每年2—5月呈现高浓度,PM 2.5高浓度期则为10月至翌年5月;③城郊的开发区站PM 10浓度最高,老城区的州政府站PM 2.5浓度最高,在PM 10和PM 2.5的高浓度期空间差异尤其显著;④PM 10与风速显著正相关,来自塔克拉玛干沙漠的风蚀沙尘颗粒物是库尔勒地区颗粒污染物的主要来源;⑤库尔勒市PM 10主要为外源输入,PM 2.5则以城市内源为主,相对湿度、风速、风向、温度等气象条件是影响大气颗粒物浓度及分布的重要因素。     

Air quality of Prague: traffic as a main pollution source

Political and economical transition in the Central and Eastern Europe at the end of eighties significantly influenced all aspects of life as well as technological infrastructure. Collapse of outdated energy demanding industry and adoption of environmental legislation resulted in seeming improvements of urban environmental quality. Hand in hand with modernization the newly adopted regulations also helped to phase out low quality coal frequently used for domestic heating. However, at the same time, the number of vehicles registered in the city increased. The two processes interestingly acted as parallel but antagonistic forces. To interpret the trends in urban air quality of Prague, Czech capital, monthly averages of PM(10), SO(2), NO(2), NO, O(3) and CO concentrations from the national network of automated monitoring stations were analyzed together with long term trends in fuel consumption and number of vehicles registered in Prague within a period of 1992-2005. The results showed that concentrations of SO(2) (a pollutant strongly related to fossil fuel burning) dropped significantly during the period of concern. Similarly NO(X) and PM(10) concentrations decreased significantly in the first half of the nineties (as a result of solid fuel use drop), but remained rather stable or increased after 2000, presumably reflecting rapid increase of traffic density. In conclusion, infrastructural changes in early nineties had a strong positive effect on Prague air quality namely in the first half of the period studied, nevertheless, the current trend in concentrations of automotive exhaust related pollutants (such as PM(10), NO(X)) needs adoption of stricter measures.     

Seasonal variation, risk assessment and source estimation of PM 10 and PM10-bound PAHs in the ambient air of Chiang Mai and Lamphun, Thailand

Daily PM10 concentrations were measured at four sampling stations located in Chiang Mai and Lamphun provinces, Thailand. The sampling scheme was conducted during June 2005 to June 2006; every 3 days for 24 h in each sampling period. The result revealed that all stations shared the same pattern, in which the PM10 (particulate matters with diameter of less than 10 microm) concentration increased at the beginning of dry season (December) and reached its peak in March before decreasing by the end of April. The maximum PM10 concentration for each sampling station was in the range of 140-182 microg/m(3) which was 1.1-1.5 times higher than the Thai ambient air quality standard of 120 microg/m(3). This distinctly high concentration of PM10 in the dry season (Dec. 05-Mar. 06) was recognized as a unique seasonal pattern for the northern part of Thailand. PM10 concentration had a medium level of negative correlation (r = -0.696 to -0.635) with the visibility data. Comparing the maximum PM10 concentration detected at each sampling station to the permitted PM10 level of the national air quality standard, the warning visibility values for the PM10 pollution-watch system were determined as 10 km for Chiang Mai Province and 5 km for Lamphun Province. From the analysis of PM10 constituents, no component exceeded the national air quality standard. The total concentrations of PM10-bond polycyclic aromatic hydrocarbons (PAHs) are calculated in terms of total toxicity equivalent concentrations (TTECs) using the toxicity equivalent factors (TEFs) method. TTECs in Chiang Mai and Lamphun ambient air was found at a level comparable to those observed in Nagasaki, Bangkok and Rome and at a lower level than those reported at Copenhagen. The annual number of lung cancer cases for Chiang Mai and Lamphun Provinces was estimated at two cases/year which was lower than the number of cases in Bangkok (27 cases/year). The principal component analysis/absolute principal component scores (PCA/APCS) model and multiple regression analysis were applied to the PM10 and its constituents data. The results pointed to the vegetative burning as the largest PM10 contributor in Chiang Mai and Lamphun ambient air. Vegetative burning, natural gas burning & coke ovens, and secondary particle accounted for 46-82%, 12-49%, and 3-19% of the PM10 concentrations, respectively. However, natural gas burning & coke ovens as well as vehicle exhaust also deserved careful attention due to their large contributions to PAHs concentration. In the wet season and transition periods, 42-60% of the total PAHs concentrations originated from vehicle exhaust while 16-37% and 14-38% of them were apportioned to natural gas burning & coke ovens and vegetative burning, respectively. In the dry period, natural gas burning & coke ovens, vehicle exhaust, and vegetative burning accounted for 47-59%, 20-25%, and 19-28% of total PAHs concentrations. The close agreement between the measured and predicted concentrations data (R(2) > 0.8) assured enough capability of PCA/APCS receptor model to be used for the PM10 and PAHs source apportionment.