Retrospective prediction of intraurban spatiotemporal distribution of PM2.5 in Taipei

Numerous studies have shown that fine airborne particulate matter particles (PM2.5) are more dangerous to human health than coarse particles, e.g. PM10. The assessment of the impacts to human health or ecological effects by long-term PM2.5 exposure is often limited by lack of PM2.5 measurements. In Taipei, PM2.5 was not systematically observed until August, 2005. Taipei is the largest metropolitan area in Taiwan, where a variety of industrial and traffic emissions are continuously generated and distributed across space and time. PM-related data, i.e., PM10 and Total Suspended Particles (TSP) are independently systematically collected by different central and local government institutes. In this study, the retrospective prediction of spatiotemporal distribution of monthly PM2.5 over Taipei will be performed by using Bayesian Maximum Entropy method (BME) to integrate (a) the spatiotemporal dependence among PM measurements (i.e. PM10, TSP, and PM2.5), (b) the site-specific information of PM measurements which can be certain or uncertain information, and (c) empirical evidence about the PM2.5/PM10 and PM10/TSP ratios. The performance assessment of the retrospective prediction for the spatiotemporal distribution of PM2.5 was performed over space and time during 2003–2004 by comparing the posterior pdf of PM2.5 with the observations. Results show that the incorporation of PM10 and TSP observations by BME method can effectively improve the spatiotemporal PM2.5 estimation in the sense of lower mean and standard deviation of estimation errors. Moreover, the spatiotemporal retrospective prediction with PM2.5/PM10 and PM2.5/TSP ratios can provide good estimations of the range of PM2.5 levels over space and time during 2003–2004 in Taipei.     

Spatial variability of PM2.5 in urban areas in the United States

Data from the U.S. Environmental Protection Agency's Aerometric Information Retrieval System (now known as the Air Quality System) database for 1999 and 2000 have been used to characterize the spatial variability of concentrations of particulate matter with aerodynamic diameter < or = 2.5 microg (PM2.5) in 27 urban areas across the United States. Different measures were used to quantify the degree of uniformity of PM2.5 concentrations in the urban areas characterized. It was observed that PM2.5 concentrations varied to differing degrees in the urban areas examined. Analyses of several urban areas in the Southeast indicated high correlations between site pairs and spatial uniformity in concentration fields. Considerable spatial variation was found in other regions, especially in the West. Even within urban areas in which all site pairs were highly correlated, a variable degree of heterogeneity in PM2.5 concentrations was found. Thus, even though concentrations at pairs of sites were highly correlated, their concentrations were not necessarily the same. These findings indicate that the potential for exposure misclassification errors in time-series epidemiologic studies exists.     

Particulate matter in California: part 1--Intercomparison of several PM2.5, PM10-2.5, and PM10 monitoring networks

It will be many years before the recently deployed network of fine particulate matter with an aerodynamic diameter less than 2.5 microm (PM2.5) Federal Reference Method (FRM) samplers produces information on nonattainment areas, trends, and source impacts. However, data on PM2.5 and its major constituents have been routinely collected in California for the past 20 years. The California Air Resources Board operated as many as 20 dichotomous (dichot) samplers for PM2.5 and coarse PM (PM10-2.5). The California Acid Deposition Monitoring Program (CADMP) collected 12-h-average PM2.5 and PM10 from 1988 to 1995 at ten urban and rural sites and 24-h-average PM2.5 at five urban sites since 1995. Beginning in 1994, the Children's Health Study collected 2-week averages of PM2.5 in 12 communities in southern California using the Two-Week Sampler (TWS). Comparisons of collocated samples establish relationships between the dichot, CADMP, and TWS samplers and the 82-site network of PM2.5 FRM samplers deployed since 1999 in California. PM mass data from the different monitoring programs have modest to high correlation to FRM mass data, fairly small systematic biases and negative proportional biases ranging from 7 to 22%. If the biases are taken into account, all of the programs should be considered comparable with the FRM program. Thus, historical data can be used to develop long-term PM trends in California.     

