Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial,California, USA

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R² for converted hourly averaged Dylos mass measurements versus a PM_2.5 BAM was 0.79 and that versus a PM₁₀ BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM_2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R² = 0.35–0.81).

Implications: The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.     

Applications of GPS-tracked personal and fixed-location PM2.5 continuous exposure monitoring

Continued development of personal air pollution monitors is rapidly improving government and research capabilities for data collection. In this study, we tested the feasibility of using GPS-enabled personal exposure monitors to collect personal exposure readings and short-term daily PM_2.5 measures at 15 fixed locations throughout a community. The goals were to determine the accuracy of fixed-location monitoring for approximating individual exposures compared to a centralized outdoor air pollution monitor, and to test the utility of two different personal monitors, the RTI MicroPEM V3.2 and TSI SidePak AM510. For personal samples, 24-hr mean PM_2.5 concentrations were 6.93 μg/m³ (stderr = 0.15) and 8.47 μg/m³ (stderr = 0.10) for the MicroPEM and SidePak, respectively. Based on time–activity patterns from participant journals, exposures were highest while participants were outdoors (MicroPEM = 7.61 µg/m³, stderr = 1.08, SidePak = 11.85 µg/m³, stderr = 0.83) or in restaurants (MicroPEM = 7.48 µg/m³, stderr = 0.39, SidePak = 24.93 µg/m³, stderr = 0.82), and lowest when participants were exercising indoors (MicroPEM = 4.78 µg/m³, stderr = 0.23, SidePak = 5.63 µg/m³, stderr = 0.08). Mean PM_2.5 at the 15 fixed locations, as measured by the SidePak, ranged from 4.71 µg/m³ (stderr = 0.23) to 12.38 µg/m³ (stderr = 0.45). By comparison, mean 24-h PM_2.5 measured at the centralized outdoor monitor ranged from 2.7 to 6.7 µg/m³ during the study period. The range of average PM_2.5 exposure levels estimated for each participant using the interpolated fixed-location data was 2.83 to 19.26 µg/m³ (mean = 8.3, stderr = 1.4). These estimated levels were compared with average exposure from personal samples. The fixed-location monitoring strategy was useful in identifying high air pollution microclimates throughout the county. For 7 of 10 subjects, the fixed-location monitoring strategy more closely approximated individuals’ 24-hr breathing zone exposures than did the centralized outdoor monitor. Highlights are: Individual PM_2.5 exposure levels vary extensively by activity, location and time of day; fixed-location sampling more closely approximated individual exposures than a centralized outdoor monitor; and small, personal exposure monitors provide added utility for individuals, researchers, and public health professionals seeking to more accurately identify air pollution microclimates.

Implications: Personal air pollution monitoring technology is advancing rapidly. Currently, personal monitors are primarily used in research settings, but could they also support government networks of centralized outdoor monitors? In this study, we found differences in performance and practicality for two personal monitors in different monitoring scenarios. We also found that personal monitors used to collect outdoor area samples were effective at finding pollution microclimates, and more closely approximated actual individual exposure than a central monitor. Though more research is needed, there is strong potential that personal exposure monitors can improve existing monitoring networks.     

Particulate matter,nitrogen oxides,ozone, and select volatile organic compounds during a winter sampling period in Logan,Utah, USA

Particulate matter mass (PM), trace gaseous pollutants, and select volatile organic compounds (VOCs) with meteorological variables were measured in Logan, Utah (Cache Valley), for >4 weeks during winter 2017 as part of the Utah Winter Fine Particle Study (UWFPS). Higher PM levels for short time periods and lower ozone (O₃) levels were present due to meteorological and mountain valley conditions. Nitrogenous pollutants were relatively strongly correlated with PM variables. Diurnal cycles of NO_x, O₃, and fine PM(PM 2.5) (aerodynamic diameter <2.5 μm [PM_2.5]) suggested formation from NO_x. O₃ levels increased from early morning into midafternoon, and NO_x and PM_2.5 increased throughout the morning, followed by sharp decreases. Toluene/benzene and xylenes/benzene ratios and VOC correlations with nitrogenous and PM species were indicative of local traffic sources. Wind sector comparisons suggested that pollutant levels were lower when winds were from nearby mountains to the east versus winds from northerly or southerly origins.

