Source Apportionment Of Metals Research Articles

Combining Cd and Pb isotope analyses for heavy metal source apportionment in facility agricultural soils around typical urban and industrial areas

Facility agriculture enhances food production capabilities. However, concerns persist regarding heavy metal accumulation resulting from extensive operation of this type of farming. This study integrated the total content, five fractions, and isotope composition of Cd and Pb in intensively farmed soils in regions characterized by industrialization (Shaoguan, SG) and urbanization (Guangzhou, GZ), to assess the sources and mechanisms causing metals accumulation. We found significantly more severe Cd/Pb accumulation and potential mobility in SG than GZ. Cd displayed higher accumulation levels and potential mobility than Pb. The distinct isotopic signals in SG (−0.54 to 0.47‰ for δ114/110Cd and 1.1755 to 1.1867 for 206Pb/207Pb) and GZ (−0.86 to 0.12‰ for δ114/110Cd and 1.1914 to 1.2012 for 206Pb/207Pb) indicated significant differences in Cd/Pb sources. The Bayesian model revealed that industrial activities and related transportation accounted for over 40% and approximately 30%, respectively, of the average contributions of Cd/Pb in SG. While urban-related (26.6%) and agricultural-related (26.3%) activities primarily contributed to Cd in GZ. The integration of δ114/110Cd and 208Pb/206Pb has further enhanced the regional contrast in sources. The present study established a comprehensive tracing system for Cd-Pb, providing crucial insights into the accumulation and distribution of these metals in facility agricultural soils.

Source Analysis Based on the Positive Matrix Factorization Models and Risk Assessment of Heavy Metals in Agricultural Soil

Soil heavy metal pollution is a severe and growing problem, and it is crucial to assess the level of soil heavy metal contamination and determine the origins of pollutants. However, there is limited research on soil heavy metal source apportionment and its carcinogenic and non-carcinogenic hazards. Positive Matrix Factorization (PMF) is a powerful technique for source apportionment of pollutants in environmental matrices such as atmospheric particulate matter and soil, as it can handle missing and imprecise data to ensure data reliability, among other benefits. In order to explore the distribution characteristics and main sources of heavy metals in agricultural land, the contents of Cd, Cr, Cu, Pb, and Ni were collected and determined. The positive matrix factorization (PMF) model was used to analyze the source of heavy metals in the soil in the study area, and the human health risk evaluation was carried out. The results showed that (1) the coefficient of variation of Cd in the four areas was much higher than that of the other four heavy metals, which showed strong variability; (2) the content and distribution of heavy metals in different regions were different under the influence of different environments; (3) the PMF model analysis showed that the heavy metal pollution sources in the four areas were divided into two types: the soil parent material, which had industrial pollution, traffic pollution, and agricultural pollution; and the contribution rate of each pollution source; (4) the non-carcinogenic risks of heavy metals in children at all points in the study area were greater than those of adults, and the carcinogenic risks were the opposite of the carcinogenic risk in the study area. And the most serious carcinogenic risk in the study area was the harm caused by oral ingestion of heavy metal Cr into the adults’ bodies.

Spatial trend and source apportionment of metals in wet atmospheric precipitation: a study on drying Urmia Lake implications, NW Iran

ABSTRACT During this decade, the drying of Urmia Lake resulted in devastating tragedies in the region, resulting in the emission of toxic metals into the atmosphere. Urmia city’s wet atmospheric depositions were analysed to assess the quantity and spatial trends of numerous heavy metals and sodium (Na), as well as their sources. Wet precipitation was collected as rainwater, and the concentration of metals was determined using an Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES). The mean concentrations of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), zinc (Zn), and sodium (Na) were 0.14, 0.18, 1, 3.7, 2.9, 5.6, 6.3 µg/L, and 2.6 mg/L, respectively, following the sequence Na > Zn > Ni > Cu > Pb > Cr > Cd > As. To identify the sources of these metals, enrichment factor analysis and principal component analysis (PCA) were employed. The enrichment factor analysis revealed that Na and As exhibited relatively low enrichment factors suggesting natural sources, whereas Zn, Cd, Cr, Cu, Ni, and Pb were highly enriched, indicating significant contributions from anthropogenic sources. The distribution map of Urmia City demonstrated that the northern and western parts of the city were highly polluted with As, Ni, Cr, and Zn. PCA analysis revealed that the emissions from vehicles and fuel combustion were the primary sources of Cd, Cr, Cu, Ni, and Pb, whereas the drying of the Urmia lake is the primary source of Na, As, and Zn. The process of the lake bottom drying likely releases these metals into the atmosphere, leading to their deposition in the surrounding areas.