Particulate matter in California: part 2--Spatial, temporal, and compositional patterns of PM2.5, PM10-2.5, and PM10

Geographic and temporal variations in the concentration and composition of particulate matter (PM) provide important insights into particle sources, atmospheric processes that influence particle formation, and PM management strategies. In the nonurban areas of California, annual-average PM2.5 and PM10 concentrations range from 3 to 10 microg/m3 and from 5 to 18 microg/m3, respectively. In the urban areas of California, annual-averages for PM2.5 range from 7 to 30 microg/m3, with observed 24-hr peaks reaching levels as high as 160 microg/m3. Within each air basin, exceedances are a mixture of isolated events as well as periods of elevated PM2.5 concentrations that are more prolonged and regional in nature. PM2.5 concentrations are generally highest during the winter months. The exception is the South Coast Air Basin, where fairly high values occur throughout the year. Annual-average PM2.5 mass, as well as the concentrations of major components, declined from 1988 to 2000. The declines are especially pronounced for the sulfate (SO4(2-)) and nitrate (NO3-) components of PM2.5 and PM10) and correlate with reductions in ambient levels of oxides of sulfur (SOx) and oxides of nitrogen (NOx). Annual averages for PM10-2.5 and PM10 exhibited similar downwind trends from 1994 to 1999, with a slightly less pronounced decrease in the coarse fraction.     

基于BP人工神经网络的城市PM2.5浓度空间预测

针对PM2.5日均质量浓度,采用BP人工神经网络模型,预测研究区空气中PM2.5浓度的空间变异,通过与普通克里格(Ordinary Kriging)插值方法对比验证BP人工神经网络预测模型的精度.结果表明:BP人工神经网络预测模型下研究区检验样本点位置的PM2.5仿真浓度与观测浓度之间的均方差、平均绝对误差、平均相对偏差和相关系数分别为0.296 μg2/m6、0.412 μg/m3、1.650％和0.851;而与此同时,普通克里格插值方法下的对应结果分别为1.041 μg2/m6、0.689 μg/m3、11.910％、0.638.研究成果在肯定BP人工神经网络预测模型可用于揭示PM2.5浓度空间变异特征的同时,也证实了其相对于普通克里格插值方法在固定空间点位准确预测PM2.5浓度方面的优势.     

PM10 and PM2.5 source apportionment in the Barcelona Metropolitan area, Catalonia, Spain

Levels of total suspended particles, PM10, PM2.5 and PM1 were continuously monitored at an urban kerbside in the Metropolitan area of Barcelona from June 1999 to June 2000. The results show that hourly levels of PM2.5 and PM1 are consistent with the daily cycle of gaseous pollutants emitted by traffic, whereas TSP and PM10 do not follow the same trend, at least in the diurnal period. The PM2.5/PM10 ratio is dependent on the traffic emissions, whereas additional contribution sources for the >10 μm fraction must be taken into account in the diurnal period. Different PM10 and PM2.5 source apportionment techniques were compared. A methodology based on the chemical determination of 83% of both PM10 and PM2.5 masses allowed us to quantify the marine (4% in PM10 and <1% in PM2.5), crustal (26% in PM10 and 8% in PM2.5) and anthropogenic (54% in PM10 and 73% in PM2.5) loads. Peaks of crustal contribution to PM10 (up to 44% of the PM10 mass) were recorded under Saharan air mass intrusions. A different seasonal trend was observed for levels of sulphate and nitrate, probably as a consequence of the different thermodynamic behaviour of these PM species and the higher summer oxidation rate of SO₂.     

Chemical speciation of PM2.5 and PM10 in south Phoenix, AZ, USA

Phoenix, AZ, experiences high particulate matter (PM) episodes, especially in the wintertime. The spatial variation of the PM concentrations and resulting differences in exposure is of particular concern. In this study, PM2.s (PM with aerodynamic diameter <2.5 microm) and PM10 (PM with aerodynamic diameter <10 microm) samples were collected simultaneously from the east and west sides of South Phoenix and at a control site in Tempe and analyzed for trace elements and bulk elemental and organic carbon. Measurements showed that although PM2.5 concentrations had similar trends in temporal scale across all sites, concentrations of PM10 did not. The difference in PM10 concentrations and fluctuation across the three sites suggest effects of a local soil source as evidenced by high concentrations of Al, Ca, and Fe in PM10. K and anthropogenic elements (e.g., Cu, Pb, and Zn) in PM2.5 samples on January 1 were strikingly high, suggesting the influence of New Year's fireworks. Concentrations of toxic elements (e.g., Pb) in the study presented here are not different from similar studies in other U.S. cities. Application of principal component analysis indicated two broad categories of emission sources--soil and combustion--together accounting for 80 and 90% of variance, respectively, in PM2.5 and PM10. The soil and combustion components explained approximately 60 and 30% of the variance in PM10, respectively, whereas combustion sources dominated PM2.5 (>50% variance). Many elements associated with anthropogenic sources were highly enriched, with enrichment factors in PM2.5 an order of magnitude higher than in PM10 relative to surface soil composition in the study area.     

