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.     

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.     

Personal exposures to particles and their relationships with personal activities for chronic obstructive pulmonary disease patients living in Boston

An exposure study of 18 subjects with chronic obstructive pulmonary disease (COPD) living in the Boston, MA, area was conducted. The objective was to examine determinants of personal exposures to particulate matter (PM) with aerodynamic diameters of less than 2.5 microm (PM2.5), less than 10 microm (PM10), and between 2.5 and 10 microm (PM2.5-10). In a previous publication, the analyses of the longitudinal individual-specific relationships among indoor, outdoor, and personal levels showed that the relationships varied by subject and by particle size fraction. In the present paper, statistical and physical models were used to examine personal PM2.5, PM10, and PM2.5-10 exposure covariates. Results indicated that time-weighted indoor concentrations were significant predictors of personal PM2.5, PM10, and PM2.5-10 exposures. Also, time-weighted outdoor concentrations, time spent near smokers, and time spent during transportation were important predictors for PM2.5 but not for personal PM2.5-10 exposures. In turn, time spent cleaning contributed to all size-fraction personal exposures, whereas cooking affected only personal PM2.5-10 exposures. The findings showed that the relationship between personal PM2.5 exposures and the corresponding ambient concentrations was influenced by home air exchange rates (or by ventilation status). Because the particle properties or components causing the health effects are unknown, it is not certain to what extent the risk posed by ambient particles can be reduced by controlling any one of these factors.     

Evaluation of time-resolved PM2.5 data in urban/suburban areas of New Jersey

Time-resolved data is needed for public notification of unhealthful air quality and to develop an understanding of atmospheric chemistry, including insights important to control strategies. In this research, continuous fine particulate matter (PM2.5) mass concentrations were measured with tapered element oscillating microbalances (TEOMs) across New Jersey from July 1997 to June 1998. Data features indicating the influence of local sources and long-distance transport are examined, as well as differences between 1-hr maxima and 24-hr average concentrations that might be relevant to acute health effects. Continuous mass concentrations were not significantly different from filter-collected gravimetric mass concentrations with 95% confidence intervals during any season. Annual mean PM2.5 concentrations from July 1997 to June 1998 were 17.3, 16.4, 14.1, and 15.3 micrograms/m3 at Newark, Elizabeth, New Brunswick, and Camden, NJ, respectively. Monthly averaged 24- and 1-hr daily maximum PM2.5 concentrations suggest the existence of a high PM2.5 (May-October) and a low PM2.5 (November-April) season. PM2.5 magnitudes and temporal trends were very similar across the state during high PM2.5 events. In fact, the between-site coefficients of determination (R2) for daily PM2.5 measurements were 84-98% for June and July. Additionally, during the most pronounced PM2.5 episode, PM2.5 concentrations closely tracked the daily maximum 1-hr O3 concentrations. These observations suggest the importance of transport and atmospheric chemistry (i.e., secondary formation) to PM2.5 episodes in New Jersey. The influence of local sources was observed in diurnal concentration profiles and annual average between-site differences. Urban wintertime data illustrate that high 1-hr maximum PM2.5 concentrations can occur on low 24-hr PM2.5 days.     

Relationships between size segregated mass concentration data and ultrafine particle number concentrations in urban areas

Mass concentration data derived from samples collected with a micro-orifice uniform deposit impactor (MOUDI) in six Australian urban centers during periods of significant particle loading have been used to investigate the relationships between TSP, PM10, PM2.5, PM1 and ultrafine particles. While PM10 and PM2.5 display a clear relationship, the lack of correlation between PM10 and the coarse fraction of PM10 (PM10–PM2.5) suggests that variation in PM10 is dominated by variance in PM2.5. Given that particles of less than 2.5 μm are suspected to have adverse health effects, increasing the extent of PM2.5 monitoring may improve detection of relationships between air pollution and human health. A lack of correlation between both PM10 and PM2.5 with ultrafine mass concentrations indicates that PM10 and PM2.5 cannot be used as a surrogate for ultrafine mass concentration. Similarly, ultrafine number concentrations cannot be inferred from mass concentration information determined by the MOUDI.     

