Tool For Source Apportionment Research Articles

Multi-isotopic composition of brown crab (Cancer pagurus) and seafloor sediment from a mine tailing sea disposal impacted fjord ecosystem

Sea disposal of mine tailings in fjord ecosystems is an important coastal management issue in Norway and occurs at the land-sea interface. Here we studied accumulation of heavy metals in brown crab (Cancer pagurus) and seafloor sediment from Jøssingfjord, Norway during 2018 to evaluate long-term, legacy pollution effects of coastal mine tailing sea disposal activities. Nickel and copper sediment pollution in the mine tailing sea disposal area was classified as moderate and severe, respectively, under Norwegian environmental quality standards, and highlights the persistent hazard and legacy impacts of heavy metals in these impacted fjord ecosystems. Mercury, zinc, and arsenic had stronger affinities to brown crab muscle likely due to the presence of thiols, and availability of metal binding sites. Our multi-isotopic composition data showed that lead isotopes were the most useful source apportionment tool for this fjord. Overall, our study highlights the importance and value of measuring several different heavy metals and multiple isotopic signatures in different crab organs and seafloor sediment to comprehensively evaluate fjord pollution and kinetic uptake dynamics. Brown crabs were suitable eco-indicators of benthic ecosystem heavy metal pollution in a fjord ecosystem still experiencing short- and long-term physical and chemical impacts from coastal mining sea disposal activities.

Source Apportionment of Polycyclic Aromatic Hydrocarbons in Indoor Fine Dusts from Residential and Public Buildings in Port Harcourt, Rivers State, Nigeria

The sources of polycyclic aromatic hydrocarbons in indoor fine dust from residential and public buildings in Port Harcourt, Rivers State, Nigeria was investigated using source apportionment tools such as diagnostic/isomeric ratios, principal component analysis (PCA) and hierarchical cluster analysis (HCA). A total of twenty-seven indoor fine dusts comprising of twenty samples from residential building and seven samples from public buildings were collected from Port Harcourt. The PAHs in the dust samples were quantified by gas chromatograph equipped with mass spectrometry (GC-MS) after extraction by ultra-sonication with hexane/dichloromethane/acetone and cleaned up on a silica gel/alumina column. The Σ16 PAH concentrations in the indoor fine dusts ranged from 3136 µg kg-1 to 44332 µg kg-1 for residential buildings and 2580 µg kg-1 to 15372 µg kg-1 for public buildings. The results of source apportionment indicated that the PAHs in the indoor fine dusts were from mixed sources pyrogenic sources (coal, wood, petroleum, biomass, and fossil fuel combustion) and petrogenic sources with significant contribution from pyrogenic sources.

Mass-Suite: a novel open-source python package for high-resolution mass spectrometry data analysis

Mass-Suite (MSS) is a Python-based, open-source software package designed to analyze high-resolution mass spectrometry (HRMS)-based non-targeted analysis (NTA) data, particularly for water quality assessment and other environmental applications. MSS provides flexible, user-defined workflows for HRMS data processing and analysis, including both basic functions (e.g., feature extraction, data reduction, feature annotation, data visualization, and statistical analyses) and advanced exploratory data mining and predictive modeling capabilities that are not provided by currently available open-source software (e.g., unsupervised clustering analyses, a machine learning-based source tracking and apportionment tool). As a key advance, most core MSS functions are supported by machine learning algorithms (e.g., clustering algorithms and predictive modeling algorithms) to facilitate function accuracy and/or efficiency. MSS reliability was validated with mixed chemical standards of known composition, with 99.5% feature extraction accuracy and ~ 52% overlap of extracted features relative to other open-source software tools. Example user cases of laboratory data evaluation are provided to illustrate MSS functionalities and demonstrate reliability. MSS expands available HRMS data analysis workflows for water quality evaluation and environmental forensics, and is readily integrated with existing capabilities. As an open-source package, we anticipate further development of improved data analysis capabilities in collaboration with interested users.Graphical abstract

