Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data

Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified.     

Source apportionment: findings from the U.S. Supersites Program

Receptor models are used to identify and quantify source contributions to particulate matter and volatile organic compounds based on measurements of many chemical components at receptor sites. These components are selected based on their consistent appearance in some source types and their absence in others. UNMIX, positive matrix factorization (PMF), and effective variance are different solutions to the chemical mass balance (CMB) receptor model equations and are implemented on available software. In their more general form, the CMB equations allow spatial, temporal, transport, and particle size profiles to be combined with chemical source profiles for improved source resolution. Although UNMIX and PMF do not use source profiles explicitly as input data, they still require measured profiles to justify their derived source factors. The U.S. Supersites Program provided advanced datasets to apply these CMB solutions in different urban areas. Still lacking are better characterization of source emissions, new methods to estimate profile changes between source and receptor, and systematic sensitivity tests of deviations from receptor model assumptions.     

Source Apportionment: Findings from the U.S. Supersites Program

Abstract

Receptor models are used to identify and quantify source contributions to particulate matter and volatile organic compounds based on measurements of many chemical components at receptor sites. These components are selected based on their consistent appearance in some source types and their absence in others. UNMIX, positive matrix factorization (PMF), and effective variance are different solutions to the chemical mass balance (CMB) receptor model equations and are implemented on available software. In their more general form, the CMB equations allow spatial, temporal, transport, and particle size profiles to be combined with chemical source profiles for improved source resolution. Although UNMIX and PMF do not use source profiles explicitly as input data, they still require measured profiles to justify their derived source factors. The U.S. Supersites Program provided advanced datasets to apply these CMB solutions in different urban areas. Still lacking are better characterization of source emissions, new methods to estimate profile changes between source and receptor, and systematic sensitivity tests of deviations from receptor model assumptions.     

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.     

Characteristics and source apportionment of VOCs measured in Shanghai,China

Volatile organic compounds (VOCs) were measured from 2007 to 2010 at the center of Shanghai, China. Because VOCs are important precursors for ozone photochemical formation, detailed information of VOC sources needs to be investigated. The results show that the measured VOC concentrations in Shanghai are dominated by alkanes (43%) and aromatics (30%), following by halo-hydrocarbons (14%) and alkenes (6%). Based on the measured VOC concentrations, a receptor model (PMF; positive matrix factorization) coupled with the information related to VOC sources (the distribution of major industrial complex, meteorological conditions, etc.) is applied to identify the major VOC sources in Shanghai. The result shows that seven major VOC sources are identified by the PMF method, including (1) vehicle related source which contributes to 25% of the measured VOC concentrations, (2) solvent based industrial source to 17%, (3) fuel evaporation to 15%, (4) paint solvent usage to 15%, (5) steel related industrial production to 12%, (6) biomass/biofuel burning to 9%, and (7) coal burning to 7%. Furthermore, ozone formation potential related to VOC sources is calculated by the MIR (maximum incremental reactivity) technique. The most significant VOC source for ozone formation potential is solvent based industrial sources (27%), paint solvent usage (24%), vehicle related emissions (17%), steel related industrial productions (14%), fuel evaporations (9%), coal burning (6%), and biomass/biofuel burning (3%). The weekend effect on the VOC concentrations shows that VOC concentrations are generally higher in the weekdays than in the weekends at the sampling site, suggesting that traffic conditions and human activities have important impacts on the VOC emissions in Shanghai.     

Receptor Model Evaluation of the Southeast Michigan Ozone Study Ambient NMOC Measurements

Abstract

Large-scale studies like the Southeast Michigan Ozone Study (SEMOS) have focused attention on quantifying and spedating inventories for volatile organic compounds (VOCs). One approach for evaluating the accuracy of a VOC emission inventory is the development of a chemical mass balance (CMB) receptor model for ambient non-methane organic compound (NMOC) measurements. CMB evaluations of ambient hydrocarbon data provide a sample-specific allocation of emissions to individual source categories. This study summarizes the results of an application of the CMB model to the NMOC data from the SEMOS study. Comparison of CMB results with emission inventory values for the Detroit area show that vehicle emissions are well represented by the inventory, as are architectural coatings and coke ovens. Estimated emissions from petroleum refineries and graphic arts industries are much lower in the inventory than determined from the receptor allocation. Under-reporting of fugitive VOC emissions from petroleum refineries is an ongoing problem. Emissions from graphic arts industries are underestimated in the inventory partly because of the broad characterization of the emission factor (i.e., mass emitted/capita), which may be less useful when specific locations and days are under consideration. This study also demonstrates the effectiveness of the CMB approach when used prospectively to track the implementation of emission control strategies. While vehicle emission concentrations were unchanged from 1988 to 1993, measurement-based CMB results suggest a decrease in evaporative emissions during this time period resulting from Reid vapor pressure (RVP) reductions (from 11.0 psi in 1988 to 8.6 psi in 1993) and fleet turnover. Changes in emissions from coke plants and petroleum refineries were also seen in the CMB allocations for these sources.     