The Steubenville comprehensive air monitoring program (SCAMP): overview and statistical considerations

Average concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5) in Steubenville, OH, have decreased by more than 10 microg/m3 since the landmark Harvard Six Cities Study associated the city's elevated PM2.5 concentrations with adverse health effects in the 1980s. Given the promulgation of a new National Ambient Air Quality Standard (NAAQS) for PM2.5 in 1997, a current assessment of PM2.5 in the Steubenville region is warranted. The Steubenville Comprehensive Air Monitoring Program (SCAMP) was conducted from 2000 through 2002 to provide such an assessment. The program included both an outdoor ambient air monitoring component and an indoor and personal air sampling component. This paper, which is the first in a series of four that will present results from the outdoor portion of SCAMP, provides an overview of the outdoor ambient air monitoring program and addresses statistical issues, most notably autocorrelation, that have been overlooked by many PM2.5 data analyses. The average PM2.5 concentration measured in Steubenville during SCAMP (18.4 microg/m3) was 3.4 microg/m3 above the annual PM2.5 NAAQS. On average, sulfate and organic material accounted for approximately 31% and 25%, respectively, of the total PM2.5 mass. Local sources contributed an estimated 4.6 microg/m3 to Steubenville's mean PM2.5 concentration. PM2.5 and each of its major ionic components were significantly correlated in space across all pairs of monitoring sites in the region, suggesting the influence of meteorology and long-range transport on regional PM2.5 concentrations. Statistically significant autocorrelation was observed among time series of PM2.5 and component data collected at daily and 1-in-4-day frequencies during SCAMP. Results of spatial analyses that accounted for autocorrelation were generally consistent with findings from previous studies that did not consider autocorrelation; however, these analyses also indicated that failure to account for autocorrelation can lead to incorrect conclusions about statistical significance.     

区域大气环境中PM_(2.5)/PM_(10)空间分布研究

提出了一种利用移动监测技术研究区域大气环境中PM2.5/PM10空间分布的方法,并在2004年12月进行了宁波市全市域PM2.5/PM10空间分布的研究.数据显示:相同路径所代表的地区PM2.5和PM10具有很好的相关性,多数路径上PM2.5与PM10数据的相关系数平方在0.95以上,而不同路径上PM2.5与PM10的比值不同.文中给出了宁波市PM2.5/PM10污染的空间分布图,直观地显示出PM2.5/PM10污染的空间分布情况,突出了污染的重点点位和地区.     

Particulate matter emissions from on-road vehicles in a freeway tunnel study

Particulate matter, including coarse particles (PM_2.5–10, aerodynamic diameter of particle between 2.5 and 10 μm) and fine particles (PM_2.5, aerodynamic diameter of particle lower than 2.5 μm) and their compositions, including elemental carbon, organic carbon, and 11 water-soluble ionic species, and elements, were measured in a tunnel study. A comparison of the six-hour average of light-duty vehicle (LDV) flow of the two sampling periods showed that the peak hours over the weekend were higher than those on weekdays. However, the flow of heavy-duty vehicles (HDVs) on the weekdays was significant higher than that during the weekend in this study. EC and OC content were 49% for PM_2.5–10 and 47% for PM_2.5 in the tunnel center. EC content was higher than OC content in PM_2.5–10, but EC was about 2.3 times OC for PM_2.5. Sulfate, nitrate, ammonium were the main species for PM_2.5–10 and PM_2.5. The element contents of Na, Al, Ca, Fe and K were over 0.8 μg m^?3 in PM_2.5–10 and PM_2.5. In addition, the concentrations of S, Ba, Pb, and Zn were higher than 0.1 μg m^?3 for PM_2.5–10 and PM_2.5. The emission factors of PM_2.5–10 and PM_2.5 were 18 ± 6.5 and 39 ± 11 mg km^?1-vehicle, respectively. The emission factors of EC/OC were 3.6/2.7 mg km^?1-vehicle for PM_2.5–10 and 15/4.7 mg km^?1-vehicle for PM_2.5 Furthermore, the emission factors of water-soluble ions were 0.028(Mg²⁺)–0.81(SO₄^2?) and 0.027(NO₂^?)–0.97(SO₄^2?) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively. Elemental emission factors were 0.003(V)–1.6(Fe) and 0.001(Cd)–1.05(Na) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively.     

