Source Apportionment Studies Research Articles

Nonpolar organic compounds as PM2.5 source tracers: Investigation of their sources and degradation in the Pearl River Delta, China

AbstractA group of nonpolar organic compounds (NPOCs) in five compound classes including alkanes, polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, and 1,3,5‐triphenylbenzene were quantified in samples of particulate matter of aerodynamic diameter less than 2.5 μm collected at four sites in the Pearl River Delta (PRD) region, China, over a 2 year period from 2011 to 2012. The four sites include industrial (Nanhai), urban (Guangzhou), urban outskirt (Dongguan), and suburban (Nansha) locations. Some NPOCs are uniquely emitted from particular combustion sources and thereby serving as markers in source apportionment. Based on this multiyear and multisite NPOC data set, spatial and seasonal variations, correlation analysis, and ratio‐ratio plots were used to investigate the source information and degradation of NPOC tracers. In summer, NPOCs showed distinct local emission characteristics, with urban sites having much higher concentrations than suburban sites. In winter, regional transport was an important influence on NPOC levels, driving up concentrations at all sampling sites and diminishing an urban‐suburban spatial gradient. The lighter NPOCs exhibited more prominent seasonal variations. Such spatiotemporal features suggest that their particle‐phase abundance is more influenced by temperature, which is a critical factor in controlling the extent of semivolatile organics partitioned into the aerosol phase. The heavier NPOCs, especially PAHs, showed negligible correlation among the four sites, suggesting more influence from local emissions. Ratio‐ratio plots indicate photodegradation and mixing of various sources for the NPOCs in the PRD. A positive matrix factorization (PMF) analysis of this large NPOC data set suggests that heavier NPOCs are more suitable source indicators than lighter NPOCs. Incorporating particle‐phase light NPOC concentrations in PMF produces a separate factor, which primarily contains those light NPOCs and likely is not a source factor. Total NPOC concentrations predicted using Pankow partitioning theory were explored as PMF inputs; however, the PMF solution is not able to fully explain the input total concentrations or to give reasonable source profiles, suggesting the need for reliable gas‐phase NPOC data before their use in source apportionment studies. In addition, degradation of NPOCs needs to be considered to avoid misinterpretation of PMF source apportionment results.

Municipal solid waste and dung cake burning: discoloring the Taj Mahal and human health impacts in Agra

The Taj Mahal—an iconic World Heritage monument built of white marble—has become discolored with time, due, in part, to high levels of particulate matter (PM) soiling its surface (Bergin et al 2015 Environ. Sci. Technol. 49 808–812). Such discoloration has required extensive and costly treatment (2015 Two Hundred Sixty Second Report on Effects of Pollution on Taj Parliament of India Rajya Sabha, New Delhi) and despite previous interventions to reduce pollution in its vicinity, the haze and darkening persists (Bergin et al 2015 Environ. Sci. Technol. 49 808–812; 2015 Two Hundred Sixty Second Report on Effects of Pollution on Taj Parliament of India Rajya Sabha, New Delhi). PM responsible for the soiling has been attributed to a variety of sources including industrial emissions, vehicular exhaust and biomass burning, but the contribution of the emissions from the burning of open municipal solid waste (MSW) may also play an important role. A recent source apportionment study of fine particulate matter (PM2.5) at the Taj Mahal showed biomass burning emissions, which would include MSW emissions, accounted for nearly 40% of organic matter (OM)—a component of PM—deposition to its surface (Bergin et al 2015 Environ. Sci. Technol. 49 808–812); dung cake burning, used extensively for cooking in the region, was the suggested culprit and banned within the city limits (2015 Two Hundred Sixty Second Report on Effects of Pollution on Taj Parliament of India Rajya Sabha, New Delhi), although the burning of MSW, a ubiquitous practice in the area (Nagpure et al 2015 Environ. Sci. Technol. 49 12904–12), may play a more important role in local air quality. Using spatially detailed emission estimates and air quality modeling, we find that open MSW burning leads to about 150 (±130) mg m−2 yr−1 of PM2.5 being deposited to the surface of the Taj Mahal compared to about 12 (±3.2) mg m−2 yr−1 from dung cake burning. Those two sources, combined, also lead to an estimated 713 (377–1050) premature mortalities in Agra each year, dominated by waste burning in socioeconomically lower status neighborhoods. An effective MSW management strategy would reduce soiling of the Taj Mahal, improve human health, and have additional aesthetic benefits.

