Spatial modeling for air pollution monitoring network design: example of residential woodsmoke

The purpose of this paper is to demonstrate how to develop an air pollution monitoring network to characterize small-area spatial contrasts in ambient air pollution concentrations. Using residential woodburning emissions as our case study, this paper reports on the first three stages of a four-stage protocol to measure, estimate, and validate ambient residential woodsmoke emissions in Vancouver, British Columbia. The first step is to develop an initial winter nighttime woodsmoke emissions surface using inverse-distance weighting of emissions information from consumer woodburning surveys and property assessment data. Second, fireplace density and a compound topographic index based on hydrological flow regimes are used to enhance the emissions surface. Third, the spatial variation of the surface is used in a location-allocation algorithm to design a network of samplers for the woodsmoke tracer compound levoglucosan and fine particulate matter. Measurements at these network sites are then used in the fourth stage of the protocol (not presented here): a mobile sampling campaign aimed at developing a high-resolution surface of woodsmoke concentrations for exposure assignment in health effects studies. Overall the results show that relatively simple data inputs and spatial analysis can be effective in capturing the spatial variability of ambient air pollution emissions and concentrations.     

epa’s research program for controlling residential wood combustion emissions

A recently completed study has shown that emissions of participate, carbon monoxide, and organics (including polycyclic organic matter) are relatively high from residential woodburning stoves and fireplaces when compared to emissions from residential gas- and oil-fired furnaces. Since these emissions include a number of potentially hazardous compounds; the trend toward greater residential wood usage can have a negative impact on local ambient air quality. EPA is currently studying ways to operate existing stoves and design new stoves to minimize air pollutant emissions.     

Wood smoke as a source of particle-phase organic compounds in residential areas

The objective of this study was to investigate the organic composition of wood smoke emissions and ambient air samples in order to determine the wood smoke contribution to the ambient air pollution in the residential areas. From November 2005 to March 2006 particle-phase PM₁₀ samples were collected in the residential town Dettenhausen surrounded by forests near Stuttgart in southern Germany. Samples collected on pre-baked glass fibre filters were extracted using toluene with ultrasonic bath and analysed by gas chromatography mass spectrometry (GC-MS). 21 polycyclic aromatic hydrocarbons (PAH) including 16 USEPA priority pollutants, different organic wood smoke tracers, primarily 21 species of syringol and guaiacol derivatives, levoglucosan and its isomers mannosan, galactosan and dehydroabietic acid were detected and quantified in this study. The concentrations of these compounds were compared with the fingerprints of emissions from hardwood and softwood combustion carried out in test facilities at Universitaet Stuttgart and field investigations at a wood stove during real operation in Dettenhausen. It was observed that the combustion derived PAH was detected in higher concentrations than other PAH in the ambient air PM₁₀ samples. Syringol and its derivatives were found in large amounts in hardwood burning but were not detected in softwood burning emissions. On the other hand, guaiacol and its derivatives were found in both softwood and hardwood burning emissions, but the concentrations were higher in the softwood smoke compared to hardwood smoke. So, these compounds can be used as typical tracer compounds for the different types of wood burning emissions. In ambient air samples both syringol and guaiacol derivatives were found which indicates the wood combustion contribution to the PM load in such residential areas. Levoglucosan was detected in high concentrations in all ambient PM₁₀ samples. A source apportionment modelling, Positive Matrix Factorization (PMF) was implemented to quantify the wood smoke contribution to the ambient PM₁₀ bound organic compounds in the residential area.     

Impact of emissions from natural gas production facilities on ambient air quality in the Barnett Shale area: A pilot study

