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.     

The impact of wood smoke on ambient PM2.5 in northern Rocky Mountain valley communities

During the winters of 2006/2007 and 2007/2008, PM_2.5 source apportionment programs were carried out within five western Montana valley communities. Filter samples were analyzed for mass and chemical composition. Information was utilized in a Chemical Mass Balance (CMB) computer model to apportion the sources of PM_2.5. Results showed that wood smoke (likely residential woodstoves) was the major source of PM_2.5 in each of the communities, contributing from 56% to 77% of the measured wintertime PM_2.5. Results of ¹⁴C analyses showed that between 44% and 76% of the measured PM_2.5 came from a new carbon (wood smoke) source, confirming the results of the CMB modeling. In summary, the CMB model results, coupled with the ¹⁴C results, support that wood smoke is the major contributor to the overall PM_2.5 mass in these rural, northern Rocky Mountain airsheds throughout the winter months.     

Temporal variation and impact of wood smoke pollution on a residential area in southern Germany

This paper is a continuation of our previous publication (Bari, M.A., Baumbach, G., Kuch, B., Scheffknecht, G., 2009. Wood smoke as a source of particle-phase organic compounds in residential areas. Atmospheric Environment 43, 4722–4732) and describes a detailed characterisation of different particle-phase wood smoke tracer compounds in order to find out the impact of wood-fired heating on ambient PM₁₀ pollution in a residential area near Stuttgart in southern Germany. The results from previous flue gas measurements help distinguishing different tracer compounds in ambient PM₁₀ samples. In the residential area, significant amounts of hardwood markers (syringaldehyde, acetosyringone, propionylsyringol, sinapylaldehyde) and low concentrations of softwood markers (vanillin, acetovanillone, coniferyldehyde, dehydroabietic acid, retene) were found in the ambient air. The general wood combustion markers Levoglucosan, mannosan and galactosan were detected in high concentrations in all particle-phase PM₁₀ samples. To find out the size distribution of ambient particles, cascade impactor measurements were carried out. It was found that more than 70% of particulate matter was in the particle diameter of less than 1 μm. Using emission ratio of levoglucosan to PM₁₀, it can be demonstrated that during winter months 59% of ambient PM₁₀ pollution could be attributed to residential wood-fired heating.     

Carbon Monoxide in an Urban Environment: Application of a Receptor Model for Source Apportionment

During the winter of 1985-86 the authors took 6-h integrated air samples and measured the concentrations of carbon monoxide and other gases at a residential site in Olympia, Washington. The 6-h average concentrations were between about 0.2 and 3.2 ppmv. For each 6-h period the observed concentration of CO was apportioned among its sources which were residential wood burning and automobiles. Small and generally insignificant amounts of CO were also observed from unidentified sources. A chemical mass balance (CMB) was formulated and applied to apportion the observed CO among its sources. Methylchloride (CH₃CI), in excess of background levels, was used as a unique tracer of wood burning and excess hydrogen (H₂) served as a tracer of CO from automobiles. The source emission factors to carry out the calculations were estimated from other experiments. The results showed that in Olympia, wood burning can often contribute as much CO as automobiles during winter. The maximum 6-h average contribution of CO from wood burning was about 2 ppmv and from automobiles it was 2.2 ppmv, and the average ambient concentration was about 1 ppmv. When pollution from wood burning was present, it contributed 0.5 ppmv on average while automobiles also contributed 0.5 ppmv. Unidentified sources contributed 0.1 ppmv and the background level was 0.15 ppmv. During the winter many times wood burning did not affect CO concentrations, while CO from automobiles was always present. On average, during the winter, automobiles contributed some 50 percent of the CO mass to the lower urban atmosphere and wood burning contributed about 30 percent. Diurnal cycles became evident in the calculated concentrations of CO from wood burning and automobiles even though the measured concentrations did not show strong diurnal variations. Wood burning contributed most during evening and nighttime and very little during the day, while automobiles contributed most during the morning and evening hours and very little at night. These patterns lend support to the accuracy of the model and source emission factors since they are as expected from the diurnal variations of the sources and atmospheric mixing.     

