Positive Matrix Factorization Model Research Articles

Heavy metals pollution characteristics, source analysis, and risk assessment in soil based on Geographic Information System: A case study of a typical area in Three Parallel Rivers of Yunnan Protected Areas, China

Three Parallel Rivers of Yunnan Protected Areas, which was listed as World Natural Heritage, was suffering from increasingly serious heavy metal pollution. However, the existing research on heavy metal pollution in the area was almost blank. This study collected 115 surface soil samples from the local area and used inductively coupled plasma optical emission spectroscopy (ICP-OES) to determine the content of local 12 kinds of heavy metals. Results indicated that mining the tungsten-beryllium mine has caused serious heavy metal pollution to the soil in nature reserves. It poses risks to ecology and human health that cannot be ignored. There was severe pollution of tungsten (W) (Igeo = 8.30) and beryllium (Be) (Igeo = 1.92) in the topsoil. Subsequently, applied the pollution index assessment, potential ecological risk assessment (PERI), human health risk assessment (HHRA), and positive matrix factorization (PMF) models in conjunction with geographic information system (GIS) mapping to systematically evaluate the potential hazards of heavy metals in an abandoned tungsten-beryllium, where located in Haba Snow Mountain Nature Reserve that’s the core area of “Three Parallel Rivers”. The PMF model and GIS mapping identified four factors, nature, transportation, mining, and miners living, as the main sources of local heavy metals. The HHRA results indicated no health risks in the study area, but the GIS mapping identified areas where there are. It is the gaps in the systematic study of heavy metal pollution in the core area of the “Three Parallel Rivers” that the results of the study supplement and provide reference data for controlling soil heavy metal pollution in tungsten-beryllium mining areas and valuable information for managers to develop pollution control and risk management strategies.

Source Profile Analysis, Source Apportionment, and Potential Health Risk of Ambient Particle-Bound Polycyclic Aromatic Hydrocarbons in Areas of Specific Interest

Ambient particulate matter (PM10) and its chemical composition in polycyclic aromatic hydrocarbons (PAHs) were studied in areas of specific interest, between September 2015 and July 2016. The principal aim of this study was to assess the different PAH source profiles in each area, as well as their potential health risk. In particular, the studied areas were (a) the semiurban industrialized zone of the Municipality of Peloponnese (Meligalas, Messini) of Messinia prefecture, due to the intensive olive-productive activity in the extensive area, (b) the industrialized zone of Oinofyta in Voiotia prefecture, and (c) the urban/traffic center of Athens (Aristotelous). Intense spatial and seasonal variations in PAH levels were observed among the study areas collectively, but also for each one individually. During the winter period, the total PAHs average concentration was 11.45 and 9.84 ng/m3 at Meligalas–Skala (S1, S2 stations), 8.84 ng/m3 at Messini (S3 station), and 6.30 ng/m3 at the center of Athens (Aristotelous). During the summer campaign, the corresponding levels were 0.99, 1.20, and 0.70 ng/m3 (S1, S2, and S3 stations), and 5.84 ng/m3 (Aristotelous), respectively. The highest potential cancer risk of the PAHs mixture was estimated based on winter season measurements taken at the Municipality of Peloponnese. In order to determine PAH sources, two different source apportionment techniques were applied, i.e., diagnostic ratios (DRs) and the positive matrix factorization (PMF) model.

A study on source identification of contaminated soil with total petroleum hydrocarbons (aromatic and aliphatic) in the Ahvaz oil field.

The oil industry in Khuzestan province (Southwest Iran) is one of the main reasons contributing to the pollution of the environment in this area. TPH, including both aromatic and aliphatic compounds, are important parameters in creating pollution. The present study aimed to investigate the source of soil contamination by TPH in the Ahvaz oil field in 2022. The soil samples were collected from four oil centers (an oil exploitation unit, an oil desalination unit, an oil rig, and a pump oil center). An area outside the oil field was determined as a control area. Ten samples with three replicates were taken from each area according to the standard methods. Aromatic and aliphatic compounds were measured by HPLC and GC methods. The positive matrix factorization (PMF) model and isomeric ratios were used to determine the source apportionment of aromatic compounds in soil samples. The effects range low and effects range median indices were also used to assess the level of ecological risk of petroleum compounds in the soil samples. The results showed that Benzo.b.fluoranthene had the highest concentration with an average of 5667.7 ug/kg in soil samples in the Ahvaz oil field. The highest average was found in samples from the pump oil center area at 7329.48 ug/kg, while the lowest was found in control samples at 1919.4 ug/kg-1. The highest level of aliphatic components was also found in the pump oil center, with a total of 3649 (mg. Kg-1). The results of source apportionment of petroleum compounds in soil samples showed that oil activities accounted for 51.5% of the measured PAHs in soil. 38.3% of other measured compounds had anthropogenic origins, and only 10.1% of these compounds were of biotic origin. The results of the isomeric ratios also indicated the local petroleum and pyrogenic origin of PAH compounds, which is consistent with the PMF results. The analysis of ecological risk indices resulting from the release of PAHs in the environment showed that, except for fluoranthene, other PAHs in the oil exploitation unit area were above the effects range median level (ERM) and at high risk. The results of the study showed that soil pollution by total petroleum hydrocarbons (TPH), both aromatic and aliphatic, is at a high level, and is mainly caused by human activities, particularly oil activities.

