Errors in coarse particulate matter mass concentrations and spatiotemporal characteristics when using subtraction estimation methods

In studies of coarse particulate matter (PM_10-2.5), mass concentrations are often estimated through the subtraction of PM_2.5 from collocated PM₁₀ tapered element oscillating microbalance (TEOM) measurements. Though all field instruments have yet to be updated, the Filter Dynamic Measurement System (FDMS) was introduced to account for the loss of semivolatile material from heated TEOM filters. To assess errors in PM_10-2.5 estimation when using the possible combinations of PM₁₀ and PM_2.5 TEOM units with and without FDMS, data from three monitoring sites of the Colorado Coarse Rural–Urban Sources and Health (CCRUSH) study were used to simulate four possible subtraction methods for estimating PM_10-2.5 mass concentrations. Assuming all mass is accounted for using collocated TEOMs with FDMS, the three other subtraction methods were assessed for biases in absolute mass concentration, temporal variability, spatial correlation, and homogeneity. Results show collocated units without FDMS closely estimate actual PM_10-2.5 mass and spatial characteristics due to the very low semivolatile PM_10-2.5 concentrations in Colorado. Estimation using either a PM_2.5 or PM₁₀ monitor without FDMS introduced absolute biases of 2.4 µg/m³ (25%) to –2.3 µg/m³ (–24%), respectively. Such errors are directly related to the unmeasured semivolatile mass and alter measures of spatiotemporal variability and homogeneity, all of which have implications for the regulatory and epidemiology communities concerned about PM_10-2.5. Two monitoring sites operated by the state of Colorado were considered for inclusion in the CCRUSH acute health effects study, but concentrations were biased due to sampling with an FDMS-equipped PM_2.5 TEOM and PM₁₀ TEOM not corrected for semivolatile mass loss. A regression-based model was developed for removing the error in these measurements by estimating the semivolatile concentration of PM_2.5 from total PM_2.5 concentrations. By estimating nonvolatile PM_2.5 concentrations from this relationship, PM_10-2.5 was calculated as the difference between nonvolatile PM₁₀ and PM_2.5 concentrations.

Implications: Errors in the estimation of PM_10-2.5 concentrations using subtraction methods were shown to be related to the unmeasured semivolatile mass when using certain combinations of TEOM instruments. For the northeastern Colorado region, the absolute bias associated with this error significantly affects mean and 95th percentile values, which would affect assessment of compliance if PM_10-2.5 is regulated in the future. Estimating PM_10-2.5 mass concentrations using nonvolatile mass concentrations from collocated PM₁₀ and PM_2.5 TEOM monitors closely estimates the total PM_10-2.5 mass concentrations. A corrective model that removes the described error was developed and applied to data from two sites in Denver.

Supplemental Materials: Supplemental materials are available for this paper. Go to the publisher's online edition of the Journal of the Air & Waste Management Association.     

Trends in speciated fine particulate matter and visibility across monitoring networks in the Southeastern United States

Trends in fine particulate matter <2.5 microm in diameter (PM2.5) and visibility in the Southeastern United States were evaluated for sites in the Interagency Monitoring of Protected Visual Environments, Speciated Trends Network, and Southeastern Aerosol Research and Characterization Study networks. These analyses are part of the technical assessment by Visibility Improvement-State and Tribal Association of the Southeast (VISTAS), the regional planning organization for the southeastern states, in support of State Implementation Plans for the regional haze rule. At all of the VISTAS IMPROVE sites, ammonium sulfate and organic carbon (OC) are the largest and second largest contributors, respectively, to light extinction on both the 20% haziest and 20% clearest days. Ammonium nitrate, elemental carbon (EC), soils, and coarse particles make comparatively small contributions to PM2.5 mass and light extinction on most days at the Class I areas. At Southern Appalachian sites, the 20% haziest days occur primarily in the late spring to fall, whereas at coastal sites, the 20% haziest days can occur through out the year. Levels of ammonium sulfate in Class I areas are similar to those in nearby urban areas and are generally higher at the interior sites than the coastal sites. Concentrations of OC, ammonium nitrate, and, sometimes, EC, tend to be higher in the urban areas than in nearby Class I areas, although differences in measurement methods complicate comparisons between networks. Results support regional controls of sulfur dioxide for both regional haze and PM2.5 implementation and suggest that controls of local sources of OC, EC, or nitrogen oxides might also be considered for urban areas that are not attaining the annual National Ambient Air Quality Standard for PM2.5.     