Implications: The Cache Valley in Idaho and Utah has been designated a PM_2.5 nonattainment area that has been attributed to air pollution buildup during winter stagnation events. To inform state implementation plans for PM_2.5 in Cache Valley and other PM_2.5 nonattainment areas in Utah, a state and multiagency federal research effort known as the UWFPS was conducted in winter 2017. As part of the UWFPS, the U.S. Environmental Protection Agency (EPA) measured ground-based PM species and their precursors, VOCs, and meteorology in Logan, Utah. Results reported here from the EPA study in Logan provide additional understanding of wintertime air pollution conditions and possible sources of PM and gaseous pollutants as well as being useful for future PM control strategies in this area.     

Ambient Ozone Concentration Patterns among Eastern U.S. Urban Areas Using Factor Analysis

Data on dally maximum ozone concentrations measured at ambient air monitoring stations operated by state and local air pollution control agencies in the Eastern United States were analyzed using principal factor analysis. Four orthogonal factors representing O₃ formation potentials were derived using the statistical package SPSS; these factors accounted for over two-thirds of the variations in 1978 summer O₃ levels at 21 urban-oriented stations. The analysis confirmed that O₃ variations are similar among stations within defined geographical areas; this confirmation supports the widely held theory that ambient O₃ formations are reglonwlde. The analysis suggested that trends analysis for determining general progress in improving O₃ air quality should be based on aggregate statistics from clusters of monitors rather than from a single monitoring station within areas associated with the derived factors.     

A Re-Examination of Ambient Air Ozone Monitor Interferences

Abstract

Attaining the National Ambient Air Quality Standard (NAAQS) for ozone (O₃) could cost billions of dollars nationwide. Attainment of the NAAQS is judged on O₃ measurements made by the Federal Reference Method (FRM), ethylene chemiluminescence, or a Federal Equivalent Method (FEM), predominantly ultraviolet (UV) absorption. Starting in the 1980s, FRM monitors were replaced by FEMs so that today virtually all monitoring in the United States uses the UV methodology. This report summarizes a laboratory and collocated ambient air monitoring study of interferences in O₃ monitors. Potential interferences examined in the laboratory included water vapor, mercury, o-nitrophenol, naphthalene, p-tolualdehyde, and mixed reaction products from smog chamber simulations of urban atmospheric photochemistry. UV absorption O₃ monitors modi?ed for humidity equilibration were also collocated with UV FEM O₃ monitors at six sites in Houston, TX, during the 2007 summer O₃ season. The results suggest that humidity and interfering species can positively bias (overestimate) O₃ measured by FEM monitors used to determine compliance with the O₃ standards. The results also suggest that humidity equilibration can mitigate this bias.     

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.     

Microscale air quality impacts of distributed power generation facilities

The electric system is experiencing rapid growth in the adoption of a mix of distributed renewable and fossil fuel sources, along with increasing amounts of off-grid generation. New operational regimes may have unforeseen consequences for air quality. A three-dimensional microscale chemical transport model (CTM) driven by an urban wind model was used to assess gaseous air pollutant and particulate matter (PM) impacts within ~10 km of fossil-fueled distributed power generation (DG) facilities during the early afternoon of a typical summer day in Houston, TX. Three types of DG scenarios were considered in the presence of motor vehicle emissions and a realistic urban canopy: (1) a 25-MW natural gas turbine operating at steady state in either simple cycle or combined heating and power (CHP) mode; (2) a 25-MW simple cycle gas turbine undergoing a cold startup with either moderate or enhanced formaldehyde emissions; and (3) a data center generating 10 MW of emergency power with either diesel or natural gas-fired backup generators (BUGs) without pollution controls. Simulations of criteria pollutants (NO₂, CO, O₃, PM) and the toxic pollutant, formaldehyde (HCHO), were conducted assuming a 2-hr operational time period. In all cases, NO_x titration dominated ozone production near the source. The turbine scenarios did not result in ambient concentration enhancements significantly exceeding 1 ppbv for gaseous pollutants or over 1 µg/m³ for PM after 2 hr of emission, assuming realistic plume rise. In the case of the datacenter with diesel BUGs, ambient NO₂ concentrations were enhanced by 10–50 ppbv within 2 km downwind of the source, while maximum PM impacts in the immediate vicinity of the datacenter were less than 5 µg/m³.

