Spatial, temporal, and interspecies patterns in fine particulate matter in Texas

The Big Bend Regional Aerosol and Visibility Observational (BRAVO) field study was conducted from July to October 1999 and was followed by several years of modeling and data analyses to examine the causes of haze at Big Bend National Park TX (BBNP). During BRAVO, daily speciated fine (diameter <2.5 microm) particulate concentrations were measured at 37 sites throughout Texas. At the primary receptor site, K-Bar Ranch, there were many additional measurements including a "high-sensitivity" version of the 24-hr fine particulate elemental data. The spatial, temporal, and interspecies patterns in these data are examined here to qualitatively investigate source regions and source types influencing the fine particulate concentrations in Texas with an emphasis on sources of sulfates, the largest contributor to fine mass and light extinction. Peak values of particulate sulfur (S) varied spatially and seasonally. Maximum S was in Northeast Texas during the summer, whereas peak S at BBNP was in the fall. Sulfate acidity at BBNP also varied by month. Sources of Se were evident in Northeast Texas and from the Carbón I and II plants. High S episodes at BBNP during BRAVO had several different trace element characteristics. Carbon concentrations at BBNP during BRAVO were probably mostly urban-related, with arrival from the Houston area likely. The Houston artificial tracer released during the second half of BRAVO was highly correlated with some carbon fractions. There was evidence of the influence of African dust at sites throughout Texas during the summer. Patterns in several trace elements were also examined. Vanadium was associated with air masses from Mexico. Lead concentrations in southern Texas have dropped dramatically over the past several years.     

Spatial variability of different fractions of particulate matter within an urban environment and between urban and rural sites

The spatial variability of different fractions of particulate matter (PM) was investigated in the city of Basel, Switzerland, based on measurements performed throughout 1997 with a mobile monitoring station at six sites and permanently recorded measurements from a fixed site. Additionally, PM10 measurements from the following year, which were concurrently recorded at two urban and two rural sites, were compared. Generally, the spatial variability of PM4, PM10, and total suspended particulates (TSP) within this Swiss urban environment (area = 36 km2) was rather limited. With the exception of one site in a street canyon next to a traffic light, traffic density had only a weak tendency to increase the levels of PM. Mean PM10 concentration at six sites with different traffic densities was in the range of less than +/- 10% of the mean urban PM10 level. However, comparing the mean PM levels on workdays to that on weekends indicated that the impact of human activities, including traffic, on ambient PM levels may be considerable. Differences in the daily PM10 concentrations between urban and more elevated rural sites were strongly influenced by the stability of the atmosphere. In summer, when no persistent surface inversions exist, differences between urban and rural sites were rather small. It can therefore be concluded that spatial variability of annual mean PM concentration between urban and rural sites in the Basel area may more likely be caused by varying altitude than by distance to the city center.     

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.     

Sources of fine urban particulate matter in Detroit, MI

Data from the speciation trends network (STN) was used to evaluate the amount and temporal patterns of particulate matter originating from local industrial sources and long-range transport at two sites in Detroit, MI: Allen Park, MI, southwest of both Detroit and the areas of heavy industrial activity; Dearborn, MI, located on the south side of Detroit near the most heavily industrialized region. Using positive matrix factorization (PMF) and comparing source contributions at Allen Park to those in Dearborn, contributions made by local industrial sources (power plants, coke refineries, iron smelting, waste incineration), local area sources (automobile and diesel truck) and long range sources of PM(2.5) can be distinguished in greater Detroit. Overall, the mean mass concentration measured at Dearborn was 19% higher than that measured at Allen Park. The mass at Allen Park was apportioned as: secondary sulfate 31%, secondary nitrate 28%, soil 8%, mixed aged sea and road salts 4%, gasoline 15%, diesel 4%, and biomass burning 3%. At Dearborn the mass was apportioned as: secondary sulfate 25%, secondary nitrate 20%, soil 12%, mixed aged sea and road salts 4%, gasoline 20%, diesel 8%, iron and steel, 5%, and mixed industrial 7%. The impact of the iron and steel, soil, and mixed aged sea and road salt was much higher at the Dearborn site than at the Allen Park site, suggesting that close proximity to a local industrial complex has a direct negative impact on local air quality.     