Rapid and extensive development of shale gas resources in the Barnett Shale region of Texas in recent years has created concerns about potential environmental impacts on water and air quality. The purpose of this study was to provide a better understanding of the potential contributions of emissions from gas production operations to population exposure to air toxics in the Barnett Shale region. This goal was approached using a combination of chemical characterization of the volatile organic compound (VOC) emissions from active wells, saturation monitoring for gaseous and particulate pollutants in a residential community located near active gas/oil extraction and processing facilities, source apportionment of VOCs measured in the community using the Chemical Mass Balance (CMB) receptor model, and direct measurements of the pollutant gradient downwind of a gas well with high VOC emissions. Overall, the study results indicate that air quality impacts due to individual gas wells and compressor stations are not likely to be discernible beyond a distance of approximately 100 m in the downwind direction. However, source apportionment results indicate a significant contribution to regional VOCs from gas production sources, particularly for lower-molecular-weight alkanes (<C6). Although measured ambient VOC concentrations were well below health-based safe exposure levels, the existence of urban-level mean concentrations of benzene and other mobile source air toxics combined with soot to total carbon ratios that were high for an area with little residential or commercial development may be indicative of the impact of increased heavy-duty vehicle traffic related to gas production

ImplicationsRapid and extensive development of shale gas resources in recent years has created concerns about potential environmental impacts on water and air quality. This study focused on directly measuring the ambient air pollutant levels occurring at residential properties located near natural gas extraction and processing facilities, and estimating the relative contributions from gas production and motor vehicle emissions to ambient VOC concentrations. Although only a small-scale case study, the results may be useful for guidance in planning future ambient air quality studies and human exposure estimates in areas of intensive shale gas production.     

Resolving local-scale emissions for modeling air quality near roadways

A large body of literature published in recent years suggests increased health risk due to exposure of people to air pollution in close proximity to roadways. As a result, there is a need to more accurately represent the spatial concentration gradients near roadways to develop mitigation strategies. In this paper, we present a practical, readily adaptable methodology, using a "bottom-up" approach to develop a detailed highway vehicle emission inventory that includes emissions for individual road links. This methodology also takes advantage of geographic information system (GIS) software to improve the spatial accuracy of the activity information obtained from a Travel Demand Model. In addition, we present an air quality modeling application of this methodology in New Haven, CT. This application uses a hybrid modeling approach, in which a regional grid-based model is used to characterize average local ambient concentrations, and a Gaussian dispersion model is used to provide texture within the modeling domain because of spatial gradients associated with highway vehicle emissions and other local sources. Modeling results show substantial heterogeneity of pollutant concentrations within the modeling domain and strong spatial gradients associated with roadways, particularly for pollutants dominated by direct emissions.     

Dependence of Home Outdoor Particulate Mass and Number Concentrations on Residential and Traffic Features in Urban Areas

Abstract

The associations between residential outdoor and ambient particle mass, fine particle absorbance, particle number (PN) concentrations, and residential and traffic determinants were investigated in four European urban areas (Helsinki, Athens, Amsterdam, and Birmingham). A total of 152 nonsmoking participants with respiratory diseases, not exposed to occupational pollution, were included in the study, which comprised a 7-day intensive exposure monitoring period of both indoor and home outdoor particle mass and number concentrations. The same pollutants were also continuously measured at ambient fixed sites centrally located to the studied areas (fixed ambient sites). Relationships between concentrations measured directly outside the homes (residential outdoor) and at the fixed ambient sites were pollutant-specific, with substantial variations among the urban areas. Differences were more pronounced for coarse particles due to resuspension of road dust and PN, which is strongly related to traffic emissions. Less significant outdoor-to-fixed variation for particle mass was observed for Amsterdam and Birmingham, predominantly due to regional secondary aerosol. On the contrary, a strong spatial variation was observed for Athens and to a lesser extent for Helsinki. This was attributed to the overwhelming and time-varied inputs from traffic and other local sources. The location of the residence and traffic volume and distance to street and traffic light were important determinants of residential outdoor particle concentrations. On average, particle mass levels in suburban areas were less than 30% of those measured for residences located in the city center. Residences located less than 10 m from a street experienced 133% higher PN concentrations than residences located further away. Overall, the findings of this multi-city study, indicated that (1) spatial variation was larger for PN than for fine particulate matter (PM) mass and varied between the cities, (2) vehicular emissions in the residential street and location in the center of the city were significant predictors of spatial variation, and (3) the impact of traffic and location in the city was much larger for PN than for fine particle mass.     