Development of source profiles and their application in source apportionment of PM2.5 in Xiamen, China

Ambient PM2.5 samples were collected at four sites in Xiamen, including Gulangyu (GLY), Hongwen (HW), Huli (HL) and Jimei (JM) during January, April, July and October 2013. Local source samples were obtained from coal burning power plants, industries, motor vehicles, biomass burning, fugitive dust, and sea salt for the source apportionment studies. The highest value of PM2.5 mass concentration and species related to human activities (SO4 2–, NO3 –, Pb, Ni, V, Cu, Cd, organic carbon (OC) and elemental carbon (EC)) were found in the ambient samples from HL, and the highest and lowest loadings of PM2.5 and its components occurred in winter and summer, respectively. The reconstructed mass balance indicated that ambient PM2.5 consisted of 24% OM (organic matter), 23% sulfate, 14% nitrate, 9% ammonium, 9% geological material, 6% sea salt, 5% EC and 10% others. For the source profiles, the dominant components were OC for coal burning, motor vehicle, biomass burning and sea salt; SO4 2– for industry; and crustal elements for fugitive dust. Source contributions were calculated using a chemical mass balance (CMB) model based on ambient PM2.5 concentrations and the source profiles. GLY was characterized by high contributions from secondary sulfate and cooking, while HL and JM were most strongly affected by motor vehicle emissions, and biomass burning and fugitive dust, respectively. The CMB results indicated that PM2.5 from Xiamen is composed of 27.4% secondary inorganic components, 20.8% motor vehicle emissions, 11.7% fugitive dust, 9.9% sea salt, 9.3% coal burning, 5.0% biomass burning, 3.1% industry and 6.8% others.

Air Quality Management through Receptor Modelling

Background: One of the major risk factors to human health is air pollution. It contains a complex mixture of gaseous and particulate pollutants which possesses dynamic properties due to the combination of anthropogenic activities and meteorological conditions. The precise characteristics of the ambient air pollutants in a given locale depend on the source origin, which in-turn is a function of economic, social and technological factors. Hence it is very essential to identify the source origins. Methods: Receptor models have been widely used in source identification and their contribution of Airborne Particulate Matter (APM). Chemical Mass Balance model (CMB) is one among them. This paper presents a critical brief reappraisal of the source apportionment of APM through CMB model. Findings: The review shows that CMB model have been frequently used and proved to be an important tool in source apportionment studies without any pre requisite of source and meteorological data sets. Applications: Source apportionment through CMB model is one among the way to control and manage the PM 10 and PM 2.5 emissions in an informed way.

Sensitivity of source apportionment results to mobile source profiles

The sensitivity of a source apportionment model to mobile source profiles was examined to determine the impact of using non-local mobile source profiles in chemical mass balance (CMB) models. We examined the impact of USA and Chinese mobile source profiles on source apportionment results in St. Louis, Missouri, and Beijing. The results showed that the use of non-local mobile source profiles did not impact the model apportionment results for vegetative detritus and biomass burning, but other primary source contributions were influenced by the use of non-local source profiles. Secondary organic carbon (SOC) contributions estimated by the CMB models with local and non-local profiles were compared to estimate of SOC from the EC tracer method and were found to be consistent with little bias. The results also showed that it is feasible to use the USA mobile profiles in China while model results were biased by using Chinese mobile profiles in the USA. Monthly and annual average concentrations of molecular markers in the source apportionment model showed lower sensitivity to source profiles than daily measurements, which has implications to the design of source apportionment studies.

