Spatiotemporal Features of Severe Air Pollution in Northern Taiwan (8 pp)

Background, Aims and Scope This research attempted to identify the dominant factors simultaneously affecting the airborne concentrations of five air pollutants with principal component analysis and to determine the meteorologically related parameters that cause severe air-pollution events. According to the definition of subPSI and PSI values through the U.S. EPA, the historical raw data of five criteria air pollutants, SO2, CO, O3, PM10 and NO2, were calculated as daily subPSI values. In addition to the airborne concentrations, this study simultaneous collected the surface meteorological parameters of the Taipei meteorological station, established by the Central Weather Bureau. Methods Principal component analysis was conducted to screen severe air pollution scenarios for five air pollutants: SO2, CO, O3, PM10 and NO2. The concentrations of various air pollutants measured at 17 air-quality stations in northern Taiwan from 1995 to 2001 were transformed into daily subPSI values. The correlation analysis of the five air pollutants and four meteorological parameters (wind speed, temperature, mixing height and ventilation rate) were included in this research. After screening severe air pollution scenarios, this study recognized the synoptic patterns easily causing the severe air-pollution events. Results and Discussion Analytical results showed that the eigenvalues of the first two principal components for SO2, CO, O3, PM10 and NO2 were greater than 1. The first component of five air pollutants explained 64, 64, 67, 76 and 63% of subPSI variance for SO2, CO, O3, PM10 and NO2, respectively. Only the correlation coefficient of NO2 and CO had statistically significant positive values (0.82); other pollutant pairs presented medium (0.4 to 0.7) or low (0 to 0.4) positive values. The correlation coefficients for air pollutants and three meteorological parameters (wind speed, mixing height and ventilation index) were medium or low negative values. In northern Taiwan, spring was most likely induced high concentrations and the component scores of the first component for SO2, CO, PM10 and NO2; summer was the worst season that caused high O3 episodes. Consequently, the analytical results of factor loadings for the first principal component and emission inventory of various sources revealed that mobile sources were dominant factors affecting ambient air quality in northern Taiwan. Conclusion According to the results of principal component analysis for the five air pollutants, the first two of 17 components were cited as major factors and explained 71% of subPSI variance. Based on the inventory of NOx emissions and the isopleth diagram of factor loading for the first component, mobile sources in the southwest Taipei City accounted for the highest factor loading values and emission inventory values. Synoptic analysis and principal component analysis demonstrated that three types of weather patterns (high-pressure recirculation, prefrontal warm sector and the southwesterly wind system) easily caused the severe air-pollution scenarios. In summary, if severe air-pollution days occurred, the average meteorological parameters experienced adverse conditions for diffusing air pollutants; that is, the average values of wind speed, mixing height and ventilation index were lower than 2.1 ms-1, 360 m and 800 m2s-1, respectively. If one of the three synoptic patterns were to occur in combination with adverse meteorological conditions, severe air-pollution events would be developed. Recommendation and Outlook By utilizing synoptic patterns, this work found three weather systems easily caused severe air-pollution events over northern Taiwan. Analytical results showed, respectively, the wind speed and mixing height were less than 2.1 m/s and 360 m during severe air-pollution events.     

Defining the photochemical contribution to particulate matter in urban areas using time-series analysis

