Historical construction, quantitative source identification and risk assessment of heavy metals contamination in sediments from the Pearl River Estuary, South China.

Historical reconstruction of heavy metals (HMs) contamination in sediments is a key for understanding the effects of anthropogenic stresses on water bodies and predicting the variation trends of environmental state. In this work, eighteen sediment cores from the Pearl River Estuary (PRE) were collected to determine concentrations and geochemical fractions of HMs. Then, their potential sources and the relative contributions during different time periods were quantitatively identified by integrating lead-210 (210Pb) radioisotope dating technique into positive matrix factorisation (PMF) method. Pollution levels and potential ecological risks (PERs) caused by HMs were accurately assessed by enrichment factors (EF) based on establishment of their geochemical baselines (GCBs) and multiparameter evaluation index (MPE). HMs concentrations generally showed a particle size- and organic matter-dependent distribution pattern. During the period of 1958-1978, HMs concentrations remained at low levels with agricultural activities and natural processes being identified as the predominant sources and averagely contributing >60%. Since the reform and opening-up in 1978, industrial and traffic factors become the primary anthropogenic sources of HMs (such as Cu, Zn, Cd, Pb, Cr, and Ni), averagely increasing from 22.1% to 28.1% and from 11.6% to 23.4%, respectively. Conversely, the contributions of agricultural and natural factors decreased from 37.0% to 28.5% and from 29.3% to 20.0%, respectively. Subsequently, implementation of environmental preservation policies was mainly responsible for the declining trend of HMs after 2010. Little enrichment of sediment Cu, Zn, Pb, Cr and Ni with EFs (0.15-1.43) was found in the PRE, whereas EFs of Cd (1.16-2.70) demonstrated a slight to moderate enrichment. MPE indices of Cu (50.7-252), Pb (52.0-147), Zn (35.5-130), Ni (19.6-71.5), Cr (14.2-68.8) and Cd (0-9.90) highlighted their potential ecological hazards due to their non-residual fractions and anthropogenic sources.

Heavy metal spatial distribution, source analysis, and ecological risks in the central hilly area of Hainan Island, China: results from a high-density soil survey.

The presence of heavy metals in soil has gained considerable attention due to their potential risks to ecosystems and human health. In this study, a thorough soil investigation was performed in the hilly region of central Hainan, which was formerly regarded as an area with the highest ecological environmental quality. A total of 7094 soil samples were systematically collected with high density over a large area. Simultaneously, a detailed investigation was conducted on the surrounding environment of each sampling point, including environmental factors such as soil, land use and crop types. The soil samples were analysed for heavy metals, pH, organic matter, and other parameters. The soil heavy metal pollution level, ecological risk and health risk were evaluated using the geo-accumulation index and the potential ecological risk index. The findings showed that the average contents of the heavy metals As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in the soil were 1.68, 0.042, 24.2, 6.49, 0.0319, 7.06, 29.6 and 49.8 mg·kg-1 respectively. Except for Hg, the mean values of the other heavy metals were either lower than or similar to the background values of Hainan. Also, only a few localised areas showed contamination by heavy metals. The primary sources of heavy metals, identified by a positive matrix factorisation model, could be categorised into four types: natural sources related to the soil formation process from acidic intrusive rocks (such as granite); natural sources primarily influenced by atmospheric deposition; anthropogenic sources associated with agricultural activities; and natural sources related to the soil formation process from middle-mafic intrusive rocks and black shales. The correlation analysis and variance analysis findings suggested that the content of heavy metals in the soil was primarily associated with the parent rock. The study area generally had low heavy metal levels and was not significantly polluted. However, agricultural activities still affected the enrichment of heavy metals. Therefore, it is imperative to remain vigilant about the ecological risks linked to soil heavy metals while continuing land development and expanding agricultural activities in the future. These findings indicate that conducting high-density soil surveys can enhance our understanding of regional soil heavy metals and enable reliable recommendations for agricultural planning. Whether in areas with low pollution risk or potential pollution risk, it is recommended that high-density soil surveys be conducted provide scientific guidance for further agricultural development.