Implications: Plausible scenarios of distributed fossil generation consistent with the electricity grid’s transformation to a more flexible and modernized system suggest that a substantial amount of deployment would be required to significantly affect air quality on a localized scale. In particular, natural gas turbines typically used in distributed generation may have minor effects. Large banks of diesel backup generators such as those used by data centers, on the other hand, may require pollution controls or conversion to natural gas-fired reciprocal internal combustion engines to decrease nitrogen dioxide pollution.     

Controls on hourly variations in urban background air pollutant concentrations

Average 21st century concentrations of urban air pollutants linked to cardiorespiratory disease are not declining, and commonly exceed legal limits. Even below such limits, health effects are being observed and may be related to transient daytime peaks in pollutant concentrations. With this in mind, we analyse >52,000 hourly urban background readings of PM₁₀ and pollutant gases throughout 2007 at a European town with legal annual average concentrations of common pollutants, but with a documented air pollution-related cardiorespiratory health problem, and demonstrate the hourly variations in PM₁₀, SO₂, NO_x, CO and O₃. Back-trajectory analysis was applied to track the arrival of exotic PM₁₀ intrusions, the main controls on air pollutants were identified, and the typical hourly pattern on ambient concentrations during 2007 was profiled. Emphasis was placed on “worst case” data (>90th percentile), when health effects are likely to be greatest. The data show marked daytime variations in pollutants result from rush-hour traffic-related pollution spikes, midday industrial SO₂ maxima, and afternoon O₃ peaks. African dust intrusions enhance PM₁₀ levels at whatever hour, whereas European PM incursions produce pronounced evening peaks due to their transport direction (across an industrial traffic corridor). Transient peak profiling moves us closer to the reality of personal outdoor exposure to inhalable pollutants in a given urban area. We argue that such an approach to monitoring data potentially offers more to air pollution health effect studies than using only 24 h or annual averages.     

Predicting residential indoor concentrations of nitrogen dioxide,fine particulate matter,and elemental carbon using questionnaire and geographic information system based data

Previous studies have identified associations between traffic-related air pollution and adverse health effects. Most have used measurements from a few central ambient monitors and/or some measure of traffic as indicators of exposure, disregarding spatial variability and factors influencing personal exposure-ambient concentration relationships. This study seeks to utilize publicly available data (i.e., central site monitors, geographic information system, and property assessment data) and questionnaire responses to predict residential indoor concentrations of traffic-related air pollutants for lower socioeconomic status (SES) urban households.As part of a prospective birth cohort study in urban Boston, we collected indoor and outdoor 3–4 day samples of nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) in 43 low SES residences across multiple seasons from 2003 to 2005. Elemental carbon (EC) concentrations were determined via reflectance analysis. Multiple traffic indicators were derived using Massachusetts Highway Department data and traffic counts collected outside sampling homes. Home characteristics and occupant behaviors were collected via a standardized questionnaire. Additional housing information was collected through property tax records, and ambient concentrations were collected from a centrally located ambient monitor.The contributions of ambient concentrations, local traffic and indoor sources to indoor concentrations were quantified with regression analyses. PM_2.5 was influenced less by local traffic but had significant indoor sources, while EC was associated with traffic and NO₂ with both traffic and indoor sources. Comparing models based on covariate selection using p-values or a Bayesian approach yielded similar results, with traffic density within a 50 m buffer of a home and distance from a truck route as important contributors to indoor levels of NO₂ and EC, respectively. The Bayesian approach also highlighted the uncertanity in the models. We conclude that by utilizing public databases and focused questionnaire data we can identify important predictors of indoor concentrations for multiple air pollutants in a high-risk population.     

Two-days ahead prediction of daily maximum concentrations of SO2, O3, PM10, NO2, CO in the urban area of Palermo,Italy

Artificial neural networks are functional alternative techniques in modelling the intricate vehicular exhaust emission dispersion phenomenon. Pollutant predictions are notoriously complex when using either deterministic or stochastic models, which explains why this model was developed using a neural network. Neural networks have the ability to learn about non-linear relationships between the used variables. In this paper a recurrent neural network (Elman model) based forecaster for the prediction of daily maximum concentrations of SO₂, O₃, PM10, NO₂, CO in the city of Palermo is proposed. The effectiveness of the presented forecaster was tested using a time series recorded between 1 January 2003 to 31 December 2004 in eight monitoring stations in urban area of Palermo (Italy). Experimental trials show that the developed and tuned model is appropriate, giving small values of root mean square error (RMSE) , mean absolute error (MAE) and mean square error (MSE). In addition, the related correlation coefficient ranges from 0.72 to 0.97 for each forecasted pollutant, underlying a small difference between the forecasted and the measured values. The above results make the proposed forecaster a powerful tool for pollution management systems.     