The objective of this project is to demonstrate how the ambient air measurement record can be used to define the relationship between O3 (as a surrogate for photochemistry) and secondary particulate matter (PM) in urban air. The approach used is to develop a time-series transfer-function model describing the daily PM10 (PM with less than 10 microm aerodynamic diameter) concentration as a function of lagged PM and current and lagged O3, NO or NO2, CO, and SO2. Approximately 3 years of daily average PM10, daily maximum 8-hr average O3 and CO, daily 24-hr average SO2 and NO2, and daily 6:00 a.m.-9:00 a.m. average NO from the Aerometric Information Retrieval System (AIRS) air quality subsystem are used for this analysis. Urban areas modeled are Chicago, IL; Los Angeles, CA; Phoenix, AZ; Philadelphia, PA; Sacramento, CA; and Detroit, MI. Time-series analysis identified significant autocorrelation in the O3, PM10, NO, NO2, CO, and SO2 series. Cross correlations between PM10 (dependent variable) and gaseous pollutants (independent variables) show that all of the gases are significantly correlated with PM10 and that O3 is also significantly correlated lagged up to two previous days. Once a transfer-function model of current PM10 is defined for an urban location, the effect of an O3-control strategy on PM concentrations is estimated by calculating daily PM10 concentrations with reduced O3 concentrations. Forecasted summertime PM10 reductions resulting from a 5 percent decrease in ambient O3 range from 1.2 microg/m3 (3.03%) in Chicago to 3.9 microg/m3 (7.65%) in Phoenix.     

Assessing the relationship between personal particulate and gaseous exposures of senior citizens living in Baltimore, MD

We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (> 64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM2.5, PM10, SO4(2-), O3, NO2, SO2, and exhaust-related VOCs. Results of this study showed that longitudinal associations between ambient PM2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM2.5 exposures and resulting personal-ambient associations. Associations between personal PM2.5 exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM2.5 sources. Evidence for this was provided by SO4(2-) measurements, which can be thought of as a tracer for ambient PM2.5. For SO4(2-), personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM2.5 sources to personal PM2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments. Results also indicate that the potential for confounding by PM2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM2.5 exposures were not significantly correlated with personal exposures to PM2.5-10, PM2.5 of non-ambient origin, O3, NO2, and SO2. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM2.5 epidemiologic studies are unlikely to be due to confounding by the PM2.5 co-pollutants measured in this study.     

Ionic composition of PM(10) in the area of Thessaloniki,Greece

Airborne particulate matter (PM(10)) was collected from July 1997 to July 1998 at three locations in the city of Thessaloniki. PM(10) samples were analyzed for Cl(-), NO3(-), SO4(2-), Ca(2+), Mg(2+), Na(+), K(+) and NH4(+). The average PM(10) concentrations were found similar in all three sites with higher values in cold period. The ionic content comprised the 17-23% of the PM(10) mass and sulfate made up the 35-38% of the PM(10) ionic content with an average concentration of 4.80-7.26 microg m(-3). Good correlation was found for SO4(2-) and NO3(-) with Ca(2+), Mg(2+) and Cl(-). Two factors were found to influence the variance of ionic constituents in PM(10) by using factor analysis. Data evaluation considering wind direction showed that higher PM(10) and other ionic concentrations are associated with calm conditions, suggesting influences of local sources.     

Characterization of atmospheric PM10 and related chemical species in southern Taiwan during the episode days

The concentrations of atmospheric PM10 on days with episodes of pollution were examined at four different sampling sites (CC, DL, LY, and HK) in southern Taiwan. The related to particulates water-soluble ionic species (Na+, K+, Mg2+, Ca2+, NH4+, Cl-, NO3-, SO4(2-)), carbonaceous species (EC and OC) and metallic species (Zn, Ni, Pb, Fe, Mn, Al, Si, V) were also analyzed. On the episode days of this study, the PM10 mass concentration ranged from 155 to 210 microgm(-3), from 150 to 208 microgm(-3), from 182 to 249 microgm(-3), and from 166 to 228 microgm(-3) at CC, DL, LY, and HK, respectively. The results indicate that the dominant water-soluble species were SO4(2-), NO3-, NH4+, and Cl- at the four sampling sites on these days. Moreover, the high sulfate and nitrate conversion values (SOR and NOR) presented herein suggest that secondary formations from SO2 to SO4(2-) and from NO2 to NO3- are present in significant quantities in the atmosphere of southern Taiwan on episode days. In particular, high SOR and NOR verified that both SO4(2-) and NO3- dominated the increase of atmospheric PM10 concentration in southern Taiwan on episode days.     

