Source and risk apportionment of selected VOCs and PM₂.₅ species using partially constrained receptor models with multiple time resolution data

Source apportionment of ambient PM2.5 in an industrialized city using dispersion-normalized, multi-time resolution factor analyses

Ambient fine particulate matter (PM_2.5) data were collected in the lower City of Hamilton, Ontario to apportion the sources of this pollutant over an 18-month period. Hamilton has complex topographical features that may result in worsened air pollution within the lower city, thus, dispersion-normalized, multi-time resolution factor analysis (DN-MT-FA) was used to identify and quantify contributions of factors in a manner that reduced the influence of local meteorology. These factors were secondary organic aerosols type 1 (SOA_1), particulate nitrate (pNO3), particulate sulphate (pSO4), primary traffic organic matter (PTOM), Steel/metal processing and vehicular road dust emissions (Steel & Mobile) and, secondary organic aerosols type 2 (SOA_2) with origins ranging from mainly regional to mainly local. Factors that were mainly local (PTOM, Steel & Mobile, SOA_2) contributed up to 17% of the average PM_2.5 mass while mixed local/regional factors (pNO3, pSO4) made up 43% on average, indicating the potential for further reduction of harmful PM concentrations locally. Of particular interest from a health protection perspective, was the composition of PM_2.5 on days when an exceedance of the 24-hr WHO air quality guideline for this pollutant was observed. In general, SOA_1 was found to drive summer exceedances while pNO3 dominated in the winter. During the summer period, SOA_1 was attributable to wildfires in the northern parts of Canada while local traffic sources in winter contributed to the high levels of pNO3. While local, industrial factors only had minor relative mass contributions during exceedances, they are high in highly oxidized organic species (SOA_2) and toxic metals (Steel & Mobile). Thus, they are likely to have more impacts on human health. The methods and results described in this work will be useful in understanding prevalent sources of particulate matter pollution in the ambient air in the presence of complex topography and meteorological effects.

Source apportionment of ambient PM10 collected at three sites in an urban-industrial area with multi-time resolution factor analyses

Chemical speciation data for PM₁₀, collected for annual trend analyses of health-relevant species, at three receptor sites in a highly industrialized area (IJmond) in the Netherlands were used in a multi-time resolution receptor model (ME-2) to identify the PM₁₀ sources in this area. Despite the available data not being optimized for receptor modelling, five-factor solutions were obtained for all sites based on independent PMF analysis on PM₁₀ data from the three sites (IJM, WAZ and BEV). Four factors were common to all three sites: nitrate-sulphate (average percentage contributions to PM₁₀: IJM: 35.3 %, WAZ: 37.7 %, and BEV: 36.3 %); sea salt (20.2 %, 23.7 %, 15.2 %); industrial (8.1 %, 11.0 %, 18.1 %) and brake wear/traffic (31.4 %, 21.2 %, 20.6 %). At WAZ, a local/site-specific factor containing most of the PAH measurements was found (6.4 %) while a crustal matter factor was resolved at IJM (7.6 %) and BEV (9.8 %). Additionally, sludge-drying was a potential source of the marker species in the industrial factor at WAZ. Bootstrapping (BS) and factor displacement (DISP) were applied to the factor profiles in this work for error estimation. In general, the factor profiles at all three sites had very small intervals from both BS and DISP methods. To our knowledge, this is the first time DISP was applied in a complex model such as the multi-time resolution model. Most of the measured metal and PAH concentrations found in the IJmond area during the 2017-2019 period had local sources, with significant contributions from several processes related to the steel industry. This study shows that available detailed PM₁₀ chemical speciation data, although primarily collected for annual trend analyses of health-relevant species, could also be used in receptor modelling by applying a multi-time framework. We propose general recommendations for the optimization of the measurement strategy for source apportionment of PM in areas with similar urban-industrial land use.

Health risks of PM2.5-bound polycyclic aromatic hydrocarbon (PAH) and heavy metals (PPAH&HM) during the replacement of central heating with urban natural gas in Tianjin, China

To investigate the health effects of fine particulate matter (≤ 2.5 μm in aerodynamic diameter; PM_2.5)-bound heavy metals and polycyclic aromatic hydrocarbons (PAHs) before and after the implementation of the Urban Natural Gas Heating Project (UNGHP), the lifetime cancer risks, hazard quotients (HQs) of heavy metals and PAHs were calculated. Seven kinds of heavy metals (Al, As, Cd, Cr, Mn, Ni and Se) and 12 kinds of PAHs including acenaphthylene (ANY), acenaphthene (ANA), fluoranthene (FLT), pyrene (PYR), chrysene (CHR), benz[a]anthracene (BaA), benzo[b]fluoranthene (BbF), benzo[k]fluoranthene (BkF), benzo[a]pyrene (BaP), dibenz[a,h]anthracene (DBA), benzo[ghi]perylene (BPE) and indeno[1,2,3-cd]pyrene (IPY) were analyzed and used for the health risk assessments. It was found that HQ of Mn fell from 1.09 in the coal-burning period to 0.72 in the gas-burning period in the suburban area. And lifetime cancer risks of PAHs fell from 35.7 × 10^-6 in the coal-burning period to 17.22 × 10^-6 in the gas-burning period in the urban area. It could be concluded that, during the gas-burning period, downward trends were observed for the lifetime cancer risks and HQs of most kinds of heavy metals and PAHs in all regions of Tianjin compared to those during the coal-burning period. The UNGHP was effective, and we should also take other measures to control the pollution.

Elucidating sources of VOCs in the Capital Region of New York State: Implications to secondary transformation and public health exposure

Exposure to ambient volatile organic compounds (VOCs) in urban areas is of interest because of their potential adverse effects to public health. A study was carried out to elucidate ambient sources of VOCs in the Capital Region of New York State for the period 2015-2019. A combined dataset of VOCs and PM_2.5 species was used in positive matrix factorization (PMF) model to better interpret the complex nature of different sources. Ten sources were revealed, where background source (3.8 μg/m³, 30%) was the largest contributor to VOCs, followed by petroleum-related emissions (2.9 μg/m³, 22%) and pyrolyzed oxygen (OP)-Elemental Carbon (EC2)-aldehydes-rich (2.7 μg/m³, 21%). Other notable VOC sources included methyl ethyl ketone (MEK)-rich, vehicular traffic, and biomass burning. Both OP-EC2-aldehydes-rich and petroleum-related emissions showed notable contribution to ozone (O₃) and secondary organic aerosol (SOA) formation, respectively. Observed mean carcinogenic risk values of benzene and formaldehyde and 95th percentiles risk values of 1,3-butadiene and acetaldehyde were above the USEPA acceptable level of 1x10^-6 but below a tolerable risk of 1x10^-4. Estimated carcinogenic risk values of OP-EC2-aldehydes-rich, vehicular traffic, background and petroleum-related emissions were above the USEPA acceptable cancer risk and posed greater risk to public health (more than 80% of total carcinogenic risk) compared to other sources. Due to lack of some VOC species data (e.g., alkanes, alkenes, terpenes, alcohols), other urban VOC sources e.g., fugitive emissions, fuel evaporation, unburned fuel were not identified. More work is needed to better understand the contribution of VOC sources to O₃ and SOA formation in Albany and surrounding region. Findings can support policy makers in developing appropriate air quality management initiatives for the Capital Region in New York State.