Particulate air pollution from combustion and construction in coastal and urban areas of China

In China, the areas that are undergoing rapid urban growth are faced with increasingly more complicated air pollution problems. Sources of air pollution need to be identified and their contributions quantified. In this study, PM2.5 (particulate matter with aerodynamic diameters < or =2.5 microm), PM2.5-10 (particulate matter with aerodynamic diameters 2.5-10 microm), organic carbon (OC), and elemental carbon (EC) concentrations were measured from April to July 2009 at four selected areas in Xiamen (the downtown area, an industrial park, a suburb, and one remote site). The contributions of carbonaceous aerosols to PM2.5 and PM2.5-10 were 20-30% and 10-20%, respectively, indicating that finer particles contained more carbonaceous aerosols. The EC concentrations in PM2.5 at the downtown, industrial, suburb, and remote sites were 2.16 +/- 0.61, 2.05 +/- 0.45, 1.69 +/- 0.54, and 0.65 +/- 0.43 microg m-3, respectively, showing a decrease from the urban and industrial hotspots to the surrounding areas. These data show that carbonaceous aerosols emitted from the combustion of fossil fuels in urban and industrial hotspots influence air quality at the regional scale. Higher levels of PM2.5 and PM2.5-10 were observed at the suburb site compared to the urban and industrial sites. Peak EC concentrations in PM2.5 were observed during the morning and evening rush hours. However, peak PM2.5 levels at the suburb site were observed around noon, which coincides with construction work hours, instead of the morning and evening rush hours when emissions from combustion dominated. These findings indicate that both fuel combustion and construction have exacerbated air pollution in coastal and urban areas in China.     

Driver exposure to particulate matter in Bangkok

The aims of this study were to determine the particulate matter with aerodynamic diameters > or = 2.5 microm (PM2.5) and 2.5-10 microm (PM10-2.5) exposure levels of drivers and to analyze the proportion of elemental carbon (EC) and organic carbon (OC) in PM2.5 in Bangkok, Thailand. Four bus routes were selected. Measurements were conducted over 10 days in August (rainy season) 2008 and 8 days in January (dry season) 2009. The mean PM2.5 exposure level of the Tuk-tuk drivers was 86 microg/m3 in August and 198 microg/m3 in January. The mean for the non-air-conditioned bus drivers was 63 microg/m3 in August and 125 microg/m3 in January. The PM2.5 and PM10-2.5 exposure levels of the drivers in January were approximately twice as high as those in August. The proportion of total carbon (TC) in PM2.5 to the PM2.5 level in August (0.97 +/- 0.28 microg/m3) was higher than in January (0.65 +/- 0.13 microg/m3). The proportion of OC in the TC of the PM2.5 in August (0.51 +/- 0.08 microg/m3) was similar to that in January (0.65 +/- 0.07 microg/m3). The TC exposure by PM25 in January (81 +/- 30 microg/m3) remained higher than in August (56-21 microg/m3). The mean level of OC in the PM2.5 was 29 +/- 13 microg/m3 in August and 50 +/- 24 microg/m3 in January. In conclusion, the PM exposure level in Bangkok drivers was higher than that in the general environment, which was already high, and it varied with the seasons and vehicle type. This study also demonstrated that the major component of the PM was carbon, likely derived from vehicles.     

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.     

The relationship between real-time and time-integrated coarse (2.5-10 micrm), intermodal (1-2.5 microm), and fine (<2.5 microm) particulate matter in the Los Angeles basin

A periodic review of the National Ambient Air Quality Standards for Particulate Matter by the U.S. Environmental Protection Agency (EPA) will assess the standards with respect to levels, particle size, and averaging times. Some members of the scientific community in the United States and Europe have suggested the use of PM1 instead of PM2.5 as the fine particle measurement standard. This proposed standard is intended to reduce the influence of coarse particle sources on PM2.5, because some evidence suggests that PM1-2.5 is dominated by coarse particulate matter (PM) sources. In this study, coarse (PM2.5-10), intermodal (PM1-2.5), and fine (PM2.5) mass concentrations at four different sites are measured with continuous and time-integrated sampling devices. The main objective is to compare variations in these three size ranges while considering the effects of location, sources, weather, wind speed, and wind direction. Results show strong correlations between PM1 and intermodal PM in receptor sites. The contribution of PM1-2.5 to PM2.5 is highest in the summer months, most likely due to enhanced long-range transport. Coarse PM is poorly correlated with intermodal PM. Continuous data suggest that PM1 is growing into PM1-2.5 via complex processes involving stagnation of the aerosol during high relative humidity conditions, followed by advection during daytime hours.     