PM2.5 source apportionment and transport cluster analysis

Introduction Source apportionment studies of particulate matter are common and have either been performed as source region analyses or by source type. The first type use air mass back trajectories and the latter one uses source apportionment techniques such as principal component analysis, chemical mass balance or positive matrix factorisation (PMF). However, by combining the two approaches it is possible to estimate the relative importance of emitters in different regions. Methods In this study we have collected one year of daily PM2.5 samples and made elemental analysis of the samples using EDXRF. Source apportionment was carried out using PMF with the US EPA PMF5.0 software. The sources long-range transport (LRT), LRT-Pb (lead containing LRT), ship emissions, combustion, marine, and resuspension were identified. We also calculated air mass trajectories using the HYSPLIT (version 4.9) model. Six transport clusters were identified, South Scandinavia (S-Scandic), North Scandinavia (N-Scandic), Baltic Sea (BalticS), Eastern Europe (E-Eur), UK/North Sea/Denmark (UK-NorthS-DK) and North Atlantic Ocean (N-Atlantic. The frequency of occurrence was 28, 21, 107, 38, 76, and 91 days, respectively. Results From the PMF analysis we found that LRT is the dominating contributor to PM2.5 levels and across all six transport clusters. LRT contributes 48% of the PM2.5 levels followed by ship emissions (20%) and combustion (19%). The transport cluster associated with the highest PM2.5 levels was E-Eur followed by S-Scandic, UK-NorthS-DK, and BalticS. After considering the frequency of the transport clusters during the study period, the transport clusters associated with the highest PM2.5 levels were UK-NorthS-DK, S-Scandic and N-Atlantic, while E-Eur only contributed 9% towards PM2.5 levels. Conclusion Our study adds knowledge to one of six research directions identified in a review, namely the combination of back-trajectory modelling with source apportionment analyses.

Source insights into the 11-h daytime and nighttime fine ambient particulate matter in China as well as the synthetic studies using the new Multilinear Engine 2-species ratios (ME2-SR) method

Modeled results are very important for environmental management. Unreasonable modeled result can lead to wrong strategy for air pollution management. In this work, an improved physically constrained source apportionment (PCSA) technology known as Multilinear Engine 2-species ratios (ME2-SR) was developed to the 11-h daytime and nighttime fine ambient particulate matter in urban area. Firstly, synthetic studies were carried out to explore the effectiveness of ME2-SR. The estimated source contributions were compared with the true values. The results suggest that, compared with the positive matrix factorization (PMF) model, the ME2-SR method could obtain more physically reliable outcomes, indicating that ME2-SR was effective, especially when apportioning the datasets with no unknown source. Additionally, 11-h daytime and nighttime PM2.5 samples were collected from Tianjin in China. The sources of the 11-h daytime and nighttime fine ambient particulate matter in China were identified using the new method and the PMF model. The calculated source contributions for ME2-SR for daytime PM2.5 samples are resuspended dust (38.91 μg m−3, 26.60%), sulfate and nitrate (38.60 μg m−3, 26.39%), vehicle exhaust and road dust (38.26 μg m−3, 26.16%) and coal combustion (20.14 μg m−3, 13.77%), and those for nighttime PM2.5 samples are resuspended dust (18.78 μg m−3, 12.91%), sulfate and nitrate (41.57 μg m−3, 28.58%), vehicle exhaust and road dust (38.39 μg m−3, 26.39%), and coal combustion (36.76 μg m−3, 25.27%). The comparisons of the constrained versus unconstrained outcomes clearly suggest that the physical meaning of the ME2-SR results is interpretable and reliable, not only for the specified species values but also for source contributions. The findings indicate that the ME2-SR method can be a useful tool in source apportionment studies, for air pollution management.

Metal Signature of Atmospheric Aerosol from Kochi, the Queen of Arabian Sea, Kerala, India

The present research article highlights the metal (Cd, Cu, Pb, Zn and Fe)distribution pattern in the RSPM generated in different hot spot sites located at Kochi, theQueen of Arabian Sea. These sampling sites are categorized under three different zonesas estuarine, riverine, and coastal. Two sampling phases are selected in order to check theconsistency in pollution trend after a two year gap and are described in Phase I and PhaseII, respectively. Metals are noticed to be intensely concentrated in the post monsoonmonths in both phases. Among the metals, Fe is revealed as the prominent metal at theestuarine sites. Estuarine and riverine zone expresses the overall enrichment pattern withslight difference at coastal regime in phase I. In phase II, insignificant metal load withirregular pattern is observed. Source apportionment study reveals that major sources ofmetals are from automobile exhausts and the estuarine zone is entangled with 45.9%.