Risk Assessment and Source Apportionment of Metals on Atmospheric Particulate Matter in a Suburban Background Area of Gran Canaria (Spain).

Concentration levels of 11 heavy metals were analyzed in PM10 and PM2.5 samples from a suburban area frequently affected by Saharan dust in which is located a school. The heavy metals risk assessment was carried out by the 2011 U.S. Environmental Protection Agency method, estimating the chronic and carcinogenic hazard levels both in adults and children. The highest level of chronic hazard was reached for Cr, with values of approximately 8 (PM10, adulthood), 2 (PM10, childhood) and 1.5 (PM2.5, adult age), significantly exceeding the limit value (equal to 1). Regarding the carcinogenic risk level, it was also high for Cr, with values between 10-3 and 10-1 for both study populations and particle size. For the rest of the studied metals, no health risk levels of concern were obtained. The positive matrix factorization method was used for the estimation of heavy metal emission sources apportionment. Non-exhaust vehicle emissions were the main source of Cr emissions under PM2.5, while industrial processes were the main source for PM10. Mineral dust and marine aerosol were common emission sources for both particles sizes-with different contributions. Vehicle emissions, construction and agricultural activities were the main emission sources for PM10, and fossil fuel combustion, road dust re-suspension and ammonium sulfate were for PM2.5. The results obtained in this study support the need to continue applying mitigation measures in suburban areas which are affected by nearby anthropogenic emissions, causing the consequent emission of materials hazardous to human health.

Ecological and health risks from heavy metal sources surrounding an abandoned mercury mine in the island paradise of Palawan, Philippines

A recent survey that determined heavy metal concentrations in an abandoned Hg mine in Palawan, Philippines, found the occurrence of Hg with As, Ba, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sb, Tl, V, and Zn. While the Hg originated from the mine waste calcines, the critical knowledge about the origin of the other heavy metals remains unknown. This study assessed the ecological and health risks from heavy metal pollution surrounding the abandoned Hg mine. Principal component analysis (PCA) showed that the abandoned mine and natural sources (i.e., local geology) are the two main contributors of heavy metal pollution. Historically, the mine waste calcines (retorted ore) were used as construction material for the wharf and as land filler for the adjacent communities. There is highly strong ecological risk associated with the heavy metals: Ni, Hg, Cr, and Mn contribute 44.3%, 29.5%, 10.7%, and 8.9% to the potential ecological risk index (RI), respectively. Hazard index (HI) exceeded 1 for both adults and children in all the sampling locations, implying non-carcinogenic adverse effects. The total cancer risk over a lifetime (LCR) also exceeded the threshold limit of 10−4 for both adults and children, contributed mainly by Cr (91.8%) and As (8.1%). By combining the results of the PCA and risk assessments, a clear link between heavy metal source apportionment to ecological and health risks was established. It was estimated that the abandoned mine contributed to most of the ecological and health risks for people living near the wharf that was built using the calcine, as well as the nearby Honda Bay. The findings of this study are expected to help policy makers develop regulations that will safeguard the ecosystem and the general public from the damaging impacts of heavy metals from the abandoned mine.

