Receptor modeling application framework for particle source apportionment

Receptor models infer contributions from particulate matter (PM) source types using multivariate measurements of particle chemical and physical properties. Receptor models complement source models that estimate concentrations from emissions inventories and transport meteorology. Enrichment factor, chemical mass balance, multiple linear regression, eigenvector. edge detection, neural network, aerosol evolution, and aerosol equilibrium models have all been used to solve particulate air quality problems, and more than 500 citations of their theory and application document these uses. While elements, ions, and carbons were often used to apportion TSP, PM10, and PM2.5 among many source types, many of these components have been reduced in source emissions such that more complex measurements of carbon fractions, specific organic compounds, single particle characteristics, and isotopic abundances now need to be measured in source and receptor samples. Compliance monitoring networks are not usually designed to obtain data for the observables, locations, and time periods that allow receptor models to be applied. Measurements from existing networks can be used to form conceptual models that allow the needed monitoring network to be optimized. The framework for using receptor models to solve air quality problems consists of: (1) formulating a conceptual model; (2) identifying potential sources; (3) characterizing source emissions; (4) obtaining and analyzing ambient PM samples for major components and source markers; (5) confirming source types with multivariate receptor models; (6) quantifying source contributions with the chemical mass balance; (7) estimating profile changes and the limiting precursor gases for secondary aerosols; and (8) reconciling receptor modeling results with source models, emissions inventories, and receptor data analyses.     

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.     

二重源解析技术及其系统实现

化学质量平衡是被广泛用于空气质量管理的受体模型之一.由于混合源(城市扬尘)和单一源因颗粒物源谱的严重共线性,采用美国环境保护署推荐使用的EPA-CMB8.2,无法定量解析出各排放源初始态和扬尘态颗粒物的贡献值和分担率.针对这一问题,完善和规范了二重源解析技术原理,开发了具有二重源解析功能的NKCMB3.0.对鞍山市样品污染物来源解析的试验结果表明,二重源解析技术在对混合源和单一源同时进行源解析时是有效的.     

水环境多环芳烃源解析研究进展

城市化和工业化给环境带来的潜在危害引起人们对环境质量的重视.污染物来源解析研究的成果为环境管理提供了有效的工具.在查阋大量文献的基础上,综述了应用于水环境尤其是沉积物中多环芳烃源解析的主要理论方法和应用模型,并初步提出了沉积物中多环芳烃源解析方法.     

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.     

Determination of buffering capacity of total suspended particle and its source apportionment using the chemical mass balance approach

The samples of total suspended particle (TSP) from sources and TSP in the ambient atmosphere were collected in 2006 at Tianjin, People's Republic of China and analyzed for 16 chemical elements, two water-soluble ions, total carbon, and organic carbon. On the basis of the chemical mass balance (CMB) model, the contributions of different TSP sources to the ambient TSP were identified. The results showed that resuspended dust has the biggest contributions to the concentration of ambient TSP. The buffering capacity of each TSP source was also determined by an analytical chemistry method, and the result showed that the constructive dust (the dust emitted from construction work) had the strongest buffering capacity among the measured sources, whereas the coal combustion dust had the weakest buffering capacity. A calculation formula of the source of buffering capacity of ambient TSP was developed based on the result of TSP source apportionment and the identification of the buffering capacity of each TSP source in this study. The results of the source apportionment of the buffering capacity of ambient TSP indicated that open sources (including soil dust, resuspended dust, and constructive dust) were the dominant sources of the buffering capacity of the ambient TSP. Acid rain pollution in cities in Northern China might become serious with a decrease of open source pollution without reducing acidic sources. More efforts must be made to evaluate this potential risk, and countermeasures should be proposed as early as possible.     

珠三角秋季臭氧污染来源解析

秋季是珠三角臭氧污染最严重的季节,选取2004年秋季珠三角典型臭氧污染过程,运用臭氧来源解析技术等分析手段,研究珠三角臭氧污染特性,分析并量化各排放源区各类源对受体点的臭氧贡献。结果表明,东莞市对珠江口地区的臭氧峰值有重大贡献,下午2-3点东莞市前体物的臭氧贡献最大可达40ppb;而广州市区的前体物排放主要影响顺德区和南海区。在珠三角,排放源区一般对下风向40km范围内的地区臭氧贡献最大。秋季大多数情况下珠三角西部(江门东湖)臭氧受中部主要排放源区臭氧前体物排放与输送的影响很大,广州和佛山地区对江门东湖的臭氧峰值贡献达50ppb左右。交通尾气排放对珠三角各受体点的臭氧贡献最大,交通源对重污染区受体点臭氧的贡献最高可达40ppb~50ppb。     