The application of positive matrix factorization with diagnostics to BIG DATA

Over the past decade, Positive Matrix Factorization (PMF) has become the most commonly used tool for source apportionment of air pollutants with a large fraction of those studies using the implementation developed by the U.S. Environmental Protection Agency (EPA-PMF) and its very useful diagnostic tools. During the same period, more studies are utilizing monitoring tools that provide hourly or even higher time resolution data leading to large data sets (millions of data points). Because of the nature of the graphic user interface in EPA-PMF, it cannot handle data sets more than approximately half a million data points. Thus, alternative approaches are needed to permit these larger data sets to be analyzed and still be able to provide the diagnostic outputs that permit better interpretations of the results. We have developed a protocol to use the multilinear engine (ME-2) that is the solver used in EPA-PMF to make such analyses. Here we report how to use this approach and present results for a representative data set of particle size distributions obtained in Rochester, New York between 2008 and 2019.

Facing the challenges of air quality and health in a future climate: The Aveiro Region case study

Air pollution and climate change are the most important environmental issues for European citizens. Despite the air quality improvements achieved in recent years, with most pollutants' concentrations below the European Union legislated values, it is necessary to understand whether this will continue in the future due to expected climate changes impacts. In this context, this work tries to answer two main questions: (i) What is the relative contribution of emission source regions/activities to air quality, now and in the future, considering a climate change scenario?; and (ii) What additional policies are needed to support win-win strategies for air quality and climate mitigation and/or adaptation, at urban scale? For that, a climate and air quality modelling system, with source apportionment tools, was applied to the Aveiro Region, in Portugal. Main results show that in the future, due to the implementation of carbon neutrality measures, air quality in the Aveiro Region may improve, with reduction up to 4 μg.m−3 for particulate matter (PM) concentrations and 22 μg.m−3 for nitrogen dioxide (NO2), and consequently, the premature deaths due to air pollution exposure will also decrease. The expected air quality improvement will ensure that, in the future, the limit values of the European Union (EU) Air Quality Directive will not be exceeded, but the same will not happen if the proposed revision of the EU Air Quality Directive is approved. Results also shown that, in the future, industrial sector will be the one with higher relative contribution for PM concentrations and the second one for NO2. For that sector, additional emission abatement measures were tested, showing that, in the future, it is possible to comply with all the new limit values proposed by the EU.

Polycyclic aromatic hydrocarbons in a Natural Heritage Estuary influenced by anthropogenic activities in the South Atlantic: Integrating multiple source apportionment approaches

Polycyclic aromatic hydrocarbons (PAHs) were analysed in the sediments of one of the most well-preserved estuaries in South Brazil, the Paranaguá Estuarine System (PES), using several source apportionment tools. The ∑PAH ranged from < DL to 125.6 ng g−1 dw (dry weight) (average 29.9 ± 26.1 ng g−1 dw), and the lowest levels detected were similar to those found in other protected areas of the world. In general, the PAH concentrations indicated excellent environmental quality for the entire estuary. Principal component analysis indicated that fine sediments and total organic carbon were the main factors controlling PAH concentrations in the PES. Multiple PAH sources were identified in the study area; biomass burning and fossil fuel combustion predominated but considerable amounts of petrogenic residues were also observed. We identified evidence of a contribution from an adjacent watershed resulting from the construction of interconnections between large rivers and from years of intense deforestation in the local Atlantic Forest.