Residential Indoor,Outdoor, and Workplace Concentrations of Carbonyl Compounds: Relationships with Personal Exposure Concentrations and Correlation with Sources

Abstract

Personal 48-hr exposures of 15 randomly selected participants as well as microenvironment concentrations in each participant’s residence and workplace were measured for 16 carbonyl compounds during summer–fall 1997 as a part of the Air Pollution Exposure Distributions within Adult Urban Populations in Europe (EXPOLIS) study in Helsinki, Finland. When formaldehyde and acetaldehyde were excluded, geometric mean ambient air concentrations outside each participant’s residence were less than 1 ppb for all target compounds. Geometric mean residential indoor concentrations of carbonyls were systematically higher than geometric mean personal exposures and indoor workplace concentrations. Additionally, residential indoor/outdoor ratios indicated substantial indoor sources for most target compounds. Carbonyls in residential indoor air correlated significantly, suggesting similar mechanisms of entry into indoor environments. Overall, this study demonstrated the important role of non-traffic-related emissions in the personal exposures of participants in Helsinki and that comprehensive apportionment of population risk to air toxics should include exposure concentrations derived from product emissions and chemical formation in indoor air.     

Evaluating an Air Quality Health Index (AQHI) amendment for communities impacted by residential woodsmoke in British Columbia,Canada

ABSTRACT

Smoke from burning biomass is an important source of fine particulate matter (PM_2.5), but the health risks may not be fully captured by the Canadian Air Quality Health Index (AQHI). In May 2018, the province of British Columbia launched an evidence-based amendment (AQHI-Plus) to improve AQHI performance for wildfire smoke, but the AQHI-Plus was not developed or tested on data from the residential woodsmoke season. This study assesses how the AQHI and AQHI-Plus are associated with acute health outcomes during the cooler seasons of 2010–2017 in British Columbia, Canada. Monthly and daily patterns of temperature and PM_2.5 concentrations were used to identify Local Health Areas (LHAs) that were impacted by residential woodsmoke. The effects of the AQHI and AQHI-Plus on five acute health outcomes (including non-accidental mortality, outpatient physician visits, and medical dispensations for cardiopulmonary conditions) were estimated using generalized linear mixed effect models with Poisson distributions adjusted for long- and short-term temperature trends. Values of the Akaike information criterion (AIC) were compared to evaluate whether the AQHI or AQHI-Plus was better fitted to each health outcome. Eleven LHAs were categorized as woodsmoke-impacted. In these LHAs, the AQHI and AQHI-Plus associations with acute health outcomes were sensitive to temperature adjustments. After temperature adjustments, the most consistent associations were observed for the two asthma-specific outcomes where the AQHI-Plus was better fitted than the AQHI. The improved performance of the AQHI-Plus for susceptible populations with asthma is consistent between communities impacted by residential woodsmoke and wildfire smoke.

Implications: Canada’s Air Quality Health Index (AQHI) is a three pollutant index used to communicate the short term health impact of degraded air quality. As fine particulate matter (PM_2.5) is the lowest weighted pollutant in the AQHI, the index is poorly reflective of woodsmoke impacts. The present analysis found that an AQHI amendment developed for improved sensitivity to PM_2.5 during wildfire seasons (AQHI-Plus) is also more predictive of acute asthma-related health outcomes in communities impacted by residential woodsmoke. The BC Ministry of Environment and Climate Change Strategy has piloted the AQHI-Plus year-round. Other jurisdictions should consider whether their air quality indices are reflective of the risks posed by woodsmoke.     

Environmental Impact of Residential Wood Combustion Emissions and its Implications

Currently available information suggests a substantial environmental impact from residential wood combustion emissions. Air pollution from this source is widespread and increasing. Current ambient measurements, surveys, and model predictions indicate winter respirable (<2 μm) emissions from residential wood combustion can easily exceed all other sources. Both the chemical potency and deliverability of the emissions from this source are of concern. The emissions are almost entirely in the inhalable size range and contain toxic and priority pollutants, carcinogens, co-carcinogens, cilia toxic, mucus coagulating agents, and other respiratory irritants such as phenols, aldehydes, etc. This source is contributing substantially to the nonattainment of current particulate, carbon monoxide, and hydrocarbon ambient air quality standards and will almost certainly have a significant impact on potential future standards such as inhalable particulates, visibility, and other chemically specific standards. Emission from this growing source is likely to require additional expenditures by industry for air pollution control equipment in nonattainment areas.     