Designing ambient particulate matter monitoring program for source apportionment study by receptor modeling

Particulate matter (PM) receptor modeling requires specific intensive input data that is always a challenge to produce cost effectively. A well-designed monitoring program is important to collect such PM ambient data in urban areas with diverse and densely distributed sources. This paper presents a general framework for designing such a monitoring program while emphasizing appropriate quality assurance and quality control elements that are particularly applicable where limited resources are available. Topics for discussion include selection of monitoring sites, sampling and analytical techniques, and the uncertainty estimation for ambient concentration input data. The design framework is illustrated by a case study of a monitoring program for PM source apportionment in the Bangkok Metropolitan Region in which 24-h fine and coarse PM samples were collected using two collocated dichotomous samplers. Comparison between black carbon measurements by Smoke Stain reflectometry and Thermal Optical Transmittance method is highlighted.     

Organic aerosol source apportionment from highly time-resolved molecular composition measurements

Organic molecular composition measurements with 3.5 min time resolution were performed with the photoionization aerosol mass spectrometer (PIAMS) over an 18-day period in October–November 2007 in Wilmington, Delaware, USA. Mass spectra were obtained for a total of 6244 time periods, and the signal intensities of 60 specific m/z ratios corresponding to key organic molecular species were modeled by positive matrix factorization (PMF). Six factors were identified that could be tentatively linked to specific sources (diesel exhaust, car emissions/road dust, meat cooking) or types of compounds (alkanes/alkanoic acids, phthalates, PAHs). Owing to the inherent high time resolution of PIAMS, the temporal (diurnal) and wind direction dependencies of these factors could be examined in detail to assess the impacts of point sources and atmospheric processes. Time-resolved EC/OC and gas-phase data (O₃, NO_x, CO) were also obtained during the measurement period to help distinguish primary (POC) and secondary (SOC) organic carbon. The total organic carbon (TOC) concentration averaged 2.6 μg m^?3 during the measurement period and most (>90%) was classified as primary. Of this, approximately one-third could be assigned as combustion POC and the other two-thirds as non-combustion POC. The PMF results were combined with EC/OC data for source apportionment. The diesel and car/road dust factors together represented about two-thirds of TOC, while the alkane/alkanoic acid and meat cooking factors contributed most of the remaining one-third. The phthalate and PAH factors contributed very little, only a few percent of the total. The diesel factor correlated most strongly to combustion POC, while the sum of the remaining factors correlated well with non-combustion POC.     

Spatial gradients and source apportionment of volatile organic compounds near roadways

Concentrations of 55 volatile organic compounds (VOCs) (C₂–C₁₂) are reported near a highway in Raleigh, NC. Thirty-minute samples were collected at eight locations, ranging from approximately 10–100 m perpendicular from the roadway. The highest concentrations of VOCs were generally measured closest to the roadway, and concentrations decreased exponentially with increasing distance from the roadway. The highest mean concentration for individual VOCs were for ethylene (3.10 ppbv) (mean concentration at x = 13 m), propane (2.27 ppbv), ethane (1.91 ppbv), isopentane (1.54 ppbv), toluene (0.95 ppbv), and n-butane (0.89 ppbv). Concentrations at the nearest roadway location (x = 13 m) were generally between 2.0 and 1.5 times those from the farthest roadway location (x = 92 m). The data were apportioned into four source categories using the EPA Chemical Mass Balance Model (CMB8.2): motor vehicle exhaust, compressed natural gas, propane gas, and evaporative gasoline. The majority of the VOCs resulted from motor vehicle exhaust (67 ± 12%) (% of total VOC at x = 13 m ± S.D.). Compressed natural gas, propane gas, and evaporative gasoline accounted for approximately 15%, 7% and 1% of the total VOC emissions, respectively, at x = 13 m.     

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.     

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".     

Diffuse source apportionment of the Po river eutrophying load to the Adriatic sea: assessment of Lombardy contribution to Po river nutrient load apportionment by means of an integrated modelling approach

The source apportionment of the annual nutrient load carried by the Po river to the Adriatic sea has been studied.