Source identification of atlanta aerosol by positive matrix factorization

Data characterizing daily integrated particulate matter (PM) samples collected at the Jefferson Street monitoring site in Atlanta, GA, were analyzed through the application of a bilinear positive matrix factorization (PMF) model. A total of 662 samples and 26 variables were used for fine particle (particles < or = 2.5 microm in aerodynamic diameter) samples (PM2.5), and 685 samples and 15 variables were used for coarse particle (particles between 2.5 and 10 microm in aerodynamic diameter) samples (PM10-2.5). Measured PM mass concentrations and compositional data were used as independent variables. To obtain the quantitative contributions for each source, the factors were normalized using PMF-apportioned mass concentrations. For fine particle data, eight sources were identified: SO4(2-) -rich secondary aerosol (56%), motor vehicle (22%), wood smoke (11%), NO(3-) -rich secondary aerosol (7%), mixed source of cement kiln and organic carbon (OC) (2%), airborne soil (1%), metal recycling facility (0.5%), and mixed source of bus station and metal processing (0.3%). The SO4(2-) -rich and NO(3-) -rich secondary aerosols were associated with NH(4+). The SO4(2-) -rich secondary aerosols also included OC. For the coarse particle data, five sources contributed to the observed mass: airborne soil (60%), NO(3-)-rich secondary aerosol (16%), SO4(2-) -rich secondary aerosol (12%), cement kiln (11%), and metal recycling facility (1%). Conditional probability functions were computed using surface wind data and identified mass contributions from each source. The results of this analysis agreed well with the locations of known local point sources.     

Evaluation of air quality by passive and active sampling in an urban city in Turkey: current status and spatial analysis of air pollution exposure

Concentrations of air pollutants, nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), ozone (O(3)), particulate matter (PM(2.5) and PM(10)), trace metals, and polycyclic aromatic hydrocarbons (PAHs) were measured in 2008 and 2009 in the city of Eski?ehir, central Turkey. Spatial distributions of NO(2), SO(2), and ozone were determined by passive sampling campaigns carried out during two different seasons with fairly large spatial coverage. A basic population exposure assessment was carried out employing Geographical Information System techniques by combining population density maps with pollutant distribution maps of NO(2) and SO(2). It was found that 95 % of the population is exposed to NO(2) levels close to the World Health Organization guideline value. Regarding SO(2), a large proportion of the population (83 %) is exposed to levels above the WHO second interim target value. Concentrations of all the pollutants showed a seasonal pattern increasing in winter period, except for ozone having higher concentrations in summer season. Daily PM(10) and PM(2.5) concentrations exceeded European Union limit values almost every sampling day. Toxic fractions of the measured PAHs were calculated and approximately fourfold increase was observed in winter period. Copper, Pb, Sn, As, Cd, Zn, Sb, and Se were found to be moderately to highly enriched in PM(10) fraction, indicating anthropogenic input to those elements measured. Exposure assessment results indicate the need for action to reduce pollutant emissions especially in the city center. Passive sampling turns out to be a practical and economical tool for air quality assessment with large spatial coverage.     

Characterization of major chemical components of fine particulate matter in North Carolina

This paper presents measurements of daily sampling of fine particulate matter (PM2.5) and its major chemical components at three urban and one rural locations in North Carolina during 2002. At both urban and rural sites, the major insoluble component of PM2.5 is organic matter, and the major soluble components are sulfate (SO4(2-)), ammonium (NH4(+)), and nitrate (NO3(-)). NH4(+) is neutralized mainly by SO4(2-) rather than by NO3(-), except in winter when SO4(2-) concentration is relatively low, whereas NO3(-) concentration is high. The equivalent ratio of NH4(+) to the sum of SO4(2-) and NO3(-) is < 1, suggesting that SO4(2-) and NO3(-) are not completely neutralized by NH4(+). At both rural and urban sites, SO4(2-) concentration displays a maximum in summer and a minimum in winter, whereas NO3(-) displays an opposite seasonal trend. Mass ratio of NO3(-) to SO4(2-) is consistently < 1 at all sites, suggesting that stationary source emissions may play an important role in PM2.5 formation in those areas. Organic carbon and elemental carbon are well correlated at three urban sites although they are poorly correlated at the agriculture site. Other than the daily samples, hourly samples were measured at one urban site. PM2.5 mass concentrations display a peak in early morning, and a second peak in late afternoon. Back trajectory analysis shows that air masses with lower PM2.5 mass content mainly originate from the marine environment or from a continental environment but with a strong subsidence from the upper troposphere. Air masses with high PM2.5 mass concentrations are largely from continental sources. Our study of fine particulate matter and its chemical composition in North Carolina provides crucial information that may be used to determine the efficacy of the new National Ambient Air Quality Standard (NAAQS) for PM fine. Moreover, the gas-to-particle conversion processes provide improved prediction of long-range transport of pollutants and air quality.     