Wood smoke contribution to winter aerosol in Fresno, CA

In an effort to better quantify wintertime particulate matter (PM) and the contribution of wood smoke to air pollution events in Fresno, CA, a field campaign was conducted in winter 2003-2004. Coarse and fine daily PM samples were collected at five locations in Fresno, including residential, urban, and industrial areas. Measurements of collected samples included gravimetric mass determination, organic and elemental carbon analysis, and trace organic compound analysis by gas chromatograph mass spectrometry (GC/MS). The wood smoke tracer levoglucosan was also measured in aqueous aerosol extracts using high-performance anion exchange chromatography coupled with pulsed amperometric detection. Sample preparation and analysis by this technique is much simpler and less expensive than derivatized levoglucosan analysis by GC/MS, permitting analysis of daily PM samples from all five of the measurement locations. Analyses revealed low spatial variability and similar temporal patterns of PM2.5 mass, organic carbon (OC), and levoglucosan. Daily mass concentrations appear to have been strongly influenced by meteorological conditions, including precipitation, wind, and fog events. Fine PM (PM2.5) concentrations are uncommonly low during the study period, reflecting frequent precipitation events. During the first portion of the study, levoglucosan had a strong relationship to the concentrations of PM2.5 and OC. In the later portion of the study, there was a significant reduction in levoglucosan relative to PM2.5 and OC. This may indicate a change in particle removal processes, perhaps because of fog events, which were more common in the latter period. Combined, the emissions from wood smoke, meat cooking, and motor vehicles appear to contribute approximately 65-80% to measured OC, with wood smoke, on average, accounting for approximately 41% of OC and approximately 18% of PM2.5 mass. Two residential sites exhibit somewhat higher contributions of wood smoke to OC than other locations.     

Source apportionment of fine particles at urban background and rural sites in the UK atmosphere

Airborne fine particulate matter (PM_2.5) has been collected at two sites in the West Midlands conurbation, UK, representing urban background and rural locations. Chemical analyses have been carried out for major anions, trace metals, total OC and EC, and for individual organic marker species including n-alkanes, hopanes, PAHs, organic acids and sterols. Source apportionment has been conducted using both a pragmatic mass closure model and the US EPA chemical mass balance (CMB) model. The pragmatic mass closure model is well able to account for the measured PM_2.5 mass in terms of chemical/source components, and the chemical mass balance model has been used to apportion the carbonaceous component of the aerosol. The dominant components of PM_2.5 at both sites are secondary inorganic (sulphate and nitrate) and carbonaceous particles. The CMB model shows the latter to arise mainly from road traffic sources, with smaller contributions from vegetative detritus, wood smoke, natural gas, coal, and dust/soil. The CMB model also identifies an important component of the organic aerosol not associated with these primary sources, which correlates very strongly with secondary organic aerosol estimated from the OC/EC ratio. The split between different automotive source types does not relate well to UK emission inventories, and may indicate that CMB source profiles from North American studies and different carbon analysis protocols may lead to erroneous conclusions.     

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.     

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.     

Wood Smoke Contribution to Winter Aerosol in Fresno,CA

Abstract

In an effort to better quantify wintertime particulate matter (PM) and the contribution of wood smoke to air pollution events in Fresno, CA, a field campaign was conducted in winter 2003–2004. Coarse and fine daily PM samples were collected at five locations in Fresno, including residential, urban, and industrial areas. Measurements of collected samples included gravimetric mass determination, organic and elemental carbon analysis, and trace organic compound analysis by gas chromatograph mass spectrometry (GC/MS). The wood smoke tracer levoglucosan was also measured in aqueous aerosol extracts using high-performance anion exchange chromatography coupled with pulsed amperometric detection. Sample preparation and analysis by this technique is much simpler and less expensive than derivatized levoglucosan analysis by GC/MS, permitting analysis of daily PM samples from all five of the measurement locations. Analyses revealed low spatial variability and similar temporal patterns of PM_2.5 mass, organic carbon (OC), and levoglucosan. Daily mass concentrations appear to have been strongly influenced by meteorological conditions, including precipitation, wind, and fog events. Fine PM (PM_2.5) concentrations are uncommonly low during the study period, reflecting frequent precipitation events. During the first portion of the study, levoglucosan had a strong relationship to the concentrations of PM_2.5 and OC. In the later portion of the study, there was a significant reduction in levoglucosan relative to PM_2.5 and OC. This may indicate a change in particle removal processes, perhaps because of fog events, which were more common in the latter period. Combined, the emissions from wood smoke, meat cooking, and motor vehicles appear to contribute ~65–80% to measured OC, with wood smoke, on average, accounting for ~41% of OC and ~18% of PM_2.5 mass. Two residential sites exhibit somewhat higher contributions of wood smoke to OC than other locations.     