Transport of atmospheric fine particulate matter: part 2--findings from recent field programs on the intraurban variability in fine particulate matter

Air quality field data, collected as part of the fine particulate matter Supersites Program and other field measurements programs, have been used to assess the degree of intraurban variability for various physical and chemical properties of ambient fine particulate matter. Spatial patterns vary from nearly homogeneous to quite heterogeneous, depending on the city, parameter of interest, and the approach or method used to define spatial variability. Secondary formation, which is often regional in nature, drives fine particulate matter mass and the relevant chemical components toward high intraurban spatial homogeneity. Those particulate matter components that are dominated by primary emissions within the urban area, such as black carbon and several trace elements, tend to exhibit greater spatial heterogeneity. A variety of study designs and data analysis approaches have been used to characterize intraurban variability. High temporal correlation does not imply spatial homogeneity. For example, there can be high temporal correlation but with spatial heterogeneity manifested as smooth spatial gradients, often emanating from areas of high emissions such as the urban core or industrial zones.     

Simulating the fine and coarse inorganic particulate matter concentrations in a polluted megacity

A three dimensional chemical transport model (PMCAMx) is applied to the Mexico City Metropolitan Area (MCMA) in order to simulate the chemical composition and mass of the major PM₁ (fine) and PM_1–10 (coarse) inorganic components and determine the effect of mineral dust on their formation. The aerosol thermodynamic model ISORROPIA-II is used to explicitly simulate the effect of Ca, Mg, and K from dust on semi-volatile partitioning and water uptake. The hybrid approach is applied to simulate the inorganic components, assuming that the smallest particles are in thermodynamic equilibrium, while describing the mass transfer to and from the larger ones. The official MCMA 2004 emissions inventory with improved dust and NaCl emissions is used. The comparison between the model predictions and measurements during a week of April of 2003 at Centro Nacional de Investigacion y Capacitacion Ambiental (CENICA) “Supersite” shows that the model reproduces reasonably well the fine mode composition and its diurnal variation. Sulfate predicted levels are relatively uniform in the area (approximately 3 μg m^?3), while ammonium nitrate peaks in Mexico City (approximately 7 μg m^?3) and its concentration rapidly decreases due to dilution and evaporation away from the urban area. In areas of high dust concentrations, the associated alkalinity is predicted to increase the concentration of nitrate, chloride and ammonium in the coarse mode by up to 2 μg m^?3 (a factor of 10), 0.4 μg m^?3, and 0.6 μg m^?3 (75%), respectively. The predicted ammonium nitrate levels inside Mexico City for this period are sensitive to the physical state (solid versus liquid) of the particles during periods with RH less than 50%.     

Spatial and temporal variability of outdoor coarse particulate matter mass concentrations measured with a new coarse particle sampler during the Detroit Exposure and Aerosol Research Study

The Detroit Exposure and Aerosol Research Study (DEARS) provided data to compare outdoor residential coarse particulate matter (PM_10–2.5) concentrations in six different areas of Detroit with data from a central monitoring site. Daily and seasonal influences on the spatial distribution of PM_10–2.5 during Summer 2006 and Winter 2007 were investigated using data collected with the newly developed coarse particle exposure monitor (CPEM). These data allowed the representativeness of the community monitoring site to be assessed for the greater Detroit metro area. Multiple CPEMs collocated with a dichotomous sampler determined the precision and accuracy of the CPEM PM_10–2.5 and PM_2.5 data.CPEM PM_2.5 concentrations agreed well with the dichotomous sampler data. The slope was 0.97 and the R² was 0.91. CPEM concentrations had an average 23% negative bias and R² of 0.81. The directional nature of the CPEM sampling efficiency due to bluff body effects probably caused the negative CPEM concentration bias.PM_10–2.5 was observed to vary spatially and temporally across Detroit, reflecting the seasonal impact of local sources. Summer PM_10–2.5 was 5 μg m^?3 higher in the two industrial areas near downtown than the average concentrations in other areas of Detroit. An area impacted by vehicular traffic had concentrations 8 μg m^?3 higher than the average concentrations in other parts of Detroit in the winter due to the suspected suspension of road salt. PM_10–2.5 Pearson Correlation Coefficients between monitoring locations varied from 0.03 to 0.76. All summer PM_10–2.5 correlations were greater than 0.28 and statistically significant (p-value < 0.05). Winter PM_10–2.5 correlations greater than 0.33 were statistically significant (p-value < 0.05). The PM_10–2.5 correlations found to be insignificant were associated with the area impacted by mobile sources during the winter. The suspected suspension of road salt from the Southfield Freeway, combined with a very stable atmosphere, caused concentrations to be greater in this area compared to other areas of Detroit. These findings indicated that PM_10–2.5, although correlated in some instances, varies sufficiently across a complex urban airshed that that a central monitoring site may not adequately represent the population's exposure to PM_10–2.5.     