The need for ammonia abatement with respect to secondary PM reductions in Europe

In Europe, secondary particulate matter (PM) comprises 50% or more of PM 2.5. To reduce PM concentrations requires lowering precursor emissions. Since the 1980s, SO(2) emissions have decreased by more than 60%, while particle concentrations have decreased less. NO(x) and NH(3) emissions have decreased slightly. The role of ammonia in particle formation is addressed here. It is shown that secondary PM concentrations can only be effectively reduced if ammonia emissions are decreased in much the same way as those of SO(2) and NO(x).     

Semicontinuous PM2.5 sulfate and nitrate measurements at an urban and a rural location in New York: PMTACS-NY summer 2001 and 2002 campaigns

Several collocated semicontinuous instruments measuring particulate matter with particle sizes < or =2.5 microm (PM2.5) sulfate (SO4(2-)) and nitrate (NO3-) were intercompared during two intensive field campaigns as part of the PM2.5 Technology Assessment and Characterization Study. The summer 2001 urban campaign in Queens, NY, and the summer 2002 rural campaign in upstate New York (Whiteface Mountain) hosted an operation of an Aerosol Mass Spectrometer, Ambient Particulate Sulfate and Nitrate Monitors, a Continuous Ambient Sulfate Monitor, and a Particle-Into-Liquid Sampler with Ion Chromatographs (PILS-IC). These instruments provided near real-time particulate SO4(2-) and NO3- mass concentration data, allowing the study of particulate SO4(2-)/NO3- diurnal patterns and detection of short-term events. Typical particulate SO4(2-) concentrations were comparable at both sites (ranging from 0 to 20 microg/m3), while ambient urban particulate NO3- concentrations ranged from 0 to 11 microg/m3 and rural NO3- concentration was typically less than 1 microg/m3. Results of the intercomparisons of the semicontinuous measurements are presented, as are results of the comparisons between the semicontinuous and time-integrated filter-based measurements. The comparisons at both sites, in most cases, indicated similar performance characteristics. In addition, charge balance calculations, based on major soluble ionic components of atmospheric aerosol from the PILS-IC and the filter measurements, indicated slightly acidic aerosol at both locations.     

A study of the association between daily mortality and ambient air pollutant concentrations in Pittsburgh, Pennsylvania

We have studied the possible association of daily mortality with ambient pollutant concentrations (PM10, CO, O3, SO2, NO2, and fine [PM2.5] and coarse PM) and weather variables (temperature and dew point) in the Pittsburgh, PA, area for two age groups--less than 75, and 75 and over--for the 3-year period of 1989-1991. Correlation functions among pollutant concentrations show important seasonal dependence, and this fact necessitates the use of seasonal models to better identify the link between ambient pollutant concentrations and daily mortality. An analysis of the seasonal model results for the younger-age group reveals significant multicollinearity problems among the highly correlated concentrations of PM10, CO, and NO2 (and O3 in spring and summer), and calls into question the rather consistent results of the single- and multi-pollutant non-seasonal models that show a significant positive association between PM10 and daily mortality. For the older-age group, dew point consistently shows a significant association with daily mortality in all models. Collinearity problems appear in the multi-pollutant seasonal and non-seasonal models such that a significant, positive PM10 coefficient is accompanied by a significant, negative coefficient of another ambient pollutant, and the identity of this other pollutant changes with season. The PM2.5 data set is half that of PM10. Identical-model runs for both data sets reveal instability in the pollutant coefficients, especially for the younger age group. The concern for the instability of the pollutant coefficients due to a small signal-to-noise ratio makes it impossible to ascertain credibly the relative associations of the fine- and coarse-particle modes with daily mortality. In this connection, we call for caution in the interpretation of model results for causal inference when the models use fully or partially estimated PM values to fill large data gaps.     