Sources of organic aerosol: Positive matrix factorization of molecular marker data and comparison of results from different source apportionment models

This paper presents results from positive matrix factorization (PMF) of organic molecular marker data to investigate the sources of organic carbon (OC) in Pittsburgh, Pennsylvania. PMF analysis of 21 different combinations of input species found essentially the same seven factors with distinctive source-class-specific groupings of molecular markers. To link factors with source classes we directly compare PMF factor profiles with actual source profiles. Six of the PMF factors appear related to primary emissions from sources such as motor vehicles, biomass combustion, and food cooking. Each primary factor contributed between 5% and 10% of the annual-average OC with the exception of the cooking related factor which contributed 20% of the OC. However, the contribution of the cooking factor was sensitive to the specific combinations of input species. PMF could not differentiate between gasoline and diesel emissions, but the aggregate contribution of primary emissions from these two source classes is estimated to be less than 10% of the annual-average OC. One factor appears related to secondary organic aerosol based on its substantial contribution to biogenic oxidation products. This secondary factor contributed more than 50% of the summertime average OC. Reasonable agreement was observed between the PMF results and those of a previously published chemical mass balance (CMB) analysis of the same molecular marker dataset. Individual PMF factors are correlated with specific CMB sources, but systematic biases exist between the two estimates. These biases were generally within the uncertainty of the two estimates, but there is also evidence that PMF is not cleanly differentiating between source classes.     

VOC source–receptor relationships in Houston during TexAQS-II

During the TRAMP field campaign in August–September 2006, C₂–C₁₀ volatile organic compounds (VOCs) were measured continuously and online at the urban Moody Tower (MT) site. This dataset was compared to corresponding VOC data sets obtained at six sites located in the highly industrialized Houston Ship Channel area (HSC). Receptor modeling was performed by positive matrix factorization (PMF) at all sites. Conditional probability functions (CPF) were used to determine the origin of the polluted air masses in the Houston area. A subdivision into daytime and nighttime was carried out to discriminate photochemical influences. Eight main source categories of industrial, mobile, and biogenic emissions were identified at the urban receptor site, seven and six, respectively, at the different HSC sites. At MT natural gas/crude oil contributed most to the VOC mass (27.4%), followed by liquefied petroleum gas (16.7%), vehicular exhaust (15.3%), fuel evaporation (14.3%), and aromatics (13.4%). Also petrochemical sources from ethylene (4.7%) and propylene (3.6%) play an important role. A minor fraction of the VOC mass can be attributed to biogenic sources mainly from isoprene (4.4%). Based on PMF analyses of different wind sectors, the total VOC mass was estimated to be twofold at MT with wind directions from HSC compared to air from a typical urban sector, for petrochemical compounds more than threefold. Despite the strong impact of air masses influenced by industrial sources at HSC, still about a third of the total mass contributions at MT can be apportioned to other sources, mainly motor vehicles and aromatic solvents. The investigation of diurnal variation in combination with wind directional frequencies revealed the greatest HSC impact at the urban site during the morning, and the least during the evening.     

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.     