Source apportionment of PM2.5 light extinction in an urban atmosphere in China.

Haze in China is primarily caused by high pollution of atmospheric fine particulates (PM2.5). However, the detailed source structures of PM2.5 light extinction have not been well established, especially for the roles of various organic aerosols, which makes haze management lack specified targets. This study obtained the mass concentrations of the chemical compositions and the light extinction coefficients of fine particles in the winter in Dongguan, Guangdong Province, using high time resolution aerosol observation instruments. We combined the positive matrix factor (PMF) analysis model of organic aerosols and the multiple linear regression method to establish a quantitative relationship model between the main chemical components, in particular the different sources of organic aerosols and the extinction coefficients of fine particles with a high goodness of fit (R2=0.953). The results show that the contribution rates of ammonium sulphate, ammonium nitrate, biomass burning organic aerosol (BBOA), secondary organic aerosol (SOA) and black carbon (BC) were 48.1%, 20.7%, 15.0%, 10.6%, and 5.6%, respectively. It can be seen that the contribution of the secondary aerosols is much higher than that of the primary aerosols (79.4% versus 20.6%) and are a major factor in the visibility decline. BBOA is found to have a high visibility destroying potential, with a high mass extinction coefficient, and was the largest contributor during some high pollution periods. A more detailed analysis indicates that the contribution of the enhanced absorption caused by BC mixing state was approximately 37.7% of the total particle absorption and should not be neglected.

Distribution, Sources and Risk Assessment of Polychlorinated Biphenyls in Sediments from Beiluo River.

The distribution and source of polychlorinated biphenyls (PCBs) pollution in the Beiluo River, the secondary tributary of the Yellow River, still remain unclear. With the purpose of determining the distribution, origins, and pollution levels of PCBs and their consequences on ecological risks, the concentrations of 27 PCBs at 17 locations in the sediments of the Beiluo River were examined in this study. The results showed that the mass concentrations of ∑PCBs in the sediment ranged from 0.12 to 1.25 ng∙g-1 (DW), with the highest point at sampling site B13 downstream of the river. Compared to most river sediments, both domestically and internationally, the concentration of PCBs in the sediment of the Beiluo River was at a low level, with 10-PCB and 6-PCB as the main components, indicating that the PCBs that are difficult to volatilise and degrade are more likely to remain in the sediment. The origins of PCBs in the sediments of the Beiluo River were examined by using positive matrix factorisation (PMF). The results revealed that the contamination of PCBs in the sediments of the Beiluo River mainly resulted from industrial emissions, technical PCB mixtures, and coal and wood combustion. The results of the ecological risk assessment indicated that PCBs in the sediments of the study area rarely contribute to adverse biological effects and the potential low risk to the environment.

Towards a better understanding of fine PM sources: Online and offline datasets combination in a single PMF.

Source apportionment (SA) techniques allocate the measured ambient pollutants with their potential source origin; thus, they are a powerful tool for designing air pollution mitigation strategies. Positive Matrix Factorization (PMF) is one of the most widely used SA approaches, and its multi-time resolution (MTR) methodology, which enables mixing different instrument data in their original time resolution, was the focus of this study. One year of co-located measurements in Barcelona, Spain, of non-refractory submicronic particulate matter (NR-PM1), black carbon (BC) and metals were obtained by a Q-ACSM (Aerodyne Research Inc.), an aethalometer (Aerosol d.o.o.) and fine offline quartz-fibre filters, respectively. These data were combined in a MTR PMF analysis preserving the high time resolution (30 min for the NR-PM1 and BC, and 24 h every 4th day for the offline samples). The MTR-PMF outcomes were assessed varying the time resolution of the high-resolution data subset and exploring the error weightings of both subsets. The time resolution assessment revealed that averaging the high-resolution data was disadvantageous in terms of model residuals and environmental interpretability. The MTR-PMF resolved eight PM1 sources: ammonium sulphate + heavy oil combustion (25%), ammonium nitrate + ammonium chloride (17%), aged secondary organic aerosol (SOA) (16%), traffic (14%), biomass burning (9%), fresh SOA (8%), cooking-like organic aerosol (5%), and industry (4%). The MTR-PMF technique identified two more sources relative to the 24 h base case data subset using the same species and four more with respect to the pseudo-conventional approach mimicking offline PMF, indicating that the combination of both high and low TR data is significantly beneficial for SA. Besides the higher number of sources, the MTR-PMF technique has enabled some sources disentanglement compared to the pseudo-conventional and base case PMF as well as the characterisation of their intra-day patterns.