EMMTE: An Excel VBA tool for source apportionment of nitrate based on the stable isotope mixing model

Dual nitrate stable isotopes combined with end-member mixing models are typically used to identify nitrate sources in fields of geochemistry and environmental science, which helps to quantitively depict the geochemical behaviors of nitrate and accurately control the sources of nitrate pollution in waters. Recently, various models with different computation principles, working efficiency, and operation difficulty have been developed and applied in the source apportionment of nitrate. In this paper, an end-member mixing model tool on Excel™, namely EMMTE, has been written with Visual Basic for Application (VBA) and built into a macro-enabled Excel™ spreadsheet. Monte Carlo simulation and constraint relative deviation between the observed and the predicted values were included in the working algorithm to solve the mass balance equation. After comparison with the internationally recognized Bayesian framework (mixing stable isotope analysis in R, MixSIAR) in different cases (three practical cases and one virtual case), the preliminary results showed that the contribution of various sources to groundwater nitrate calculated by EMMTE was highly consistent with that by MixSIAR and the performance of EMMTE seemed to be as good as that of MixSIAR as indicated by the higher goodness-of-prediction, lower root-mean-square error, and lower relative deviation. Therefore, EMMTE is applicable in the source apportionment of groundwater nitrate, and might also be extended to other water bodies and mixtures. It provides a simple, feasible, and user-friendly for front-line workers without experience with MixSIAR to quantitively source apportionment of nitrate in waters.

Why did air quality experience little improvement during the COVID-19 lockdown in megacities, northeast China?

To inhibit the COVID-19 (Coronavirus disease 2019) outbreak, unprecedented nationwide lockdowns were implemented in China in early 2020, resulting in a marked reduction of anthropogenic emissions. However, reasons for the insignificant improvement in air quality in megacities of northeast China, including Shenyang, Changchun, Jilin, Harbin, and Daqing, were scarcely reported. We assessed the influences of meteorological conditions and changes in emissions on air quality in the five megacities during the COVID-19 lockdown (February 2020) using the WRF-CMAQ model. Modeling results indicated that meteorology contributed a 14.7% increment in Air Quality Index (AQI) averaged over the five megacities, thus, the local unfavorable meteorology was one of the causes to yield little improved air quality. In terms of emission changes, the increase in residential emissions (+15%) accompanied by declining industry emissions (−15%) and transportation (−90%) emissions resulted in a slight AQI decrease of 3.1%, demonstrating the decrease in emissions associated with the lockdown were largely offset by the increment in residential emissions. Also, residential emissions contributed 42.3% to PM2.5 concentration on average based on the Integrated Source Apportionment tool. These results demonstrated the key role residential emissions played in determining air quality. The findings of this study provide a scenario that helps make appropriate emission mitigation measures for improving air quality in this part of China.

Evaluation of FEAST for metagenomics-based source tracking of antibiotic resistance genes.

A metagenomics-based technological framework has been proposed for evaluating the potential and utility of FEAST as an ARG profile-based source apportionment tool. To this end, a large panel of metagenomic data sets was analyzed, associating with eight source types of ARGs in environments. Totally, 1089 different ARGs were found in the 604 source metagenomes, and 396 ARG indicators were identified as the source-specific fingerprints to characterize each of the source types. With the source fingerprints, predictive performance of FEAST was checked using "leave-one-out" cross-validation strategy. Furthermore, artificial sink communities were simulated to evaluate the FEAST for source apportionment of ARGs. The prediction of FEAST showed high accuracy values (0.933±0.046) and specificity values (0.959±0.041), confirming its suitability to discriminate samples from different source types. The apportionment results reflected well the expected output of artificial communities which were generated with different ratios of source types to simulate various contamination levels. Finally, the validated FEAST was applied to track the sources of ARGs in river sediments. Results showed STP effluents were the main contributor of ARGs, with an average contribution of 76 %, followed by sludge (10 %) and aquaculture effluent (2.7 %), which were basically consistent with the actual environment in the area.

Future year (2028) source apportionment modeling to support Regional Haze Rule planning in the western U.S.