On-road traffic emissions of polycyclic aromatic hydrocarbons and their oxy- and nitro- derivative compounds measured in road tunnel environments

Vehicular emissions are a key source of polycyclic aromatic compounds (PACs), including polycyclic aromatic hydrocarbons (PAHs) and their oxygenated (OPAH) and nitrated (NPAH) derivatives, in the urban environment. Road tunnels are a useful environment for the characterisation of on-road vehicular emissions, providing a realistic traffic fleet and a lack of direct sunlight, chemical reactivity and non-traffic sources. In the present investigation the concentrations of selected PAHs, OPAHs and NPAHs have been measured in the Parc des Princes Tunnel in Paris (PdPT, France), and at the Queensway Road Tunnel and an urban background site in Birmingham (QT, U.K). A higher proportion of semi-volatile (3–4 ring) PAH, OPAH and NPAH compounds are associated with the particulate phase compared with samples from the ambient environment. A large (~85%) decline in total PAH concentrations is observed between 1992 and 2012 measurements in QT. This is attributed primarily to the introduction of catalytic converters in the U.K as well as increasingly stringent EU vehicle emissions legislation. In contrast, NPAH concentrations measured in 2012 are similar to those measured in 1996. This observation, in addition to an increased proportion of (Phe+Flt+Pyr) in the observed PAH burden in the tunnel, is attributed to the increased number of diesel passenger vehicles in the U.K during this period. Except for OPAHs, comparable PAH and NPAH concentrations are observed in both investigated tunnels (QT and PdP). Significant differences are shown for specific substances between PAC chemical profiles in relation with the national traffic fleet differences (33% diesel passenger cars in U.K. vs 69% in France and up to 80% taking into account all vehicle categories). The dominating and sole contribution of 1-Nitropyrene observed in the PdPT NPAH profile strengthens the promising use of this compound as a diesel exhaust marker for PM source apportionment studies.

Composition of ambient and fresh biomass burning aerosols at a savannah site, South Africa

Atmospheric aerosols play a key role in climate change, and have adverse effects on human health. Given South Africa’s status as a rapidly-developing country with increasing urbanisation and industrial growth, information on the quality of ambient air is important. In this study, the chemical composition of ambient particles and the particles in fresh biomass burning plumes were studied at a savannah environment in Botsalano, South Africa. The results showed that Botsalano was regularly affected by air masses that had passed over several large point sources. Air masses that had passed over the coal-fired Matimba power station in the Waterberg, or over the platinum group metal smelters in the western Bushveld Igneous Complex, contained high sulfate concentrations in the submicron ranges. These concentrations were 14 to 37 times higher compared with air masses that had passed only over rural areas. Because of the limited nature of this type of data in literature for the interior regions of southern Africa, our report serves as a valuable reference for future studies. In addition, our biomass burning study showed that potassium in the fresh smoke of burning savannah grass was likely to take the form of KCl. Clear differences were found in the ratios for potassium and levoglucosan in the smouldering and flaming phases. Our findings highlight the need for more comprehensive chamber experiments on various fuel types used in southern Africa, to confirm the ratio of important biomass burning tracer species that can be used in source apportionment studies in the future.

Source Apportionment of PM2.5 in Delhi, India Using PMF Model.

Chemical characterization of PM2.5 [organic carbon, elemental carbon, water soluble inorganic ionic components, and major and trace elements] was carried out for a source apportionment study of PM2.5 at an urban site of Delhi, India from January, 2013, to December, 2014. The annual average mass concentration of PM2.5 was 122±94.1µgm(-3). Strong seasonal variation was observed in PM2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon. A receptor model, positive matrix factorization (PMF) was applied for source apportionment of PM2.5 mass concentration. The PMF model resolved the major sources of PM2.5 as secondary aerosols (21.3%), followed by soil dust (20.5%), vehicle emissions (19.7%), biomass burning (14.3%), fossil fuel combustion (13.7%), industrial emissions (6.2%) and sea salt (4.3%).

Distribution and source apportionment studies of heavy metals in soil of cotton/wheat fields.

Heavy metals enriched agricultural soils have been the subject of great concern because these metals have potential to be transferred to the soil solution and afterward accumulated in food chain. To study the trace metal persistence in crop soil, 90 representative soil samples were collected and analyzed for heavy metal (As, Cd, Cu, Fe, Mn, Ni, Pb, and Zn) and anions (chloride, nitrates, phosphates and sulfates). Cluster and factor analysis techniques were used for the source identification of these excessive heavy metal levels and ecological risk was determined with potential ecological risk assessment. The degree of enrichment of eight studied heavy metals in comparison with the corresponding background levels decreased in order: Cd > Pb > Fe > Ni > Mn > As > Cu ~ Zn. Arsenic and cadmium exhibited 1.30- and 1.64-fold exceeded levels than threshold limits set by National environment quality standards, respectively. Cd in cotton field's soil may lead to higher potential risk than other heavy metals. On overall basis, the cumulative mean potential ecological risk for the district (207.75) corresponded to moderate risk level with higher contributions from As and Pb especially from Cd. Cadmium formed strong positive correlation with phosphate content of soil at p < 0.01. Cluster analysis indicated that Cluster 1 (extremely polluted) probably originated from anthropogenic inputs of phosphate fertilizer and past usage of arsenical pesticides.