Characterization of Particulate Matter in California

ABSTRACT

The size, composition, and concentration of particulate matter (PM) vary with location and time. Several monitoring/sampling programs are operated in California to characterize PM less than 2.5 and 10 µm in aerodynamic diameter (PM_2.5 and PM₁₀). This paper presents a broad summary of the spatial and temporal variations observed in ambient PM_2.5 and PM₁₀ concentrations in California. Many areas that have high PM₁₀ concentrations also have relatively high PM_2.5 concentrations, and data indicate that a significant portion of the PM₁₀ air quality problem is caused by PM_2.5. To develop effective plans for attaining the ambient PM standards, improved understanding of these unique problems is needed. Since 1989, pollution control efforts—whether specifically targeted for particulate matter or indirectly via controls on gaseous emissions—have caused annual average PM_2.5 and PM₁₀ concentrations to decline at most sites in California.     

A reanalysis of fine particulate matter air pollution versus life expectancy in the United States

A reduction in population exposure to fine particulate matter air pollution (PM2.5) has been associated with improvements in life expectancy. This article presents a reanalysis of this relationship and comments on the results from a study on the reduction of ambient air PM_2.5 concentrations versus life expectancy in metropolitan areas of the United States. The results of the reanalysis show that the statistical significance of the correlation is lost after removing one of the metropolitan areas from the regression analysis, suggesting that the results may not be suitable for a meaningful and reliable inference.

Implications: The observed loss of statistical significance in the correlation between the reduction of ambient air PM_2.5 concentrations and life expectancy in metropolitan areas of the United States, after removing one of the metropolitan areas from the regression analysis, may raise concern for the policymakers in decisions regarding further reductions in permitted levels of air pollution emissions.     

A Chemical Mass Balance for Volatile Organics in Chicago

Increasing attention to the presence of atmospheric volatile organic compounds has focused interest on the sources and fate of organics in ambient air. The purpose of this study was to develop a chemical mass balance receptor model (CMB) to determine the contributions of major organic pollution source types to ambient pollution levels. Twenty mid-day ambient air samples were analyzed for the presence of volatile hydrocarbons by gas chromatographlc procedures. Based on these measurements, contributions from vehicles, gasoline vapor emissions, and petroleum refineries to ambient organic concentrations were estimated. For the receptor site studied, vehicles were the dominant source type and accounted for 60.8 percent of the organics evaluated. Contributions from refineries, gasoline vapor, and all other sources were 10.1, 11.1, and 17.9 percent, respectively. Validation of the predictions showed that the model is sensitive to the effect of overall upwind emissions. The CMB model was shown to produce reasonable predictive results for vehicles, gasoline vapor, and refinery contributions to ambient non-methane organic concentrations.     

Dependence of home outdoor particulate mass and number concentrations on residential and traffic features in urban areas

The associations between residential outdoor and ambient particle mass, fine particle absorbance, particle number (PN) concentrations, and residential and traffic determinants were investigated in four European urban areas (Helsinki, Athens, Amsterdam, and Birmingham). A total of 152 nonsmoking participants with respiratory diseases, not exposed to occupational pollution, were included in the study, which comprised a 7-day intensive exposure monitoring period of both indoor and home outdoor particle mass and number concentrations. The same pollutants were also continuously measured at ambient fixed sites centrally located to the studied areas (fixed ambient sites). Relationships between concentrations measured directly outside the homes (residential outdoor) and at the fixed ambient sites were pollutant-specific, with substantial variations among the urban areas. Differences were more pronounced for coarse particles due to resuspension of road dust and PN, which is strongly related to traffic emissions. Less significant outdoor-to-fixed variation for particle mass was observed for Amsterdam and Birmingham, predominantly due to regional secondary aerosol. On the contrary, a strong spatial variation was observed for Athens and to a lesser extent for Helsinki. This was attributed to the overwhelming and time-varied inputs from traffic and other local sources. The location of the residence and traffic volume and distance to street and traffic light were important determinants of residential outdoor particle concentrations. On average, particle mass levels in suburban areas were less than 30% of those measured for residences located in the city center. Residences located less than 10 m from a street experienced 133% higher PN concentrations than residences located further away. Overall, the findings of this multi-city study, indicated that (1) spatial variation was larger for PN than for fine particulate matter (PM) mass and varied between the cities, (2) vehicular emissions in the residential street and location in the center of the city were significant predictors of spatial variation, and (3) the impact of traffic and location in the city was much larger for PN than for fine particle mass.     