Contamination and source apportionment of metals in urban road dust (Jinan, China) integrating the enrichment factor, receptor models (FA-NNC and PMF), local Moran's index, Pb isotopes and source-oriented health risk

Contamination and source identifications of metals in urban road dust are critical for remediation and health protection. Receptor models are commonly used for metal source identification, whereas the results are usually subjective and not verified by other indicators. Here we present and discuss a comprehensive approach to study metal contamination and sources in urban road dust (Jinan) in spring and winter by integrating the enrichment factor (EF), receptor models (positive matrix factorization (PMF) and factor analysis with nonnegative constraints (FA-NNC)), local Moran's index, traffic factors and Pb isotopes. Cadmium, Cr, Cu, Pb, Sb, Sn and Zn were the main contaminants, with mean EFs of 2.0–7.1. The EFs were 1.0–1.6 times higher in winter than in spring but exhibited similar spatial trends. Chromium contamination hotspots occurred in the northern area, with other metal contamination hotspots in the central, southeastern and eastern areas. The FA-NNC results indicated Cr contamination primarily resulting from industrial sources and other metal contamination primarily originating from traffic emissions during the two seasons. Coal burning emissions also contributed to Cd, Pb and Zn contamination in winter. FA-NNC model-identified metal sources were verified via traffic factors, atmospheric monitoring and Pb isotopes. The PMF model failed to differentiate Cr contamination from other detrital metals and the above anthropogenic sources, largely due to the model grouping metals by emphasizing hotspots. Considering the FA-NNC results, industrial and traffic sources accounted for 28.5 % (23.3 %) and 44.7 % (28.4 %), respectively, of the metal concentrations in spring (winter), and coal burning emissions contributed 34.3 % in winter. Industrial emissions primarily contributed to the health risks of metals due to the high Cr loading factor, but traffic emissions dominated metal contamination. Through Monte Carlo simulations, Cr had 4.8 % and 0.4 % possibilities posing noncarcinogenic and 18.8 % and 8.2 % possibilities posing carcinogenic risks for children in spring and winter, respectively.

Source apportionment of mine contamination across streamflows

Globally, metals released by mine waste represent a challenge for protecting water quality and ecosystems. Understanding metal dispersion in catchments is critical for developing efficient remediation strategies and reducing contamination from mining activities. Efforts to address the issue have been constrained by diffuse sources and variation of source contributions across streamflows. In the UK, metal source apportionment is typically addressed using monitoring strategies with low spatial resolution, which can underestimate the contribution of diffuse sources. In this proof-of-concept study, diffuse sources were accurately apportioned in a mining-impacted catchment in Mid-Wales (UK), using a hydrogeochemical approach with combined continuous tracer injections, gulp injections, and streambed sediment geochemistry. The continuous tracer injections identified a major Zn and Pb point source, diffuse sources due to mine waste tip runoff, and potential groundwater contributions. Variations in source contributions were estimated during high and low flow conditions, with Zn having similar sources and importance across streamflows and Pb being released mainly from overground tips during high flow conditions (22% Pb under low flow and 80% Pb under high flow). The distribution of metal-bearing sediment along the stream sheds light on metal release mechanisms across streamflow conditions. This hydrogeochemical approach for source apportionment, builds on common monitoring methods, and represents a substantial advance in accounting diffuse mine contamination sources, understanding potential metal release mechanisms, and designing remediation strategies.

An insight into source apportionment of metals in superficial sediments from the Tien Hai nature reserve of the Red River delta, Vietnam.

In the present study, concentrations of 23 metallic elements (Al, Fe, K, Mg, Ti, Mn, V, Cr, Co, Ni, Cu, Zn, Ga, As, Sr, Zr, Mo, Cd, Ba, W, Hg, Pb and U) were determined in superficial sediments from 20 sites within the Tien Hai nature reserve of the Red River delta. An integrated approach including correlation analysis (CA), principal components analysis (PCA) and positive matrix factorization (PMF) was combined to identify and quantify the sources of these metals. The results indicated that the correlation analysis was able to identify both allochthonous and authigenous origin of metals while the remaining methods were unable to identify these origins. With the help of CA, the PMF model performed better at the source identification of metals than the PCA. The results of PMF demonstrated that weathering products formed on different parent rocks were the biggest contributor to natural sources of metals in the superficial sediments, while agricultural activities were regarded as the major contributor to anthropogenic sources of metals. These findings could provide a scientific basis for environmental protection authority to prevent and control the sediment metal pollution. Accordingly, application of organic amendments and reduction of inorganic fertilizer should be encouraged to minimize metal accumulation in sediments.