Comparison of receptor models for source apportionment of volatile organic compounds in Beijing, China

Identifying the sources of volatile organic compounds (VOCs) is key to reducing ground-level ozone and secondary organic aerosols (SOAs). Several receptor models have been developed to apportion sources, but an intercomparison of these models had not been performed for VOCs in China. In the present study, we compared VOC sources based on chemical mass balance (CMB), UNMIX, and positive matrix factorization (PMF) models. Gasoline-related sources, petrochemical production, and liquefied petroleum gas (LPG) were identified by all three models as the major contributors, with UNMIX and PMF producing quite similar results. The contributions of gasoline-related sources and LPG estimated by the CMB model were higher, and petrochemical emissions were lower than in the UNMIX and PMF results, possibly because the VOC profiles used in the CMB model were for fresh emissions and the profiles extracted from ambient measurements by the two-factor analysis models were "aged".     

Is levoglucosan a suitable quantitative tracer for wood burning? Comparison with receptor modeling on trace elements in Lycksele, Sweden

Particle emissions from residential wood combustion in small communities in Northern Sweden can sometimes increase the ambient particle concentrations to levels comparable to densely trafficked streets in the center of large cities. The reason for this is the combination of increased need for domestic heating during periods of low temperatures, leading to higher emission rates, and stable meteorological conditions. In this work, the authors compare two different approaches to quantify the wood combustion contribution to fine particles in Northern Sweden: a multivariate source-receptor analysis on inorganic compounds followed by multiple linear regression (MLR) of fine particle concentrations and levoglucosan used as a tracer. From the receptor model, it can be seen that residential wood combustion corresponds with 70% of modeled particle mass. Smaller contributions are also seen from local nonexhaust traffic particles, road dust, and brake wear (each contributing 14%). Of the mass, 1.5% is explained by long-distance transported particles, and 2% derives from a regional source deriving from either oil combustion or smelter activities. In samples collected in ambient air, a significant linear correlation was found between wood burning particles and levoglucosan. The levoglucosan fraction in the ambient fine particulate matter attributed to wood burning according to the multivariate analysis ranged from < 2% to 50%. This is much higher than the fraction found in the emission from the boilers expected to be responsible for most emissions at this site (between 3% and 6%). A laboratory emission study of wood and pellet boilers gave 0.3% wt to 22% wt levoglucosan to particle mass, indicating that the levoglucosan fraction may be highly dependent on combustion conditions, making it uncertain to use it as a quantitative tracer under real-world burning conditions. Thus, quantitative estimates of wood burning contributions will be very uncertain using solely levoglucosan as a tracer.     