Identification and elucidation of anthropogenic source contribution in PM10 pollutant: Insight gain from dispersion and receptor models

Source apportionment study of PM10 (Particulate Matter) in a critically polluted area of Jharia coalfield, India has been carried out using Dispersion model, Principle Component Analysis (PCA) and Chemical Mass Balance (CMB) techniques. Dispersion model Atmospheric Dispersion Model (AERMOD) was introduced to simplify the complexity of sources in Jharia coalfield. PCA and CMB analysis indicates that monitoring stations near the mining area were mainly affected by the emission from open coal mining and its associated activities such as coal transportation, loading and unloading of coal. Mine fire emission also contributed a considerable amount of particulate matters in monitoring stations. Locations in the city area were mostly affected by vehicular, Liquid Petroleum Gas (LPG) & Diesel Generator (DG) set emissions, residential, and commercial activities. The experimental data sampling and their analysis could aid understanding how dispersion based model technique along with receptor model based concept can be strategically used for quantitative analysis of Natural and Anthropogenic sources of PM10.

Chemical composition, sources, and aging process of submicron aerosols in Beijing: Contrast between summer and winter

AbstractTo investigate the seasonal characteristics of submicron aerosol (PM1) in Beijing urban areas, a high‐resolution time‐of‐flight aerosol‐mass‐spectrometer (HR‐ToF‐AMS) was utilized at an urban site in summer (August to September 2011) and winter (November to December 2010), coupled with multiple state of the art online instruments. The average mass concentrations of PM1 (60–84 µg m−3) and its chemical compositions in different campaigns of Beijing were relatively consistent in recent years. In summer, the daily variations of PM1 mass concentrations were stable and repeatable. Eighty‐two percent of the PM1 mass concentration on average was composed of secondary species, where 62% is secondary inorganic aerosol and 20% secondary organic aerosol (SOA). In winter, PM1 mass concentrations changed dramatically because of the different meteorological conditions. The high average fraction (58%) of primary species in PM1 including primary organic aerosol (POA), black carbon, and chloride indicates primary emissions usually played a more important role in the winter. However, aqueous chemistry resulting in efficient secondary formation during occasional periods with high relative humidity may also contribute substantially to haze in winter. Results of past OA source apportionment studies in Beijing show 45–67% of OA in summer and 22–50% of OA in winter can be composed of SOA. Based on the source apportionment results, we found 45% POA in winter and 61% POA in summer are from nonfossil sources, contributed by cooking OA in both seasons and biomass burning OA (BBOA) in winter. Cooking OA, accounting for 13–24% of OA, is an important nonfossil carbon source in all years of Beijing and should not be neglected. The fossil sources of POA include hydrocarbon‐like OA from vehicle emissions in both seasons and coal combustion OA (CCOA) in winter. The CCOA and BBOA were the two main contributors (57% of OA) for the highest OA concentrations (&gt;100 µg m−3) in winter. The POA/ΔCO ratios in winter and summer are 11 and 16 µg m−3 ppm−1, respectively, similar to ratios from western cities. Higher OOA/Ox (= NO2 + O3) ratio (0.49 µg m−3 ppb−1) in winter study than these ratios from western cities (0.03–0.16 µg m−3 ppb−1) was observed, which may be due to the aqueous reaction or extra SOA formation contributed by semivolatile organic compounds from various primary sources (e.g., BBOA or CCOA) in Beijing. The evolution of oxygen to carbon ratio (O/C) with photochemical age allows to estimate an equivalent rate constant for chemical aging of OA in summer as kOH ~ 4.1 × 10−12 cm3 molecule−1 s−1, which is of the same order as obtained in other anthropogenic influenced areas and may be useful for OA modeling.