Chemical characterization and health risk assessement of size segreated PM at world heritage site, Agra

Air quality at two traffic junctions representing GLA indicating pollution at highway and Iradatnagar indicating rural pollution was evaluated in Uttar Pradesh, India. The present study aimed to determine the concentration of size-segregated PM with the characterization of metals at different traffic junctions i.e. (Agra and Mathura). In the study, PM2.5–1.0 and PM1.0–0.5 were measured with the help of Cascade Sioutas Impactor during the study period December to January 2018. The size fraction of PM2.5–1.0 was found to be higher at GLA (350.92 µg/m3) followed by Iradatnagar (329.12 µg/m3), whereas the average value of size fraction of PM1.0–0.5 was found higher at Iradatnagar (341.01 µg/m3) in comparison with GLA (313.47 µg/m3) respectively. The average PM2.5 concentration in all the sampling sites was found to be 7–8 times higher when compared with the National Ambient Air Quality Standards (60 µg/m3) (NAAQS, India). Twelve metals viz. (Al, Ba, Ca, Cd, Cr, Cu, Fe, Mg, Mn, Ni, Pb, and Zn) were subsequently determined by ICP-OES. Al, Ba, Ca, and Mg, were found in higher concentrations in comparison with other metals. Source apportionment of metals was done by PCA (Principal Component Analysis) which shows that metal loading of Al, Ca, Cr, Cu, Fe, and Ni was influenced by vehicular emission with 33.6% constitutes of the total variance. Higher bioavaiablity was observed for PM2.5–1.0 (5.12–6.46%) and least was found for PM1.0–0.5 (4.56–7.055%). For health risk estimation, the average value of HQs was found higher for PM1.0–0.5 size fraction. HQ values were recorded higher for GLA (7.95) for PM2.5–1.0 and (9.50) for PM1.0–0.5 fraction. Overall, the observed HQs values far exceeded the acceptable level. Average value (1 × 10–6) of carcinogenic risk factor was found higher for an adult and child respectively.

Refining the diagnostics of non-point source metals pollution to urban lakes based on interaction normalized PMF coupled with Bayesian network

Spatiotemporal variability complicates source apportionment of metals in urban lakes, especially when rainfall drives urban non-point source pollution. As, Cd, Cr, Pb, Hg, Ag, Co, Cu, Fe, Mn, Ni, Sb, Sr and Zn concentrations in 648 water samples collected before and after rain in 6 urban lakes of Beijing, China were determined during 2013–2015. The response of metals concentrations after rain to the interaction between rainfall and antecedent dry days was significant. Metals concentrations were normalized pursuant to the interaction effect as the input of positive matrix factorization (PMF) to develop the interaction normalized-PMF (IN-PMF). Four primary pollution sources were diagnosed. Sediment release was considered to be the main source of Fe, Co and Ni independent of rainfall. Hg, As and some Cr associated with pesticides and fertilizers were likely to come from soil erosion and runoff from green space. It is probable that road runoff was the dominant source for heavy metals related to traffic emissions, including Pb, Cd, Cu, Sb, Mn and Zn. Cr, Sr and some Cu and Zn as key elements of rooftops can be regarded as from roof runoff. The IN-PMF lowered roof and road runoff contributions and raised the contribution of soil erosion from green space, with Pb, Sb, Cu, Zn, Cd and Mn increasing by 15.9%, 10.7%, 13.1%, 12.2%, 13.3% and 16.8%. The results shed more light on the stormwater runoff pollution mitigation on impervious surfaces and metals enrichment problems in infiltration soil on green space in the low impact development (LID) setting. The Bayesian network revealed the spatial variability of transport and fate of metal elements from land surfaces to urban lakes, supplementing the secondary pollution sources from different land use. This study will provide new insights for source apportionment of non-point source pollution under the background of sponge city construction.