Characterization of saccharides and other organic compounds in fine particles and the use of saccharides to track primary biologically derived carbon sources

A total of 134 aerosol samples (d_p < 2.5 μm) were collected at one rural site and one urban site in Texas from November 2005 to July 2006 to investigate the different sources that contribute to the ambient levels of different compounds. In particular, saccharide compounds were studied as potential tracers to track aerosols of biologically derived origin. The ambient concentration, seasonal variation, and urban/rural comparison of major saccharides and other organic compounds including normal alkanes, hopanes, and carboxylic acids were determined and analyzed relative to characterizing sources of PM2.5. Saccharides, together with other known molecular markers, were analyzed by a positive matrix factorization model and eight source factors were isolated that provide meaningful interpretation of aerosol sources. Three isolated factors were characterized by the dominance of different saccharide compounds and were attributed to wood smoke, sucrose rich bio-aerosols, and fungal spore derived bio-aerosols. It was estimated that wood smoke and primary biologically derived carbon sources contributed 22% and 14% to the measured ambient PM2.5 mass at San Augustine and 16% and 5% to the measured ambient PM2.5 mass at Dallas. The relative PM contribution from other resolved sources were also calculated.     

Is Levoglucosan a Suitable Quantitative Tracer for Wood Burning? Comparison with Receptor Modeling on Trace Elements in Lycksele,Sweden

Abstract

Particle emissions from residential wood combustion in small communities in Northern Sweden can sometimes increase the ambient particle concentrations to levels comparable to densely trafficked streets in the center of large cities. The reason for this is the combination of increased need for domestic heating during periods of low temperatures, leading to higher emission rates, and stable meteorological conditions. In this work, the authors compare two different approaches to quantify the wood combustion contribution to fine particles in Northern Sweden: a multivariate source-receptor analysis on inorganic compounds followed by multiple linear regression (MLR) of fine particle concentrations and levoglucosan used as a tracer. From the receptor model, it can be seen that residential wood combustion corresponds with 70% of modeled particle mass. Smaller contributions are also seen from local nonexhaust traffic particles, road dust, and brake wear (each contributing 14%). Of the mass, 1.5% is explained by long-distance transported particles, and 2% derives from a regional source deriving from either oil combustion or smelter activities.

In samples collected in ambient air, a significant linear correlation was found between wood burning particles and levoglucosan. The levoglucosan fraction in the ambient fine particulate matter attributed to wood burning according to the multivariate analysis ranged from <2% to 50%. This is much higher than the fraction found in the emission from the boilers expected to be responsible for most emissions at this site (between 3% and 6%). A laboratory emission study of wood and pellet boilers gave 0.3%_wt to 22%_wt levoglucosan to particle mass, indicating that the levoglucosan fraction may be highly dependent on combustion conditions, making it uncertain to use it as a quantitative tracer under real-world burning conditions. Thus, quantitative estimates of wood burning contributions will be very uncertain using solely levoglucosan as a tracer.     

Source apportionment with site specific source profiles

A receptor modeling study was performed to identify and apportion the sources of PM10 mass in Granite City, Illinois, an area of historic TSP nonattainment. Samples of the ambient aerosol were collected using a dichotomous sampler. Each sample was analyzed by x-ray fluorescence and instrumental neutron activation analysis. To begin the study, a factor analysis was performed. Two different chemical mass balance (CMB) analyses were then made. The first CMB analysis used only source profiles available from the literature while the second included twelve source profiles developed from dust samples collected in Granite City. Both CMB analyses used 20 of the 33 analyzed elements since many of the source profiles in the literature did not include the other thirteen elements. The results from both sets of CMB analyses were grouped by the predominate wind direction at the site during the time each sample was taken to identify the direction of each source relative to the sampler. It was found that regional sources were the primary contributors to the fine fraction while the coarse fraction was composed of material from local industries. These sources were generally the ones identified during the Regional Air Pollution Study previously conducted in the area. However, the emission profiles from these sources were observed to have changed between the studies. It was also found that the use of the locally generated profiles greatly improved the results of the CMB analysis.     