Identification of possible sources for potentially toxic elements and polycyclic aromatic hydrocarbons and their spatially varying relationships in urban soils of Dublin, Ireland.

Potentially toxic elements (PTEs) and polycyclic aromatic hydrocarbons (PAHs) harm the ecosystem and human health, especially in urban areas. Identifying and understanding their potential sources and underlying interactions in urban soils are critical for informed management and risk assessment. This study investigated the potential sources and the spatially varying relationships between 9 PTEs and PAHs in the topsoil of Dublin by combining positive matrix factorisation (PMF) and geographically weighted regression (GWR). The PMF model allocated four possible sources based on species concentrations and uncertainties. The factor profiles indicated the associations with high-temperature combustion (PAHs), natural lithologic factors (As, Cd, Co, Cr, Ni), mineralisation and mining (Zn), as well as anthropogenic inputs (Cu, Hg, Pb), respectively. In addition, selected representative elements Cr, Zn, and Pb showed distinct spatial interactions with PAHs in the GWR model. Negative relationships between PAHs and Cr were observed in all samples, suggesting the control of Cr concentrations by natural factors. Negative relationships between PAHs and Zn in the eastern and north-eastern regions were related to mineralisation and anthropogenic Zn-Pb mining. In contrast, the surrounding regions exhibited a natural relationship between these two variables with positive coefficients. Increasing positive coefficients from west to east were observed between PAHs and Pb in the study area. This special pattern was consistent with prevailing south-westerly wind direction in Dublin, highlighting the predominant influences on PAHs and Pb concentrations from vehicle and coal combustion through atmospheric deposition. Our results provided a better understanding of geochemical features for PTEs and PAHs in the topsoil of Dublin, demonstrating the efficiency of combined approaches of receptor models and spatial analysis in environmental studies.

Measurement of road traffic brake and tyre dust emissions using both particle composition and size distribution data.

Estimates of tyre and brake wear emission factors are presented, derived from data collected from roadside and urban background sites on the premises of the University of Birmingham, located in the UK's second largest city. Size-fractionated particulate matter samples were collected at both sites concurrently in the spring/summer of 2019 and analysed for elemental concentrations and magnetic properties. Using Positive Matrix Factorisation (PMF), three sources were identified in the roadside mass increment of the 1.0-9.9 µm stages of MOUDI impactors located at both sites, namely: brake dust (7.1%); tyre dust (9.6%); and crustal (83%). The large fraction of the mass apportioned to crustal material was suspected to be mainly from a nearby construction site rather than resuspension of road dust. By using Ba and Zn as elemental tracers, brake and tyre wear emission factors were estimated as 7.4 mg/veh.km and 9.9 mg/veh.km, respectively, compared with the PMF-derived equivalent values of 4.4 mg/veh.km and 11 mg/veh.km. Based on the magnetic measurements, an emission factor can be estimated independently for brake dust of 4.7 mg/veh.km. A further analysis was carried out on the concurrently measured roadside increment in the particle number size distribution (10 nm-10 µm). Four factors were identified in the hourly measurements: traffic exhaust nucleation; traffic exhaust solid particles; windblown dust; and an unknown source. The high increment of the windblown dust factor, 3.2 µg/m3, was comparable in magnitude to the crustal factor measured using the MOUDI samples (3.5 µg/m3). The latter's polar plot indicated that this factor was dominated by a large neighbouring construction site. The number emission factors of the exhaust solid particle and exhaust nucleation factors were estimated as 2.8 and 1.9 x 1012/veh.km, respectively.