Model for forecasting expressway fine particulate matter and carbon monoxide concentration: application of regression and neural network models

The Borman Expressway is a heavily traveled 16-mi segment of the Interstate 80/94 freeway through Northwestern Indiana. The Lake and Porter counties through which this expressway passes are designated as particulate matter < 2.5 microm (PM2.5) and ozone 8-hr standard nonattainment areas. The Purdue University air quality group has been collecting PM2.5, carbon monoxide (CO), wind speed, wind direction, pressure, and temperature data since September 1999. In this work, regression and neural network models were developed for forecasting hourly PM2.5 and CO concentrations. Time series of PM2.5 and CO concentrations, traffic data, and meteorological parameters were used for developing the neural network and regression models. The models were compared using a number of statistical quality indicators. Both models had reasonable accuracy in predicting hourly PM2.5 concentration with coefficient of determination -0.80, root mean square error (RMSE) <4 microg/m3, and index of agreement (IA) > 0.90. For CO prediction, both models showed moderate forecasting performance with a coefficient of determination -0.55, RMSE < 0.50 ppm, and IA -0.85. These models are computationally less cumbersome and require less number of predictors as compared with the deterministic models. The availability of real time PM2.5 and CO forecasts will help highway managers to identify air pollution episodic events beforehand and to determine mitigation strategies.     

Comparison of real-time instruments and gravimetric method when measuring particulate matter in a residential building

This study used several real-time and filter-based aerosol instruments to measure PM_2.5 levels in a high-rise residential green building in the Northeastern US and compared performance of those instruments. PM_2.5 24-hr average concentrations were determined using a Personal Modular Impactor (PMI) with 2.5 µm cut (SKC Inc., Eighty Four, PA) and a direct reading pDR-1500 (Thermo Scientific, Franklin, MA) as well as its filter. 1-hr average PM_2.5 concentrations were measured in the same apartments with an Aerotrak Optical Particle Counter (OPC) (model 8220, TSI, Inc., Shoreview, MN) and a DustTrak DRX mass monitor (model 8534, TSI, Inc., Shoreview, MN). OPC and DRX measurements were compared with concurrent 1-hr mass concentration from the pDR-1500. The pDR-1500 direct reading showed approximately 40% higher particle mass concentration compared to its own filter (n = 41), and 25% higher PM_2.5 mass concentration compared to the PMI_2.5 filter. The pDR-1500 direct reading and PMI_2.5 in non-smoking homes (self-reported) were not significantly different (n = 10, R² = 0.937), while the difference between measurements for smoking homes was 44% (n = 31, R² = 0.773). Both OPC and DRX data had substantial and significant systematic and proportional biases compared with pDR-1500 readings. However, these methods were highly correlated: R² = 0.936 for OPC versus pDR-1500 reading and R² = 0.863 for DRX versus pDR-1500 reading. The data suggest that accuracy of aerosol mass concentrations from direct-reading instruments in indoor environments depends on the instrument, and that correction factors can be used to reduce biases of these real-time monitors in residential green buildings with similar aerosol properties.

Implications: This study used several real-time and filter-based aerosol instruments to measure PM_2.5 levels in a high-rise residential green building in the northeastern United States and compared performance of those instruments. The data show that while the use of real-time monitors is convenient for measurement of airborne PM at short time scales, the accuracy of those monitors depends on a particular instrument. Bias correction factors identified in this paper could provide guidance for other studies using direct-reading instruments to measure PM concentrations.     

Quantification of elemental and total carbon in combustion particulate matter using thermal-oxidative analysis

The use of a two-step thermal-oxidative analysis (TOA) technique for quantification of the mass of total carbon (TC) and elemental carbon (EC) of turbine engine-borne particulate matter (PM) has been evaluated. This approach could be used in lieu of analysis methods which were developed to characterize diluted PM. This effort is of particular interest as turbine engine PM emissions typically have a higher EC content than ambient aerosols, and filter sample mass loadings can be significantly greater than recommended for existing analysis techniques. Analyses were performed under a pure oxygen environment using a two-step temperature profile; reference carbon and actual PM samples were used to identify appropriate analysis conditions. Thermal gravimetric analysis (TGA) methods were used to provide guidance on the nature of the carbon in several of the materials. This was necessary as a standard reference material does not exist for determination of the EC fraction in PM. The TGA also assisted in identifying an appropriate temperature range for the first-stage of the TOA method. Quantification of TC and EC for turbine engine PM samples using TOA was compared to results obtained using the NIOSH 5040 thermal-optical method. For first-stage TOA temperatures of 350°C and 400°C, excellent agreement between the techniques was observed in both the quantified TC and EC, supporting the viability for using TOA for analysis of turbine engine PM samples. A primary benefit of using TOA for these types of PM samples is that filters with relatively high PM mass loadings (sampled at the emission source) can be readily analyzed. In addition, an entire filter sample can be evaluated, as compared to the use of a filter punch sample for the NIOSH technique. While the feasibility of using a TOA method for engine PM samples has been demonstrated, future studies to estimate potential OC charring and oxidation of EC-type material may provide additional data to assess its impact on the OC/EC fractions for other carbon-type measurements.