Inorganic PM2.5 at a U.S. agricultural site

In this study, we present approximately two years (January 1999-December 2000) of atmospheric NH3, NH4+, HCl, Cl-, HNO3, NO3-, SO2, and SO4= concentrations measured by the annular denuder/filter pack method at an agricultural site in eastern North Carolina. This site is influenced by high NH3 emissions from animal production and fertilizer use in the surrounding area and neighboring counties. The two-year mean NH3 concentration is 5.6 (+/-5.13) microg m(-3). The mean concentration of total inorganic PM2.5, which includes SO4=, NO3-, NH4+, and Cl-, is 8.0 (+/-5.84) microg m(-3). SO4=, NO3-, NH4+, and Cl- represent, respectively, 53, 24, 22, and 1% of measured inorganic PM2.5. NH3 contributes 72% of total NH3 + NH4+, on an average. Equilibrium modeling of the gas+aerosol NH3/H2SO4/HNO3 system shows that inorganic PM2.5 is more sensitive to reductions in gas + aerosol concentrations of sulfate and nitrate relative to NH3.     

百色市右江区大气PM10中水溶性无机离子的化学特征与来源

2010年10月至2011年9月采集百色市右江区大气PM10样品,分析PM10及其水溶性无机离子的化学特征与来源。结果表明:(1)百色市右江区大气PM10为13.89～319.44μg/m3,年均117.48μg/m3,年均值超过《环境空气质量标准》(GB 3095-2012)二级标准(100μg/m3)。百色市右江区大气可吸入颗粒物的污染主要出现在春冬季节。(2)水溶性无机离子浓度年均值依次为SO24->NO3->Cl->NH4+>K+>Na+>Mg2+>F-,SO24-、NO3-和Cl-浓度最高,分别占水溶性无机离子的57.7%、14.9%和14.5%。(3)百色市右江区大气PM10呈较强的酸性,高浓度的SO42-可能是导致百色市右江区大气PM10呈较强酸性的主要原因。(4)PM10的季节变化受气温和风速的影响极显著;气象因素对SO42-、NO3-、F-的影响不显著。(5)主因子分析表明,PM10中水溶性无机离子可能来自3个方面,Cl-和NO3-主要来自于当地低烟卤煤燃烧排放的烟气;Mg2+、K+和Na+主要来自于自然源;F-、SO24-和NH4+主要来自于混合源。     

Analysis of aerosol particles and coarse particulate matter concentrations in Chillán, Chile, 2001-2003

Daily particle samples were collected in Chillán, Chile, at six urban locations from September 1, 2001, through September 30, 2003. Aerosol samples were collected using monitors equipped with a Sierra Andersen 246-b cyclone inlet on Teflon filters. Average concentrations of coarse particulate matter (PM10) for the 2001-2003 period ranged from 43.4 microg/m3 to 81.8 microg/m3 across the six sites. Annual PM10 concentration levels exceeded the European Union concentration limits. Mean PM10 levels during the cold season (April through September) were more than twice as high as those observed in the warm season (October through March). Average contributions to PM10 from organic matter, soil dust, nitrate (NO3-), elemental carbon, ammonium (NH4+), and sulfate (SO4(2-)) were 31%, 27%, 11%, 8%, 7%, and 5%, respectively. The chemical analyses indicated that carbonaceous substances were the most abundant components of PM10 in cold months, whereas crustal material was the most abundant component of PM10 during warm months. Higher concentration levels were observed in the downtown area suggesting a clear anthropogenic origin, whereas in the rural sites the source was mainly natural, such as resuspended soil dust associated with traffic on unpaved roads and agricultural activities.     

