Effects of Instrument Precision and Spatial Variability on the Assessment of the Temporal Variation of Ambient Air Pollution in Atlanta,Georgia

Abstract

Data from the U.S. Environmental Protection Agency Air Quality System, the Southeastern Aerosol Research and Characterization database, and the Assessment of Spatial Aerosol Composition in Atlanta database for 1999 through 2002 have been used to characterize error associated with instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, GA. These data are being used in time series epidemiologic studies in which associations of acute respiratory and cardiovascular health outcomes and daily ambient air pollutant levels are assessed. Modified semivariograms are used to quantify the effects of instrument precision and spatial variability on the assessment of daily metrics of ambient gaseous pollutants (SO₂, CO, NO_x, and O₃) and fine particulate matter ([PM_2.5] PM_2.5 mass, sulfate, nitrate, ammonium, elemental carbon [EC], and organic carbon [OC]). Variation because of instrument imprecision represented 7–40% of the temporal variation in the daily pollutant measures and was largest for the PM_2.5 EC and OC. Spatial variability was greatest for primary pollutants (SO₂, CO, NO_x, and EC). Population–weighted variation in daily ambient air pollutant levels because of both instrument imprecision and spatial variability ranged from 20% of the temporal variation for O₃ to 70% of the temporal variation for SO₂ and EC. Wind rose plots, corrected for diurnal and seasonal pattern effects, are used to demonstrate the impacts of local sources on monitoring station data. The results presented are being used to quantify the impacts of instrument precision and spatial variability on the assessment of health effects of ambient air pollution in Atlanta and are relevant to the interpretation of results from time series health studies that use data from fixed monitors.     

Determination of Source Contributions to Ambient PM2.5 in Kaohsiung,Taiwan, Using a Receptor Model

ABSTRACT

Ambient particulates of PM_2.5 were sampled at three sites in Kaohsiung, Taiwan, during February and March 1999. In addition, resuspended PM_2.5 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 PM_2.5.

The mean concentration of ambient PM_2.5 was 42.6953.68 μj.g/m³ for the sampling period. The abundant species in ambient PM_2.5 in the mass fraction for three sites were OC (12.7-14.2%), SO₄ ^2- (12.8-15.1%), NO₃ ^- (8.110.3%), NH₄+ (6.7-7.5%), and EC (5.3-8.5%). Results of CMB modeling show that major pollution sources for ambient PM_2.5 are traffic exhaust (18-54%), secondary aerosols (30-41% from SO₄ ^2- and NO₃ ^-), and outdoor burning of agriculture wastes (13-17%).     

Source Identification and Trends in Concentrations of Gaseous and Fine Particulate Principal Species in Seoul,South Korea

Abstract

Ambient measurements were made using two sets of annular denuder system during the four seasons (April 2001 to February 2002) and were then compared with the results during the period of 1996–1997 to estimate the trends and seasonal variations in concentrations of gaseous and fine particulate matter (PM_2.5) principal species. Annual averages of gaseous HNO₃ and NH₃ increased by 11% and 6%, respectively, compared with those of the previous study, whereas HONO and SO₂ decreased by 11% and 136%, respectively. The PM_2.5 concentration decreased by ～17%, 35% for SO₄ ^2?, and 29% for NH₄ ⁺, whereas NO₃ ^? increased by 21%. Organic carbon (OC) and elemental carbon (EC) were 12.8 and 5.98 μg/m^-3, accounting for ～26 and 12% of PM_2.5 concentration, respectively. The species studied accounted for 84% of PM_2.5 concentration, ranging from 76% in winter to 97% in summer.

Potential source contribution function (PSCF) analysis was used to identify possible source areas affecting air pollution levels at a receptor site in Seoul. High possible source areas in concentrations of PM_2.5, NO₃ ^?, SO₄ ^2?, NH₄ ⁺, and K⁺ were coastal cities of Liaoning province (possibly emissions from oil-fired boilers on ocean liners and fishing vessels and industrial emissions), inland areas of Heibei/Shandong provinces (the highest density areas of agricultural production and population) in China, and typical port cities (Mokpo, Yeosu, and Busan) of South Korea. In the PSCF map for OC, high possible source areas were also coastal cities of Liaoning province and inland areas of Heibei/Shandong provinces in China. In contrast, high possible source areas of EC were highlighted in the south of the Yellow Sea, indicating possible emissions from oil-fired boilers on large ships between South Korea and Southeast Asia. In summary, the PSCF results may suggest that air pollution levels in Seoul are affected considerably by long-range transport from external areas, such as the coastal zone in China and other cities in South Korea, as well as Seoul itself.     