Emissions of liquefied petroleum gas (LPG) from motor vehicles

Continuous on-site measurements of 50 speciated volatile organic compounds (VOCs) were conducted in downtown Guangzhou to characterize the sources and concentration profiles of ambient VOCs. The synchronicity in diurnal variation between the VOCs and NO suggests that traffic emissions were responsible for the observed VOCs in downtown Guangzhou.It was found that the three major constituent species of liquefied petroleum gas (LPG), i.e., propane, iso-butane, and n-butane, together termed LPG alkanes, contributed, on average, 24% of the total VOCs (TVOCs). Their high correlation and synchronized diurnal variations between NO and the LPG alkanes suggest that their origin lies in LPG fueled car exhaust in Guangzhou. LPG buses and taxis were likely to be responsible for the bulk of ambient LPG species. Using propane and 3-methyl pentane (3MC5A) as the indicators for the LPG and gasoline emissions, respectively, the emissions of the LPG fleet were found to increase more than those of the gasoline fleet during the morning and evening rush hours, as well the noontime break in downtown Guangzhou.Although LPG alkanes account for 24% of the TVOC, their contribution to the total ozone forming potential (OFP) is only about 7%. Ethylene and propylene contribute about 26% to the total OFP despite their lower contribution of 16% to the TVOC.     

Source profiles of volatile organic compounds associated with solvent use in Beijing,China

Compositions of volatile organic compound (VOC) emissions from painting applications and printing processes were sampled and measured by gas chromatography–mass spectrometry/flame ionization detection (GC–MS/FID) in Beijing. Toluene and C8 aromatics were the most abundant species, accounting for 76% of the total VOCs emitted from paint applications. The major species in printing emissions included heavier alkanes and aromatics, such as n-nonane, n-decane, n-undecane, toluene, and m/p-xylene. Measurements of VOCs obtained from furniture paint emissions in 2003 and 2007 suggest a quick decline in benzene levels associated with formulation changes in furniture paints during these years. A comparison of VOC source profiles for painting and printing between Beijing and other parts of the world showed significant region-specific discrepancies, probably because of different market demands and environmental standards. We conducted the evaluation of the source reactivities for various VOC emission sources. The ozone formation potential (OFP) for unit mass of VOCs source emissions is the highest for paint applications. Substituting solvent-based paints by water-based in Beijing will lead to an OFP reduction of 152,000 tons per year, which is more than 1/4 of the OFPs for VOCs emissions from vehicle exhaust in the city.     

Careers in Air Pollution Control Monitoring-Surveillance

ABSTRACT

The temporal and longitudinal characteristics of volatile organic compound (VOC) emissions from the aeration units of a publicly owned treatment works (POTWs) have been investigated by systematic monitoring and mathematical modeling. Field tests have been conducted at a 120-mgd wastewater treatment plant to investigate the hourly, weekly, and seasonal changes of VOC emissions. Variations of VOC emissions along the length of the aeration units have been tested and modeled. Most VOCs have decreasing concentration profiles. Henry's law coefficients and biodegradation constants for the detected compounds have been validated with the improved models and the field test data. More than one-half of the emissions were found to have been generated from the first one-third of the aeration unit length.     

Chemical composition of major VOC emission sources in the Seoul atmosphere

This paper describes a chemical analysis of volatile organic compounds (VOCs) for five emission sources in Seoul. The source categories included motor vehicle exhaust, gasoline evaporation, paint solvents, natural gas and liquefied petroleum gas (LPG). These sources were selected because they have been known to emit significant quantities of VOCs in the Seoul area (more than 5% of the total emission inventory). Chemical compositions of the five emission sources are presented for a group of 45 C2-C9 VOCs. Motor vehicle exhaust profiles were developed by conducting an urban tunnel study. These emissions profiles were distinguished from the other emission profiles by a high weight percentage of butanes over seasons and propane in the wintertime. It was found that this is due to the wide use of butane-fueled vehicles. To obtain gasoline vapor profiles, gasoline samples from five major brands for each season were selected. The brands were blended on the basis of the marketshare of these brands in Seoul area. Raoult's law was used to calculate gasoline evaporative compositions based on the liquid gasoline compositions. The measured and estimated gasoline vapor compositions were found to be in good agreement. Vehicle and gasoline evaporation profiles were made over seasons because of the seasonal change in their compositions. Paint solvent emissions profiles were produced based on a product-use survey and sales figures. These profiles are a composite of four major oil-based paints and thinning solvent. The source profile of natural gas was made on a methane-free basis. It was found that Ethane and propane were the most abundant compounds accounting for 95% of the natural gas composition. LPG was largely composed of propane and ethane and the remaining components were minor contributors.     