Application and evaluation of two air quality models for particulate matter for a southeastern U.S. episode

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29-July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O3), particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 microm (PM10) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O3 and PM than CMAQ. Both models tend to predict O3 values that are higher than those observed. For observed O3 values above 60 ppb, O3 performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O3 values above 40 ppb. Both models predict similar amounts of sulfate (SO4(2-)) and organic matter, and both predict SO4(2-) to be the largest contributor to PM2.5. PMCAMx generally predicts higher amounts of ammonium (NH4+), nitrate (NO3-), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO3-, NH4+, and BC than observed, which degrades its performance. For PM10 and PM2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37-43% and -33-4% for CMAQ and 50-59% and 7-30% for PMCAMx. Both models predict the largest MNGEs for NO3- (98-104% for CMAQ 138-338% for PMCAMx). The inaccurate NO3- predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.     

基于改进型灰色神经网络组合模型的空气质量预测

基于空气质量数据不足及波动较大的情况,将灰色GM（1,1）模型与人工神经网络模型组合并改进,建立改进型灰色神经网络组合模型。利用天津市2001—2008年PM10、SO2和NO2年均值作为原始数据预测2009—2010年PM10、SO2和NO2的浓度以进行模型精度检验,最后利用该模型预测2011—2015年天津市空气质量状况。结果表明,与灰色GM（1,1）模型、传统灰色神经网络组合模型相比,所建立的改进型灰色神经网络组合模型相对模拟误差小,预测结果更为可靠,可以用于空气质量预测。     

Effects of SO2 and NOx emission reductions on PM2.5 mass concentrations in the southeastern United States

Measurements from sites of the Southeastern Aerosol Research and Characterization (SEARCH) program, made from 1998 to 2001, are used with a thermodynamic equilibrium model, Simulating Composition of Atmospheric Particles at Equilbrium (SCAPE2), to extend an earlier investigation of the responses of fine particulate nitrate (NO3-) and fine particulate matter (PM2.5) mass concentrations to changes in concentrations of nitric acid (HNO3) and sulfate (SO42-). The responses were determined for a projected range of variations of SO42- and HNO3 concentrations resulting from adopted and proposed regulatory initiatives. The predicted PM2.5 mass concentration decreases averaged 1.8-3.9 microg/m3 for SO42- decreases of 46-63% from current concentrations. Combining the S042- decrease with a 40% HNO3 decrease from current concentrations (approximating expected mobile-source oxides of nitrogen [NOx] reductions by 2020) yielded additional incremental reductions of mean predicted PM2.5 mass concentration of 0.2 microg/m3 for three nonurban sites and 0.8-1 microg/m3 for one nonurban and two urban sites. Increasing the HNO3 reduction to 55% (an estimate of adding Clear Skies Phase II NOx reductions) yielded additional incremental reductions of mean predicted PM2.5 mass concentration of 0-0.4 microg/m3. Because of the well-documented losses of particulate NO3- from Federal Reference Method (FRM) filters, only a fraction of these incremental changes would be observed.     

Characterization of chemical species in atmospheric aerosols in a metropolitan basin

Ambient PM10 aerosol samples were collected from Taiwan's Taichung metropolitan basin between October 1997 and January 1998, and their chemical characteristics studied. The average mass concentration of PM10 was 109.0 +/- 54.1 microg/m3. Carbonaceous materials, sulfate, nitrate, and ammonium were the most important contributors to the PM10 component. On average, 64% of the PM10 was made up of fine particles. During PM10 episodes, average wind speed was 0.7 m/s and relative humidity was high, 83% on average, probably giving rise to stagnation of air pollutants and their entrapment close to the surface. With relative humidity < 70%, NO3-, NH4+, SO4(2-), carbonaceous materials, and PM10 mass showed high correlation with maximum hourly average ozone (O3M). Variation in atmospheric humidity may affect the gas-to-particle interactions of S and N species. The most significant contribution to PM10 in the Taichung urban basin was from the photochemical formation of secondary aerosols and carbonaceous materials in the atmospheric environment.     