Tracing riverine sulfate source in an agricultural watershed: Constraints from stable isotopes

The sulfate pollution in water environment gains more and more concerns in recent years. The discharge of domestic, municipal, and industrial wastewaters increases the riverine sulfate concentrations, which may cause local health and ecological problems. To better understand the sources of sulfate, this study collected water samples in a typical agricultural watershed in East Thailand. The source apportionment of sulfide was conducted by using stable isotopes and receptor models. The δ³⁴S_SO4 value of river water varied from 1.2‰ to 16.4‰, with a median value of 8.9‰. The hydrochemical data indicated that the chemical compositions of Mun river water were affected by the anthropogenic inputs and natural processes such as halite dissolution, carbonate, and silicate weathering. The positive matrix factorization (PMF) model was not suitable to trace source of riverine sulfate, because the meaning of the extracted factors seems to be vague. Based on the elemental ratio and isotopic composition, the inverse model yielded the relative contribution of sulfide oxidation (approximately 46.5%), anthropogenic input (approximately 41.5%), and gypsum dissolution (approximately 12%) to sulfate in Mun river water. This study indicates that the selection of models for source apportionment should be careful. The large contribution of anthropogenic inputs calls an urgent concern of the Thai government to establish effective management strategies in the Mun River basin.

Quantifying spatial heterogeneity of vulnerability to short-term PM2.5 exposure with data fusion framework

The current estimations of the burden of disease (BD) of PM_2.5 exposure is still potentially biased by two factors: ignorance of heterogeneous vulnerabilities at diverse urbanization levels and reliance on the risk estimates from existing literature, usually from different locations. Our objectives are (1) to build up a data fusion framework to estimate the burden of PM_2.5 exposure while evaluating local risks simultaneously and (2) to quantify their spatial heterogeneity, relationship to land-use characteristics, and derived uncertainties when calculating the disease burdens. The feature of this study is applying six local databases to extract PM_2.5 exposure risk and the BD information, including the risks of death, cardiovascular disease (CVD), and respiratory disease (RD), and their spatial heterogeneities through our data fusion framework. We applied the developed framework to Tainan City in Taiwan as a use case estimated the risks by using 2006-2016 emergency department visit data, air quality monitoring data, and land-use characteristics and further estimated the BD caused by daily PM_2.5 exposure in 2013. Our results found that the risks of CVD and RD in highly urbanized areas and death in rural areas could reach 1.20-1.57 times higher than average. Furthermore, we performed a sensitivity analysis to assess the uncertainty of BD estimations from utilizing different data sources, and the results showed that the uncertainty of the BD estimations could be contributed by different PM_2.5 exposure data (20-32%) and risk values (0-86%), especially for highly urbanized areas. In conclusion, our approach for estimating BD based on local databases has the potential to be generalized to the developing and overpopulated countries and to support local air quality and health management plans.

Associations of fine particulate matter and constituents with pediatric emergency room visits for respiratory diseases in Shanghai, China

BACKGROUND

Although ambient fine particulate matter (PM_2.5) has been associated with adverse respiratory outcomes in children, few studies have examined PM_2.5 constituents with respiratory diseases in children in China.

OBJECTIVES

To investigate the associations of short-term exposure to PM_2.5 and its constituents with pediatric emergency room visits (ERVs) for respiratory diseases in Shanghai, China.

METHODS

We collected daily concentrations of PM_2.5 and its constituents in urban Shanghai from January 1, 2016, to December 31, 2018. Daily pediatric ERVs for four major respiratory diseases, including upper respiratory tract infection, bronchitis, pneumonia, and asthma, were obtained from 66 hospitals in Shanghai during the same period. Associations of exposure to daily PM_2.5 and constituents with respiratory ERVs were estimated using the over-dispersed generalized additive models.

RESULT

Short-term exposure to PM_2.5 and its constituents were associated with increased pediatric ERVs for respiratory diseases. Specifically, an interquartile range increase in the 3-day average PM_2.5 level (31 μg/m³) was associated with 1.86% (95%CI: 0.52, 3.22), 1.53% (95%CI: 0.01, 3.08), 1.90% (95%CI: 0.30, 3.52), and 2.67% (95%CI: 0.70, 4.68) increase of upper respiratory tract infection, bronchitis, pneumonia, and asthma ERVs, respectively. As for PM_2.5 constituents, we found organic carbon, ammonium, nitrate, selenium, and zinc were associated with higher risk of respiratory ERVs in the single constituent and the constituent-PM_2.5 models.

CONCLUSION

Short-term exposure to PM_2.5 was associated with increased pediatric ERVs for respiratory diseases. Constituents related to anthropogenic combustion and traffic might be the dominant contributors of the observed associations.

Recent Progress of Thermocatalytic and Photo/Thermocatalytic Oxidation for VOCs Purification over Manganese-based Oxide Catalysts

Volatile organic compounds (VOCs) are one of the main sources of air pollution, which are of wide concern because of their toxicity and serious threat to the environment and human health. Catalytic oxidation has been proven to be a promising and effective technology for VOCs abatement in the presence of heat or light. As environmentally friendly and low-cost materials, manganese-based oxides are the most competitive and promising candidates for the catalytic degradation of VOCs in thermocatalysis or photo/thermocatalysis. This article summarizes the research and development on various manganese-based oxide catalysts, with emphasis on their thermocatalytic and photo/thermocatalytic purification of VOCs in recent years in detail. Single manganese oxides, manganese-based oxide composites, as well as improving strategies such as morphology regulation, heterojunction engineering, and surface decoration by metal doping or universal acid treatment are reviewed. Besides, manganese-based monoliths for practical VOCs abatementare also discussed. Meanwhile, relevant catalytic mechanisms are also summarized. Finally, the existing problems and prospect of manganese-based oxide catalysts for catalyzing combustion of VOCs are proposed.