Compilation of a database on the composition of anthropogenic VOC emissions for atmospheric modeling in Europe

To analyse and generate air pollution control strategies and policies, e.g. efficient abatement strategies or action plans that lead to a fulfilment of air quality aims, atmospheric dispersion models (CTMs) have to be used. These models include a chemical model, where the numerous volatile organic compounds (VOCs) species are lumped together in classes. On the other hand, emission inventories usually report only total non-methane VOC (NMVOC), but not a subdivision into these classes. Thus, VOC species profiles are needed that resolve total NMVOC emission data. The objective of this publication is to present the results of a compilation of VOC species profiles that dissolve total VOC into single-species profiles for all relevant anthropogenic emission source categories and the European situation. As in atmospheric dispersion models usually modules for generating biogenic emissions are directly included, only anthropogenic emissions are addressed. VOC species profiles for 87 emission source categories have been developed. The underlying data base can be used to generate the data for all chemical mechanisms. The species profiles have been generated using recent measurements and studies on VOC species resolution and thus represent the current state of knowledge in this area. The results can be used to create input data for atmospheric dispersion models in Europe.The profiles, especially those for solvent use, still show large uncertainties. There is still an enormous need for further measurements to achieve an improved species resolution. In addition, the solvent use directive and the DECOPAINT directive of the European Commission will result in a change of the composition of paints; more water-based and high-solid paints will be used; thus the species resolution will change drastically in the next years. Of course, the species resolution for combustion and production processes also requires further improvement.     

Fine particulate source apportionment using data from the USEPA speciation trends network in Chicago,Illinois: Comparison of two source apportionment models

Data from two of the United States Environmental Protection Agency's speciation trends network fine particulate matter sites within Chicago, Illinois were analyzed using the chemical mass balance (CMB) and positive matrix factorization (PMF) models to determine source contributions to the ambient fine particulate concentrations. The results from the two models were compared to determine the similarities and differences in the source contributions. This included examining the differences in the magnitude of the individual source contributions as well as the correlation between the contribution values from the two methods. The results showed that both models predicted sulfates, nitrates and motor vehicles as the three highest fine particle contributors for the two sites accounting for approximately 80% of the total. The PMF model attributed a slightly greater amount of fine particulate to the road salt, steel and soil sources while vegetative burning contributed more in the CMB results. Correlations between the contribution results from the two models were high for sulfates, nitrates and road salt with very good correlations existing for motor vehicles and petroleum refineries. The predicted PMF profiles agreed well with measured source profiles for the major species associated with each source.     

Utilizing the Chemical Mass Balance and Positive Matrix Factorization models to determine influential species and examine possible rotations in receptor modeling results

Data from two of the United States Environmental Protection Agency's Speciation Trends Network fine particulate matter sites within Chicago, Illinois were used to examine the influence that the results and profiles of the Chemical Mass Balance (CMB) receptor model have on the source contributions and profiles of the Positive Matrix Factorization (PMF) model. This was accomplished using the target shape technique, which utilizes a priori information from the CMB source profiles inputted into the PMF model. The target shape methodology involves inputting specific information for the source profiles into the PMF model as it is resolving source profile and contribution matrices. The target shape results demonstrated it is possible to determine in both the CMB and PMF source profiles those species, which do not influence the solutions of either model.A second method utilizing information from the CMB results was used to impose a condition where the Motor Vehicles source never had a zero contribution as was applied to the CMB model. This involved utilizing an edge rotation to rotate the PMF results to yield a different solution without worsening the fit of the original results. The purpose of this work is to achieve a rotation, which produced a PMF solution where all of the Motor Vehicles contributions were greater than zero. Comparing the rotated Motor Vehicles and Sulfates source contributions in PMF to those obtained from CMB showed a better correlation between the PMF Motor Vehicles contributions to the original CMB results than those prior to rotation.     

Evaluation of non-enteric sources of non-methane volatile organic compound (NMVOC) emissions from dairies

Dairies are believed to be a major source of volatile organic compounds (VOC) in Central California, but few studies have characterized VOC emissions from these facilities. In this work, samples were collected from six sources of VOCs (Silage, Total Mixed Rations, Lagoons, Flushing Lanes, Open Lots and Bedding) at six dairies in Central California during 2006–2007 using emission isolation flux chambers and polished stainless steel canisters. Samples were analyzed by gas chromatography/mass spectrometry and gas chromatography/flame ionization detection. Forty-eight VOCs were identified and quantified in the samples, including alcohols, carbonyls, alkanes and aromatics. Silage and Total Mixed Rations are the dominant sources of VOCs tested, with ethanol as the major VOC present. Emissions from the remaining sources are two to three orders of magnitude smaller, with carbonyls and aromatics as the main components. The data suggest that animal feed rather than animal waste are the main source of non-enteric VOC emissions from dairies.     