Spatial/temporal variations of elemental carbon, organic carbon, and trace elements in PM10 and the impact of land-use patterns on community air pollution in Paterson, NJ

An urban community PM10 (particulate matter < or = 10 microm in aerodynamic diameter) air pollution study was conducted in Paterson, NJ, a mixed land-use community that is interspersed with industrial, commercial, mobile, and residential land-use types. This paper examines (1) the spatial/temporal variation of PM10, elemental carbon (EC), organic carbon (OC), and nine elements; and (2) the impact of land-use type on those variations. Air samples were collected from three community-oriented locations in Paterson that attempted to capture industrial, commercial, and mobile source-dominated emissions. Sampling was conducted for 24 hr every 6 days from November 2005 through December 2006. Samples were concurrently collected at the New Jersey Department of Environmental Protection-designated air toxics background site in Chester, NJ. PM10 mass, EC, OC, and nine elements (Ca, Cu, Fe, Pb, Mn, Ni, S, Ti, and Zn) that had more than 50% of samples above detection and known sources or are toxic were selected for spatial/temporal analysis in this study. The concentrations of PM10, EC, OC, and eight elements (except S) were significantly higher in Paterson than in Chester (P < 0.05). The concentrations of these elements measured in Paterson were also found to be higher during winter than the other three seasons (except S), and higher on weekdays than on weekends (except Pb). The concentrations of EC, Cu, Fe, and Zn at the commercial site in Paterson were significantly higher than the industrial and mobile sites; however, the other eight species were not significantly different within the city (P > 0.05). These results indicated that anthropogenic sources of air pollution were present in Paterson. The source apportionment confirmed the impact of vehicular and industrial emissions on the PM10 ambient air pollution in Paterson. The multiple linear regression analysis showed that categorical land-use type was a significant predictor for all air pollution levels, explaining up to 42% of the variability in concentration by land-use type only.     

Assessment of contribution of SO2 and NO2 from different sources in Jamshedpur region, India

Contribution of pollution from different types of sources in Jamshedpur, the steel city of India, has been estimated in winter 1993 using two approaches in order to delineate and prioritize air quality management strategies for the development of region in an environmental friendly manner. The first approach mainly aims at preparation of a comprehensive emission inventory and estimation of spatial distribution of pollution loads in terms of SO₂ and NO₂ from different types of industrial, domestic and vehicular sources in the region. The results indicate that industrial sources account for 77% and 68% of the total emissions of SO₂ and NO₂, respectively, in the region, whereas vehicular emissions contributed to about 28% of the total NO₂ emissions. In the second approach, contribution of these sources to ambient air quality levels to which the people are exposed to, was assessed through air pollution dispersion modelling. Ambient concentration levels of SO₂ and NO₂ have been predicted in winter season using the ISCST3 model. The analysis indicates that emissions from industrial sources are responsible for more than 50% of the total SO₂ and NO₂ concentration levels. Vehicular activities contributed to about 40% of NO₂ pollution and domestic fuel combustion contributed to about 38% of SO₂ pollution. Predicted 24-h concentrations were compared with measured concentrations at 11 ambient air monitoring stations and good agreement was noted between the two values. In-depth zone-wise analysis of the above indicates that for effective air quality management, industrial source emissions should be given highest priority, followed by vehicular and domestic sources in Jamshedpur region.     