Effects of wind direction on coarse and fine particulate matter concentrations in southeast Kansas

Field data for coarse particulate matter ([PM] PM10) and fine particulate matter (PM2.5) were collected at selected sites in Southeast Kansas from March 1999 to October 2000, using portable MiniVol particulate samplers. The purpose was to assess the influence on air quality of four industrial facilities that burn hazardous waste in the area located in the communities of Chanute, Independence, Fredonia, and Coffeyville. Both spatial and temporal variation were observed in the data. Variation because of sampling site was found to be statistically significant for PM10 but not for PM2.5. PM10 concentrations were typically slightly higher at sites located within the four study communities than at background sites. Sampling sites were located north and south of the four targeted sources to provide upwind and downwind monitoring pairs. No statistically significant differences were found between upwind and downwind samples for either PM10 or PM2.5, indicating that the targeted sources did not contribute significantly to PM concentrations. Wind direction can frequently contribute to temporal variation in air pollutant concentrations and was investigated in this study. Sampling days were divided into four classifications: predominantly south winds, predominantly north winds, calm/variable winds, and winds from other directions. The effect of wind direction was found to be statistically significant for both PM10 and PM2.5. For both size ranges, PM concentrations were typically highest on days with predominantly south winds; days with calm/variable winds generally produced higher concentrations than did those with predominantly north winds or those with winds from "other" directions. The significant effect of wind direction suggests that regional sources may exert a large influence on PM concentrations in the area.     

Fine particulate matter and carbon monoxide exposure concentrations in urban street transport microenvironments

Personal exposure studies are crucial alongside microenvironment and ambient studies in order to get a better understanding of the health risks posed by fine particulate matter and carbon monoxide in the urban transport microenvironment and for making informed decisions to manage and reduce the health risks. Studies specifically assessing the PM_2.5, ultrafine particle count and carbon monoxide personal exposure concentrations of adults in an urban transport microenvironment have steadily increased in number over the last decade. However, no recent collective summary is available, particularly one which also considers ultrafine particles; therefore, we present a review of the personal exposure concentration studies for the above named pollutants on different modes of surface transportation (walking, cycling, bus, car and taxi) in the urban transport microenvironment. Comparisons between personal exposure measurements and concentrations recorded at fixed monitoring sites are considered in addition to the factors influencing personal exposure in the transport microenvironment.In general, the exposure studies examined revealed pedestrians and cyclists to experience lower fine particulate matter and CO exposure concentrations in comparison to those inside vehicles—the vehicle shell provided no protection to the passengers. Proximity to the pollutant sources had a significant impact on exposure concentration levels experienced, consequently individuals should be encouraged to use back street routes. Fixed monitoring stations were found to be relatively poor predictors of CO and PM_2.5 exposure concentration levels experienced by individuals in the urban transport microenvironment. Although the mode of transport, traffic and meteorology parameters were commonly identified as significant factors influencing exposure concentrations to the different pollutants under examination, a large amount of the exposure concentration variation in the exposure studies remained unexplained.     

Spatial and temporal variations in traffic-related particulate matter at New York City high schools

Relatively little is known about exposures to traffic-related particulate matter at schools located in dense urban areas. The purpose of this study was to examine the influences of diesel traffic proximity and intensity on ambient concentrations of fine particulate matter (PM_2.5) and black carbon (BC), an indicator of diesel exhaust particles, at New York City (NYC) high schools. Outdoor PM_2.5 and BC were monitored continuously for 4–6 weeks at each of 3 NYC schools and 1 suburban school located 40 km upwind of the city. Traffic count data were obtained using an automated traffic counter or video camera. BC concentrations were 2–3 fold higher at urban schools compared with the suburban school, and among the 3 urban schools, BC concentrations were higher at schools located adjacent to highways. PM_2.5 concentrations were significantly higher at urban schools than at the suburban school, but concentrations did not vary significantly among urban schools. Both hourly average counts of trucks and buses and meteorological factors such as wind direction, wind speed, and humidity were significantly associated with hourly average ambient BC and PM_2.5 concentrations in multivariate regression models. An increase of 443 trucks/buses per hour was associated with a 0.62 μg/m³ increase in hourly average BC at an NYC school located adjacent to a major interstate highway. Car traffic counts were not associated with BC. The results suggest that local diesel vehicle traffic may be important sources of airborne fine particles in dense urban areas and consequently may contribute to local variations in PM_2.5 concentrations. In urban areas with higher levels of diesel traffic, local, neighborhood-scale monitoring of pollutants such as BC, which compared to PM_2.5, is a more specific indicator of diesel exhaust particles, may more accurately represent population exposures.     