Characterization of PM2.5 and PM10 in the South Coast Air Basin of southern California: Part 1--Spatial variations

In December 1994, the South Coast Air Quality Management District (SCAQMD) initiated a comprehensive program, the PM10 Technical Enhancement Program (PTEP), to characterize fine PM in the South Coast Air Basin (SCAB). A 1-year special particulate monitoring project was conducted from January 1995 to February 1996 as part of the PTEP. Under this enhanced monitoring, HNO3, NH3, and speciated PM10 and PM2.5 concentrations were measured at five stations (Anaheim, downtown Los Angeles, Diamond Bar, Fontana, and Rubidoux) in the SCAB and at one background station at San Nicolas Island. PM2.5 and PM10 mass and 43 individual species were analyzed for a full chemical speciation of the particle data. The PTEP data indicate that the most abundant chemical components of PM10 and PM2.5 in the SCAB are NH4+ (8-9% of PM10 and 14-17% of PM2.5), NO3- (23-26% of PM10 and 28-41% of PM2.5), SO4- (6-11% of PM10 and 9-18% of PM2.5), organic carbon (OC) (15-19% of PM10 and 18-26% of PM2.5), and elemental carbon (EC) (5-8% of PM10 and 8-13% of PM2.5). On an annual average basis, PM2.5 comprises 52-59% of the SCAB PM10. Annual average PM10 and PM2.5 concentrations showed strong spatial variations, low at coastal sites and high at inland sites. Annual average PM10 concentrations varied from 40.8 micrograms/m3 at Anaheim to 76.8 micrograms/m3 at Rubidoux, while annual average PM2.5 concentrations varied from 21.7 micrograms/m3 at Anaheim to 39.8 micrograms/m3 at Rubidoux. The chemical characterizations of the PM2.5 and PM10 concentrations, as well as their spatial variations, were examined; the important findings are summarized in this paper, and the temporal variations are discussed in the companion paper.     

Source contributions to fine particulate matter in an urban atmosphere

This paper proposes a practical method for estimating source attribution by using a three-step methodology. The main objective of this study is to explore the use of the three-step methodology for quantifying the source impacts of 24-h PM2.5 particles at an urban site in Seoul, Korea. 12-h PM2.5 samples were collected and analyzed for their elemental composition by ICP-AES/ICP-MS/AAS to generate the source composition profiles. In order to assess the daily average PM2.5 source impacts, 24-h PM2.5 and polycyclic aromatic hydrocarbons (PAH) ambient samples were simultaneously collected at the same site. The PM2.5 particle samples were then analyzed for trace elements. Ionic and carbonaceous species concentrations were measured by ICP-AES/ICP-MS/AAS, IC, and a selective thermal MnO2 oxidation method. The 12-h PM2.5 chemical data was used to estimate possible source signatures using the principal component analysis (PCA) and the absolute principal component scores method followed by the multiple linear regression analysis. The 24-h PM2.5 source categories were extracted with a combination of PM2.5 and some PAH chemical data using the PCA, and their quantitative source contributions were estimated by chemical mass balance (CMB) receptor model using the estimated source profiles and those in the literature. The results of PM2.5 source apportionment using the 12-h derived source composition profiles show that the CMB performance indices; chi2, R2, and percent of mass accounted for are 2.3%, 0.97%, and 100.7%, which are within the target range specified. According to the average PM2.5 source contribution estimate results, motor vehicle exhaust was the major contributor at the sampling site, contributing 26% on average of measured PM2.5 mass (41.8 microg m-3), followed by secondary sulfate (23%) and nitrate (16%), refuse incineration (15%), soil dust (13%), field burning (4%), oil combustion (2.7%), and marine aerosol (1.3%). It can be concluded that quantitative source attribution to PM2.5 in an urban area where source profiles have not been developed can be estimated using the proposed three-step methodology approach.     