The assessment and source apportionment of metals in the water-level fluctuation zone of the upper reaches Yangtze mainstream

The assessment and source apportionment of metals in the water-level fluctuation zone of the upper reaches Yangtze mainstream

Pollution assessment and source apportionment of metals in paddy field of Salem, South India

Pollution assessment and source apportionment of metals in paddy field of Salem, South India

Contamination Assessment and Source Apportionment of Metals and Metalloids Pollution in Agricultural Soil: A Comparison of the APCA-MLR and APCA-GWR Models

Metals and metalloids accumulate in soil, which not only leads to soil degradation and crop yield reduction but also poses hazards to human health. Commonly, source apportionment methods generate an overall relationship between sources and elements and, thus, lack the ability to capture important geographical variations of pollution sources. The present work uses a dataset collected by intensive sampling (1848 topsoil samples containing the metals Cd, Hg, Cr, Pb, and a metalloid of As) in the Shanghai study area and proposes a synthetic approach to source apportionment in the condition of spatial heterogeneity (non-stationarity) through the integration of absolute principal component scores with geographically weighted regression (APCA-GWR). The results showed that three main sources were detected by the APCA, i.e., natural sources, such as alluvial soil materials; agricultural activities, especially the overuse of phosphate fertilizer; and atmospheric deposition pollution from industry coal combustion and transportation activities. APCA-GWR provided more accurate and site-specific pollution source information than the mainstream APCA-MLR, which was verified by higher R2, lower AIC values, and non-spatial autocorrelation of residuals. According to APCA-GWR, natural sources were responsible for As and Cr accumulation in the northern mainland and Pb accumulation in the southern and northern mainland. Atmospheric deposition was the main source of Hg in the entire study area and Pb in the eastern mainland and Chongming Island. Agricultural activities, especially the overuse of phosphate fertilizer, were the main source of Cd across the study area and of As and Cr in the southern regions of the mainland and the middle of Chongming Island. In summary, this study highlights the use of a synthetic APCA-GWR model to efficiently handle source apportionment issues with spatial heterogeneity, which can provide more accurate and specific pollution source information and better references for pollution prevention and human health protection.

Spatiotemporal variations and source apportionment of metals in atmospheric particulate matter in Beijing and its surrounding areas

To explore the pollution characteristics and sources of metals in fine particulate matter (PM2.5) in Beijing and surrounding areas, PM2.5 samples were collected at four sites in North China (Dongzhimen and Huairou in Beijing, Baoding, and Cangzhou in Hebei) for one year. Sixteen metals (K, Na, Ca, Mg, Al, Fe, Cu, Pb, Zn, Cd, As, Mn, Co, Ni, Cr, and V) were identified via inductively coupled plasma mass spectrometry (ICP-MS) assisted by microwave digestion. Concentrations of PM2.5 and the detected elements were the highest at Baoding and lowest at Huairou sites. Similar diurnal variations were observed at higher levels of PM2.5 and metals at night than during the day at four sites. Enrichment factor analysis indicated that Zn, As, Cu, Cd and Pb were the most abundant elements in the study area and originated from anthropogenic emissions. The positive matrix factorization (PMF) model was used to analyze the sources of PM2.5, namely, soil dust, vehicle emissions, fuel combustion, and coal combustion. The major source of metals in PM2.5 at the four sampling sites was soil dust and its contribution was above 35%. A health risk assessment revealed that Ni poses no cancer risk to adults and children at any site; Cd and Co pose no cancer risk to children at Dongzhimen, Huairou, and Cangzhou; and As and Cr pose cancer risk to adult men, women, and children.