Major ionic compositions of fine particulate matter in an animal feeding operation facility and its vicinity

Animal feeding operations (AFOs) produce particulate matter (PM) and gaseous pollutants. Investigation of the chemical composition of PM_2.5 inside and in the local vicinity of AFOs can help to understand the impact of the AFO emissions on ambient secondary PM formation. This study was conducted on a commercial egg production farm in North Carolina. Samples of PM_2.5 were collected from five stations, with one located in an egg production house and the other four located in the vicinity of the farm along four wind directions. The major ions of NH₄⁺, Na⁺, K⁺, SO₄^2?, Cl^?, and NO₃^? were analyzed using ion chromatography (IC). In the house, the mostly abundant ions were SO₄^2?, Cl^?, and K⁺. At ambient stations, SO₄^2?, and NH₄⁺ were the two most abundant ions. In the house, NH₄⁺, SO₄^2?, and NO₃^? accounted for only 10% of the PM_2.5 mass; at ambient locations, NH₄⁺, SO₄^2?, and NO₃^? accounted for 36–41% of the PM_2.5 mass. In the house, NH₄⁺ had small seasonal variations indicating that gas-phase NH₃ was not the only major force driving its gas–particle partitioning. At the ambient stations, NH₄⁺ had the highest concentrations in summer. In the house, K⁺, Na⁺, and Cl^? were highly correlated with each other. In ambient locations, SO₄^2? and NH₄⁺ had a strong correlation, whereas in the house, SO₄^2? and NH₄⁺ had a very weak correlation. Ambient temperature and solar radiation were positively correlated with NH₄⁺ and SO₄^2?. This study suggests that secondary PM formation inside the animal house was not an important source of PM_2.5. In the vicinity, NH₃ emissions had greater impact on PM_2.5 formation.

ImplicationsThe chemical composition of PM_2.5 inside and in the local vicinity of AFOs showed the impact of the AFO emissions on ambient secondary PM_2.5 formation, and the fate and transport of air pollutants associated with AFOs. The results may help to manage in-house animal facility air quality, and to develop regional air quality control strategies and policies, especially in animal agriculture-concentrated areas.     

Source Identification of Atlanta Aerosol by Positive Matrix Factorization

Abstract

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 ≤2.5 µm in aerodynamic diameter) samples (PM_2.5 ), and 685 samples and 15 variables were used for coarse particle (particles between 2.5 and 10 µm in aerodynamic diameter) samples (PM_10–2.5 ). 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%), NO₃ ^?-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 NO₃ ^?-rich secondary aerosols were associated with NH₄ ⁺. The SO₄ ^2?-rich secondary aerosols also included OC. For the coarse particle data, five sources contributed to the observed mass: airborne soil (60%), NO₃ ^?-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.     

Major air pollutants in Bursa,Turkey: their levels,temporal changes,interactions, and sources

Bursa is one of the largest cities of Turkey and it hosts 17 organized industrial zones. Parallel to the increase in population, rapidly growing energy consumption, and increased numbers of transport vehicles have impacts on the air quality of the city. In this study, regularly calibrated automatic samplers were employed to get the levels of air pollution in Bursa. The concentrations of CH₄ and N-CH₄ as well as the major air pollutants including PM₁₀, PM_2.5, NO, NO₂, NO_x, SO₂, CO, and O₃, were determined for 2016 and 2017 calendar years. Their levels were 1641.62?±?718.25, 33.11?±?5.45, 42.10?±?10.09, 26.41?±?9.01, 19.47?±?16.51, 46.73?±?16.56, 66.23?±?32.265, 7.60?±?3.43, 659.397?±?192.73, and 51.92?±?25.63 µg/m³ for 2016, respectively. Except for O₃, seasonal concentrations were higher in winter and autumn for both years. O₃, CO, and SO₂ had never exceeded the limit values specified in the regulations yet PM₁₀, PM_2.5, and NO₂ had violated the limits in some days. The ratios of CO/NO_x, SO₂/NO_x, and PM_2.5/PM₁₀ were examined to characterize the emission sources. Generally, domestic and industrial emissions were dominated in the fall and winter seasons, yet traffic emissions were effective in spring and summer seasons. As a result of the correlation process between O_x and NO_x, it was concluded that the most important source of O_x concentrations in winter was NO_x and O₃ was in summer.     