Vapor-phase and fine particulate matter concentrations of polycyclic aromatic hydrocarbons measured during the winter months in a northern Rocky Mountain urban airshed

A fine particulate matter (PM2.5) sampling program was conducted in Missoula, MT, to investigate both the particle and vapor phases of PM2.5-associated polycyclic aromatic hydrocarbons (PAHs) found in a northern Rocky Mountain urban airshed. Twenty-four-hour samples were collected during the cold winter months of January through April 2002, when many of the more volatile organic components of PM2.5 were expected to be found in the condensed particle form. To meet analytical detection limits, each of the 12 individual sample days were aggregated into four total filter and polyurethane foam (PUF) samples, respectively, with each aggregate containing 3 sample days. Quartz filter (particle-phase PAHs) and PUF (vapor-phase PAHs) aggregates were analyzed separately for 18 individual PAHs and phenolics by gas chromatography/mass spectrometry. Results showed that 87% of the PM2.5-associated phenolics and PAHs measured in this study were found in the vapor phase. PM2.5-associated gas/particle partition coefficients (Kp,2.5) ranged from 0 for the lighter phenolics and PAHs to approximately 0.1 for some of the heavier PAHs, such as fluoranthene and pyrene. Calculating Kp,2.5 for the heaviest measured PAHs was not feasible because of low or undetectable concentrations in the vapor phases of these compounds. Phenolics and two-ringed and three-ringed PAHs were found almost exclusively in the vapor phase. Four-ringed PAHs were distributed between the particle and vapor phases, with more mass measured in the vapor phase. Very little five-ringed and higher PAHs were measured from either the filter or PUF sampling medium. These results provide information on both the concentrations and different phases of PM2.5-associated PAHs measured during the winter months in a northern Rocky Mountain urban airshed, when concentrations of PM2.5 are generally at their highest compared with the rest of the year.     

Proinflammatory effect of fine and ultrafine particulate matter using size-resolved urban aerosols from Paris

Epidemiological and experimental studies have underlined that exposure to particulate matter (PM) leads mainly to airway inflammation, but the roles of particle size and chemical composition associated to such adverse health outcomes need to be better investigated. This study was performed to validate novel strategies of particle sampling, recovery and cell exposure in order to evaluate the pro-inflammatory potential of fine and ultrafine particles from a fractionated aerosol. Samplings of Paris background aerosols using 13-stage low pressure impactors (0.03-10 microm) gave bimodal mass distributions with an accumulation mode centered on a median diameter of 0.42 microm and a coarse one on 3.25 microm. PM 1 accounted for 70% and PM 0.1 for 12% of PM 10. The latter mainly comprised carbon-chained aggregates. The development of an efficient and reproducible method to recover fine (PM 1-0.1) and ultrafine (PM 0.1-0.03) particulate matter has permitted experimental comparison of the impact of such particles on human bronchial epithelial cells (HBECs). In this study we have compared the relative effects of fine and ultrafine particles at non-cytotoxic concentrations over 24h on the production of the pro-inflammatory cytokine GM-CSF by HBECs. Combining two cell exposure strategies to the size-fraction particles according to either their proportion (isovolume exposure) or their quantity in the aerosol (isomass exposure), we showed that both ultrafine and fine particles induced a concentration-dependent GM-CSF release by HBECs which is significant from 1 microg cm(-2). In conclusion, short duration samplings using 13-stage impactors enable to obtain size-resolved PM in sufficient quantities to carry out toxicological investigations. These findings are promising in view to conduct a more intensive study joining chemical and toxicological assays.     

Respirable particulate matter at an urban and nearby industrial location: concentrations and variability and synoptic weather conditions during high pollution episodes

Continuous data of the concentration measurements of respirable suspended particulates (PM10, particles with aerodynamic diameter smaller than or equal to 10 pm) were analyzed. These measurements were carried out at an urban and nearby industrial location in northern Greece for the 5-year period 1996-2000. The time series concentration trend was examined, the seasonal and diurnal variations were identified, and the lognormality of the daily mean concentration data sets was tested. Over the 5-year data-gathering period, the days on which the U.S. Environmental Protection Agency (EPA) 24-hr PM10 standard was exceeded (episode days) were identified and their relation to prevailing synoptic-scale meteorological conditions was studied. The analysis led to useful information concerning the air quality levels, the contribution of the main pollution sources in this area, as well as some of the mechanisms that influence the PM10 concentrations. It also was proved that the measured PM10 concentrations are a result of a combination of processes including local anthropogenic sources, mesoscale transport, and resuspension. A complex system of sources and meteorological conditions modulate the heavy particulate pollution in the area of interest.     