Source apportionment of PM2.5 before and after COVID-19 lockdown in an urban-industrial area of the Lisbon metropolitan area, Portugal.

The lockdowns held due to the COVID-19 pandemic conducted to changes in air quality. This study aimed to understand the variability of PM2.5 levels and composition in an urban-industrial area of the Lisbon Metropolitan Area and to identify the contribution of the different sources. The composition of PM2.5 was assessed for 24 elements (by PIXE), secondary inorganic ions and black carbon. The PM2.5 mean concentration for the period (December 2019 to November 2020) was 13 ± 11 µg.m-3. The most abundant species in PM2.5 were BC (19.9%), SO4 2- (15.4%), NO3 - (11.6%) and NH4 + (5.3%). The impact of the restrictions imposed by the COVID-19 pandemic on the PM levels was found by comparison with the previous six years. The concentrations of all the PM2.5 components, except Al, Ba, Ca, Si and SO4 2-, were significantly higher in the winter/pre-confinement than in post-confinement period. A total of seven sources were identified by Positive Matrix Factorisation (PMF): soil, secondary sulphate, fuel-oil combustion, sea, vehicle non-exhaust, vehicle exhaust, and industry. Sources were greatly influenced by the restrictions imposed by the COVID-19 pandemic, with vehicle exhaust showing the sharpest decrease. Secondary sulphate predominated in summer/post-confinement. PM2.5 levels and composition also varied with the types of air mass trajectories.

Multi-scale volatile organic compound (VOC) source apportionment in Tianjin, China, using a receptor model coupled with 1-hr resolution data.

The multi-scale chemical characteristics and source apportionment of volatile organic compounds (VOCs) were analysed in Tianjin, China, using 1-hr resolution VOC-species data between November 1, 2018 and March 15, 2019. The average total VOC (TVOC) concentration was 30.6 ppbv during the heating season. The alkanes accounted for highest proportion of the TVOC, while the alkenes were the predominant species forming ozone, especially ethylene. Compared to the clean period, the concentration of acetylene during the haze events showed highest increase rate, followed by the ethane; and the concentrations and proportions of alkanes and alkenes were highest during the growth stage (GS) of haze events. The multi-scale apportionment results suggested petrochemical industry and solvent usage (PI/SU, 31.2%), vehicle emissions and liquefied petroleum gas (VE/LPG, 20.5%), and combustion emissions (CE, 19.1%) were the main VOC sources during the heating season. Compared to the clean period, the contributions of PI/SU, VE/LPG, CE, and refinery emissions notably increased during the haze events, while that of gasoline evaporation decreased. The contributions of PI/SU and RPI showed significantly increase during the GS of haze events, whereas most sources decreased during the dissipation stage of haze events. Diurnal-variations in source contributions during the haze events were clearer than the clean period, and the contributions of PI/SU, VE/LPG, and CE during the haze events were markedly higher at night. These findings provide valuable information to inform effective VOC control and prevention measures with specific relevance for the control of ozone pollution in Tianjin.

Chemical characteristics and source apportionment of PM2.5 using PMF modelling coupled with 1-hr resolution online air pollutant dataset for Linfen, China.