Photochemical model performance for PM2.5 sulfate,nitrate, ammonium,and precursor species SO2, HNO3, and NH3 at background monitor locations in the central and eastern United States

Health studies have shown premature death is statistically associated with exposure to particulate matter <2.5 μm in diameter (PM2.5). The United States Environmental Protection Agency requires all States with PM2.5 non-attainment counties or with sources contributing to visibility impairment at Class I areas to submit an emissions control plan. These emission control plans will likely focus on reducing emissions of sulfur oxides and nitrogen oxides, which form two of the largest chemical components of PM2.5 in the eastern United States: ammonium sulfate and ammonium nitrate. Emission control strategies are simulated using three-dimensional Eulerian photochemical transport models.A monitor study was established using one urban (Detroit) and nine rural locations in the central and eastern United States to simultaneously measure PM2.5 sulfate ion (SO₄²⁻), nitrate ion (NO₃⁻), ammonium ion (NH₄⁺), and precursor species sulfur dioxide (SO₂), nitric acid (HNO₃), and ammonia (NH₃). This monitor study provides a unique opportunity to assess how well the modeling system predicts the spatial and temporal variability of important precursor species and co-located PM2.5 ions, which is not well characterized in the central and eastern United States.The modeling system performs well at estimating the PM2.5 species, but does not perform quite as well for the precursor species. Ammonia is under-predicted in the coldest months, nitric acid tends to be over-predicted in the summer months, and sulfur dioxide appears to be systematically over-predicted. Several indicators of PM2.5 ammonium sulfate and ammonium nitrate formation and chemical composition are estimated with the ambient data and photochemical model output. PM2.5 sulfate ion is usually not fully neutralized to ammonium sulfate in ambient measurements and is usually fully neutralized in model estimates. The model and ambient estimates agree that the ammonia study monitors tend to be nitric acid limited for PM2.5 nitrate formation. Regulatory strategies in this part of the country should focus on reductions in NO_X rather than ammonia to control PM2.5 ammonium nitrate.     

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.     

Air pollution in cities

Air quality in cities is the result of a complex interaction between natural and anthropogenic environmental conditions. Air pollution in cities is a serious environmental problem – especially in the developing countries. The air pollution path of the urban atmosphere consists of emission and transmission of air pollutants resulting in the ambient air pollution. Each part of the path is influenced by different factors. Emissions from motor traffic are a very important source group throughout the world. During transmission, air pollutants are dispersed, diluted and subjected to photochemical reactions. Ambient air pollution shows temporal and spatial variability. As an example of the temporal variability of urban air pollutants caused by motor traffic, typical average annual, weekly and diurnal cycles of NO, NO₂, O₃ and O_x are presented for an official urban air-quality station in Stuttgart, southern Germany. They are supplemented by weekly and diurnal cycles of selected percentile values of NO, NO₂, and O₃. Time series of these air pollutants give information on their trends. Results are discussed with regard to air pollution conditions in other cities. Possibilities for the assessment of air pollution in cities are shown. In addition, a qualitative overview of the air quality of the world's megacities is given.     

The role of transboundary air pollution over Galicia and North Portugal area

In summer, high levels of ozone (O₃) are frequently measured at both Galicia and Northern Portugal air quality monitoring stations, even exceeding the limit values imposed by legislation. This work aims to investigate the origin of these high O₃ concentrations by the application of a chemical transport modelling system over the northwestern area of the Iberian Peninsula. The WRF–CHIMERE modelling system was applied with high resolution to simulate the selected air pollution episodes that occurred simultaneously in Galicia and North Portugal and in order to study both the contribution of local emission sources and the influence of transboundary pollution. Emission inputs have been prepared based on the development of the Portuguese and Galician emission inventories. The obtained results for O₃ have been evaluated and validated against observations. Modelling results show possible contribution of the transboundary transport over the border of two neighbour regions/countries, indicating that the O₃ episode starts over the urban and industrialised area of North coast of Portugal, reaching the maximum peaks over this region; at the same time, O₃ levels increased over Galicia region, where lower concentrations, but still high, were observed. These results pointed out that air quality management should not be driven by political boundaries and highlight the importance of joining efforts between neighbouring countries.     