Implications: This work presents results and procedures of an analytical method for the determination of total and elemental carbon, i.e., TC and EC present in combustion source particulate matter samples. In general, it is shown that the LECO TOA methodology is as reliable and comprehensive as NIOSH 5040 for determining TC and EC carbon types in particulate matter present in turbine emission sources, and should be considered as an alternative. Principles of the methodology, differences, and corresponding agreement with the standard NIOSH 5040 method and TGA analysis are discussed.     

Sorption of organic pollutants by marine sediments: implication for the role of particulate organic matter

The objective of this study was to quantify sorption properties for kerogen/black carbon (BC)-bearing sediments. Single-solute sorption isotherms were measured for five pristine marine sediments using phenanthrene, naphthalene, 1,3,5-trichlorobenzene, and 1,4-dichlorobenzene as the sorbates. The results showed that the sorption isotherms were nonlinear and that the organic carbon normalized single point K_OC values were comparable to those reported in the literature for the purified keorgen and BC, but are much higher than the data reported for HA and kerogen/BC-containing terrestrial soils and sediments. It is likely that koergen and BC associated with these pristine marine sediments may not be encapsulated with humic acids or Fe and Mn oxides and hydroxides as often do in terrestrial soils and sediments. As a result, they may be fully accessible to sorbing molecules, exhibiting higher sorption capacities. The study suggests that competition from background HOCs and reduced accessibility when kerogen and BC are associated with terrestrial sediments may dramatically increase variability of sorption reactivities of geosorbents. Such variability may lead to large uncertainties in the prediction of sorption from the contents of kerogen and/or BC along with TOC.     

Concentrations of volatile organic compounds,carbon monoxide,carbon dioxide and particulate matter in buses on highways in Taiwan

Although airborne pollutants in urban buses have been studied in many cities globally, long-distance buses running mainly on highways have not been addressed in this regard. This study investigates the levels of volatile organic compounds (VOCs), carbon monoxide (CO), carbon dioxide (CO₂) and particulate matter (PM) in the long-distance buses in Taiwan. Analytical results indicate that pollutants levels in long-distance buses are generally lower than those in urban buses. This finding is attributable to the driving speed and patterns of long-distance buses, as well as the meteorological and geographical features of the highway surroundings. The levels of benzene, toluene, ethylbenzene and xylene (BTEX) found in bus cabins exceed the proposed indoor VOC guidelines for aromatic compounds, and are likely attributable to the interior trim in the cabins. The overall average CO level is 2.3 ppm, with higher average level on local streets (2.9 ppm) than on highways (2.2 ppm). The average CO₂ level is 1493 ppm, which is higher than the guideline for non-industrial occupied settings. The average PM level in this study is lower than those in urban buses and IAQ guidelines set by Taiwan EPA. However, the average PM₁₀ and PM_2.5 is higher than the level set by WHO. Besides the probable causes mentioned above, fewer passenger movements and less particle re-suspension from bus floor might also cause the lower PM levels. Measurements of particle size distribution reveal that more than 75% of particles are in submicron and smaller sizes. These particles may come from the infiltration from the outdoor air. This study concludes that air exchange rates in long-distance buses should be increased in order to reduce CO₂ levels. Future research on long-distance buses should focus on the emission of VOCs from brand new buses, and the sources of submicron particles in bus cabins.     