ABSTRACT The Western Regional Air Partnership (WRAP) has developed a modeling platform to simulate the formation of haze-causing particles that impact federally-protected lands in the western United States. To assist state air quality planners in determining which emission sources are likely candidates for future mitigation, several source apportionment scenarios were evaluated, and two sets of results for the year 2028 are presented here: 1) a “high-level important regional sources” version, with broad emission categories (i.e. U.S. anthropogenic, international anthropogenic, natural, and fires), and 2) a “low-level anthropogenic emission sources within individual states” version, which refines the U.S. anthropogenic contribution to specific emission sectors within individual WRAP region states. Eight examples are discussed, which reflect the variation in source apportionment results at national parks, wilderness areas, and wildlife refuges in the western U.S. and suggest which emission sectors are candidates for mitigation to improve future visibility. In 2028, the contribution of domestic anthropogenic emissions at the eight sites ranges from 17% to 58%, with significant impacts from oil and gas production, fossil fuel electric generation, and federally-regulated mobile sources. The contribution from international anthropogenic sources can also be considerable, and ranges from 17% to 43%. Most sectors that are emitting sulfur dioxide (SO2) and nitrogen oxides (NOx), which are the two most likely particle precursors to be curtailed in the states’ Regional Haze plans, are declining. For example, in the 13 contiguous WRAP region states, NOx emissions from on-road mobile sources and electric generating units (EGUs) declined by 738 kton/yr (29% decrease) and 65 kton/yr (31% decrease), respectively, in 2028 as compared to current emission estimates, and SO2 emissions from EGUs declined by 42 kton/yr (29% decrease). NOx emissions from oil and gas development also declined by 25 kton/yr (9% decrease) but rose for SO2 emissions by 12 kton/yr (20% increase). Implications: The goal of the Regional Haze Rule (RHR) is to improve visibility at federally-protected areas, and to eventually arrive at natural conditions by the year 2064. Source apportionment tools within regional air quality models are useful for identifying which emission regions and sectors are contributing to haze-causing particles and can indicate to air quality planners where additional emission controls may be warranted.

Source Diversity of Intermediate Volatility n-Alkanes Revealed by Compound-Specific δ13C-δD Isotopes.

Intermediate volatility organic compounds (IVOCs) are important precursors of secondary organic aerosols, and their sources remain poorly defined. N-alkanes represent a considerable portion of IVOCs in atmosphere, which can be well identified and quantified out of the complex IVOC pool. To investigate the potential source diversity of intermediate volatility n-alkanes (IVnAs, nC12-nC20), we apportioned the sources of IVnAs in the atmosphere of four North China cities, based on their compound-specific δ13C-δD isotope compositions and Bayesian model analysis. The concentration level of IVnAs reached 1195 ± 594 ng/m3. The δ13C values of IVnAs ranged -32.3 to -27.6‰ and δD values -161 to -90‰. The δD values showed a general increasing trend toward higher carbon number alkanes, albeit a zigzag odd-even prevalence. Bayesian MixSIAR model using δ13C and δD compositions revealed that the source patterns of individual IVnAs were inconsistent; the relative contributions of liquid fossil combustion were higher for lighter IVnAs (e.g., nC12-nC13), while those of coal combustion were higher for heavier IVnAs (e.g., nC17-nC20). This result agrees with principal component analysis of the dual isotope data. Overall, coal combustion, liquid fossil fuel combustion, and biomass burning contributed about 47.8 ± 0.1, 35.7 ± 4.0, and 16.3 ± 4.2% to the total IVnAs, respectively, highlighting the importance of coal combustion as an IVnA source in North China. Our study demonstrates that the dual-isotope approach is a powerful tool for source apportionment of atmospheric IVOCs.