Sources, variability and parameterizations of intra-city factors obtained from dispersion-normalized multi-time resolution factor analyses of PM2.5 in an urban environment

Ambient fine particulate matter (PM_2.5) data of similar continuously monitored species at two air monitoring sites with different characteristics within the City of Toronto were used to gauge the intra-city variations in the PM composition over a largely concurrent period spanning two years. One location was <8 m from the side of a major highway while the other was an urban background location. For the first time, multi-time resolution factor analysis was applied to dispersion-normalized concentrations to identify and quantify source contributions while reducing the influence of local meteorology. These factors were particulate sulphate (pSO4), particulate nitrate (pNO3), secondary organic aerosols (SOA), crustal matter (CrM) that were common to both sites, a hydrocarbon-like organic matter (HOM) exclusive to the urban background site, three black carbon related factors (BC, BC-HOM at the highway site, and a brown carbon rich factor (BC-BrC) at the urban background site), biomass burning organic matter (BBOM) and brake dust (BD) factors exclusive to the highway site. The PM_2.5 composition was different between these two locations, over only a 10 km distance. The sum of SOA, pSO4 and pNO3 at the urban background site averaged 57% of the PM_2.5 mass while the same species represented 43% of the average PM_2.5 mass at the highway site. Local or site-specific factors may be of greater interest for control policy design. Thus, regression analyses with potential explanatory, site-specific variables were performed for results from the highway site. Three model approaches were explored: multiple linear regression (MLR), regression with a generalized reduced gradient (GRG) algorithm, and a generalized additive model (GAM). GAM gave the largest fraction of variance for the locally-found factors at the highway site. Heavy-duty vehicles were most important for explaining the black carbon (BC and BC-HOM) factors. Light-duty vehicles were dominant for the brake dust (BD) factor. The auxiliary modelling for the local factors showed that the traffic-related factors likely originated along the main roadways at their respective sites while the more regional factors, - pSO4, pNO3, SOA, - had sources that were both regional and local in origin and with contributions that varied seasonally. These results will be useful in understanding ambient particulate matter sources on a city scale that will support air quality management planning.

Source apportionment and source-specific health risk assessment of heavy metals in size-fractionated road dust from a typical mining and smelting area, Gejiu, China

Source-specific health risk apportionment for heavy metals is critical for pollution prevention and risk management in mining and smelting areas. An integrated method combining health risk assessments with the positive matrix factorization model was proposed to evaluate source-specific health risks for adults and children. A typical mining and smelting area was taken as an example in the present study to apportion the source-specific health risks to humans. A total of 37 road dust samples collected from the industrial (IA) and residential areas (RA) of Gejiu (China) were analyzed for heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn). The results indicated that road dust in the study area was mainly contaminated with Cd, Cu, Pb, and Zn. Three potential sources, including atmospheric deposition, industrial waste, and natural sources, were identified and quantified, with contributions of 43.32%, 30.83%, and 25.85%, respectively. For non-carcinogenic risks, a similar trend of the source contribution was found for adults and children under the same land use; atmospheric deposition made the greatest contribution to the non-carcinogenic risk in both IA and RA. However, for carcinogenic risk, natural sources were the greatest contributor to human health risks in both IA and RA, followed by atmospheric deposition and industrial waste. The investigation in this study allowed the evaluation of health risks from potential contamination sources and the results provide valuable information on health risk mitigation strategies for environmental managers.

A review of confined-structure catalysts in the catalytic oxidation of VOCs: synthesis, characterization, and applications

This picture depicts the process of the catalytic oxidation of VOCs on confined-structure catalysts, which possess excellent activity and can effectively protect the active phase from aggregation and poisoning.

Chemical Composition and Source Apportionment of PM10 in a Green-Roof Primary School Building

Research on air quality issues in recently refurbished educational buildings is relatively limited. However, it is an important topic as students are often exposed to high concentrations of air pollutants, especially in urban environments. This study presents the results of a 25-day experimental campaign that took place in a primary school located in a densely built-up area, which retains a green roof system (GRS). All measurements refer to mass concentrations and chemical analysis of PM10 (particulate matter less than 10 micrometers), and they were implemented simultaneously on the GRS and within the classroom (C3) below during different periods of the year. The results demonstrated relatively low levels of PM10 in both experimental points, with the highest mean value of 72.02 μg m−3 observed outdoors during the cold period. Elemental carbon (EC) was also found be higher in the ambient environment (with a mean value of 2.78 μg m−3), while organic carbon (OC) was relatively balanced between the two monitoring sites. Moreover, sulfate was found to be the most abundant water soluble anion (2.57 μg m−3), mainly originating from ambient primary SO2 and penetrating into the classroom from windows. Additionally, the crustal origin of particles was shown in trace metals, where Al and Fe prevailed (9.55% and 8.68%, respectively, of the total PM10). Nevertheless, infiltration of outdoor particles within the classroom was found to affect indoor sources of metals. Finally, source apportionment using a positive matrix factorization (PMF) receptor model demonstrated six main factors of emissions, the most important of which were vehicles and biomass burning (30.30% contribution), along with resuspension of PM10 within the classroom from human activities (29.89% contribution). Seasonal variations seem to play a key role in the results.

Effect of Absorbed Sulfate Poisoning on the Performance of Catalytic Oxidation of VOCs over MnO2

Manganese oxides have displayed vast potential for future development in the field of catalytic abatement of volatile organic compounds (VOCs) because of their low cost, high stability, and enhanced catalytic activity. Manganese sulfate and manganese chloride are widely used as reaction sources to prepare manganese oxides. As reported, absorbed chloride usually affects the performance of catalysts. However, the effect of absorbed sulfate on catalysts has been overlooked at present. Herein, the poisoning effect of absorbed sulfate on MnO₂ catalyst in the catalytic oxidation of VOCs has been uncovered. Manganese sulfate-derived MnO₂ catalyst exhibits a significantly enhanced performance after repeated washing by water, which indicates that absorbed sulfate has an adverse effect on MnO₂ catalyst for removal of VOCs. The blocking of the surface oxygen species and active sites is considered as the reason for sulfate poisoning. Hence, elimination of absorbed sulfate by thorough washing or other effective method is essential for preparing high-performance manganese sulfate-derived manganese oxide catalysts.