The Steubenville Comprehensive Air Monitoring Program (SCAMP): analysis of short-term and episodic variations in PM2.5 concentrations using hourly air monitoring data

One-hour average ambient concentrations of particulate matter (PM) with an aerodynamic diameter < 2.5 microm (PM2.5) were determined in Steubenville, OH, between June 2000 and May 2002 with a tapered element oscillating microbalance (TEOM). Hourly average gaseous copollutant [carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxide (NOx), and ozone (O3)] concentrations and meteorological conditions also were measured. Although 75% of the 14,682 hourly PM2.5 concentrations measured during this period were < or = 17 microg/m3, concentrations > 65 microg/m3 were observed 76 times. On average, PM2.5 concentrations at Steubenville exhibited a diurnal pattern of higher early morning concentrations and lower afternoon concentrations, similar to the diurnal profiles of CO and NO(x). This pattern was highly variable; however, PM2.5 concentrations > 65 microg/m3 were never observed during the mid-afternoon between 1:00 p.m. and 5:00 p.m. EST. Twenty-two episodes centered on one or more of these elevated concentrations were identified. Five episodes occurred during the months June through August; the maximum PM2.5 concentration during these episodes was 76.6 microg/m3. Episodes occurring during climatologically cooler months often featured higher peak concentrations (five had maximum concentrations between 95.0 and 139.6 microg/m3), and many exhibited strong covariation between PM2.5 and CO, NO(x), or SO2. Case studies suggested that nocturnal surface-based temperature inversions were influential in driving high nighttime concentrations of these species during several cool season episodes, which typically had dramatically lower afternoon concentrations. These findings provide insights that may be useful in the development of PM2.5 reduction strategies for Steubenville, and suggest that studies assessing possible health effects of PM2.5 should carefully consider exposure issues related to the intraday timing of PM2.5 episodes, as well as the potential for toxicological interactions among PM2.5, and primary gaseous pollutants.     

Short-term temporal variation in PM2.5 mass and chemical composition during the Atlanta Supersite Experiment, 1999

Measurements in urban Atlanta of transient aerosol events in which PM2.5 mass concentrations rapidly rise and fall over a period of 3-6 hr are reported. The data are based on new measurement techniques demonstrated at the U.S. Environmental Protection Agency (EPA) Atlanta Supersite Experiment in August 1999. These independent instruments for aerosol chemical speciation of NO3-, SO4(2-), NH4+, and organic and elemental carbon (OC and EC), reconstructed the observed hourly dry PM2.5 mass to within 20% or better. Data from the experiment indicated that transient PM2.5 events were ubiquitous in Atlanta and were typically characterized by a sudden increase of EC (soot) and OC in the early morning or SO4(2-) in the late afternoon. The frequent temporal decoupling of these events provides insights into their origins, suggesting mobile sources in metro Atlanta as the main contributor to early morning PM2.5 and more regionally located point SO2 sources for afternoon PM2.5 events. The transient events may also have health implications. New data suggest that short-term PM2.5 exposures may lead to adverse health effects. Standard integrated filter-based techniques used in PM2.5 compliance monitoring networks and in most past PM2.5 epidemiologic studies collect samples over 24-hr periods and thus are unable to capture these transient events. Moreover, health-effects studies that focus on daily PM2.5 mass alone cannot evaluate the health implications of the unique and variable chemical properties of these episodes.     

Ambient fine particulate matter in China: Its negative impacts and possible countermeasures

In recent decades, China has experienced rapid economic development accompanied by increasing concentrations of ambient PM_2.5, particulate matter of less than 2.5 μm in diameter. PM_2.5 is now believed to be a carcinogen, causing higher lung cancer risks and generating losses to the economy and society. This meta-analysis evaluates the losses generated by ambient PM_2.5 in Suzhou from 2014 to 2016 and predicts losses at different concentrations. Estimations of total losses in Beijing, Shanghai, Hangzhou, Guangzhou, Dalian, and Xiamen are also presented, with a total national loss in 2015. The authors then demonstrate that lowering ambient PM_2.5 concentrations would be a realistic way for China to reduce the evaluated social losses in the short term. Possible legal measures are listed for lowering ambient PM_2.5 concentrations.

Implications: The present findings quantify the economic effects of ambient PM_2.5 due to the increased incidence rate and mortality rate of lung cancer. Lowering ambient PM_2.5 concentrations would be the most realistic way for China to reduce tghe evaluated social losses in the short term. Possible legal measures for lowering ambient PM_2.5 concentrations to reduce the total losses are identified.     