Wood burning impact on PM10 in three Austrian regions

Anhydrosugars (levoglucosan, mannosan and galactosan) were investigated during one year in three Austrian regions at three types of sites (city-heavy traffic-impacted, city-residential and background) in order to assess the magnitude of the contribution of wood smoke to the particulate matter load and its organic fraction. The annually averaged concentrations of levoglucosan ranged from 0.12 to 0.48 μg m^?3. The levoglucosan concentration exhibited a strong annual cycle with higher concentrations in the cold season. The minor anhydrosugars had a similar annual trend, but their concentrations were lower by a factor of about 5 and about 25 in the cold season for mannosan and galactosan, respectively. Levoglucosan concentrations were higher at the inner-urban as compared to rural sites. The contribution of wood smoke to organic carbon and PM₁₀ levels was calculated using a constant ratio of levoglucosan and OC, respectively PM₁₀ as derived for fire wood typical for Alpine European regions [Schmidl, C., Marr, I.L., Caseiro, A.e, Kotianová, P., Berner, A., Bauer, H., Kasper-Giebl, A., Puxbaum, H., 2008a. Chemical characterisation of fine particle emissions from wood stove combustion of common woods growing in mid-European Alpine regions. Atmospheric Environment 42, 126–141]. The estimated contribution of wood smoke-OC to the OC of PM₁₀ ranged from one third to more than half in the cold season with higher contributions up to 70% in winter (December, January and February) in the smaller cities and the rural background. This indicates, that wood smoke is the predominant source of organic material at rural and small urban sites in central Europe. Consistently, wood smoke was an important contributor to PM₁₀ during the cold season, with contributions of around 10% in the Vienna larger region and around 20% at rural sites in the densely forested regions of Salzburg and Styria during the winter months. In those regions residential sites exhibited highest relative wood smoke contents in PM₁₀ during autumn (September till November), indicating the use of wood stoves for auxiliary heating in the transition of warm to cold season. Using the relationships between the different anhydrosugars the combustion of softwood was found to be dominant for the wood smoke occurrence in ambient air at the investigated sites. Potassium, a commonly used tracer for biomass burning, correlated well to levoglucosan, with a mass ratio of around 0.80 in the cold season.     

Source contributions to fine particulate matter in an urban atmosphere

This paper proposes a practical method for estimating source attribution by using a three-step methodology. The main objective of this study is to explore the use of the three-step methodology for quantifying the source impacts of 24-h PM2.5 particles at an urban site in Seoul, Korea. 12-h PM2.5 samples were collected and analyzed for their elemental composition by ICP-AES/ICP-MS/AAS to generate the source composition profiles. In order to assess the daily average PM2.5 source impacts, 24-h PM2.5 and polycyclic aromatic hydrocarbons (PAH) ambient samples were simultaneously collected at the same site. The PM2.5 particle samples were then analyzed for trace elements. Ionic and carbonaceous species concentrations were measured by ICP-AES/ICP-MS/AAS, IC, and a selective thermal MnO2 oxidation method. The 12-h PM2.5 chemical data was used to estimate possible source signatures using the principal component analysis (PCA) and the absolute principal component scores method followed by the multiple linear regression analysis. The 24-h PM2.5 source categories were extracted with a combination of PM2.5 and some PAH chemical data using the PCA, and their quantitative source contributions were estimated by chemical mass balance (CMB) receptor model using the estimated source profiles and those in the literature. The results of PM2.5 source apportionment using the 12-h derived source composition profiles show that the CMB performance indices; chi2, R2, and percent of mass accounted for are 2.3%, 0.97%, and 100.7%, which are within the target range specified. According to the average PM2.5 source contribution estimate results, motor vehicle exhaust was the major contributor at the sampling site, contributing 26% on average of measured PM2.5 mass (41.8 microg m-3), followed by secondary sulfate (23%) and nitrate (16%), refuse incineration (15%), soil dust (13%), field burning (4%), oil combustion (2.7%), and marine aerosol (1.3%). It can be concluded that quantitative source attribution to PM2.5 in an urban area where source profiles have not been developed can be estimated using the proposed three-step methodology approach.     