Identification of heavy metal pollution in estuarine sediments under long-term reclamation: Ecological toxicity, sources and implications for estuary management

Sediment samples were collected to clarify the effect of changing sedimentary environment under long-term reclamation on heavy metals (Cr, Zn, Pb, Cu, Cd, and Ni) in a partially mixed estuary (Modaomen) of the Pearl River Delta. The ecological toxicity and source apportionment of these metals were discussed as well. The metal species during the 2010s (as 2015, 2018) was more enriched than that during the 2000s (as 2003) and 1990s (as 1991). This estuary overall suffered from a “moderate-to-high” pollution status. The element Cd was a major concern for the ecosystem's health because of its high toxicity. Sediment quality guidelines suggested that adverse biological effects were likely to be caused by Cu and Cd in the early adjustment stage, while the threats to marine organisms caused by the elements of Cu, Cr, Zn, and Ni were elevated during the 2010s. Two receptor models of PCA-MLR and PMF quantified the source types and contributions of these heavy metals. Strong intensity of industrial activities coupling with agricultural applications and import of adjacent seas were responsible for the enriched accumulation of heavy metals in sediments. Metal source apportionment would help to control the metal input into the estuary; identifying the role of sedimentary environment on heavy metals can inform the sediment quality management in the estuary.

Metal pollution in the Pearl River Estuary and implications for estuary management: The influence of hydrological connectivity associated with estuarine mixing

Understanding the metal pollution can help governments and estuary management groups manage metal inputs. Here, we comprehensively analyzed the behaviors of seven metals Cd, Zn, Cu, As, Pb, Cr, and Hg in water and the responses of these metals to hydrological connectivity in the Pearl River Estuary. The analyses were based on the field measurements of August-2016 in the estuary and January-2016 in the upper river mouth. We also assessed the ecosystem health of these metals. Overall, this estuary had an overall moderate pollution level, with occasional severe perturbations. The mean concentration of individual metal was in the order of Zn > As > Cu > Cr > Pb > Cd > Hg. The eastern estuary was more heavily polluted by metals (notably, Zn, Cd, and Cu) than the western estuary; this condition was attributable to sewage and industrial effluent discharges from the eastern urban cities of Dongguan and Shenzhen. Longitudinally, high levels of Cd and Zn appeared in the upper estuary, while elevated levels of Cu, As, Pb, Cr, and Hg were found in the middle and lower estuaries. The riverine inputs and estuarine mixing significantly influenced the distribution and movement of trace metals in the estuary, and have contributed to phytoplankton productivity (chlorophyll-a > 10 μg/L). River inflow inhibited the vertical diffusion of metals, and tidal currents facilitated surface-to-bottom mixing. Cu and Cd posed ecological risks. We determined the source contributions and transport routes of the metals using principal component analysis combining with multiple linear regression. The results of this study suggest that the source apportionment of metals can help to manage the source input entering into the estuary. Further, identified hydrological connectivity of metals can inform water quality managers in the highly anthropogenically influenced estuary.

Spatial distribution and source apportionment of metals in sediments of Meriç-Ergene Basin, Turkey

Spatial distribution and source apportionment of metals in sediments of Meriç-Ergene Basin, Turkey

Metal concentration, source, and health risk assessment of PM2.5 in children's bedrooms: Rural versus urban areas