Assessment of personal integrated exposure to fine particulate matter of urban residents in Hong Kong

Metropolitan residents are concerned about their exposure to airborne pollutants. But establishing these exposures is challenging. A compact personal exposure kit (PEK) was developed to evaluate personal integrated exposure (PIE) from time-resolved data to particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5) in five microenvironments, including office, home, commuting, other indoor activities (other than home and office), and outdoor activities experienced both on weekdays and weekends. The study was conducted in Hong Kong. The PEK measured PM_2.5, reported location and several other factors, stored collected data, as well as reported the data back to the investigators using global system for mobile communication (GSM) telemetry. Generally, PM_2.5 concentrations in office microenvironment were found to be the smallest (13.0 μg/m³), whereas the largest PM_2.5 concentration microenvironments were experienced during outdoor activities (54.4 μg/m³). Participants spent more than 85% of their time indoors, including in offices, homes, and other public indoor venues. On average, 42% and 81% of the time were spent in homes, which contributed 52% and 79% of PIE (during weekdays and weekends, respectively), suggesting that improvement of air quality in homes may reduce overall exposures and indicating the need for actions to mitigate possible public health burdens in Hong Kong. This study also found that various indoor/outdoor microenvironments experienced by urban office workers cannot be accurately represented by general urban air quality data reported from the regulatory monitoring. Such personalized air quality information, especially while in transit or in offices and homes, may provide improved information on population exposures to air pollution.

Implications: A newly developed personal exposure kit (PEK) was used to monitor PM_2.5 exposure of metropolitan citizens in their daily life. Different microenvironments and time durations caused various personal integrated exposure (PIE). The stationary monitoring method for PIE was also compared and evaluated with PEK. Positive protection actions can be taken after understanding the major contribution to PM_2.5 exposure.     

Determination of levoglucosan in atmospheric fine particulate matter

A microanalytical method suitable for the quantitative determination of the sugar anhydride levoglucosan in low-volume samples of atmospheric fine particulate matter (PM) has been developed and validated. The method incorporates two sugar anhydrides as quality control standards. The recovery standard sedoheptulosan (2,7-anhydro-beta-D-altro-heptulopyranose) in 20 microL solvent is added onto samples of the atmospheric fine PM and aged for 1 hr before ultrasonic extraction with ethylacetate/ triethylamine. The extract is reduced in volume, an internal standard is added (1,5-anhydro-D-mannitol), and a portion of the extract is derivatized with 10% by volume N-trimethylsilylimidazole. The derivatized extract is analyzed by gas chromatography/mass spectrometry (GC/MS). The recovery of levoglucosan using this procedure was 69 +/- 6% from five filters amended with 2 microg levoglucosan, and the reproducibility of the assay is 9%. The limit of detection is approximately 0.1 microg/mL, which is equivalent to approximately 3.5 ng/m3 for a 10 L/min sampler or approximately 8.7 ng/m3 for a 4 L/min personal sampler (assuming 24-hr integrated samples). We demonstrated that levoglucosan concentrations in collocated samples (expressed as ng/m3) were identical irrespective of whether samples were collected by PM with aerodynamic diameter < or = 2.5 microm or PM with aerodynamic diameter < or = 10 microm impactors. It was also demonstrated that X-ray fluorescence analysis of samples of atmospheric PM, before levoglucosan determinations, did not alter the levels of levoglucosan.     