Ambient particulate matter source apportionment using receptor modelling in European and Central Asia urban areas

This work presents the results of a PM2.5 source apportionment study conducted in urban background sites from 16 European and Asian countries. For some Eastern Europe and Central Asia cities this was the first time that quantitative information on pollution source contributions to ambient particulate matter (PM) has been performed. More than 2200 filters were sampled and analyzed by X-Ray Fluorescence (XRF), Particle-Induced X-Ray Emission (PIXE), and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) to measure the concentrations of chemical elements in fine particles. Samples were also analyzed for the contents of black carbon, elemental carbon, organic carbon, and water-soluble ions. The Positive Matrix Factorization receptor model (EPA PMF 5.0) was used to characterize similarities and heterogeneities in PM2.5 sources and respective contributions in the cities that the number of collected samples exceeded 75. At the end source apportionment was performed in 11 out of the 16 participating cities. Nine major sources were identified to have contributed to PM2.5: biomass burning, secondary sulfates, traffic, fuel oil combustion, industry, coal combustion, soil, salt and "other sources". From the averages of sources contributions, considering 11 cities 16% of PM2.5 was attributed to biomass burning, 15% to secondary sulfates, 13% to traffic, 12% to soil, 8.0% to fuel oil combustion, 5.5% to coal combustion, 1.9% to salt, 0.8% to industry emissions, 5.1% to "other sources" and 23% to unaccounted mass. Characteristic seasonal patterns were identified for each PM2.5 source. Biomass burning in all cities, coal combustion in Krakow/POL, and oil combustion in Belgrade/SRB and Banja Luka/BIH increased in Winter due to the impact of domestic heating, whereas in most cities secondary sulfates reached higher levels in Summer as a consequence of the enhanced photochemical activity. During high pollution days the largest sources of fine particles were biomass burning, traffic and secondary sulfates.

Source apportionment of hourly-resolved ambient volatile organic compounds: Influence of temporal resolution

High temporal-resolution VOC concentration data can provide detailed and important temporal variations of VOC species and emission sources, which is not possible when using coarse temporal-resolution data. In this study, we utilized the positive matrix factorization (PMF) model to conduct source apportionment of hourly concentrations of nineteen VOC species and CO measured at the Mong Kok air quality monitoring station, operated by the Hong Kong Environmental Protection Department, from January 2013 to December 2014. The PMF analysis of the hourly dataset (PMF_Hourly) identified five sources, including liquefied petroleum gas (LPG) (contribution of 45%), gasoline exhaust (21%), combustion (20%), biogenic emission (9%), and paint solvents (6%). The diurnal patterns of VOC emissions from identified sources are likely to be affected by the strength of emissions, variation of the planetary boundary layer height, and photochemical reactions. In addition, the PMF analyses of hourly and 24-hour averaged data of the hourly-resolved data (PMF_Hourly and PMF_Daily) were generally comparable, but the time series of VOC emissions from PMF_Hourly could not be well captured by PMF_Daily for two local VOC sources of gasoline exhaust and LPG. This study highlights the benefit of high temporal-resolution measurement data in apportioning VOC sources, hence providing critical information on VOC emission sources (e.g., diurnal variations) for controlling VOC emissions effectively.

Vertical distribution of source apportioned PM2.5 using particulate-bound elements and polycyclic aromatic hydrocarbons in an urban area

Receptor models have been widely used for identifying and quantifying source-specific contributions from mixtures of air pollutants. Nonetheless, our knowledge is still limited on how various components of air pollution are vertically distributed and the sources of such pollutants. In this study, we collected 135 samples of PM_2.5 (particles with aerodynamic diameter less than or equal to 2.5 µm) from building balconies at three altitudes in the metropolis of Taipei (Taiwan) and analyzed the samples for elements and polycyclic aromatic hydrocarbons that could be used to identify the sources of those pollutants. We used positive matrix factorization (PMF) to identify seven likely sources, including combustion, sulfur-rich aerosol, fresh traffic, industry/Cr-rich, oil combustion/vehicle, dust, and traffic. Although PM_2.5 mass differed significantly between low-level and mid-level sites, the largest contributor to PM_2.5 mass (sulfur-rich aerosol, 35.2%) showed nonsignificant variation in the vertical distribution. In contrast, oil combustion/vehicle, which exhibited significant difference between mid-level sites and the other two altitudes, might be a determinant in the vertical variation of PM_2.5. We also observed negative trends with sampling height for combustion and traffic emissions.

Bimetallic Catalysts for Volatile Organic Compound Oxidation

In recent years, the impending necessity to improve the quality of outdoor and indoor air has produced a constant increase of investigations in the methodologies to remove and/or to decrease the emission of volatile organic compounds (VOCs). Among the various strategies for VOC elimination, catalytic oxidation and recently photocatalytic oxidation are regarded as some of the most promising technologies for VOC total oxidation from urban and industrial waste streams. This work is focused on bimetallic supported catalysts, investigating systematically the progress and developments in the design of these materials. In particular, we highlight their advantages compared to those of their monometallic counterparts in terms of catalytic performance and physicochemical properties (catalytic stability and reusability). The formation of a synergistic effect between the two metals is the key feature of these particular catalysts. This review examines the state-of-the-art of a peculiar sector (the bimetallic systems) belonging to a wide area (i.e., the several catalysts used for VOC removal) with the aim to contribute to further increase the knowledge of the catalytic materials for VOC removal, stressing the promising potential applications of the bimetallic catalysts in the air purification.

Ambient volatile organic compounds in a suburban site between Beijing and Tianjin: Concentration levels, source apportionment and health risk assessment

Volatile organic compounds (VOCs) have vital implications for secondary pollutants, atmospheric oxidation and human health. Ambient VOCs were investigated using an online system, gas chromatography-mass spectrometry/flame ionization detector (GC-MS/FID), at a suburban site in Xianghe in the North China Plain from 6 November 2017 to 29 January 2018. Positive matrix factorization (PMF) receptor model was applied to identify the major VOC contributing sources. Four-step health risk assessment method was used to estimate risks of all risk-posing VOC species. A total of 101 VOCs were quantified, and the mean concentration of total VOCs was 61.04 ± 65.18 ppbv. The VOCs were dominated by alkanes (38.76%), followed by alkenes, aromatics, halocarbons, OVOCs, acetylene and acetonitrile. The results of PMF revealed that vehicle exhaust, industrial emissions, liquefied petroleum gas & natural gas, solvent utilization and secondary and long-lived species contributed 31.0%, 26.4%, 18.6%, 13.6% and 10.4%, respectively, to the total VOCs. Pollutant-specific and source-specific noncarcinogenic and carcinogenic risk estimates were conducted, which showed that acrolein and vehicle exhaust had evident noncarcinogenic risks of 4.9 and 0.9, respectively. The carcinogenic risks of specific species (1,3-butadiene, acetaldehyde, benzene, chloroform and 1,2-dichloroethane) and identified sources were above the United States Environmental Protection Agency (USEPA) acceptable level (1.0 × 10^-6) but below the tolerable risk level (1.0 × 10^-4). Vehicle exhaust was the largest contributor (56.2%) to noncarcinogenic risk, but solvent utilization (32.6%) to carcinogenic risk. Moreover, with the evolution of pollution levels, almost all VOC species, contributions of alkenes, aromatics, solvent utilization and vehicle exhaust, and pollutant-specific and source-specific risks increased continuously and noticeably. Collectively, our findings unraveled the importance of alkenes, aromatics, solvent utilization and vehicle exhaust in the evolution of pollution levels. Future studies should consider targeting these VOC groups and sources when focusing on effective reduction strategies and assessing public health risks.