Elemental characterization of PM10, PM2.5 and PM1 in the town of Genoa (Italy)

The particulate matter (PM) concentration and composition, the PM10, PM2.5, PM1 fractions, were studied in the urban area of Genoa, a coastal town in the northwest of Italy. Two instruments, the continuous monitor TEOM and the sequential sampler PARTISOL, were operated almost continuously on the same site from July 2001 to September 2004. Samples collected by PARTISOL were weighted to obtain PM concentration and then analysed by PIXE (particle induced X-ray emission) and by ED-XRF (energy dispersion X-ray fluorescence), obtaining concentrations for elements from Na to Pb. Some of the filters used in the TEOM microbalance were analysed by ED-XRF to calculate Pb concentration values averaged over 7-30 d periods.     

Determination of source contributions to ambient PM2.5 in Kaohsiung, Taiwan, using a receptor model

Ambient particulates of PM2.5 were sampled at three sites in Kaohsiung, Taiwan, during February and March 1999. In addition, resuspended PM2.5 collected from traffic tunnels, paved roads, fly ash of a municipal solid waste (MSW) incinerator, and seawater was obtained. All the samples were analyzed for twenty constituents, including water-soluble ions, organic carbon (OC), elemental carbon (EC), and metallic elements. In conjunction with local source profiles and the source profiles in the model library SPECIATE EPA, the receptor model based on chemical mass balance (CMB) was then applied to determine the source contributions to ambient PM2.5. The mean concentration of ambient PM2.5 was 42.69-53.68 micrograms/m3 for the sampling period. The abundant species in ambient PM2.5 in the mass fraction for three sites were OC (12.7-14.2%), SO4(2-) (12.8-15.1%), NO3- (8.1-10.3%), NH4+ (6.7-7.5%), and EC (5.3-8.5%). Results of CMB modeling show that major pollution sources for ambient PM2.5 are traffic exhaust (18-54%), secondary aerosols (30-41% from SO4(2-) and NO3-), and outdoor burning of agriculture wastes (13-17%).     

Levoglucosan in PM2.5 at the Fresno supersite

Ambient air monitoring for PM2.5 has been conducted on a daily basis at the Fresno, CA, supersite since 1999. It has been found that PM2.5 concentrations routinely exceed the National Ambient Air Quality Standards during the winter months. In an effort to determine the effect of biomass burning on PM2.5 concentrations, samples during 2000 were analyzed for levoglucosan, palmitic acid, and stearic acid. The results of this study are presented.     

Pollution characteristics and toxic effects of PM1.0 and PM2.5 in Harbin,China

Environmental Science and Pollution Research - In 2019, PM2.5 and PM1.0 samples were collected in Harbin City, Heilongjiang Province, China, to research their mass concentration, number...     

Source apportionment of indoor, outdoor, and personal PM2.5 in Seattle, Washington, using positive matrix factorization

As part of a large exposure assessment and health-effects panel study, 33 trace elements and light-absorbing carbon were measured on 24-hr fixed-site filter samples for particulate matter with an aerodynamic diameter <2.5 microm (PM2.5) collected between September 26, 2000, and May 25, 2001, at a central outdoor site, immediately outside each subject's residence, inside each residence, and on each subject (personal sample). Both two-way (PMF2) and three-way (PMF3) positive matrix factorization were used to deduce the sources contributing to PM2.5. Five sources contributing to the indoor and outdoor samples were identified: vegetative burning, mobile emissions, secondary sulfate, a source rich in chlorine, and a source of crustal-derived material. Vegetative burning contributed more PM2.5 mass on average than any other source in all microenvironments, with average values estimated by PMF2 and PMF3, respectively, of 7.6 and 8.7 microg/m3 for the outdoor samples, 4 and 5.3 microg/m3 for the indoor samples, and 3.8 and 3.4 microg/m3 for the personal samples. Personal exposure to the combustion-related particles was correlated with outdoor sources, whereas exposure to the crustal and chlorine-rich particles was not. Personal exposures to crustal sources were strongly associated with personal activities, especially time spent at school among the child subjects.     