Chemical mass balance receptor model applied to ambient C2–C9 VOC concentration in Seoul,Korea: Effect of chemical reaction losses

A chemical mass balance (CMB) receptor model was used for estimating the diurnal contributions of VOC emission sources to the ambient C₂–C₉ VOC concentration in Seoul, Korea. For this purpose, the VOC concentrations were measured in the morning, the afternoon, and the evening. The samples were collected using a 2-h integrated SUMMA canister. The source profiles were developed for the CMB calculation in the Seoul area. To investigate the effect of the chemical reaction loss of VOCs on the CMB calculation, the modified model employing a decay factor and the standard model that considers no loss were compared. The modified model estimated that the vehicle exhaust (52%) was the largest leading source of VOCs in the Seoul atmosphere, followed by the use of solvents (26%), gasoline evaporation (15%), the use of liquefied petroleum gas (LPG) (5%), and the use of liquefied natural gas (LNG) (2%). Relative source contribution for vehicle exhaust showed a clear diurnal variation with a high in the morning and evening and a low in the afternoon, while the contribution of evaporative emissions (gasoline evaporation and solvent usage) showed a different diurnal pattern from that of the vehicle exhaust, exhibiting a high in the afternoon and evening and a low in the morning. It was found that the difference between the total source contribution (μg m⁻³) estimated from these two models was not statistically significant. However, when the paired-sample t-test is applied to the individual sources, a significant difference was found for the vehicle exhaust and the solvent use. In addition, the modified model brought forth a better performance with high R² and low χ² as compared to those obtained from the standard model in the CMB calculation. The vehicle exhaust and solvent use were estimated to be the largest and the second largest contributors to ambient benzene as well as ozone formation potential (OFP), respectively. Based on above results we believe that incorporating the reaction loss in the CMB calculations helps to better fit the source profile to the ambient VOC concentrations. However, the reaction loss does not significantly affect the estimation of source contributions.     

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.     

Combined source apportionment,using positive matrix factorization–chemical mass balance and principal component analysis/multiple linear regression–chemical mass balance models

The methods of positive matrix factorization–chemical mass balance and principal component analysis/multiple linear regression–chemical mass balance were studied in this paper, for combined source apportionment. Due to the high similarity among the source profiles, several problems would raised when only one receptor model was applied. For example, the collinearity problem would result in the negative contributions when applying CMB model; certain sources would not to be separated out when applying PCA or PMF model. In this study, PCA/MLR–CMB model and PMF–CMB were attempted to resolve the problem, where the combined models were applied to study the synthetic and ambient datasets. In synthetic dataset, there were seven sources (six actual sources from real world, and one unknown source). The results obtained by the combined models show that the combined source apportionment technique is feasible. In addition, an ambient dataset from a northern city in China was analyzed by PCA/MLR–CMB model and PMF–CMB model, and these two models got the similar results. The results show that coal combustion contributed the largest fraction to the total mass.     

Diagnostics for Determining Influential Species in the Chemical Mass Balance Receptor Model

ABSTRACT

The chemical mass balance (CMB) model can be applied to estimate the amount of airborne particulate matter (PM) coming from various sources given the ambient chemical composition of the particles measured at the receptor and the chemical composition of the source emissions. Of considerable practical importance is the identification of those chemical species that have a large effect on either the source contributions or errors estimated by the CMB model. This paper details a study of a number of influential diagnostics for application of the CMB software. Some of the diagnostics studied are standard regression diagnostics based on single-row deletion diagnostics. A number of new diagnostics were developed specifically for the CMB application, based on the pseudo-inverse of the source composition matrix and called nondeletion diagnostics to distinguish them from the standard deletion diagnostics. Simulated data sets were generated to compare the diagnostics and their response to controlled amounts of random error.

A particular diagnostic called a modified pseudoinverse matrix (MPIN), developed for this study, was found to be the best choice for CMB model application. The MPIN diagnostic contains virtually all the information present in both deletion and nondeletion diagnostics. Since the MPIN diagnostic requires only the source profiles, it can be used to identify influential species in advance without sampling the ambient data and to improve CMB results through possible remedial actions for the influential species. Specific recommendations are given for interpretation and use of the MPIN diagnostic with the CMB model software. Elements with normalized MPIN absolute values of 1 to 0.5 are associated with influential elements. Noninfluential elements have normalized MPIN absolute values of 0.3 or less. Elements with absolute values between 0.3 and 0.5 are ambiguous but should generally be considered noninfluential.