SPECIEUROPE: The European data base for PM source profiles

A new database of atmospheric particulate matter emission source profiles in Europe (SPECIEUROPE) developed in the framework of the Forum for air quality modeling in Europe (FAIRMODE, Working Group 3) is accessible at the website http://source-apportionment.jrc.ec.europa.eu/Specieurope/index.aspx. It contains the chemical composition of particulate matter emission sources reported in the scientific literature and reports drafted by competent authorities. The first release of SPECIEUROPE consists of 151 measured (original), 13 composite (merging different subcategories of similar sources), 6 calculated (from stoichiometric composition) and 39 derived (results of source apportionment studies) profiles. Each profile is related to one or more source categories or subcategories. The sources with the highest PM relative mass toxic pollutants such as PAHs are fuel oil burning, ship emissions, coke burning and wood burning. Heavy metals are most abundant in metal processing activities while halogens are mostly present in fertilizer production, coal burning and metallurgic sector. Anhydrosugars are only measured in biomass and wood burning source categories, because are markers for these categories. The alkaline earth metals are mostly present in road dust, cement production, soil dust and sometimes coal burning. Source categories like traffic and industrial, which contain heterogeneous subcategories, show the greatest internal variability.The relationships between sources profiles were also explored using a cluster analysis approach based upon the Standardized Identity Distance (SID) indicator. The majority of profiles are allocated in 8 major clusters. Some of the clusters include profiles mainly from one source category (e.g. wood burning) while others, such as industrial source profiles, are more heterogeneous and spread over three different clusters.

Mercury isotopes of atmospheric particle bound mercury for source apportionment study in urban Kolkata, India

Abstract The particle bound mercury (PBM) in urban-industrial areas is mainly of anthropogenic origin, and is derived from two principal sources: Hg bound to particulate matter directly emitted by industries and power generation plants, and adsorption of gaseous elemental mercury (GEM) and gaseous oxidized mercury (GOM) on air particulates from gas or aqueous phases. Here, we measured the Hg isotope composition of PBM in PM10 samples collected from three locations, a traffic junction, a waste incineration site and an industrial site in Kolkata, the largest metropolis in Eastern India. Sampling was carried out in winter and monsoon seasons between 2013–2015. The objective was to understand whether the isotope composition of the PBM represents source composition. The PBM collected from the waste burning site showed little mass independent fractionation (MIF) (Δ199Hg = +0.12 to -0.11‰), similar to the signature in liquid Hg and Hg ores around the world with no seasonal variations. Samples from the industrial site showed mostly negative MDF and MIF (δ202Hg = -1.34 to -3.48 ‰ and Δ199Hg = +0.01 to -0.31‰). The MDF is consistent with PBM generated by coal combustion however, the MIF is 0.15‰ more negative compared to the Hg isotope ratios in Indian coals. The traffic junction PBM is probably not produced in situ, but has travelled some distances from nearby industrial sources. The longer residence time of this PBM in the atmosphere has resulted in-aerosol aqueous photoreduction. Thus, the MIF displays a larger range (Δ199Hg = +0.33 to -0.30‰) compared to the signature from the other sites and with more positive values in the humid monsoon season. Different Hg isotopic signature of PBM in the three different sampling locations within the same city indicates that both source and post emission atmospheric transformations play important roles in determining isotopic signature of PBM.

Effect of Uncertainty on Source Contributions from the Positive Matrix Factorization Model for a Source Apportionment Study

Uncertainty estimation plays an important role in source apportionment models such as the positive matrix factorization (PMF) model. In this study, synthetic datasets were generated and analyzed using PMF with specified uncertainties at different levels to investigate the impact of uncertainty inputs on the results of PMF model, as well as the benefits and risks of emphasizing on certain species. The results showed that: (1) uncertainties for the PMF model should be estimated based on characteristics of the dataset being analyzed; (2) emphasizing on correct tracers will improved model performance; and (3) emphasizing on unsuitable tracers may lead to disruptive consequences that might not be captured by the Q metric. Tests were also performed on collected ambient PM_(2.5) samples and similar conclusions were drawn: emphasizing on correct tracers was shown to improve the separation of important source categories from mixed sources. When emphasizing on incorrect tracers, a counterfeit factor of Fe industrial source was extracted, which are inconsistent with field observations. Results from this study provide insights on how uncertainties should be estimated for the PMF model.