Source apportionment of PM10 and PM2.5 in five Chilean cities using factor analysis

Chile is a fast-growing country with important industrial activities near urban areas. In this study, the mass and elemental concentrations of PM10 and PM2.5 were measured in five major Chilean urban areas. Samples of particles with diameter less than 10 microm (PM10) and 2.5 microm (PM2.5) were collected in 1998 in Iquique (northern Chile), Valparaiso, Vi?a del Mar, Rancagua (central Chile), and Temuco (southern Chile). Both PM10 and PM2.5 annual mean concentrations (PM10: 56.9-77.6 microg/m3; PM2.5: 22.4-42.6 microg/m3) were significantly higher than the corresponding European Union (EU) and U.S. Environmental Protection Agency (EPA) air quality standards. Moreover, the 24-hr PM10 and PM2.5 U.S. standards were exceeded infrequently for some of the cities (Rancagua and Valparaiso). Elements ranging from Mg to Pb were detected in the aerosol samples using X-ray fluorescence (XRF). For each of the five cities, factor analysis (FA) was applied to identify and quantify the sources of PM10 and PM2.5. The agreement between calculated and measured mass and elemental concentrations was excellent in most of the cities. Both natural and anthropogenic sources were resolved for all five cities. Soil and sea were the most important contributors to coarse particles (PM10-PM2.5), whereas their contributions to PM2.5 were negligible. Emissions from Cu smelters and oil refineries (and/or diesel combustion) were identified as important sources of PM2.5, particularly in the industrial cities of Rancagua, Valparaiso, and Vi?a del Mar. Finally, motor vehicles and wood burning were significant sources of both PM2.5 and PM10 in most of the cities (wood burning was not identified in Iquique).     

Estimation of ambient PM2.5 concentrations in Maryland and verification by measured values

In 1997, Maryland had no available ambient Federal Reference Method data on particulate matter less than 2.5 microm in aerodynamic diameter (PM23), but did have annual ambient data for PM smaller than 10 microm (PM10) at 24 sites. The PM10 data were analyzed in conjunction with local annual and seasonal zip-code-level emission inventories and with speciated PM2.5 data from four nearby monitors in the IMPROVE network (located in the national parks, wildlife refuges, and wilderness areas) in an effort to estimate annual average and seasonal high PM2.5 concentrations at the 24 PM10 monitor sites operating from 1992 to 1996. All seasonal high concentrations were estimated to be below the 24-hr PM2.5 National Ambient Air Quality Standards (NAAQS) at the sites operating in Maryland between 1992 and 1996. The estimates also indicated that 12 monitor sites might exceed the 3-year annual average PM2.5 NAAQS of 15 microg/m3, but Maryland's air quality shows signs that it has been improving since 1992. The estimates also were compared with actual measurements after the PM2.5 monitor network was installed. The estimates were adequate for describing the chemical composition of the PM2.5, forecasting compliance status with the 24-hr and annual standards, and determining the spatial variations in PM2.5 across central Maryland.     

Loss of PM2.5 nitrate from filter samples in central California

Evaporative loss of particulate matter (with aerodynamic diameter < 2.5 microm, [PM2.5]) ammonium nitrate from quartz-fiber filters during aerosol sampling was evaluated from December 3, 1999, through February 3, 2001, at two urban (Fresno and Bakersfield) and three nonurban (Bethel Island, Sierra Nevada Foothills, and Angiola) sites in central California. Compared with total particulate nitrate, evaporative nitrate losses ranged from < 10% during cold months to > 80% during warm months. In agreement with theory, evaporative loss from quartz-fiber filters in nitric acid denuded samplers is controlled by the ambient nitric acid-to-particulate nitrate ratio, which is determined mainly by ambient temperature. Accurate estimation of nitrate volatilization requires a detailed thermodynamic model and comprehensive chemical measurements. For the 14-month average of PM2.5 acquired on Teflon-membrane filters, measured PM2.5 mass was 8-16% lower than actual PM2.5 mass owing to nitrate volatilization. For 24-hr samples, measured PM2.5 was as much as 32-44% lower than actual PM2.5 at three California Central Valley locations.