Apportioning black carbon to sources using highly time-resolved ambient measurements of organic molecular markers in Pittsburgh

We present highly time-resolved measurements of organic molecular markers in downtown Pittsburgh, which are used to investigate sources contributing to atmospheric aerosols in the area. Two-hour average concentrations of condensed-phase and semivolatile organic species were measured using a Thermal Desorption Aerosol GC/MS (TAG). Concentrations for mobile source markers like hopanes had regular diurnal and day-of-week patterns. Pairing high time-resolved measurements with meteorological data helped identify contributions from known point sources for markers correlated with wind direction. Black carbon (BC), volatile organic compounds (VOCs) and organic molecular markers were apportioned to sources using the Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) receptor models. Diesel and gasoline mobile source factors were identified as the main sources of BC in the downtown Pittsburgh area, contributing 67% and 20% of the study-average BC. 13% of the BC was associated with a source factor tentatively identified as an industrial or regional source. The high time resolution of the TAG has the potential to provide important new insight into source apportionment efforts using organic molecular marker measurements.     

Global comparison of VOC and CO observations in urban areas

Speciated volatile organic compound (VOC) and carbon monoxide (CO) measurements from the Marylebone Road site in central London from 1998 through 2008 are presented. Long-term trends show statistically significant decreases for all the VOCs considered, ranging from ?3% to ?26% per year. Carbon monoxide decreased by ?12% per year over the measurement period. The VOC trends observed at the kerbside site in London showed greater rates of decline relative to trends from monitoring sites in rural England (Harwell) and a remote high-altitude site (Hohenpeissenberg), which showed decreases for individual VOCs from ?2% to ?13% per year. Over the same 1998 through 2008 period VOC to CO ratios for London remained steady, an indication that emissions reduction measures affected the measured compounds equally. Relative trends comparing VOC to CO ratios between Marylebone Road and Hohenpeissenberg showed greater similarities than absolute trends, indicating that emissions reductions measures in urban areas are reflected by regional background locations. A comparison of VOC mixing ratios and VOC to CO ratios was undertaken for London and other global cities. Carbon monoxide and VOCs (alkanes greater than C₅, alkenes, and aromatics) were found to be strongly correlated (>0.8) in the Annex I countries, whereas only ethene and ethyne were strongly correlated with CO in the non-Annex I countries. The correlation results indicate significant emissions from traffic-related sources in Annex I countries, and a much larger influence of other sources, such as industry and LPG-related sources in non-Annex I countries. Yearly benzene to ethyne ratios for London from 2000 to 2008 ranged from 0.17 to 0.29 and compared well with previous results from US cities and three global megacities.     

Source contributions to primary organic aerosol: Comparison of the results of a source-resolved model and the chemical mass balance approach

A source-resolved model has been developed to predict the contribution of different sources to primary organic aerosol concentrations. The model was applied to the eastern US during a 17 day pollution episode beginning on 12 July 2001. Primary organic matter (OM) and elemental carbon (EC) concentrations are tracked for eight different sources: gasoline vehicles, non-road diesel vehicles, on-road diesel vehicles, biomass burning, wood burning, natural gas combustion, road dust, and all other sources. Individual emission inventories are developed for each source and a three-dimensional chemical transport model (PMCAMx) is used to predict the primary OM and EC concentrations from each source. The source-resolved model is simple to implement and is faster than existing source-oriented models. The results of the source-resolved model are compared to the results of chemical mass balance models (CMB) for Pittsburgh and multiple urban/rural sites from the Southeastern Aerosol Research and Characterization (SEARCH) network. Significant discrepancies exist between the source-resolved model and the CMB model predictions for some of the sources. There is strong evidence that the organic PM emissions from natural gas combustion are overestimated. It also appears that the OM and EC emissions from wood burning and off-road diesel are too high in the Northeastern US. Other similarities and discrepancies between the source-resolved model and the CMB model for primary OM and EC are discussed along with problems in the current emission inventory for certain sources.