Validating a nondestructive optical method for apportioning colored particulate matter into black carbon and additional components

Exposure of black carbon (BC) is associated with a variety of adverse health outcomes. A number of optical methods for estimating BC on Teflon filters have been adopted but most assume all light absorption is due to BC while other sources of colored particulate matter exist. Recently, a four-wavelength-optical reflectance measurement for distinguishing second hand cigarette smoke (SHS) from soot-BC was developed (Brook et al., 2010; Lawless et al., 2004). However, the method has not been validated for soot-BC nor SHS and little work has been done to look at the methodological issues of the optical reflectance measurements for samples that could have SHS, BC, and other colored particles. We refined this method using a lab-modified integrating sphere with absorption measured continuously from 350 nm to 1000 nm. Furthermore, we characterized the absorption spectrum of additional components of particulate matter (PM) on PM(2.5) filters including ammonium sulfate, hematite, goethite, and magnetite. Finally, we validate this method for BC by comparison to other standard methods. Use of synthesized data indicates that it is important to optimize the choice of wavelengths to minimize computational errors as additional components (more than 2) are added to the apportionment model of colored components. We found that substantial errors are introduced when using 4 wavelengths suggested by Lawless et al. to quantify four substances, while an optimized choice of wavelengths can reduce model-derived error from over 10% to less than 2%. For environmental samples, the method was sensitive for estimating airborne levels of BC and SHS, but not mass loadings of iron oxides and sulfate. Duplicate samples collected in NYC show high reproducibility (points consistent with a 1:1 line, R(2) = 0.95). BC data measured by this method were consistent with those measured by other optical methods, including Aethalometer and Smoke-stain Reflectometer (SSR); although the SSR looses sensitivity at filter loadings above 90 ng/mm(2). Furthermore, positive correlations (R(2) = 0.7) were observed between EC measured by NIOSH Method 5040 on quartz filters and BC measured in co-located Teflon filter samples collected from both heating and non-heating seasons. Overall, the validation data demonstrates the usefulness of this method to evaluate BC from archived Teflon filters while potentially providing additional component information.     

Analysis and apportionment of organic carbon and fine particulate matter sources at multiple sites in the midwestern United States

Speciated fine particulate matter (PM2.5) data collected as part of the Speciation Trends Network at four sites in the Midwest (Detroit, MI; Cincinnati, OH; Indianapolis, IN; and Northbrook, IL) and as part of the Interagency Monitoring of Protected Visual Environments program at the rural Bondville, IL, site were analyzed to understand sources contributing to organic carbon (OC) and PM2.5 mass. Positive matrix factorization (PMF) was applied to available data collected from January 2002 through March 2005, and seven to nine factors were identified at each site. Common factors at all of the sites included mobile (gasoline)/secondary organic aerosols with high OC, diesel with a high elemental carbon/OC ratio (only at the urban sites), secondary sulfate, secondary nitrate, soil, and biomass burning. Identified industrial factors included copper smelting (Northbrook, Indianapolis, and Bondville), steel/manufacturing with iron (Northbrook), industrial zinc (Northbrook, Cincinnati, Indianapolis, and Detroit), metal plating with chromium and nickel (Detroit, Indianapolis, and Bondville), mixed industrial with copper and iron (Cincinnati), and limestone with calcium and iron (Bondville). PMF results, on average, accounted for 96% of the measured PM2.5 mass at each site; residuals were consistently within tolerance (+/-3), and goodness-of-fit (Q) was acceptable. Potential source contribution function analysis helped identify regional and local impacts of the identified source types. Secondary sulfate and soil factors showed regional characteristics at each site, whereas industrial sources typically appeared to be locally influenced. These regional factors contributed approximately one third of the total PM2.5 mass, on average, whereas local mobile and industrial sources contributed to the remaining mass. Mobile sources were a major contributor (55-76% at the urban sites) to OC mass, generally with at least twice as much mass from nondiesel sources as from diesel. Regional OC associated with secondary sulfate and soil was generally low.     

Absorption and fluorescence properties of chromophoric dissolved organic matter: implications for the monitoring of water quality in a large subtropical reservoir

The development of techniques for real-time monitoring of water quality is of great importance for effectively managing inland water resources. In this study, we first analyzed the absorption and fluorescence properties in a large subtropical reservoir and then used a chromophoric dissolved organic matter (CDOM) fluorescence monitoring sensor to predict several water quality parameters including the total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), dissolved organic carbon (DOC), and CDOM fluorescence parallel factor analysis (PARAFAC) components in the reservoir. The CDOM absorption coefficient at 254 nm (a(254)), the humic-like component (C1), and the tryptophan-like component (C3) decreased significantly along a gradient from the northwest to the lake center, northeast, southwest, and southeast region in the reservoir. However, no significant spatial difference was found for the tyrosine-like component (C2), which contributed only four marked peaks. A highly significant linear correlation was found between the a(254) and CDOM concentration measured using the CDOM fluorescence sensor (r ²?=?0.865, n?=?76, p?相似文献   

A Possible formation pathway for the 2-nitrofluoranthene observed in ambient particulate organic matter

The reaction of N₂O₅ with gaseous fluoranthene has been shown to be a possible formation pathway for the 2-nitrofluoranthene observed in ambient particulate organic matter.     