Spatial characteristics of fine particulate matter: identifying representative monitoring locations in Seattle, Washington

This study investigates how PM2.5 varies spatially and how these spatial characteristics can be used to identify potential monitoring sites that are most representative of the overall ambient exposures to PM2.5 among susceptible populations in the Seattle, WA, area. Data collected at outdoor sites at the homes of participants of a large exposure assessment study were used in this study. Harvard impactors (HIs) were used at 40 outdoor sites throughout the Seattle metropolitan area. Up to six sites at a time were monitored for 10 consecutive 24-hr average periods. A fixed-effect analysis of variance (ANOVA) model that included date and location effects was used to analyze the spatial variability of outdoor PM2.5 concentrations. Both date and location effects were shown to be highly significant, explaining 92% of the variability in outdoor PM2.5 measurements. The day-to-day variability was 10 times higher than the spatial variability between sites. The site mean square was more than twice the error mean square, showing that differences between sites, while modest, are potentially an important contribution to measurement error. Variances of the model residuals and site effects were examined against spatial characteristics of the monitoring sites. The spatial characteristics included elevation, distance from arterials, and distance from major PM2.5 point sources. Results showed that the most representative PM2.5 sites were located at elevations of 80-120 m above sea level, and at distances of 100-300 m from the nearest arterial road. Location relative to industrial PM2.5 sources is not a significant predictor of residential outdoor PM2.5 measurements. Additionally, for sites to be representative of the average population exposures to PM2.5 among those highly susceptible to the health effects of PM2.5, areas of high elderly population density were considered. These representative spatial characteristics were used as multiple, overlapping criteria in a Geographic Information System (GIS) analysis to determine where the most representative sites are located.     

A land use regression for predicting fine particulate matter concentrations in the New York City region

We developed regression equations to predict fine particulate matter (PM_2.5) at air monitoring locations in the New York City region using data on nearby traffic and land use patterns. Three-year averages (1999–2001) of PM_2.5 at US Environmental Protection Agency (EPA) monitors in the 28 counties including and surrounding New York City were calculated using daily data from the EPA's Air Quality Subsystem. As the secondary contribution to PM_2.5 concentrations is lowest in the winter, we also calculated and modeled average winter 2000 PM_2.5 to conduct a preliminary evaluation of model sensitivity to source contribution. Candidate predictor variables included traffic, land use, census and emissions data from local, state and national sources and were tabulated for a series of circular buffer regions at varying distances around the monitors using a geographic information system. In total, more than 25 variables at 5 different buffer distances were considered for inclusion in the model. Before evaluating the variables we removed several samples from the modeling for validation. For comparison and validation purposes we computed both a model using data for the full 28-county region as well as a more urbanized 9-county region. We found that traffic within a buffer of 300 or 500 m explains the greatest proportion of variance (37–44%) in all 3 models. Measures of urbanization, specifically population density, explain a significant amount of the residual variation (7–18%) after including a traffic variable. Finally, a measure of industrial land use further improves the 28-county and 9-county models based on the 3-yr annual averages, explaining an additional 4% and 11% of the variation, respectively, while vegetative land use improves the winter model explaining an additional 6%. The final models predicted well at validation locations. In total, the final land use regression models explain between 61% and 64% of the variation in PM_2.5.     

Personal exposure to fine particulate matter concentrations in central business district of a tropical coastal city

In the present study, personal exposure to fine particulate matter (particulate matter with an aerodynamic diameter <2.5 μm [PM_2.5]) concentrations in an urban hotspot (central business district [CBD]) was investigated. The PM monitoring campaigns were carried out at an urban hotspot from June to October 2015. The personal exposure monitoring was performed during three different time periods, i.e., morning (8 a.m.?9 a.m.), afternoon (12.30 p.m.–1.30 p.m.), and evening (4 p.m.–5 p.m.), to cover both the peak and lean hour activities of the CBD. The median PM_2.5 concentrations were 38.1, 34.9, and 40.4 µg/m³ during the morning, afternoon, and evening hours on the weekends. During weekdays, the median PM_2.5 concentrations were 59.5, 29.6, and 36.6 µg/m³ in the morning, afternoon, and evening hours, respectively. It was observed that the combined effect of traffic emissions, complex land use, and micrometeorological conditions created localized air pollution hotspots. Furthermore, the total PM_2.5 lung dose levels for an exposure duration of 1 hr were 8.7 ± 5.7 and 12.3 ± 5.2 µg at CBD during weekends and weekdays, respectively, as compared with 2.5 ± 0.8 µg at the urban background (UB). This study emphasizes the need for mobile measurement for short-term personal exposure assessment complementing the fixed air quality monitoring.

Implications: Personal exposure monitoring at an urban hotspot indicated space and time variation in PM concentrations that is not captured by the fixed air quality monitoring networks. The short-term exposure to higher concentrations can have a significant impact on health that need to be considered for the health risk–based air quality management. The study emphasizes the need of hotspot-based monitoring complementing the already existing fixed air quality monitoring in urban areas. The personal exposure patterns at hotspots can provide additional insight into sustainable urban planning.