An integrated modelling approach was applied to the Lombardy plain area, which covers about 34% of the Po river watershed area and accounts for about 50% of the point sources’ loads carried by the river. To extract all the information available from direct instream measurements, two different modelling tools were alternatively used. The source apportionment was investigated considering both dry and wet weather scenarios. In order to quantify the apportionment in dry-weather conditions, the Lombardy portion of the Po river basin was modelled by using the US-EPA QUAL2E model. Such a simulation allowed to assess a significant contribution (about 50% of the total dry-weather load) of a not rain-driven diffuse pollution component (i.e. groundwater, springs, lake emissaries). Moreover, to estimate the rain-driven surface runoff contribution to the instream total load, the Lombardy plain area was also modelled by means of the US-DA SWAT model. SWAT results indicate a runoff contribution to the Po river instream total load of about 10 000 t N yr⁻¹ and 1300 t P yr⁻¹ (i.e. approximately the 10–20% of the total annual Lombardy nutrient load). At the event scale (i.e. the single rainstorm event) the runoff contribution may rise up to 30–80% of the total instream load. Finally, the total annual nitrogen load at the Po basin closure was estimated for the period 1985–2001. Out of a total annual load of 140 000 t N yr⁻¹, Lombardy accounts for 43% (point plus diffuse sources). The rain-driven diffuse sources constitute the 20% of the overall total load, the point sources account for 40%, whereas the remaining 40% is mainly constituted by “dry-weather diffuse sources” (i.e. groundwater, springs, lake emissaries).     

Estimation of source apportionment and potential source locations of PM2.5 at a west coastal IMPROVE site

Particle composition data for PM_2.5 samples collected at Kalmiopsis Interagency Monitoring of Protected Visual Environments (IMPROVE) site in southwestern Oregon from March 2000 to May 2004 were analyzed to provide source identification and apportionment. A total of 493 samples were collected and 32 species were analyzed by particle induced X-ray emission, proton elastic scattering analysis, photon-induced X-ray fluorescence, ion chromatography, and thermal optical reflectance methods. Positive matrix factorization (PMF) was used to estimate the source profiles and their mass contributions. The PMF modeling identified nine sources. In the Kalmiopsis site, the average mass was apportioned to wood/field burning (38.4%), secondary sulfate (26.9%), airborne soil including Asian dust (8.6 %), secondary nitrate (7.6%), fresh sea salt (5.8%), OP-rich sulfate (4.9%), aged sea salt (4.5 %), gasoline vehicle (1.9%), and diesel emission (1.4%). The potential source contribution function (PSCF) was then used to help identify likely locations of the regional sources of pollution. The PSCF map for wood/field burning indicates there is a major potential source area in the Siskiyou County and eastern Oregon. The potential source locations for secondary sulfate are found in western Washington, northwestern Oregon, and the near shore Pacific Ocean where there are extensive shipping lanes. It was not possible to extract a profile directly attributable to ship emissions, but indications of their influence are seen in the secondary sulfate and aged sea salt compositions.     

Coarse and fine aerosol source apportionment in Rio de Janeiro,Brazil

The metropolitan area of Rio de Janeiro is one of the twenty biggest urban agglomerations in the world, with 11 million inhabitants in the metropolitan area, and has a high population density, with 1700 hab. km^?2. For this aerosol source apportionment study, the atmospheric aerosol sampling was performed at ten sites distributed in different locations of the metropolitan area from September/2003 to December/2005, with sampling during 24 h on a weekly basis. Stacked filter units (SFU) were used to collect fine and coarse aerosol particles with a flow rate of 17 L min^?1. In both size fractions trace elements were analyzed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) as well as water-soluble species by Ion-Chromatography (IC). Also gravimetric analysis and reflectance measurements provided aerosol mass and black carbon concentrations. Very good detection limits for up to 42 species were obtained. Mean annual PM₁₀ mass concentration ranged from 20 to 37 μg m^?3, values that are within the Brazilian air quality standards. Receptor models such as principal factor analysis, cluster analysis and absolute principal factor analysis were applied in order to identify and quantify the aerosol sources. For fine and coarse modes, circa of 100% of the measured mass was quantitatively apportioned to relatively few identified aerosol sources. A very similar and consistent source apportionment was obtained for both fine and coarse modes for all 10 sampling sites. Soil dust is an important component, accounting for 22–72% and for 25–48% of the coarse and fine mass respectively. On the other hand, anthropogenic sources as vehicle traffic and oil combustion represent a relatively high contribution (52–75%) of the fine aerosol mass. The joint use of ICP-MS and IC analysis of species in aerosols has proven to be reliable and feasible for the analysis of large amount of samples, and the coupling with receptor models provided an excellent method for quantitative aerosol source apportionment in large urban areas.     