Polycyclic aromatic hydrocarbons and total extractable particulate organic matter in the Arctic aerosol

Samples of total suspended paniculate matter were collected in March and August 1979 at Barrow, Alaska, a remote site in the Arctic. Ambient concentrations of extractable paniculate organic matter (POM), of polycyclic aromatic hydrocarbons (PAH) and of ²¹⁰Pb were determined. The samples were also examined by optical and scanning electron microscopy. Average concentrations of POM and PAH were similar to those reported for other remote sites in the northern hemisphere, but the concentrations were considerably higher in March than in August. The presence of fly ash in the samples collected during the March sampling period, as well as seasonal differences in the concentrations of the organic species and ²¹⁰Pb and in meteorology indicate that the principal source of POM and PAH was fossil fuel combustion in the mid-latitudes during the March sampling period.     

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.     

An evaluation of measurement methods for organic, elemental and black carbon in ambient air monitoring sites

The carbonaceous components of Particulate Matter samples form a substantial fraction of their total mass, but their quantification depends strongly on the instruments and methods used. United Kingdom monitoring networks have provided many relevant data sets that are already in the public domain. Specifically, hourly organic carbon (OC) and elemental carbon (EC) were determined at four sites between 2003 and 2007 using Rupprecht and Pattashnik (R & P) 5400 automatic instruments. Since 2007, daily OC/EC measurements have been made by manual thermo-optical analysis of filter samples using a Sunset Laboratory Carbon Aerosol Analysis instrument. In parallel, long term daily measurements of Black Smoke, a quantity directly linked to black carbon (measured by aethalometers) and indirectly related to elemental carbon, have been made at many sites. The measurement issues associated with these techniques are evaluated in the context of UK measurements, making use of several sets of parallel data, with the aim of aiding the interpretation of network results. From the results available, the main conclusions are that the R & P 5400 instruments greatly under-read EC and total carbon (TC = OC + EC) at kerbside sites, probably due to the fact that the smaller particles are not sampled by the instrument; the R & P 5400 instrument is inherently difficult to characterise, so that all quantitative results need to be treated with caution; both aethalometer and Black Smoke (converted to black carbon) measurements can show reasonable agreement with elemental carbon results; and manual thermo-optical OC/EC results may under-read EC (and hence over-read OC), whether either transmittance or reflectance is used for the pyrolysis correction, and this effect is significant at rural sites.     

Determination of 2-nitrofluoranthene and 2-nitropyrene in ambient particulate organic matter: Evidence for atmospheric reactions

We have identified and quantified 2-nitrofluoranthene (2-NO₂-FL) and 2-nitropyrene (2-NO₂-PY), both strong, direct mutagens in paniculate organic matter (POM) samples collected in polluted ambient air in southern California. Samples were collected during four consecutive 6-h periods on 18–19 September 1984, during which the ambient concentrations of gaseous co-pollutants were characterized by long pathlength spectroscopic techniques and conventional analyzers. Concentrations ranged up to 0.3 ng m⁻³ for 2-NO₂-FL and 0.02 ng m⁻³ for 2-NO₂-PY. The 2-nitro isomers of fluoranthene and pyrene have not been observed in direct emissions of POM (e.g. diesel exhaust and wood smoke). However, we recently observed these isomers from laboratory reactions involving N₂O₅ or OH radicals and the parent compounds. Thus the identification of 2-NO₂-FL and 2-NO₂-PY in ambient POM suggests that chemical transformations of fluoranthene and pyrene may take place in polluted atmospheres.     