The chemical species in PM2.5 and air pollutant concentration data with 1-hr resolution were monitored synchronously between 15 November 2018 and 20 January 2019 in Linfen, China, which were analysed for multiple temporal patterns, and PM2.5 source apportionment using positive matrix factorisation (PMF) modelling coupled with online chemical species data was conducted to obtain the apportionment results of distinct temporal patterns. The mean concentration of PM2.5 was 124 µg/m3 during the heating period, and NO3- and organic carbon (OC) were the dominant species. The concentrations and percentages of NO3-, SO42-, and OC increased notably during the growth periods of haze events, thereby indicating secondary particle formation. Six factors were identified by the PMF model during the heating period, including vehicular emissions (VE: 26.5%), secondary nitrate (SN: 16.5%), coal combustion and industrial emissions (CC&IE: 25.7%), secondary sulfate and secondary organic carbon (SS&SOC: 24.4%), biomass burning (BB: 1.0%), and crustal dust (CD: 5.9%). The primary sources of PM2.5 on clean days were CD (33.3%), VE (23.1%), and SS&SOC (20.6%), while they were CC&IE (32.9%) and SS&SOC (28.3%) during the haze events. The contributions of secondary sources and CC&IE increased rapidly during the growth periods of haze events, while that of CD increased during the dissipation period. Diurnal variations in the contribution of secondary sources were mainly related to the accumulation and transformation of corresponding gaseous precursors. In comparison, contributions of CC&IE and VE varied as a function of the domestic heating load and peak levels occurred during the morning and evening rush hours. High contributions of major sources (CC&IE and SS&SOC) during haze events originated mainly from the north and south, while high contribution of a major source (CD) on clean days was from the northwest.

Physicochemical factors and their potential sources inferred from long-term rainfall measurements at an urban and a remote rural site in tropical areas.

Air pollution can be detected through rainwater composition. In this study, long-term measurements (2000-2014) of wet deposition were made to evaluate the physicochemical interaction and the potential sources of pollution due to changes of land use. The rainwater samples were obtained from an urban site in Kuala Lumpur and a highland-rural site in the middle of Peninsular Malaysia. The compositions of rainwater were obtained from the Malaysian Meteorological Department. The results showed that the urban site experienced more acidity in rainwater (avg=277mm, range of 13.8 to 841mm; pH=4.37) than the rural background site (avg=245mm, range of 2.90 to 598mm; pH=4.97) due to higher anthropogenic input of acid precursors. The enrichment factor (EF) analysis showed that at both sites, SO42-, Ca2+ and K+ were less sensitive to seawater but were greatly influenced by soil dust. NH4+ and Ca2+ can neutralise a larger fraction of the available acid ions in the rainwater at the urban and rural background sites. However, acidifying potential was dominant at urban site compared to rural site. Source-receptor relationship via positive matrix factorisation (PMF 5.0) revealed four similar major sources at both sites with a large variation of the contribution proportions. For urban, the major sources influence on the rainwater chemistry were in the order of secondary nitrates and sulfates>ammonium-rich/agricultural farming>soil components>marine sea salt and biomass burning, while at the background site the order was secondary nitrates and sulfates>marine sea salt and biomass burning=soil components>ammonia-rich/agricultural farming. The long-term trend showed that anthropogenic activities and land use changes have greatly altered the rainwater compositions in the urban environment while the seasonality strongly affected the contribution of sources in the background environment.

Chemical characterisation and source identification of atmospheric aerosols in the Snowy Mountains, south-eastern Australia.