Nitrate runoff loss and source apportionment in a typical subtropical agricultural watershed

Environmental Science and Pollution Research - Nitrate (NO3?) loss and enrichment in water bodies caused by fertilization are a major environmental problem in agricultural areas. However, the...     

PM10 source apportionment in a Swiss Alpine valley impacted by highway traffic

Although trans-Alpine highway traffic exhaust is one of the major sources of air pollution along the highway valleys of the Alpine regions, little is known about its contribution to residential exposure and impact on respiratory health. In this paper, source-specific contributions to particulate matter with an aerodynamic diameter?<?10 μm (PM₁₀) and their spatio-temporal distribution were determined for later use in a pediatric asthma panel study in an Alpine village. PM₁₀ sources were identified by positive matrix factorization using chemical trace elements, elemental, and organic carbon from daily PM₁₀ filters collected between November 2007 and June 2009 at seven locations within the village. Of the nine sources identified, four were directly road traffic-related: traffic exhaust, road dust, tire and brake wear, and road salt contributing 16 %, 8 %, 1 %, and 2 % to annual PM₁₀ concentrations, respectively. They showed a clear dependence with distance to highway. Additional contributions were identified from secondary particles (27 %), biomass burning (18 %), railway (11 %), and mineral dust including a local construction site (13 %). Comparing these source contributions with known source-specific biomarkers (e.g., levoglucosan, nitro-polycyclic aromatic hydrocarbons) showed high agreement with biomass burning, moderate with secondary particles (in winter), and lowest agreement with traffic exhaust.     

南京大气细粒子中重金属污染特征及来源解析

利用2011年1月、4月、7月和10月在南京市区和北郊采集的气溶胶样品,研究了南京大气细粒子中zn、Ph、Hg、As和cd5种重金属的污染水平,通过元素相关性分析和因子分析方法,对细粒子中这些重金属的污染来源进行了初步解析。结果表明,南京大气细粒子及其重金属污染严重,北郊普遍比市区严重;As严重超标,cd在南京北郊超标约5倍,zn在市区与北郊的质量浓度均高于其他重金属元素。每种重金属的浓度均随季节而变化。市区细粒子中,As和zn可能主要与燃煤、轮胎灰尘和建筑扬尘等有关,Pb、Hg和cd主要来自交通尘、城市垃圾焚烧等。北郊细粒子中,As、Hg和zn主要来源于燃煤、钢铁冶炼等工业,Pb和cd主要与农作物秸秆燃烧、汽车尾气、道路扬尘等影响有关。     

Seasonal variability and source apportionment of metals in the atmospheric deposition in Belgrade

The primary objective of this study is to assess anthropogenic impacts on the environment by determination of element atmospheric depositions. Bulk depositions were collected monthly, from June 2002 to December 2006, at three urban locations in Belgrade. Concentrations of Al, V, Cr, Mn, Fe, Ni, Cu, Zn, Cd and Pb were analyzed by atomic absorption spectrometry and the current deposition fluxes of atmospheric metals were established. Fourier analysis was applied in order to investigate seasonal variation of the monthly data set. Nickel, V, Fe and Al showed pronounced seasonal dependence, while seasonal variation of the other elements was not evident. The enrichment factors of Pb, Zn, Cd and Cu were obviously above those who could have been caused by natural processes, indicating a mainly anthropogenic origin. Nickel was intermediately enriched suggesting participation of both natural and anthropogenic sources. The multivariate receptor model, Unmix, was used to analyze a 5-yr element atmospheric depositions data set. Three main source profiles (mixed road dust, oil combustion and metal processing) were identified and the overall average percentage source contributions determined.     

Monitoring and source apportionment of particulate matter near a large phosphorus production facility

A source apportionment study was conducted to identify sources within a large elemental phosphorus plant that contribute to exceedances of the National Ambient Air Quality Standards (NAAQS) for 24-hr PM10. Ambient data were collected at three monitoring sites from October 1996 through July 1999, and included the following: 24-hr PM10 mass, 24-hr PM2.5 and PM10-2.5 mass and chemistry, continuous PM10 and PM2.5 mass, continuous meteorological data, and wind-direction-resolved PM2.5 and PM10 mass and chemistry. Ambient-based receptor modeling and wind-directional analysis were employed to help identify major sources or source locations and source contributions. Fine-fraction phosphate was the dominant species observed during PM10 exceedances, though in general, resuspended coarse dusts from raw and processed materials at the plant were also needed to create an exceedance. Major sources that were identified included the calciners, the CO flares, process-related dust, and electric-arc furnace operations.