Chemical characterization and factor analysis of PM2.5 in two sites of Monterrey, Mexico

The Monterrey Metropolitan Area (MMA) has shown a high concentration of PM2.5 in its atmosphere since 2003. The contribution of possible sources of primary PM2.5 and its precursors is not known. In this paper we present the results of analyzing the chemical composition of sixty 24-hr samples of PM2.5 to determine possible sources of PM2.5 in the MMA. The samples were collected at the northeast and southeast of the MMA between November 22 and December 12, 2007, using low-volume devices. Teflon and quartz filters were used to collect the samples. The concentrations of 16 airborne trace elements were determined using x-ray fluorescence (XRF). Anions and cations were determined using ion chromatography. Organic carbon (OC) and elemental carbon (EC) were determined by thermal optical analysis. The results show that Ca had the maximum mean concentration of all elements studied, followed by S. Enrichment factors above 50 were calculated for S, Cl, Cu, Zn, Br and Pb. This indicates that these elements may come from anthropogenic sources. Overall, the major average components of PM2.5 were OC (41.7%), SO4(2-) (22.9%), EC (7.4%), crustal material (11.4%), and NO3- (12.6%), which altogether accounted for 96% of the mass. Statistically, we did not find any difference in SO4(2-) concentrations between the two sites. The fraction of secondary organic carbon was between 24% and 34%. The results of the factor analysis performed over 10 metals and OC and EC show that there are three main sources of PM2.5: crustal material and vehicle exhaust; industrial activity; and fuel oil burning. The results show that SO4(2-), OC, and crustal material are important components of PM2.5 in MMA. Further work is necessary to evaluate the proportion of secondary inorganic and organic aerosol in order to have a better understanding of the sources and precursors of aerosols in the MMA.     

Fine and coarse particulate matter chemical characterization in a heavily industrialized city in central Mexico during Winter 2003

This paper presents the results of the first reported study on fine particulate matter (PM) chemical composition at Salamanca, a highly industrialized urban area of Central Mexico. Samples were collected at six sites within the urban area during February and March 2003. Several trace elements, organic carbon (OC), elemental carbon (EC), and six ions were analyzed to characterize aerosols. Average concentrations of PM with aerodynamic diameter of less than 10 microm (PM10) and fine PM with aerodynamic diameter of less than 2.5 microm (PM2.5) ranged from 32.2 to 76.6 [g m(-3) and 11.1 to 23.7 microg m(-3), respectively. OC (34%), SO4= (25.1%), EC (12.9%), and geological material (12.5%) were the major components of PM2.5. For PM10 geological material (57.9%), OC (17.3%), and SO4= (9.7%) were the major components. Coarse fraction (PM,, -PM2.5), geological material (81.7%), and OC (8.6%) were the dominant species, which amounted to 90.4%. Correlation analysis showed that sulfate in PM2.5 was present as ammonium sulfate. Sulfate showed a significant spatial variation with higher concentrations to the north resulting from predominantly southwesterly winds above the surface layer and by major SO2 sources that include a power plant and refinery. At the urban site of Cruz Roja it was observed that PM2.5 mass concentrations were similar to the submicron fraction concentrations. Furthermore, the correlation between EC in PM2.5 and EC measured from an aethalometer was r(2) = 0.710. Temporal variations of SO2 and nitrogen oxide were observed during a day when the maximum concentration of PM2.5 was measured, which was associated with emissions from the nearby refinery and power plant. From cascade impactor measurements, the three measured modes of airborne particles corresponded with diameters of 0.32, 1.8, and 5.6 microm.