Speciation of organic fractions does matter for aerosol source apportionment. Part 3: Combining off-line and on-line measurements

The present study proposes an advanced methodology to refine the source apportionment of organic aerosol (OA). This methodology is based on the combination of offline and online datasets in a single Positive Matrix Factorization (PMF) analysis using the multilinear engine (ME-2) algorithm and a customized time synchronization procedure. It has been applied to data from measurements conducted in the Paris region (France) during a PM pollution event in March 2015. Measurements included OA ACSM (Aerosol Chemical Speciation Monitor) mass spectra and specific primary and secondary organic molecular markers from PM₁₀ filters on their original time resolution (30 min for ACSM and 4 h for PM₁₀ filters). Comparison with the conventional PMF analysis of the ACSM OA dataset (PMF-ACSM) showed very good agreement for the discrimination between primary and secondary OA fractions with about 75% of the OA mass of secondary origin. Furthermore, the use of the combined datasets allowed the deconvolution of 3 primary OA (POA) factors and 7 secondary OA (SOA) factors. A clear identification of the source/origin of 54% of the total SOA mass could be achieved thanks to specific molecular markers. Specifically, 28% of that fraction was linked to combustion sources (biomass burning and traffic emissions). A clear identification of primary traffic OA was also obtained using the PMF-combined analysis while PMF-ACSM only gave a proxy for this OA source in the form of total hydrocarbon-like OA (HOA) mass concentrations. In addition, the primary biomass burning-related OA source was explained by two OA factors, BBOA and OPOA-like BBOA. This new approach has showed undeniable advantages over the conventional approaches by providing valuable insights into the processes involved in SOA formation and their sources. However, the origins of highly oxidized SOA could not be fully identified due to the lack of specific molecular markers for such aged SOA.

Associations of daily mortality with short-term exposure to PM2.5 and its constituents in Shanghai, China

Epidemiological studies have shown that fine particulate matter (PM_2.5) has adverse impacts on human health. However, limited studies have investigated the effects of short-term exposure to PM_2.5 and its constituents on mortality in China. This study used the generalized linear model (GLM) to investigate the effects of PM_2.5 and its constituents, including organic carbon (OC), element carbon (EC), ammonium (NH₄⁺), nitrate (NO₃^-), sulfate (SO₄^2-), on different causes of mortality in Shanghai from January 1, 2013 to December 31, 2015. The single-day lagged model and the moving average lagged model were used to examine the lagging effects of pollutants on mortality. At lag0 day, PM_2.5 had a significant effect on all-cause mortality, and a 10 μg/m³ increase leads to 0.68% increase in all-cause mortality (RR 1.0068, 95%CI 1.0013-1.0123). Among the five constituents, EC had the greatest impact on all-cause mortality in Shanghai, with 10.48% increase of mortality (RR 1.1048, 95%CI 1.0266-1.1891) per 10 μg/m³ increase of concentrations, followed by OC (RR 1.0577, 95%CI 1.0277-1.0886), NH₄⁺ (RR 1.0272, 95%CI 1.0028-1.0522) and SO₄^2- (RR 1.0104, 95%CI 1.0003-1.0206). For respiratory diseases mortality, EC, OC, NO₃^- and NH₄⁺ had significant impacts and caused an increase of mortality by 44.99% (RR 1.4499, 95%CI 1.1813-1.7794), 10.40% (RR 1.1040, 95%CI 1.0260-1.1880), 5.338% (RR 1.0533, 95%CI 1.0097-1.0989) and 7.34% (RR 1.0734, 95%CI 1.0015-1.1505) per 10 μg/m³ increase of concentrations, respectively. The cumulative effect of PM_2.5 on mortality was significant in Shanghai. Except for SO₄^2-, the RR value of the single-day lagged model was smaller than the moving average lagged model.

Pollution Characterization and Source Apportionment of Day and Night PM2.5 Samples in Urban and Suburban Communities of Tianjin (China)

Day and night PM_2.5 samples were collected from two typical urban and suburban communities in Tianjin. The major chemical components in PM_2.5, including the metal elements, polycyclic aromatic hydrocarbons (PAHs), and inorganic water-soluble ions, were monitored. A positive matrix factorization (PMF) model was used to apportion the potential sources of PM_2.5 at the two sites in the daytime and nighttime. The results indicated that the PM_2.5 concentration was higher in the suburban area than in the urban area during the daytime in winter. The daytime and nighttime PAHs concentrations at both sites were both generally higher in winter than in summer. The concentrations of some of the metal elements were higher in summer than in winter. Regional differences and day and night differences in the metals and water-soluble ions commonly existed. The PMF analysis indicated that coal combustion and transportation-related sources were the predominant sources in the urban and suburban areas in the daytime in winter, and secondary aerosols were the most important source for the suburban area in the nighttime in winter. There were more pollution sources of PM_2.5 during the daytime in summer, especially in the suburban area. In the nighttime in summer, the pollution sources of PM_2.5 in the urban and suburbs areas were basically the same, but the source apportionment was quite different.

PM2.5 source apportionment for the port city of Thessaloniki, Greece

This paper aims to identify the chemical fingerprints of potential PM2.5 sources and estimate their contribution to Thessaloniki port-city's air quality. For this scope, Positive Matrix Factorization model was applied on a comprehensive PM2.5 dataset collected over a one-year period, at two sampling sites: the port and the city center. The model indicated six and five (groups of) sources contributing to particle concentration at the two sites, respectively. Traffic and biomass burning (winter months) comprise the major local PM sources for Thessaloniki (their combined contribution can exceed 70%), revealing two of the major control-demanding problems of the city. Shipping and in-port emissions have a non-negligible impact (average contribution to PM2.5: 9-13%) on both primary and secondary particles. Road dust factor presents different profile and contribution at the two sites (19.7% at the port; 7.4% at the city center). The secondary-particle factor represents not only the aerosol transportation over relatively long distances, but also a part of traffic-related pollution (14% at the port; 34% at the city center). The study aims to contribute to the principal role of quantitative information on emission sources (source apportionment) in port-cities for the implementation of the air quality directives and guidelines for public health.