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.

     

A Statistical Assessment of Saturation and Mobile Sampling Strategies to Estimate Long-Term Average Concentrations across Urban Areast

Abstract

The objectives of this study were: (1) to quantify the errors associated with saturation air quality monitoring in estimating the long-term (i.e., annual and 5 yr) mean at a given site from four 2-week measurements, once per season; and (2) to develop a sampling strategy to guide the deployment of mobile air quality facilities for characterizing intraurban gradients of air pollutants, that is, to determine how often a given location should be visited to obtain relatively accurate estimates of the mean air pollutant concentrations. Computer simulations were conducted by randomly sampling ambient monitoring data collected in six Canadian cities at a variety of settings (e.g., population-based sites, near-roadway sites). The 5-yr (1998–2002) dataset consisted of hourly measurements of nitric oxide (NO), nitrogen dioxide (NO₂), oxides of nitrogen (NO_x), sulfur dioxide (SO₂), coarse particulate matter (PM₁₀), fine particulate matter (PM_2.5)_, and CO. The strategy of randomly selecting one 2-week measurement per season to determine the annual or long-term average concentration yields estimates within 30% of the true value 95% of the time for NO₂, PM₁₀ and NO_x. Larger errors, up to 50%, are expected for NO, SO₂, PM_2.5, and CO. Combining concentrations from 85 random 1-hr visits per season provides annual and 5-yr average estimates within 30% of the true value with good confidence. Overall, the magnitude of error in the estimates was strongly correlated with the variability of the pollutant. A better estimation can be expected for pollutants known to be less temporally variable and/or over geographic areas where concentrations are less variable. By using multiple sites located in different settings, the relationships determined for estimation error versus number of measurement periods used to determine long-term average are expected to realistically portray the true distribution. Thus, the results should be a good indication of the potential errors one could expect in a variety of different cities, particularly in more northern latitudes.     

Fine particulate speciation profile and emission factor of municipal solid waste incinerator established by dilution sampling method

In this study, fine particulate matter (PM_2.5) emitted from a municipal solid waste incinerator (MSWI) was collected using dilution sampling method. Chemical compositions of the collected PM_2.5 samples, including carbon content, metal elements, and water-soluble ions, were analyzed. Traditional in-stack hot sampling was simultaneously conducted to compare the influences of dilution on PM_2.5 emissions and the characteristics of the bonded chemical species. The results, established by a dilution sampling method, show that PM_2.5 and total particulate matter (TPM) emission factors were 61.6 ± 4.52 and 66.1 ± 5.27 g ton-waste^?1, respectively. The average ratio of PM_2.5/TPM is 0.93, indicating that more than 90% of PM emission from the MSWI was fine particulate. The major chemical species in PM_2.5 included organic carbon (OC), Cl^?, NH₄⁺, elemental carbon (EC) and Si, which account for 69.7% of PM_2.5 mass. OC was from the unburned carbon in the exhaust, which adsorbed onto the particulate during the cooling process. High Cl^? emission is primarily attributable to wastes containing plastic bags made of polyvinyl chloride, salt in kitchen refuse and waste biomass, and so on. Minor species that account for 0.01–1% of PM_2.5 mass included SO₄^2-, K⁺, Na, K, NO₃^?, Al, Ca²⁺, Zn, Ca, Cu, Fe, Pb, and Mg. The mean ratio of dilution method/in-stack hot method was 0.454. The contents of water-soluble ions (Cl^?, SO₄^2-, NO₃^?) were significantly enriched in PM_2.5 via gas-to-particle conversion in the dilution process. Results indicate that in-stack hot sampling would underestimate levels of these species in PM_2.5.