Assessing source characteristics of PM2.5 in the eastern United States using positive matrix factorization

Fine aerosol (PM2.5) measurements obtained from the first year of operation of the nationwide network of PM2.5 monitors were studied with the factor analysis technique of positive matrix factorization (PMF). PM2.5 mass concentration data were extracted from the Atmospheric Information Retrieval System (AIRS) database of the U.S. Environmental Protection Agency (EPA). PMF was applied to measurements at more than 350 monitoring locations in the eastern half of the United States. Data consisted of PM2.5 24-hr averaged concentrations measured every third day from April through December 1999. The PMF model suggested six factors representing source influences to the PM2.5 mass concentrations at measurement sites. Factor 5, covering much of the Appalachian states, exhibited significant seasonal behavior.     

Analysis of PM10, PM2.5, and PM2 5-10 concentrations in Santiago, Chile, from 1989 to 2001

Daily particle samples were collected in Santiago, Chile, at four urban locations from January 1, 1989, through December 31, 2001. Both fine PM with da < 2.5 microm (PM2.5) and coarse PM with 2.5 < da < 10 microm (PM2.5-10) were collected using dichotomous samplers. The inhalable particle fraction, PM10, was determined as the sum of fine and coarse concentrations. Wind speed, temperature and relative humidity (RH) were also measured continuously. Average concentrations of PM2.5 for the 1989-2001 period ranged from 38.5 microg/m3 to 53 microg/m3. For PM2.5-10 levels ranged from 35.8-48.2 microg/m3 and for PM10 results were 74.4-101.2 microg/m3 across the four sites. Both annual and daily PM2.5 and PM10 concentration levels exceeded the U.S. National Ambient Air Quality Standards and the European Union concentration limits. Mean PM2.5 levels during the cold season (April through September) were more than twice as high as those observed in the warm season (October through March); whereas coarse particle levels were similar in both seasons. PM concentration trends were investigated using regression models, controlling for site, weekday, month, wind speed, temperature, and RH. Results showed that PM2.5 concentrations decreased substantially, 52% over the 12-year period (1989-2000), whereas PM2.5-10 concentrations increased by approximately 50% in the first 5 years and then decreased by a similar percentage over the following 7 years. These decreases were evident even after controlling for significant climatic effects. These results suggest that the pollution reduction programs developed and implemented by the Comisión Nacional del Medio Ambiente (CONAMA) have been effective in reducing particle levels in the Santiago Metropolitan region. However, particle levels remain high and it is thus imperative that efforts to improve air quality continue.     

Impact of Covid-19 partial lockdown on PM2.5, SO2, NO2, O3, and trace elements in PM2.5 in Hanoi,Vietnam

Covid-19 lockdowns have improved the ambient air quality across the world via reduced air pollutant levels. This article aims to investigate the effect of the partial lockdown on the main ambient air pollutants and their elemental concentrations bound to PM_2.5 in Hanoi. In addition to the PM_2.5 samples collected at three urban sites in Hanoi, the daily PM_2.5, NO₂, O₃, and SO₂ levels were collected from the automatic ambient air quality monitoring station at Nguyen Van Cu street to analyze the pollution level before (March 10th–March 31st) and during the partial lockdown (April 1st–April 22nd) with “current” data obtained in 2020 and “historical” data obtained in 2014, 2016, and 2017. The results showed that NO₂, PM_2.5, O₃, and SO₂ concentrations obtained from the automatic ambient air quality monitoring station were reduced by 75.8, 55.9, 21.4, and 60.7%, respectively, compared with historical data. Besides, the concentration of PM_2.5 at sampling sites declined by 41.8% during the partial lockdown. Furthermore, there was a drastic negative relationship between the boundary layer height (BLH) and the daily mean PM_2.5 in Hanoi. The concentrations of Cd, Se, As, Sr, Ba, Cu, Mn, Pb, K, Zn, Ca, Al, and Mg during the partial lockdown were lower than those before the partial lockdown. The results of enrichment factor (EF) values and principal component analysis (PCA) concluded that trace elements in PM_2.5 before the partial lockdown were more affected by industrial activities than those during the partial lockdown.