An innovative expression model of human health risk based on the quantitative analysis of soil metals sources contribution in different spatial scales

Toxicity of heavy metals from industrialization poses critical concern, and analysis of sources associated with potential human health risks is of unique significance. Assessing human health risk of pollution sources (factored health risk) concurrently in the whole and the sub region can provide more instructive information to protect specific potential victims. In this research, we establish a new expression model of human health risk based on quantitative analysis of sources contribution in different spatial scales. The larger scale grids and their spatial codes are used to initially identify the level of pollution risk, the type of pollution source and the sensitive population at high risk. The smaller scale grids and their spatial codes are used to identify the contribution of various sources of pollution to each sub region (larger grid) and to assess the health risks posed by each source for each sub region. The results of case study show that, for children (sensitive populations, taking school and residential area as major region of activity), the major pollution source is from the abandoned lead-acid battery plant (ALP), traffic emission and agricultural activity. The new models and results of this research present effective spatial information and useful model for quantifying the hazards of source categories and human health a t complex industrial system in the future.

Chemical characterization and quantitativ e assessment of source-specific health risk of trace metals in PM1.0 at a road site of Delhi, India

This study presents the concentration of submicron aerosol (PM_1.0) collected during November, 2009 to March, 2010 at two road sites near the Indian Institute of Technology Delhi campus. In winter, PM_1.0 composed 83% of PM_2.5 indicating the dominance of combustion activity-generated particles. Principal component analysis (PCA) proved secondary aerosol formation as a dominant process in enhancing aerosol concentration at a receptor site along with biomass burning, vehicle exhaust, road dust, engine and tire tear wear, and secondary ammonia. The non-carcinogenic and excess cancer risk for adults and children were estimated for trace element data set available for road site and at elevated site from another parallel work. The decrease in average hazard quotient (HQ) for children and adults was estimated in following order: Mn > Cr > Ni > Pb > Zn > Cu both at road and elevated site. For children, the mean HQs were observed in safe level for Cu, Ni, Zn, and Pb; however, values exceeded safe limit for Cr and Mn at road site. The average highest hazard index values for children and adults were estimated as 22 and 10, respectively, for road site and 7 and 3 for elevated site. The road site average excess cancer risk (ECR) risk of Cr and Ni was close to tolerable limit (10^-4) for adults and it was 13-16 times higher than the safe limit (10^-6) for children. The ECR of Ni for adults and children was 102 and 14 times higher at road site compared to elevated site. Overall, the observed ECR values far exceed the acceptable level.

Ambient fine particulate matter (PM2.5) in Canadian oil sands communities: Levels, sources and potential human health risk

An investigation of levels and potential sources affecting ambient fine particulate matter (PM_2.5) and associated risk to public health was undertaken at two Canadian oil sands communities (Fort McKay and Fort McMurray) using a 4-year dataset (2010-2013). Geometric mean concentrations of PM_2.5 at Fort McKay and Fort McMurray are not considered high and were 5.47μg/m³ (interquartile range, IQR=3.02-8.55μg/m³) and 4.96μg/m³ (IQR=3.20-7.04μg/m³), respectively. Carcinogenic risks of trace elements were below acceptable (1×10^-6) and/or within tolerable risk (1×10^-4), and non-carcinogenic risks were below a safe level of concern (hazard index=1). Positive matrix factorization (PMF) modeling revealed five sources, where fugitive dust appeared as the major contributor to PM_2.5 mass (Fort McKay: 32%, Fort McMurray: 46%) followed by secondary sulfate (31%, 42%) and secondary nitrate/biomass burning (26%, 8%). Other minor sources included a mining/mobile and a Mn-rich/Mn-Co-Zn-rich source. Source-specific risk values were also estimated and were well below acceptable and safe level of risks. Further work would be needed to better understand the contribution of secondary organic aerosols to PM_2.5 formation in these oil sands communities.

Source contributions to total concentrations and carcinogenic potencies of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) in ambient air: a case study in Suzhou City, China

The potential source categories and source contributions of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) in ambient air from Suzhou City, China, were performed by principal component analysis-multiple linear regression (PCA-MLR) and positive matrix factorization (PMF). The carcinogenic potencies of PCDD/Fs were quantitatively apportioned based on the positive matrix factorization-toxic equivalent concentration (PMF-TEQ) method. The results of the present study were summarized as follows. (1) The total concentrations and toxic equivalent concentrations of PCDD/Fs (∑PCDD/Fs and TEQ) in ambient air from Suzhou City were 1.34-42.80 pg N m^-3 and 0.081-1.22 pg I-TEQ N m^-3, respectively. (2) PCA-MLR suggested that industrial combustion (IC), electric arc furnaces (EAFs) and secondary aluminum smelters (ALSs), unleaded gas-fueled vehicle sources (UGFVs), ALSs, and hazardous solid waste incinerators (HSWIs) could be the primary PCDD/F contributors, accounting for 13.2, 16.7, 35.5, 19.4, and 15.2% of ∑PCDD/Fs, respectively. (3) PMF and PMF-TEQ indicated that EAFs (carbon steel), UGFVs, IC, ALSs, municipal solid waste incinerators (MSWIs) and hospital waste incinerators (HWIs), and HSWIs contributed 10.9, 10.9, 42.8, 11.3, 10.7, and 13.4% to ∑PCDD/Fs, but contributed 8.3, 12.3, 50.3, 12.7, 6.0, and 10.4% to carcinogenic potencies of PCDD/Fs. This study was the first attempt to quantitatively apportion the source-specific carcinogenic potencies of PCDD/Fs in ambient air.