Development of a GIS-based decision support system for urban air quality management in the city of Istanbul

A decision support system has been developed for urban air quality management in the metropolitan area of Istanbul. The system is based on CALMET/CALPUFF dispersion modeling system, digital maps, and related databases to estimate the emissions and spatial distribution of air pollutants with the help of a GIS software. The system estimates ambient air pollution levels at high temporal and spatial resolutions and enables mapping of emissions and air quality levels. Mapping and scenario results can be compared with air quality limits. Impact assessment of air pollution abatement measures can also be carried out.     

Air Pollution Problems of the Steel Industry

Urban air pollution has traditionally been modeled using annual, or at best, seasonal emissions inventories and climatology. These averaging techniques may introduce uncertainty into the analysis, if specific emissions (e.g. SO₂) are correlated with dispersion factors on a short-term basis. This may well be the case for space heating emissions. An analysis of this problem, using hourly climatological and residential emission estimates for six U.S. cities, indicates that the errors introduced using such averages are modest (~ ± 12%) for annual average concentrations. Maximum hourly concentrations vary considerably more, since maximum heat demand and worst case dispersion are in general not coincident. The paper thus provides a basis for estimating more realistic air pollution Impacts due to residential space heating.     

NO2 and SO2dispersion modeling and relative roles of emission sources over Map Ta Phut industrial area,Thailand

Map Ta Phut industrial area (MA) is the largest industrial complex in Thailand. There has been concern about many air pollutants over this area. Air quality management for the area is known to be difficult, due to lack of understanding of how emissions from different sources or sectors (e.g., industrial, power plant, transportation, and residential) contribute to air quality degradation in the area. In this study, a dispersion study of NO₂ and SO₂ was conducted using the AERMOD model. The area-specific emission inventories of NO_x and SO₂ were prepared, including both stack and nonstack sources, and divided into 11 emission groups. Annual simulations were performed for the year 2006. Modeled concentrations were evaluated with observations. Underestimation of both pollutants was found, and stack emission estimates were scaled to improve the modeled results before quantifying relative roles of individual emission groups to ambient concentration over four selected impacted areas (two are residential and the others are highly industrialized). Two concentration measures (i.e., annual average area-wide concentration or AC, and area-wide robust highest concentration or AR) were used to aggregately represent mean and high-end concentrations for each individual area, respectively. For AC-NO₂, on-road mobile emissions were found to be the largest contributor in the two residential areas (36–38% of total AC-NO₂), while petrochemical-industry emissions play the most important role in the two industrialized areas (34–51%). For AR-NO₂, biomass burning has the most influence in all impacted areas (>90%) except for one residential area where on-road mobile is the largest (75%). For AC-SO₂, the petrochemical industry contributes most in all impacted areas (38–56%). For AR-SO₂, the results vary. Since the petrochemical industry was often identified as the major contributor despite not being the largest emitter, air quality workers should pay special attention to this emission group when managing air quality for the MA.

Implications: Effective air quality management in Map Ta Phut Industrial Area, Thailand requires better understanding of how emissions from various sources contribute to the degradation of ambient air quality. Based on the dispersion study here, petrochemical industry was generally identified as the major contributor to ambient NO₂ and SO₂. By accounting for all stack and non-stack sources, on-road mobile emissions were found to be important in some particular areas.     

Characterization of Spatially Homogeneous Regions Based on Temporal Patterns of Fine Particulate Matter in the Continental United States

Abstract

Statistical analyses of time-series or spatial data have been widely used to investigate the behavior of ambient air pollutants. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both spatial and temporal characteristics. The objective of this study is 2-fold: (1) to identify an efficient way to characterize the spatial variations of fine particulate matter (PM_2.5) concentrations based solely upon their temporal patterns, and (2) to analyze the temporal and seasonal patterns of PM_2.5 concentrations in spatially homogenous regions. This study used 24-hr average PM_2.5 concentrations measured every third day during a period between 2001 and 2005 at 522 monitoring sites in the continental United States. A k-means clustering algorithm using the correlation distance was used to investigate the similarity in patterns between temporal profiles observed at the monitoring sites. A k-means clustering analysis produced six clusters of sites with distinct temporal patterns that were able to identify and characterize spatially homogeneous regions of the United States. The study also presents a rotated principal component analysis (RPCA) that has been used for characterizing spatial patterns of air pollution and discusses the difference between the clustering algorithm and RPCA.