     

湍流环形通道热泳脱除可吸入颗粒物技术研究

湍流中PM2．5粒子的热泳沉积是国际上研究热门课题。但目前单纯热泳沉积效率也不过20％左右。依据热泳基本原理，设计了一种新型湍流方环形双壁冷却式通道。计算表明，该类型通道比一般单管通道有着较高的可吸入颗粒物脱除效率。同时，利用湍流的沉积效率，加上热泳沉积效率。可以达到较高的总泳沉积效率。通过结构设计，可以提高可吸入颗粒物的脱除效率，是值得进一步探索的新路子。     

Determination of PM2.5 sources using time-resolved integrated source and receptor models

Multivariate statistical techniques are applied to particulate matter (PM) and meteorological data to identify the sources responsible for evening PM spikes at Sunland Park, NM (USA). The statistical techniques applied are principal components analysis (PCA), redundancy analysis (RDA), and absolute principal components scores analysis (APCSA), and the data evaluated are 3-h average (6–9 p.m.) PM_2.5 mass and chemical composition and 1-h average PM_2.5 and PM₁₀ mass and environmental data collected in the winter of 2002. Although the interpretation of the data was complicated by the presence of sources which are likely changing in time (e.g. brick kilns), the multivariate analyses indicate that the evening high PM_2.5 is associated with burning-activities occurring to the south of Sunland Park, and these emissions are characterized by elevated Sb, Cl⁻, and elemental carbon; 68% of the PM_2.5 mass can be attributed to this source. The PM₁₀ evening peaks, on the other hand, are mainly caused by resuspended dust generated by vehicular movements south of the site and transported by the local terrain-induced drainage flow.     

Semi-volatile species in PM2.5: comparison of integrated and continuous samplers for PM2.5 research or monitoring

Fine particles in urban atmospheres contain substantial quantities of semi-volatile material [e.g., NH4NO3 and semi-volatile organic compounds (SVOCs)] that are lost from particles during collection on a filter. Several diffusion denuder samplers have been developed for the determination of both NO3- and organic semi-volatile fine particulate components. The combination of technology used in the BOSS diffusion denuder sampler and the Harvard particle concentrator has resulted in the Particle Concentrator-Brigham Young University Organic Sampling System (PC-BOSS) for the 24-hr (or less) integrated collection of PM2.5, including NH4NO3 and semi-volatile organic material. Modification of the BOSS sampler allows for the weekly determination of these same species. Combination of BOSS denuder and tapered element oscillating microbalance (TEOM) monitor technology has resulted in the real-time ambient mass sampler (RAMS) for the continuous measurement of PM2.5, including the semi-volatile components. Comparison of the results obtained with the BOSS and with each of the newly developed modifications of the BOSS indicates that the modified versions can be used for the continuous, daily, or weekly monitoring of PM2.5, including semi-volatile species, as appropriate to the design of each sampler.     

PM2.5–10, PM2.5 and associated water-soluble inorganic species at a coastal urban site in the metropolitan region of Rio de Janeiro

The concentrations of PM_2.5−10, PM_2.5 and associated water-soluble inorganic species (WSIS) were determined in a coastal site of the metropolitan region of Rio de Janeiro, Southeastern Brazil, from October 1998 to September 1999 (n=50). Samples were dissolved in water and analyzed for major inorganic ions. The mean (± standard deviation; median) concentrations of PM_2.5−10 and PM_2.5 were, respectively, 26 (± 16; 21) μg m⁻³ and 17 (± 13; 14) μg m⁻³. Their mean concentrations were 1.7–1.8 times higher in dry season (May–October) than in rainy season (November–April). The WSIS comprised, respectively, 34% and 28% of the PM_2.5−10 and PM_2.5 masses. Chloride, Na⁺ and Mg²⁺ were the predominant ions in PM_2.5−10, indicating a significant influence of sea-salt aerosols. In PM_2.5, SO₄²⁻ (∼97% nss-SO₄²⁻) and NH₄⁺ were the most abundant ions and their equivalent concentration ratio (SO₄²⁻/NH₄⁺ ∼1.0) suggests that they were present as (NH₄)₂SO₄ particles. The mean concentration of (NH₄)₂SO₄ was 3.4 μg m⁻³. The mean equivalent PM_2.5 NO₃⁻ concentration was eight times smaller than those of SO₄²⁻ and NH₄⁺. The PM_2.5 NO₃⁻ concentration in dry season was three times higher than in rainy season, probably due to reaction of NaCl (sea salt) with HNO₃ as a result of higher levels of NO_y during the dry season and/or reduced volatilization of NH₄NO₃ due to lower wintertime temperature. Chloride depletion was observed in both size ranges, although more pronouncely in PM_2.5.