Implications: PM_2.5 samples from a municipal solid waste incinerator (MSWI) were collected simultaneously by a dilution sampling technique and a traditional in-stack method. PM_2.5 emission factors and chemical speciation profiles were established. Dilution sampling provides more reliable data than in-stack hot sampling. The results can be applied to estimate the PM_2.5 emission inventories of MSWI, and the source profile can be used for contribution estimate of chemical mass balance modeling.     

Feasibility of coupling a thermal/optical carbon analyzer to a quadrupole mass spectrometer for enhanced PM2.5 speciation

A thermal/optical carbon analyzer (TOA), normally used for quantification of organic carbon (OC) and elemental carbon (EC) in PM_2.5 (fine particulate matter) speciation networks, was adapted to direct thermally evolved gases to an electron impact quadrupole mass spectrometer (QMS), creating a TOA-QMS. This approach produces spectra similar to those obtained by the Aerodyne aerosol mass spectrometer (AMS), but the ratios of the mass to charge (m/z) signals differ and must be remeasured using laboratory-generated standards. Linear relationships are found between TOA-QMS signals and ammonium (NH₄⁺), nitrate (NO₃^?), and sulfate (SO₄^2-) standards. For ambient samples, however, positive deviations are found for SO₄^2-, compensated by negative deviations for NO₃^?, at higher concentrations. This indicates the utility of mixed-compound standards for calibration or separate calibration curves for low and high ion concentrations. The sum of the QMS signals across all m/z after removal of the NH₄⁺, NO₃^?, and SO₄^2- signals was highly correlated with the carbon content of oxalic acid (C?H?O?) standards. For ambient samples, the OC derived from the TOA-QMS method was the same as the OC derived from the standard IMPROVE_A TOA method. This method has the potential to reduce complexity and costs for speciation networks, especially for highly polluted urban areas such as those in Asia and Africa.

Implications: Ammonium, nitrate, and sulfate can be quantified by the same thermal evolution analysis applied to organic and elemental carbon. This holds the potential to replace multiple parallel filter samples and separate laboratory analyses with a single filter and a single analysis to account for a large portion of the PM_2.5 mass concentration.     

Rapid Nitrate Loss from PM10 Filters

The Monterrey Metropolitan Area (MMA) has shown a high concentration of PM_2.5 in its atmosphere since 2003. The contribution of possible sources of primary PM_2.5 and its precursors is not known. In this paper we present the results of analyzing the chemical composition of sixty 24-hr samples of PM_2.5 to determine possible sources of PM_2.5 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 PM_2.5 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 PM_2.5: 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 PM_2.5 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.

Implications: The MMA has become one of the most air polluted areas in Mexico. High levels of PM_2.5 have been measured and effective actions need to be taken to reduce air pollution and the associated health risks. Several sources of primary PM_2.5 and precursors of secondary particles exist in the MMA. This study provides valuable information for the local environmental authorities to identify possible sources of primary PM_2.5 and its precursors. The effectiveness of the actions taken to improve air quality will lead to health benefits for the population, reducing their associated costs.     

Characterization of Major Chemical Components of Fine Particulate Matter in North Carolina

Abstract

This paper presents measurements of daily sampling of fine particulate matter (PM_2.5) 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 PM_2.5 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 PM_2.5 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. PM_2.5 mass concen trations display a peak in early morning, and a second peak in late afternoon. Back trajectory analysis shows that air masses with lower PM_2.5 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 PM_2.5 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.     