Daily Mortality in the Philadelphia Metropolitan Area and Size-Classified Particulate Matter

ABSTRACT

Time-series of daily mortality data from May 1992 to September 1995 for various portions of the seven-county Philadelphia, PA, metropolitan area were analyzed in relation to weather and a variety of ambient air quality parameters. The air quality data included measurements of size-classified PM, SO₄ ^2-, and H+ that had been collected by the Harvard School of Public Health, as well as routine air pollution monitoring data. Because the various pollutants of interest were measured at different locations within the metropolitan area, it was necessary to test for spatial sensitivity by comparing results for different combinations of locations. Estimates are presented for single pollutants and for multiple-pollutant models, including gaseous pollutants and mutually exclusive components of PM (PM_2.5 and coarse particles, SO₄ ^2- and non-SO₄ ^2- portions of total suspended particulate [TSP] and PM₁₀), measured on the day of death and the previous day.

We concluded that associations between air quality and mortality were not limited to data collected in the same part of the metropolitan area; that is, mortality for one part may be associated with air quality data from another, not necessarily neighboring, part. Significant associations were found for a wide variety of gaseous and particulate pollutants, especially for peak O₃. Using joint regressions on peak O₃ with various other pollutants, we found that the combined responses were insensitive to the specific other pollutant selected. We saw no systematic differences according to particle size or chemistry. In general, the associations between daily mortality and air pollution depended on the pollutant or the PM metric, the type of collection filter used, and the location of sampling. Although peak O₃ seemed to exhibit the most consistent mortality responses, this finding should be confirmed by analyzing separate seasons and other time periods.     

Binational school-based monitoring of traffic-related air pollutants in El Paso, Texas (USA) and Ciudad Juárez, Chihuahua (México)

Paired indoor and outdoor concentrations of fine and coarse particulate matter (PM), PM2.5 reflectance [black carbon(BC)], and nitrogen dioxide (NO₂) were determined for sixteen weeks in 2008 at four elementary schools (two in high and two in low traffic density zones) in a U.S.-Mexico border community to aid a binational health effects study. Strong spatial heterogeneity was observed for all outdoor pollutant concentrations. Concentrations of all pollutants, except coarse PM, were higher in high traffic zones than in the respective low traffic zones. Black carbon and NO₂ appear to be better traffic indicators than fine PM. Indoor air pollution was found to be well associated with outdoor air pollution, although differences existed due to uncontrollable factors involving student activities and building/ventilation configurations. Results of this study indicate substantial spatial variability of pollutants in the region, suggesting that children’s exposures to these pollutants vary based on the location of their school.     

Investigation of time-resolved atmospheric conditions and indoor/outdoor particulate matter concentrations in homes with gas and biomass cook stoves in Nogales,Sonora, Mexico

This paper reports findings from a case study designed to investigate indoor and outdoor air quality in homes near the United States–Mexico border. During the field study, size-resolved continuous particulate matter (PM) concentrations were measured in six homes, while outdoor PM was simultaneously monitored at the same location in Nogales, Sonora, Mexico, during March 14–30, 2009. The purpose of the experiment was to compare PM in homes using different fuels for cooking, gas versus biomass, and to obtain a spatial distribution of outdoor PM in a region where local sources vary significantly (e.g., highway, border crossing, unpaved roads, industry). Continuous PM data were collected every 6 seconds using a valve switching system to sample indoor and outdoor air at each home location. This paper presents the indoor PM data from each home, including the relationship between indoor and outdoor PM. The meteorological conditions associated with elevated ambient PM events in the region are also discussed. Results indicate that indoor air pollution has a strong dependence on cooking fuel, with gas stoves having hourly averaged median PM₃ concentrations in the range of 134 to 157 μg m^?3 and biomass stoves 163 to 504 μg m^?3. Outdoor PM also indicates a large spatial heterogeneity due to the presence of microscale sources and meteorological influences (median PM₃: 130 to 770 μg m^?3). The former is evident in the median and range of daytime PM values (median PM₃: 250 μg m^?3, maximum: 9411 μg m^?3), while the meteorological influences appear to be dominant during nighttime periods (median PM₃: 251 μg m^?3, maximum: 10,846 μg m^?3). The atmospheric stability is quantified for three nighttime temperature inversion episodes, which were associated with an order of magnitude increase in PM10 at the regulatory monitor in Nogales, AZ (maximum increase: 12 to 474 μg m^?3).