Source apportionment of urban air pollutants using constrained receptor models with a priori profile information

Exposure to air pollutants such as volatile organic compounds (VOCs) and fine particulate matter (PM_2.5) are associated with adverse health effects. This study applied multiple time resolution data of hourly VOCs and 24-h PM_2.5 to a constrained Positive Matrix Factorization (PMF) model for source apportionment in Taipei, Taiwan. Ninety-two daily PM_2.5 samples and 2208 hourly VOC measurements were collected during four seasons in 2014 and 2015. With some a priori information, we used different procedures to constrain retrieved factors toward realistic sources. A total of nine source factors were identified as: natural gas/liquefied petroleum gas (LPG) leakage, solvent use/industrial process, contaminated marine aerosol, secondary aerosol/long-range transport, oil combustion, traffic related, evaporative gasoline emission, gasoline exhaust, and soil dust. Results showed that solvent use/industrial process was the largest contributor (19%) to VOCs while the largest contributor to PM_2.5 mass was secondary aerosol/long-range transport (57%). A robust regression analysis showed that secondary aerosol was mostly contributed by regional transport related factor (25%).

Ambient PM2.5 in the residential area near industrial complexes: Spatiotemporal variation, source apportionment, and health impact

This study systemically investigated the ambient PM_2.5 (n=108) with comprehensive analyses of the chemical composition, identification of the potential contributors, and estimation of the resultant respiratory physician visits in the residential regions near energy-consuming and high-polluting industries in central Taiwan. The positive matrix fraction (PMF) model with chemical profiles of trace metals, water-soluble ions, and organic/elemental carbons (OC/EC) was applied to quantify the potential sources of PM_2.5. The influences of local sources were also explored using the conditional probability function (CPF). Associations between the daily PM_2.5 concentration and the risk of respiratory physician visits for the elderly (≥65years of age) were estimated using time-series analysis. A seasonal variation, with higher concentrations of PM_2.5, metals (As, Cd, Sb, and Pb), OC/EC and ions (i.e., NO^3-, SO₄^2- and NH₄⁺) in the winter than in the spring and summer, was observed. Overall, an increase of 10μgm^-3 in the same-day PM_2.5 was associated with an ~2% (95% CI: 1.5%-2.5%) increase in respiratory physician visits. Considering the health benefits of an effective reduction, we suggest that the emission from coal combustion (23.5%), iron ore and steel industry (17.1%), and non-ferrous metallurgy (14.4%), accounting for ~70% of the primary PM_2.5 in the winter are prioritized to control.

Effects of fine particulate matter and its constituents on emergency room visits for asthma in southern Taiwan during 2008-2010: a population-based study

This population-based study evaluated the short-term association between fine particulate matter (PM_2.5) concentrations and its constituents and hospital emergency room visits (ERVs) for asthma in southern Taiwan during the period 2008-2010. Data on hospital ERVs for asthma and ambient PM_2.5 levels and its constituents were obtained from the National Health Insurance Research database and the Environmental Protection Administration, respectively. The quasi-Poisson generalized additive model was used to explore the associations between PM_2.5 and hospital ERVs for asthma. During the study period, the average daily number of ERVs for asthma and mean 24-h average level of PM_2.5 was 20.0 and 39.4 μg m^-3, respectively. The estimated effects of PM_2.5 on asthma ERVs fluctuated with increasing tendencies after adjusting for O₃ and attenuating tendencies after adjusting for NO₂, SO₂, and CO. Children were more susceptible than other age groups to the effects of PM_2.5 exposure on asthma ERVs, with the relative risks (RRs) for every 10 μg m^-3 increase in PM_2.5 being 1.016 [95% confidence interval (CI) = 1.002-1.030] and 1.018 (95% CI = 1.002-1.034), respectively, at a lag 0 day (i.e., no lag days) and lag 0-1 days. The effect of PM_2.5 concentrations on asthma ERVs was similar in male and female. Furthermore, asthma ERVs was significantly associated with concentrations of nitrate (NO₃^-), with the RR for each 1 μg m^-3 increase in NO₃^- concentrations being 1.004 (95% CI = 1.001-1.007) at lag 0 day. In conclusion, both PM_2.5 concentrations and its chemical constituents are associated with ERVs for asthma; moreover, children were more susceptible to the effects of PM_2.5 in southern Taiwan. PM_2.5 constituent, nitrate, is more closely related to ERVs for asthma.

A review of AirQ Models and their applications for forecasting the air pollution health outcomes

Even though clean air is considered as a basic requirement for the maintenance of human health, air pollution continues to pose a significant health threat in developed and developing countries alike. Monitoring and modeling of classic and emerging pollutants is vital to our knowledge of health outcomes in exposed subjects and to our ability to predict them. The ability to anticipate and manage changes in atmospheric pollutant concentrations relies on an accurate representation of the chemical state of the atmosphere. The task of providing the best possible analysis of air pollution thus requires efficient computational tools enabling efficient integration of observational data into models. A number of air quality models have been developed and play an important role in air quality management. Even though a large number of air quality models have been discussed or applied, their heterogeneity makes it difficult to select one approach above the others. This paper provides a brief review on air quality models with respect to several aspects such as prediction of health effects.

Spatiotemporal distribution and source apportionment of low molecular weight organic acids in wet precipitation at a coastal city, China

To investigate the characteristics and sources of low molecular weight (LMW) organic acids in wet precipitation at a coastal city, Xiamen, a total of 313 rainwater samples were collected at seven different functional areas from September 2012 to August 2013. Spatiotemporal characteristics of LMW organic acids as well as pH and electrical conductivity were analyzed. Meanwhile, air mass clusters in different seasons and the positive matrix factorization (PMF) source apportion model were comprehensively used to identify the sources of organic acids. In conclusion, the volume-weighted mean (VWM) concentration of formic (3.20 μmol/L), acetic (1.84 μmol/L), lactic (0.44 μmol/L), and oxalic acid (0.53 μmol/L) were obtained, which jointly contributed to 4.33% of the total free acidity (TFA). At the same time, the highest wet deposition flux of LMW organic acids and contribution of that to TFA were achieved at the forest protection area during growing season in Xiamen. In addition, biogenic emissions (77.12%), sea salts (13.77%), regional agriculture activities (3.92%), soil emissions (2.56%), biomass burning (1.47%), and secondary aerosols (1.15%) were determined as the source of LMW organic acids. Besides, the dominancy of biomass burning via long-range transport in non-growing season (NGS) and the contribution of biogenic emission in growing season (GS) were recognized. Finally, the considerable influence of sea salts on the LMW organic acids (13.77%) in Xiamen was quantified, especially for oxalic acid.