The objective of this study is to gain a better understanding of the metal characteristics, sources, and health risks of children's exposure to PM2.5 and related metals in children's bedrooms in urban and rural areas. PM2.5 personal environmental monitoring samplers were used to collect both indoor and outdoor PM2.5 in urban and rural areas in Taiwan. Al, Cd, Cr, Mn, Pb, V, and Zn were analyzed by inductively coupled plasma mass spectrometry. Source apportionment of metals in PM2.5 was carried out with factor analysis (FA). Health risk assessment of metals was performed on children via inhalation. The average indoor PM2.5 concentrations were 11.9 ± 5.2 μg/m3 and 11.9 ± 4.7 μg/m3 in urban and rural areas, respectively. The most predominant metal indoors in urban areas was Al, followed by Zn, Pb, Mn, V, Cr, and Cd, with a similar result in rural areas. The results from FA indicated that traffic emission and oil combustion in the outside environment were major pollution sources to indoor Mn, V, and Zn; corrosion of building material could be a contributor to Al, Cd, and Pb; pollution sources were different to Cr in two areas. The carcinogenic risk for indoor Cr(VI) via inhalation was higher in urban areas (boy: 6.61E-06; girl: 6.18E-06) than that in rural areas (boy: 2.80E-06; girl: 2.62E-06). These findings will help us to further understand the pollution sources, health risks, and control strategies for metals in PM2.5 in children's bedrooms for reducing adverse health effects, including in rural areas.

Selection of metric for indoor-outdoor source apportionment of metals in PM2.5 : mg/kg versus ng/m3.

Trends in the elemental composition of fine particulate matter (PM2.5) collected from indoor, outdoor, and personal microenvironments were investigated using two metrics: ng/m3 and mg/kg. Pearson correlations that were positive using one metric commonly disappeared or flipped to become negative when the other metric was applied to the same dataset. For example, the correlation between Mo and S in the outdoor microenvironment was positive using ng/m3 (p < 0.05) but negative using mg/kg (p < 0.05). In general, elemental concentrations (mg/kg) within PM2.5 decreased significantly (p < 0.05) as PM2.5 concentrations (µg/m3) increased—a dilution effect that was observed in all microenvironments and seasons. An exception was S: in the outdoor microenvironment, the correlation between wt% S and PM2.5 flipped from negative in the winter (p < 0.01) to positive (p < 0.01) in the summer, whereas in the indoor microenvironment, this correlation was negative year‐round (p < 0.05). Correlation analyses using mg/kg indicated that elemental associations may arise from Fe‐Mn oxyhydroxide sorption processes that occur as particles age, with or without the presence of a common anthropogenic source. Application of mass‐normalized concentration metrics (mg/kg or wt%), enabled by careful gravimetric analysis, revealed new evidence of the importance of indoor sources of elements in PM2.5.

Potentially toxic elements in the Middle East oldest oil refinery zone soils: source apportionment, speciation, bioaccessibility and human health risk assessment.

In this research, fifteen potentially toxic elements (PTEs) (Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Sb, Sc and Zn) were analysed and quantified in samples collected at 44 sites in an urban area of Iran. Sources were apportioned using enrichment factors (EFs), modified pollution index (MPI), principal component analysis (PCA), multivariate linear regression of absolute principal component scores (MLR-APCS) and speciation, with a focus on anthropogenic PTEs in the urban and industrial soils of the Arvand Free Zone area, an oil-rich zone in the country. Furthermore, the bioaccessibility and the human health risks of PTEs were investigated. The EF revealed a significant enrichment for elements such as Cd, Cu, Hg, Mo, Pb, Sb and Zn. Values of MPI showed that Abadan industrial district and Abadan petrochemical complex are the most polluted sites in the study area.The PCA/MLR analysis revealed four main sources: natural sources, fossil fuel combustion, traffic and oil derivatives and petroleum waste. The relative contribution of each source to PTE concentration varied from 32.3% of the natural sources to 30.6% of traffic and from 20.1% of petroleum waste to 17% of fossil fuel combustion. The source apportionment of metals generated using MLR-APCS receptor modelling revealed that 85.0% of Hg was generated by oil products. Chemical speciation results were compatible with the results obtained from PCA. Bioaccessibility of PTEs decreased from gastric to intestinal phase except Mo and Sb due to their different geochemical characteristics. Hazard index (HI) for non-cancer risk of PTEs for both children and adults based on total element concentrations was estimated to range from 2-fold to more than 10-fold higher than that of bioaccessible phases.