Investigating sources of surface ozone in central Europe during the hot summer in 2018: High temperatures, but not so high ozone

The changing emissions and climate have largely influenced the contribution of different sources on surface ozone, while the relations between the emissions, meteorological conditions and ozone sources are highly uncertain. In this study we modeled the sources of surface ozone in central Europe in the summer (June–July–August) of 2018, one of the warmest summers in Europe, with the regional chemical transport model CAMx and its source apportionment tool OSAT. Additional simulations with the anthropogenic emissions in 2000 were performed as high-emission scenarios to investigate the effects of reduced emissions on ozone sources, and a specific analysis on the coupled effects from meteorology was conducted based on measurements and backward trajectory calculations at three Swiss sites. The model results indicate that the highest contribution to summer afternoon surface ozone in Europe in 2018 comes from the boundary import (65%), followed by off-road traffic (11%) and road traffic (8%). Compared to the case using 2000 emissions, the lower emissions in 2018 lead to lower ozone in most of the areas in Europe except for some urban areas and shipping routes, and the highest decrease is from the road traffic for both the whole domain and the Swiss sites. The backward trajectory analysis at Swiss sites in 2000 (base year), 2003 (the warmest year) and 2018 (the 3rd warmest year) show that 2018 is the year with the highest fraction of air mass from the high ozone areas (from east in southern Switzerland and from north in northern Switzerland). The results indicate that the reduced anthropogenic emissions are the main reason responsible for the reduced high level ozone in the hot summer in central Europe.

Vehicular influence on atmospheric concentrations and source apportionment of polycyclic aromatic hydrocarbons in some major cities in three regions of Ghana using epiphytic lichens

The present study employed epiphytic lichens as biomonitor and passive air sampler for the assessment of fifteen (15) atmospheric polycyclic aromatic hydrocarbons (PAHs) in some major cities in three regions of Ghana. A total of 36 composite lichen samples were collected and analysed using Gas Chromatography - Tandem Mass Spectrometry (GC-MS-MS). The total PAH recorded ranged between 1909.9 ng/kg (A36) and 250,091.4 ng/kg (W15). Due to the inherent deficiencies in using a single source apportionment tool, multiple source apportionment methods including diagnostic ratios, principal component analysis/absolute principal component scores (PCA-APCS) and APCS with automatic linear model (APCS–ALM) were used to ascertain the source of PAHs in the lichens. The diagnostic ratios revealed a mix source of wood/grass and petrol/petroleum fuel combustion, with the major source ascribing to wood/grass combustion. The source apportionment confirmatory statistical test conducted with the PCA-APCS and APCS–ALM, were in good agreement with the diagnostic ratio. Both PCA-APCS and APCS–ALM suggested two significant sources (p < 0.0), with wood/grass combustion as the major (contributing 77.8%) and mix petroleum related sources being the other with 22.2% contribution of PAHs to the receptor sites. The study found PCA-APCS and especially APCS–ALM to be an effective statistical tool for PAH source apportionment in passive air samplers. To our knowledge, this is the first use of lichens for PAH monitoring in the country. Therefore, this study could serve as an inexpensive and real time bio-monitoring tool for air quality assessment in the African sub-region and the world at large.

Human serum elements’ levels and leukemia: A first pilot study from an adult Greek cohort

BackgroundThe present study focuses on the evaluation of potential relationships between trace elements and acute and chronic types of leukemia, via the determination of their levels in human blood serum. MethodsA total of 199 serum samples from a Greek cohort were examined, including both leukemia cases and controls. Elements’ analysis was carried out using inductively coupled plasma mass spectrometry (ICP-MS) and demographic features such as age, gender, smoking habits and area of residence were recorded and statistically treated applying Shapiro-Wilk, Kolmogorov-Smirnov, Mann Whitney and Kruskal Wallis tests (p < 0.05). Spearman correlation and principal component analysis (PCA) were also performed to investigate possible associations. ResultsThe results demonstrated significantly higher (p < 0.05) trace elements concentrations in cases’ serum compared to that of controls excluding Ba, with Cu (median concentration 1295 μg L−1) being the most abundant in cases. Additionally, concentration of toxic Pb and Cd were found at seven and four fold higher concentrations in cases, respectively. Among the trace elements examined, only Rb (164 μg L−1) was detected in higher concentrations in controls. Ba, Cd and Co presented the lowest concentrations (lower than 1 μg L−1). PCA was performed for overall and classified data, indicating a stronger relation among the toxic As, Cd, Ni and Pb in cases than controls, particularly referring to smokers and industrial sites’ residents. Hematological parameters and factors such as age and gender did not present any significant outcome or correlation. ConclusionsThe findings from this pilot study suggest a potential relationship between metals and leukemia, especially concerning the toxic ones. Results from the employed source apportionment tools imply that smoking and atmospheric degradation may be positively related with higher metal serum levels in leukemia patients.