Implications:Regulatory air quality standards are based on outdoor ambient air measurements. However, a large fraction of time is typically spent indoors where a variety of activities including cooking, heating, tobacco smoking, and cleaning can lead to elevated PM concentrations. This study investigates the influence of meteorology, outdoor PM, and indoor activities on indoor air pollution (IAP) levels in the United States–Mexico border region. Results indicate that cooking fuel type and meteorology greatly influence the IAP in homes, with biomass fuel use causing the largest increase in PM concentration.     

Ground-level ozone in the Pearl River Delta region: Analysis of data from a recently established regional air quality monitoring network

The ambient air quality monitoring data of 2006 and 2007 from a recently established Pearl River Delta (PRD) regional air quality monitoring network are analyzed to investigate the characteristics of ground-level ozone in the region. Four sites covering urban, suburban, rural and coastal areas are selected as representatives for detailed analysis in this paper. The results show that there are distinct seasonal and diurnal cycles in ground-level ozone across the PRD region. Low ozone concentrations are generally observed in summer, while high O₃ levels are typically found in autumn. The O₃ diurnal variations in the urban areas are larger than those at the rural sites. The O₃ concentrations showed no statistically significant difference between weekend and weekdays in contrast to the findings in many other urban areas in the world. The average ozone concentrations are lower in urban areas compared to the sites outside urban centers. Back trajectories are used to show the major air-mass transport patterns and to examine the changes in ozone from the respective upwind sites to a site in the center of the PRD (Wanqingsha). The results show higher average ozone concentrations at the upwind sites in the continental and coastal air masses, but higher 1 h-max O₃ concentrations (by 8–16 ppbv) at the center PRD site under each of air-mass category, suggesting that the ozone pollution in the PRD region exhibits both regional and super-regional characteristics.     

Spatial heterogeneity of PM10 and O3 in São Paulo, Brazil, and implications for human health studies

Developing exposure estimates is a challenging aspect of investigating the health effects of air pollution. Pollutant levels recorded at centrally located ambient air quality monitors in a community are commonly used as proxies for population exposures. However, if ample intraurban spatial variation in pollutants exists, city-wide averages of concentrations may introduce exposure misclassification. We assessed spatial heterogeneity of particulate matter with an aerodynamic diameter < or = 10 microm (PM10) and ozone (O3) and evaluated implications for epidemiological studies in S?o Paulo, Brazil, using daily (24-hr) and daytime (12-hr) averages and 1-hr daily maximums of pollutant levels recorded at the regulatory monitoring network. Monitor locations were also analyzed with respect to a socioeconomic status index developed by the municipal government. Hourly PM10 and O3 data for the Sāo Paulo Municipality and Metropolitan Region (1999-2006) were used to evaluate heterogeneity by comparing distance between monitors with pollutants' correlations and coefficients of divergence (CODs). Both pollutants showed high correlations across monitoring sites (median = 0.8 for daily averages). CODs across sites averaged 0.20. Distance was a good predictor of CODs for PM10 (p < 0.01) but not O3, whereas distance was a good predictor of correlations for O3 (p < 0.01) but not PM10. High COD values and low temporal correlation indicate a spatially heterogeneous distribution of PM10. Ozone levels were highly correlated (r > or = 0.75), but high CODs suggest that averaging over O3 levels may obscure important spatial variations. Of municipal districts in the highest of five socioeconomic groups, 40% have > or = 1 monitor, whereas districts in the lowest two groups, representing half the population, have no monitors. Results suggest that there is a potential for exposure misclassification based on the available monitoring network and that spatial heterogeneity depends on pollutant metric (e.g., daily average vs. daily 1-hr maximum). A denser monitoring network or alternative exposure methods may be needed for epidemiological research. Findings demonstrate the importance of considering spatial heterogeneity and differential exposure misclassification by subpopulation.