Ambient suspended particulate matters and related chemical species study in central Taiwan,Taichung during 1998–2001

Ambient suspended particulate (PM_2.5, PM_2.5–10, TSP) was collected from June 1998 to February 2001 in Taichung, central Taiwan. In addition, the related water-soluble ionic species (Cl⁻, NO₃⁻, SO₄²⁻, Na⁺, NH₄⁺, K⁺, Mg²⁺, Ca²⁺) and metallic species (Fe, Zn, Pb, Ni) were also analyzed in this study. The results showed that the concentrations of particulate mass are higher in the traffic site (CCRT) than the other sampling sites in this study. Also, the fine particle (PM_2.5) concentration is the dominant species of the total suspended particles in Taichung, central Taiwan. The dominant species for PM_2.5 are sulfate and ammonium at all sampling sites during the period of 1998–2001. The results of diurnal variation at THUC sampling site are also discussed in this study. Overall, acidic and secondary aerosol (Cl⁻, NO₃⁻, SO₄²⁻ and NH₄⁺) is a more serious air pollutant issue in southern and central Taiwan than at several sites around the world. Therefore, ambient suspended particulate monitoring in Taichung, central Taiwan will be continuing in our following study to provide more information for the government to formulate environmental strategy.     

PM2.5 carbon measurements in two urban areas: Seoul and Kwangju,Korea

24-h PM_2.5 carbonaceous samples were collected between 27 November and 9 December 1999 in Seoul, and between 7 and 20 June 2000 in Kwangju to investigate characteristics of carbonaceous species, and the relationship between elemental carbon (EC) and Aethalometer-based black carbon (BC) measurements. 5-min PM_2.5 BC and criteria air pollutant data were also measured using the Aethalometer and ambient air monitoring system. The PM_2.5 samples were analyzed for EC and OC using a selective thermal manganese dioxide oxidation (TMO) method. The daily average EC and OC concentrations in Seoul were higher in the winter than in the summer (Atmos. Environ. 35 (2001a) 657). It was found that difference between ambient BC levels in the two cities was not directly proportional to the population ratio (∼8) or diesel traffic ratio (∼5.9) since particulate matter or BC concentration is strongly influenced by a result of varying traffic and meteorological conditions at the site. Using the primary OC/EC ratio approach, the results suggest that most of the measured OC in Kwangju is of primary origin during the summer. In Seoul, the observed OC includes additional secondary organic aerosol during the wintertime conditions. The relationship between the 24-h TMO-EC and Aethalometer BC measurements in PM_2.5 reflected very good agreement for the two urban sites, with correlation coefficients of R²=0.99 and 0.92, and BC/EC slopes of 0.93 and 1.07, respectively. It was found that comparing TMO-EC to BC at a different location in Korea, a different scaling factor was needed.     

Air quality at Santiago,Chile: a box modeling approach II. PM2.5, coarse and PM10 particulate matter fractions

Ambient monitored data at Santiago, Chile, are analyzed using box models with the goal of assessing contributions of different economic activities to air pollution levels. The box modeling approach was applied to PM₁₀, PM_2.5 and coarse (PM₁₀–PM_2.5) particulate matter (PM) fractions; the period analyzed is 1989–1999. A linear model for each PM fraction was obtained, having as independent variables CO and SO₂ concentrations, plus a term proportional to (wind speed)⁻¹ that lumps together non-combustion emissions and secondary generation terms; wet scavenging is included as another independent variable. Model identification results show good agreement for the different parameters across monitoring stations. The washout ratios and scavenging coefficients agree with data published in the literature, being higher for the coarse PM fraction. The CO and SO₂ coefficients fitted for 1989–1995 agree with a priori estimates for the same period. Background estimates for the PM fractions are in agreement with measurement campaigns in upwind sites. Results show that transportation sources have become the dominant contributors to ambient PM levels, while stationary sources have decreased their contributions in the last years. The relative importance of mobile sources to PM_2.5 ambient concentrations has doubled in the last 10 years, whereas stationary sources have reduced their relative contributions to half the value in the early 1990s. Model estimates of regional background of PM_2.5 and PM₁₀ have decreased 50% and 22% in the last decade, respectively; coarse background has shown no significant change. The final conclusion is that there is room and need for a more intensive emission reduction strategy for Santiago, focusing on mobile sources. The approach pursued in this work is feasible for cities or regions where comprehensive, transport and chemistry models are not available yet, but estimates of air quality contributions are needed for policy purposes. The methodology requires data on ambient air quality measurements and surface meteorology.     

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.     