Source apportionment of atmospheric particle number concentrations with wide size range by nonnegative matrix factorization (NMF)

Quantifying the sources of atmospheric particles is essential to air quality control but remains challenging, especially for the source apportionment of particles based on number concentration with wide size range. Here, particle number concentrations (PNC) with size range 19–20,000 nm involving four modes Nucleation, Aitken, Accumulation, and Coarse are used to do source apportionment of PNC at the Guangdong Atmospheric Supersite (Heshan) during July–October 2015 by nonnegative matrix factorization (NMF) with 6 factors. For July 2015, separated source apportionments for three different size ranges from collocated instruments nano scanning mobility particle sizer (NSMPS), SMPS, and aerodynamic particle sizer (APS) and for two different size ranges (below and above 100 nm) show similar quantitative source information with that for the one whole size range. The mean absolute difference of contribution percentages of total particle number concentrations (TPNC) based on 5 unique apportioned sources is 5.6 % (4.3–7.6 %) for the instrument segregated apportionment and 4.2 % (0–5.3 %) for the size range segregated apportionment respectively, relative to the one whole apportionment. Moreover, the contribution percentages of TPNC are close to the weighted sum of contribution percentages of all size bins, with a mean absolute difference of 1.1 % (0–3.4 %). In both these two aspects, the consistency among different technical paths proves the matrix factorization by NMF is practically desirable and the simplicity of reducing some steps or calculations saves time. Besides, dust can be identified with the wide size range including larger than 3000 nm. Six apportioned sources in the 4 months are Accumulation (32.4 %), Nucleation (20.0 %), Aitken (15.2 %), traffic (14.6 %), dust (10.6 %), and Coarse (7.1 %). Therefore, NMF would serve as a promising tool for PNC source apportionment with wide size range and conducting the apportionment with the whole size range in one matrix factorization procedure and using the single TPNC contribution percentage are feasible.

Secondary organic aerosol markers and related polar organic compounds in summer aerosols from a sub-urban site in Athens: Size distributions, diurnal trends and source apportionment

Size-segregated aerosols (six stages with a diameter from <0.49 to >7.2 μm) were collected during daytime and nighttime in the summer of 2020 and were analyzed for dicarboxylic acids, isoprene, α/β-pinene and β-caryophyllene secondary organic aerosol (SOA) tracers, aromatic acids, hydroxy-polyacids, monocarboxylic acids and levoglucosan. The vast majority of the detected compounds presented significantly higher (p < 0.05) concentrations in fine than in coarse modes, excluding benzoic and oleic acids for which the higher fine mode than coarse mode concentrations were not significant and pinonic acid which was found at higher coarse mode concentrations. The dominant compound in the fine mode was 2-methylerythritol (mean of 213 ± 79.4 ng m−3), whereas in coarse particles palmitic acid was the most abundant (mean of 22.8 ± 9.7 ng m−3). All of the detected compounds, except for terephthalic acid, presented higher daytime concentrations, a difference that in the cases of glutaric, suberic, azelaic and pinic acids was significant (p < 0.05). The six-stage size distribution showed various patterns, with most species peaking at particles with a diameter of <1.1 μm suggesting photoxidation sources, while significant peaks at the size of 3–7.2 μm have been observed for suberic, azelaic, pinonic, benzoic, trimellitic and monocarboxylic acids. The hydroscopic growth of particles during nighttime may explain the observed decrease of the fine to coarse concentration ratio. From the employed source apportionment tools four factors where derived explaining 83.0% of total the variance including oxidation of anthropogenic volatile organic compounds (35.6%), oxidation of monoterpenes and sesquiterpenes (21.5%), isoprene's oxidation (14.1%) and photoxidation of unsaturated fatty acids (11.8%).