Characterisation of atmospheric aerosols is of major importance for: climate, the hydrological cycle, human health and policymaking, biogeochemical and palaeo-climatological studies. In this study, the chemical composition and source apportionment of PM2.5 (particulate matter with aerodynamic diameters less than 2.5µm) at Yarrangobilly, in the Snowy Mountains, SE Australia are examined and quantified. A new aerosol monitoring network was deployed in June 2013 and aerosol samples collected during the period July 2013 to July 2017 were analysed for 22 trace elements and black carbon by ion beam analysis techniques. Positive matrix factorisation and back trajectory analysis and trajectory clustering methods were employed for source apportionment and to isolate source areas and air mass travel pathways, respectively. This study identified the mean atmospheric PM2.5 mass concentration for the study period was (3.3±2.5)µgm-3. It is shown that automobile (44.9±0.8)%, secondary sulfate (21.4±0.9)%, smoke (12.3±0.6)%, soil (11.3±0.5)% and aged sea salt (10.1±0.4)% were the five PM2.5 source types, each with its own distinctive trends. The automobile and smoke sources were ascribed to a significant local influence from the road network and bushfire and hazard reduction burns, respectively. Long-range transport are the dominant sources for secondary sulfate from coal-fired power stations, windblown soil from the inland saline regions of the Lake Eyre and Murray-Darling Basins, and aged sea salt from the Southern Ocean to the remote alpine study site. The impact of recent climate change was recognised, as elevated smoke and windblown soil events correlated with drought and El Niño periods. Finally, the overall implications including potential aerosol derived proxies for interpreting palaeo-archives are discussed. To our knowledge, this is the first long-term detailed temporal and spatial characterisation of PM2.5 aerosols for the region and provides a crucial dataset for a range of multidisciplinary research.

Receptor modelling study of polycyclic aromatic hydrocarbons in Jeddah, Saudi Arabia.

Measurements of 14 polycyclic aromatic hydrocarbons (PAH) have been made in Jeddah, Saudi Arabia, with a view to establishing the concentrations in this major city, and quantifying the contributions of major sources. Particulate and vapour forms have been sampled and analysed separately. The concentrations are compared to measurements from other sites in the Middle Eastern region and are towards the lower end of the range, being far lower than concentrations reported from Riyadh (Saudi Arabia), Assiut (Egypt) and Tehran (Iran) but broadly similar to those measured in Damascus (Syria) and higher than those measured in Kuwait. The partitioning between vapour and particle phases is similar to that in data from Egypt and China, but with many compounds showing a higher particle-associated percentage than in Birmingham (UK) possibly reflecting a higher concentration of airborne particulate matter in the former countries. Concentrations in Jeddah were significantly higher at a site close to the oil refinery and a site close to a major ring road than at a suburban site to the north of the city. Application of positive matrix factorisation to the pooled data elicited three factors accounting respectively for 17%, 33% and 50% of the measured sum of PAH and these are interpreted as arising from gasoline vehicles, industrial sources, particularly the oil refinery, and to diesel/fuel oil combustion.

The qualitative and quantitative source apportionments of polycyclic aromatic hydrocarbons in size dependent road deposited sediment.

This study showcases the qualitative and quantitative source apportionments of size-dependent polycyclic aromatic hydrocarbons (PAHs) in road deposited sediment by means of molecular diagnostic ratio (MDR) and positive matrix factorisation (PMF) approaches. The MDR was initially used to narrow the PAH source candidates. PMF modelling was subsequently used to provide more precise source apportionment with the assistance of a multiple linear regression analysis. Through a combined qualitative and quantitative source apportionment, different potential source contributors were identified at different size fractions. Explicitly, three major contributors to sorption at the size fraction of 1000-400 µm were tentatively identified as incineration (26%), coal combustion (53%) and gasoline-powered vehicle (20%). Four major contributors to the size fraction of 400-100 µm were identified as gasoline-powered vehicle (25%), surface pavement (15%), diesel-powered vehicle (37%) and industrial boiler (24%). Four major contributors to the size fraction of 100-63 µm were identified as cogeneration emission (13%), diesel-powered vehicle (28%), tire debris (45%) and wood combustion (14%). The potential contributors in the size fraction 63-0.45 µm were identified as diesel-powered vehicle (21%), heterogeneous sources (41%) and biomass burning (38%). In addition, the highest ∑16PAH concentration was found in the smallest size fraction of 63-0.45 µm, which is also where the highest BaPE and TEF values for potential risk assessment occurred.