Correction to: Determination of phthalates in particulate matter and gaseous phase emitted in indoor air of offices

Environmental Science and Pollution Research - A Correction to this paper has been published: https://doi.org/10.1007/s11356-020-11749-1     

Tracing the sources of refractory dissolved organic matter in a large artificial lake using multiple analytical tools

Structural and chemical characteristics of refractory dissolved organic matter (RDOM) from seven different sources (algae, leaf litter, reed, compost, field soil, paddy water, treated sewage) were examined using multiple analytical tools, and they were compared with those of RDOM in a large artificial lake (Lake Paldang, Korea). Treated sewage, paddy water, and field soil were distinguished from the other sources investigated by their relatively low specific UV absorbance (SUVA) values and more pronounced fulvic-like versus humic-like fluorescence of the RDOM samples. Microbial derived RDOM from algae and treated sewage showed relatively low apparent molecular weight and a higher fraction of hydrophilic bases relative to the total hydrophilic fraction. For the biopolymer types, the presence of polyhydroxy aromatics with the high abundance of proteins was observed only for vascular plant-based RDOM (i.e., leaf litter and reed). Molecular weight values exhibited positive correlations with the SUVA and the hydrophobic content among the different RDOM, suggesting that hydrophobic and condensed aromatic structures may be the main components of high molecular weight RDOM. Principal component analysis revealed that approximately 77% of the variance in the RDOM characteristics might be explained by the source difference (i.e., terrestrial and microbial derived) and a tendency of further microbial transformation. Combined results demonstrated that the properties of the lake RDOM were largely affected by the upstream sources of field soil, paddy water, and treated sewage, which are characterized by low molecular weight UV-absorbing and non-aromatic structures with relatively high resistance to further degradation.     

Emission factors of fine particulate matter,organic and elemental carbon,carbon monoxide,and carbon dioxide for four solid fuels commonly used in residential heating by the U.S. Navajo Nation

Most homes in the Navajo Nation use wood as their primary heating fuel, often in combination with locally mined coal. Previous studies observed health effects linked to this solid-fuel use in several Navajo communities. Emission factors (EFs) for common fuels used by the Navajo have not been reported using a relevant stove type. In this study, two softwoods (ponderosa pine and Utah juniper) and two high-volatile bituminous coals (Black Mesa and Fruitland) were tested with an in-use residential conventional wood stove (homestove) using a modified American Society for Testing and Materials/U.S. Environmental Protection Agency (ASTM/EPA) protocol. Filter sampling quantified PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm) and organic (OC) and elemental (EC) carbon in the emissions. Real-time monitoring quantified carbon monoxide (CO), carbon dioxide (CO₂), and total suspended particles (TSP). EFs for these air pollutants were developed and normalized to both fuel mass and energy consumed. In general, coal had significantly higher mass EFs than wood for all pollutants studied. In particular, coal emitted, on average, 10 times more PM_2.5 than wood on a mass basis, and 2.4 times more on an energy basis. The EFs developed here were based on fuel types, stove design, and operating protocols relevant to the Navajo Nation, but they could be useful to other Native Nations with similar practices, such as the nearby Hopi Nation.

Implications: Indoor wood and coal combustion is an important contributor to public health burdens in the Navajo Nation. Currently, there exist no emission factors representative of Navajo homestoves, fuels, and practices. This study developed emission factors for PM_2.5, OC, EC, CO, and CO₂ using a representative Navajo homestove. These emission factors may be utilized in regional-, national-, and global-scale health and environmental models. Additionally, the protocols developed and results presented here may inform on-going stove design of the first EPA-certified wood and coal combination stove.     

Modeling the space/time distribution of particulate matter in Thailand and optimizing its monitoring network

The space/time distribution of PM₁₀ in Thailand is modeled using the Bayesian maximum entropy (BME) method of modern spatiotemporal geostatistics. Three kinds of BME spatiotemporal maps over Thailand are sought on the most polluted day for each year of a 6-year period from 1998 to 2003. These three maps are (1) the map of the BME estimate of daily PM₁₀, (2) the map of the associated BME prediction error, and (3) the BME non-attainment map showing areas where the BME estimate does not attain a 68% probability of meeting the ambient standard for PM₁₀. These detailed space/time PM₁₀ maps provide invaluable information for decision-makers in air quality management. Knowing accurately the spatiotemporal distribution of PM₁₀ is necessary to develop and evaluate strategies used to abate PM₁₀ levels. The space/time BME estimate of PM₁₀ on the worst day of the year offers a general picture as to where daily PM₁₀ levels are not in compliance with the air-quality standard. Delineating these areas leads to the BME non-attainment maps, which are useful in identifying unhealthy zones, where sensitive population such as asthmatic children, seniors, or those with cardiopulmonary disease should be advised to avoid outdoor activities. The results of the space/time BME analysis of PM₁₀ are further extended to assess whether the current monitoring network is adequate. The current distribution of monitoring stations can be evaluated by combining the available demographic information with the BME estimation error maps. Administrative districts with large population size and high BME normalized estimation error are suggested as the target for adding new monitoring stations.