Long-term spatial and temporal trends, and source apportionment of polycyclic aromatic compounds in the Athabasca Oil Sands Region

We investigated the spatio-temporal trends of polycyclic aromatic compounds (PACs) deposition in the Athabasca Oil Sands Region (AOSR) between 2008 and 2017, and applied source apportionment tools to assess sources using snowpacks. Estimated PAC mass deposition was significantly correlated with crude oil production (R2 = 0.48, p = 0.03), and increased between 2008 and 2017. Loadings of alkylated PACs c1-, c2-fluorenes/pyrenes and c1-, c3-benzo[a]anthracenes/chrysenes/triphenylenes significantly increased at mid-field sites (25–50 km from central industrial reference site, AR6) (Mann-Kendall, p < 0.05) reflecting physical expansion of the AOSR. The distance from emission sources was important in the deposition of PACs, including the distance from AR6 (R2 = 0.69–0.91), nearest petcoke storage (R2 = 0.77–0.88), 0.89) and upgrader stack (R2 = 0.56–0.61). Source apportionment PAC distribution profiles of the source materials (petcokes, oil sand ores, road dust) did not show unique matching profiles with the snowpacks. However, the minimal presence of retene in petcokes and an abundance of benzo[ghi]fluoranthene in road dust was observed, and suggests potential for these compounds as chemical markers in distinguishing sources. Furthermore, correlations between PACs and selected metal(loid)s in the AOSR snowpacks were assessed to infer potential common sources. Significant positive (p < 0.05) correlations between metal(loid)s enriched in bitumen (vanadium, molybdenum, nickel) and PACs, at near to mid-field (0–50 km from AR6) sites suggests common sources or similar transfer and fate processes. The results of our study convey data necessary for monitoring studies in the constantly developing AOSR, advance our knowledge of PACs profiles in source materials (including the much less studied alkylated PACs and dibenzothiophenes), which will be valuable for other studies related to oil pollution, urban run-off and forest fires.PACs mass deposition increasing between 2008 and 2017 coincident with crude oil production, and retene and benzo[ghi]fluoranthene show potential in distinguishing AOSR sources.

Leukemia and PAHs levels in human blood serum: Preliminary results from an adult cohort in Greece

This study focused on the evaluation of any possible relationship of polycyclic aromatic hydrocarbons and their hydroxylated derivatives, originated from different anthropogenic activities, with leukemia via determination of polycyclic aromatic hydrocarbons levels in human blood serum. It attempts to provide a sufficient profile of polycyclic aromatic hydrocarbons and their derivatives in leukemia patients (cases) and healthy donors (controls) in Greece, for which pertinent data is lacking. The determination was applied to 198 serum samples, including cases and controls. Demographic and environmental data, such as age, gender, smoking habits and area of residence were subjected to clustered analysis during the statistical treatment of the results. The results demonstrated a statistically significant difference between cases and controls regarding polycyclic aromatic hydrocarbons concentrations, with phenanthrene, fluorene and acenaphthene being the most abundant compounds (<19 ng mL−1). The same difference was also observed for hydroxylated derivatives measured in cases of acute leukemia and controls, with 1-hydroxy phenanthrene and 1-hydroxy pyrene appearing more enriched, with their median concentrations calculated at 11.3 and 7.6 ng mL−1, respectively. Source apportionment tools were employed for the evaluation of any potential associations among polycyclic aromatic hydrocarbons and several parameters. Molecular diagnostic ratios, applied in the classified data, indicated mainly that polycyclic aromatic hydrocarbons detected particularly in patients from rural sites could be originated from wood, grass or biomass burning. Principal Component Analysis, performed for overall and classified data, indicated a bioaccumulation of high molecular weight polycyclic aromatic hydrocarbons with age and chronic types of leukemia and a possible common origin of these toxic compounds in cases of smokers living in industrial residence areas.