Spatial distribution, risk assessment and source identification of heavy metals in sediments of the Yangtze River Estuary, China

The aim of this study was to determine the spatial distribution, potential risks and sources of seven heavy metals in sediments of the Yangtze River Estuary. Analyses of 55 sediment samples revealed that the distributions of metals within the YRE were determined by the combined effects of their sources, hydrodynamic conditions, pH and Eh. According to the geoaccumulation index (I_geo) and sediment quality guidelines, Pb, Cd and Cr were present at low levels of pollution, with Cd posing the largest ecological risk. Positive Factor Matrix (PMF) results indicated that Hg, Zn, As, Pb and Cr mainly originated from natural geological background sources, while Cu originated from anthropogenic activities and atmospheric deposition was the source of Cd. These three sources contributed to 53.0%, 32.8% and 14.2%, respectively of total heavy metal concentrations. These results suggest that reducing the emission of Cd would promote a reduction of potential risks in sediments of the YRE.

Source apportionment of mass concentration and inhalation risk with long-term ambient PCDD/Fs measurements in an urban area

This study applies a receptor model to quantify source contributions to ambient concentration of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and inhalation cancer risk in Taipei from 2003 through 2009. Seventeen PCDD/F congeners were used in the effective variance solution to the Chemical Mass Balance equations to estimate source-specific mass contributions and inhalation risks. The average total PCDD/F concentration was 0.611pg/Nm(3) (0.036pg I-TEQ/Nm(3)). Traffic emissions contributed the most to the PCDD/F concentration (55.7%), followed by waste incinerators (18.6%) and joss stick burning (9.6%). For the inhalation cancer risk, the average was 1.1×10(-6) with traffic, waste incinerators, and joss paper burning as the main contributors (67.3%, 19.4%, and 6.3%, respectively). The mass and risk contributions of waste incinerators decreased significantly from 2003 to 2009 and were higher at downwind sites than at upwind sites. Reducing PCDD/F emissions from traffic and waste incinerators would provide the greatest health benefit. Policies that reduce the uncontrolled burning of joss stick and joss paper also need to be implemented.

Characterization and source apportionment of volatile organic compounds based on 1-year of observational data in Tianjin, China

From November 2014 to October 2015, the concentrations of volatile organic compounds (VOCs), O₃ and NOx were simultaneously monitored by using online instruments at the air monitoring station belonged to Tianjin Environmental Protection Bureau (TEPB). The results indicated that VOCs concentrations were higher in autumn and lower in spring, while O₃ concentrations were higher in summer, and lower in winter. The diurnal variations of VOCs and NOx (NO₂ plus NO) showed opposite tendency comparing to that of O₃. The concentrations of alkanes were higher (the average of 18.2 ppbv) than that of aromatics (5.3 ppbv) and alkenes (5.2 ppbv), however, the alkenes and aromatics made larger contributions to ozone because of their high reactivity. Tianjin belonged to the VOC-limited region during most of seasons (except summer) according to the VOC/NOx ratios (the 8:1 threshold). The automobile exhaust, industrial emission, liquefied petroleum gas/natural gas (LPG/NG), combustion, gasoline evaporation, internal combustion engine emission and solvent usage were identified as major sources of VOCs by Positive Matrix Factorization (PMF) model in Tianjin, and the contributions to VOCs for the entire year were 23.1%, 19.9%, 18.6%, 10.6%, 8.7%, 5.4% and 4.7%, respectively. The conditional probability function (CPF) analysis indicated that the contributing directions of automobile exhaust and industrial emission were mainly affected by source distributions, and that of other sources might be mainly affected by wind direction. The backward trajectory analysis indicated that the trajectory of air mass originated from Mongolia, which reflected the features of large-scale and long-distance air transport, and that of beginning in Jiangsu, Shandong and Tianjin, which showed the features of small-scale and short-distance. Tianjin, Beijing, Hebei and Northwest of Shandong were identified as major potential source-areas of VOCs by using potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models.

Review of receptor modeling methods for source apportionment

Efforts have been made to relate measured concentrations of airborne constituents to their origins for more than 50 years. During this time interval, there have been developments in the measurement technology to gather highly time-resolved, detailed chemical compositional data. Similarly, the improvements in computers have permitted a parallel development of data analysis tools that permit the extraction of information from these data. There is now a substantial capability to provide useful insights into the sources of pollutants and their atmospheric processing that can help inform air quality management options. Efforts have been made to combine receptor and chemical transport models to provide improved apportionments. Tools are available to utilize limited numbers of known profiles with the ambient data to obtain more accurate apportionments for targeted sources. In addition, tools are in place to allow more advanced models to be fitted to the data based on conceptual models of the nature of the sources and the sampling/analytical approach. Each of the approaches has its strengths and weaknesses. However, the field as a whole suffers from a lack of measurements of source emission compositions. There has not been an active effort to develop source profiles for stationary sources for a long time, and with many significant sources built in developing countries, the lack of local profiles is a serious problem in effective source apportionment. The field is now relatively mature in terms of its methods and its ability to adapt to new measurement technologies, so that we can be assured of a high likelihood of extracting the maximal information from the collected data.

IMPLICATIONS

Efforts have been made over the past 50 years to use air quality data to estimate the influence of air pollution sources. These methods are now relatively mature and many are readily accessible through publically available software. This review examines the development of receptor models and the current state of the art in extracting source identification and apportionments from ambient air quality data.

Implementing constrained multi-time approach with bootstrap analysis in ME-2: An application to PM2.5 data from Florence (Italy)

Advanced receptor models have been recently developed and tested in order to improve the resolution of apportionment problems reducing rotational ambiguity of results and aiming at identifying a larger number of sources. In particular, multi-time model is a factor analysis method able to compute source profiles and contributions using aerosol compositional data with different time resolutions. Unlike traditional factor analysis, each measured value can be inserted into multi-time model with its original time schedule, thus all temporal information can be effectively used in the modelling process. In this work, multi-time model was expanded in order to impose constraints on modelled factors aiming at improving the source identification. Moreover, as far as we know for the first time, a suitable bootstrap technique was implemented in the multi-time scheme to estimate the uncertainty of the final constrained solutions. These implemented approaches were tested on a PM2.5 (particulate matter with aerodynamic diameter <2.5 μm) dataset composed of 24-h samples collected during one year and hourly data sampled in parallel for two shorter periods in Florence (Italy). The daily samples were chemically characterised for elements, ions and carbonaceous components while elemental concentrations only were available for high-time resolved samples. The application of the advanced model revealed the major contribution from traffic (accounting for 37% of PM2.5 as annual average) and allowed an accurate characterisation of involved emission processes. In particular, exhaust and non-exhaust emissions were identified. The constraints imposed in the continuation run led to a better description of the factor associated to nitrates and also of biomass burning profile and the bootstrap results gave useful information to assess the reliability of source apportionment solutions. Finally, the comparison with the results computed by ME-2 base model applied to daily and hourly compositional data separately demonstrated the advantages provided by the multi-time approach.