Association between Levels of Fine Particulate and Emergency Visits for Pneumonia and other Respiratory Illnesses among Children in Santiago,Chile

ABSTRACT

Recent evidence has implicated the fine fraction of particulate as the major contributor to the increase in mortality and morbidity related to particulate ambient levels. We therefore evaluated the impact of daily variation of ambient PM_2.5 and other pollutants on the number of daily respiratory-related emergency visits (REVs) to a large pediatric hospital of Santiago, Chile. The study was conducted from February 1995 to August 1996. Four monitoring stations from the network of Santiago provided air pollution data. The PM2.5 24-hr average ranged from 10 to 111 μg/m³ during September to April (warm months) and from 10 to 156 μg/m³ during May to August (cold months). Other contaminants (ozone (O₃), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂)) were, in general, low during the study period. The increase in REVs was significantly related to PM₁₀ and PM_2.5 ambient levels, with the relationship between PM_2.5 levels and the number of REVs the stronger. During the cold months, an increase of 45 ìg/m³ in the PM_2.5 24-hr average was related to a 2.7% increase in the number of REVs (95% CI, 1.1–4.4%) with a two-day lag, and to an increase of 6.7% (95% CI, 1.7–12.0%) in the number of visits for pneumonia with a three-day lag. SO₂ and NO₂ were also related to REVs. We conclude that urban air pollutant mixture, particularly fine particulates, adversely affect the respiratory health of children residing in Santiago.     

Roadside Particulate Air Pollution in Bangkok

Abstract

Airborne fine particles of PM_2.5-10 and PM_2.5 in Bangkok, Nonthaburi, and Ayutthaya were measured from December 22, 1998, to March 26, 1999, and from November 30, 1999, to December 2, 1999. Almost all the PM₁₀ values in the high-polluted (H) area exceeded the Thailand National Ambient Air Quality Standards (NAAQS) of 120 μg/m³. The low-polluted (L) area showed low PM₁₀ (34–74 μg/m³ in the daytime and 54–89 μg/m³ at night). PM_2.5 in the H area varied between 82 and 143 μg/m³ in the daytime and between 45 and 146 μg/m³ at night. In the L area, PM_2.5 was quite low both day and night and varied between 24 and 54 μg/m³, lower than the U.S. Environmental Protection Agency (EPA) standard (65 μg/m³). The personal exposure results showed a significantly higher proportion of PM_2.5 to PM₁₀ in the H area than in the L area (H = 0.80 ± 0.08 and L = 0.65 ± 0.04).

Roadside PM₁₀ was measured simultaneously with the Thailand Pollution Control Department (PCD) monitoring station at the same site and at the intersections where police work. The result from dual simultaneous measurements of PM₁₀ showed a good correlation (correlation coefficient: r = 0.93); however, PM levels near the roadside at the intersections were higher than the concentrations at the monitoring station. The relationship between ambient PM level and actual personal exposures was examined. Correlation coefficients between the general ambient outdoors and personal exposure levels were 0.92 for both PM_2.5 and PM₁₀.

Bangkok air quality data for 1997–2000, including 24-hr average PM₁₀, NO₂, SO₂, and O₃ from eight PCD monitoring stations, were analyzed and validated. The annual arithmetic mean PM₁₀ of the PCD data at the roadside monitoring stations for the last 3 years decreased from 130 to 73 μg/m³, whereas the corresponding levels at the general monitoring stations decreased from 90 to 49 μg/m³. The proportion of days when the level of the 24-hr average PM₁₀ exceeded the NAAQS was between 13 and 26% at roadside stations. PCD data showed PM₁₀ was well correlated with NO₂ but not with SO₂, suggesting that automobile exhaust is the main source of the particulate air pollution. The results obtained from the simultaneous measurement of PM_2.5 and PM₁₀ indicate the potential environmental health hazard of fine particles. In conclusion, Bangkok traffic police were exposed to high levels of automobile-derived particulate air pollution.     

Defining the Photochemical Contribution to Particulate Matter in Urban Areas Using Time-Series Analysis

Abstract

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 μm 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 μg/m³ (3.03%) in Chicago to 3.9 μg/m³ (7.65%) in Phoenix.