Single source impacts on secondary pollutants using a Lagrangian reactive puff model: Comparison with photochemical grid models

Abstract Recent updates to U.S. regulatory guidelines for modeling impacts of single sources to secondary pollutants, such as ozone (O3) and fine particulate matter (PM2.5), require the use of established photochemical models with a complete treatment of gas-phase and aerosol chemistry as the preferred method for a Tier 2 demonstration approach. Such models include photochemical grid models (PGMs), as well as Lagrangian puff models with the requisite treatment of processes governing the formation of secondary pollutants from their precursors. SCICHEM is an open source reactive puff model that includes treatments for gas, aerosol, and aqueous-phase chemistry that are comparable to those in PGMs. The dispersion component of SCICHEM is based on the state-of-the-science puff model, SCIPUFF (Second-order Closure Integrated Puff). The model is a valuable tool that requires fewer resources and setup cost to run than PGMs to calculate the impacts of a single source or a small number of sources on downwind ozone and PM2.5. This paper describes a model inter-comparison study of secondary pollutant impacts due to emissions from a hypothetical coal-fired power plant stack. The models compared in this study include SCICHEM and the two most commonly used PGMs, CMAQ and CAMx. Stacks are located in 4 separate regions of the U.S. with distinct differences in chemical environments and geographical features. The key inputs (hypothetical stack parameters and emission rates, meteorology) to the three models are based on a common dataset for consistency. The source impacts calculated by the PGMs are based on zero-out simulations (i.e., with and without the source of interest) as well as the source apportionment tools available in CAMx, while SCICHEM directly predicts source impacts in a single simulation. Annual simulations are conducted to determine the frequency distribution of source impacts over the 4 regions. The comparison of model results shows both similarities and differences in the frequencies and magnitudes of peak impacts predicted by the three models. There is good agreement among all models in their predictions of 98th and 99th percentile impacts.

Polar organic compounds in PM10 and PM2.5 atmospheric aerosols from a background Eastern Mediterranean site during the winter period: Secondary formation, distribution and source apportionment

Atmospheric particle samples with aerodynamic diameter <10 μm (PM₁₀) and <2.5 μm (PM₂.₅) were analyzed for elemental (EC), organic (OC) carbon and polar organic compounds. Samples were collected, on a daily basis, over 44 days during the winter period in Agia Maria Xyliatou, a background location of Cyprus. Polar organic compounds were determined using a 3-step derivatization method prior to analysis with GC/MS. Gas phase compounds and meteorological data were also measured. Secondary OC was estimated and found to be significantly higher in PM₂.₅ than PM₁₀ fraction (mean of 0.81 ± 0.58 over 0.51 ± 0.66 μg m⁻³). Concentrations of biogenic secondary formation tracers, monocarboxylic acids, dicarboxylic acids and aromatic acids ranged from 7.3 to 29.0, 2.9–162, 7.6–82.0 and 1.9–19.6 ng m⁻³ respectively, in all aerosol samples, accumulated mostly on PM₂.₅ fraction. Molecular diagnostic ratios of selected carboxylic acids indicated influence of biogenic sources and aged aerosols. Source apportionment tools employed, including principal component analysis, demonstrated anthropogenic activity, biomass burning, biogenic volatile organic compounds oxidation and oxidation of unsaturated fatty acids as the basic sources of the studied analytes. Estimation of OC contribution from different sources was performed using tracer-based methods, such as “SOA tracer method” presenting biomass burning as a significant contributor (12.8 ± 14.8% in PM₂.₅ and 5.8 ± 4.8% in PM₁₀). Oxidation of biogenic volatile organic compounds accounted for 13.0 ± 8.9% and 5.6 ± 3.5% of OC in PM₂.₅ and PM₁₀ samples respectively. Dust episodes that occurred during the sampling period, appear to enhance secondary formation mostly on PM₁₀ particles.