A case study of surface ozone source apportionment during a high concentration episode, under frequent shifting wind conditions over the Yangtze River Delta, China

Surface ozone is an environmental issue occurring at several scales, ranging from local to continental. One of the most developed regions in China, the Yangtze River Delta (YRD), experiences severe tropospheric ozone problem. Hence, quantifying the contributions from various geographical source regions is helpful for better understanding the regional ozone problem. Ozone source apportionment studies can provide relevant information for designing suitable air pollution protection strategies. In the present work, the WRF-Chem model coupled with an online ozone tagging method is applied to a case study, with the objective of exploring the ozone contributions to the surface ozone from different source regions over the YRD region, during a frequent wind-shifting period. Our results show that the YRD was highly affected by the upwind source regions bearing high values both ozone and its precursors. The contribution from the source region outside the main air pollution zones in the Central Eastern China (super regional contribution) was also important, accounting for more than 30ppb of daytime maximum mean ozone concentrations. Ozone arising from increased local and regional emissions during high-concentration events was more significant than super regional contribution. It reveals that the ozone from Anhui region was transported through vertical mixing and horizontal advection to receptor areas in the YRD during the study time focus. Chemical process contributed significantly at ground and high altitude levels of 500 and 1000m. However, most of the ozone from the remote regions of Henan and Hubei provinces was transported to the receptor of Nanjing through physical processes. The vertical mixing process played a crucial positive role at super regional scales, with regard to the formation of surface ozone over the YRD region during the addressed time interval.

Optimization of a large-volume injection method for compound-specific isotope analysis of polycyclic aromatic compounds at trace concentrations.

Compound-specific isotope analysis (CSIA) of persistent organic contaminants can be used for source apportioning in the environment if appropriate sensitivity can be achieved. This paper describes the optimization and validation of a sensitive analytical approach for the determination of the carbon isotope composition of semi-volatile organic compounds, such as polycyclic aromatic hydrocarbons (PAHs). Analyses are based on the introduction of up to 150 μL of organic extracts by means of programmed temperature vaporization-large-volume injection combined with gas chromatography coupled to isotope ratio mass spectrometry (PTV-LVI-GC/IRMS). To allow for the analysis of more volatile, low-molecular-weight PAHs, the PTV injector was equipped with a sub-ambient/cryogenic cooling. Accuracy, precision, linearity and determination limits for application in isotope analysis were evaluated for a set of individual PAHs ranging from two- to five-ring molecular structures. The method was exemplified by determining the δ(13) C values of individual PAHs in soil samples in a source apportionment study at a contaminated site. The choice of PTV injection parameters is crucial to prevent isotope fractionation during injection and largely depends on the analytes to be determined. The observed isotope fractionation effect on semi-volatiles depends on the applied solvent and injection temperature and demonstrates the importance of performing appropriate tests with given PTV parameters for each of the compounds of interest. The proposed PTV-LVI-GC/IRMS method allows the carbon isotope ratio (δ(13) C value) of individual PAHs to be determined accurately and precisely at concentrations of 0.04-0.1 ng μL(-1) even for volatile PAHs such as naphthalene or acenaphthene. LVI with PTV injector cooling allows for the isotopic analysis of volatile and semi-volatile PAHs at trace concentrations, thus considerably expanding the applicability of CSIA in environmental studies.

Stable chlorine isotope analysis of chlorinated acetic acids using gas chromatography/quadrupole mass spectrometry.

The environmental occurrence of chlorinated acetic acids (CAAs) has been extensively studied, but the sources and transport are still not yet fully understood. A promising approach for source apportionment and process studies is the isotopic characterization of target compounds. We present the first on-line stable chlorine isotope analysis of CAAs by use of gas chromatography/quadrupole mass spectrometry (GC/qMS). Following approved procedures for concentration analysis, CAAs extracted into MTBE were methylated to GC-amenable methyl esters (mCAAs). These mCAAs were then analyzed by GC/qMS for their stable chlorine isotope composition using a sample/standard-bracketing approach (CAA standards in the range δ(37) Cl -6.3 to -0.2 ‰, Standard Mean Ocean Chloride). Cross-calibration of the herein presented method with off-line reference methods (thermal ionization and continuous-flow GC isotope ratio mass spectrometry; TI-MS and CF-GC/IRMS, respectively) shows good agreement between the methods (regression slope for GC/qMS vs reference method data sets: 0.92 ± 0.29). Sample amounts as small as 10 pmol Cl can herewith be analyzed with a precision of 0.1 to 0.4 ‰. This method should be useful for environmental studies of CAAs at ambient concentrations in precipitations (<0.06 to 100 nmol L(-1) ), surface waters (<0.2 to 5 nmol L(-1) ) and soil (<0.6 to 2000 nmol kg(-1) dry soil) where conventional off-line methods cannot be applied.