Predictive analysis and risk assessment of potentially toxic elements in Beijing gas station soils using machine learning and two-dimensional Monte Carlo simulations

Gas stations not only serve as sites for oil storage and refueling but also as locations where vehicles frequently brake, significantly enriching the surrounding soil with potentially toxic elements (PTEs). Herein, 117 topsoil samples from gas stations were collected in Beijing to explore the impact of gas stations on PTE accumulation. The analysis revealed that the average Pollution Index (PI) values for Cd, Hg, Pb, Cu, and Zn in the soil samples all exceeded 1. The random forest (RF) model, achieving an AUC score of 0.95, was employed to predict PTE pollution at 372 unsampled gas stations. Additionally, a Positive Matrix Factorization (PMF) model indicated that gas station operations and vehicle emissions were responsible for 70 % of the lead (Pb) enrichment. Probabilistic health risk assessments showed that the carcinogenic risk (CR) and noncarcinogenic risk (NCR) for PTE pollution to adult females were the highest, at 0.451 and 1.61E-05 respectively, but still within acceptable levels. For adult males at contaminated sites, the Pb-associated CR and NCR were approximately twice as high as those at uncontaminated sites, with increases of 107 % and 81 %, respectively. This study provides new insights for managing pollution caused by gas stations.

Health Risk Assessment of Road-Dust-Bound Heavy Metals via Ingestion Exposure from One Typical Inland City of Northern China: Incorporation of Sources and Bioaccessibility

Heavy metals in road dust pose potential health risks to humans, while oral bioaccessibility and sources are all important factors influencing this health risk. However, few prior studies have combined them for health risk analysis. In this study, road dust samples were collected from different geographical locations of Jinan (west area, WA; central area, CA; and east area, EA) to analyze the source-specific and bioaccessibility-based health risks of heavy metals. The mean concentrations of heavy metals in the three areas were CA > EA > WA, with Cd, Cu, Mn, Pb, and Zn exceeding their corresponding background values. A source analysis using a Positive Matrix Factorization (PMF) model showed that traffic emissions were the main source of heavy metals in the WA and CA, while industrial activities were the main source in the EA. The mean bioaccessibility of heavy metals extracted using the Solubility Bioaccessibility Research Consortium (SBRC) method followed the order of Cd (75.5%) > Zn (42.2%) > Mn (42.1%) > Pb (42.0%) > Cu (32.9%) > As (23.6%) > Ni (20.1%) > V (16.8%) > Cr (13.3%). According to the combined source analysis, traffic was the primary risk factor in the WA (54.5 and 58.3% of NCR and CR, respectively) and CA (61.8 and 51.2%), with solid waste being the main risk factor in the EA (41.9 and 51.3%). In oral bioaccessibility testing, lower non-carcinogenic (<1.0) and carcinogenic risks (<1 × 10−6) of heavy metals were observed than those based on the total metal content. More importantly, As (43.4%) was replaced by V (29.7%) as the main contributor to NCR. Source-specific and bioaccessibility-based health risk assessments can accurately identify priority pollutants and heavy metals in urban road dust that need to be controlled. This provides more effective and accurate urban environmental risk management recommendations for sustainable urban development and population health.

Identify the seasonal differences in water quality and pollution sources between river-connected and gate-controlled lakes in the Yangtze River basin

The river-connected Dongting Lake (DT) and Poyang Lake (PY), and the gate-controlled Taihu Lake (TH) and Chaohu Lake (CH) are the four important lakes in the Yangtze River Basin. The comprehensive Water Quality Index (WQI), the Eutrophication Integrated Index (TLI(Σ)), and the Positive Matrix Factorization (PMF) model were employed to evaluate water quality and the contribution of pollution sources for these lakes. The results show that WQI for all lakes indicated generally good water quality, with DT scoring 73.52–86.18, the highest among them. During the wet season, the eutrophication degree of river-connected lake was medium, and that of gate-controlled lakes was high. The surface runoff and agricultural non-point sources are the main pollution sources for both types of lakes, but their impact is more pronounced in gate-controlled lakes during the wet season. The study provides evidence support for scientific understanding of water quality problems and management strategies in these areas.

High-density sampling of soil heavy metals in the upper Bailang River basin: contamination characteristics, sources, and source-oriented health risk assessment.

Heavy metals (HMs) seriously harm soil environment and threaten crop quality and human health. The aim of the study was to investigate the characteristics, quantify the sources and assess the risks of HMs in soil of upper Bailang River Basin (UBRB). The results indicated that the soils in UBRB were at a non-polluted level and posed a low ecological risk to the environment as a whole. The main pollutants were Ni and Cr obtained by indices Pi and Igeo. Based on the consideration of toxicity, the fuzzy comprehensive evaluation model and Ei index revealed that Hg and Cd were dominating pollutants and ecological risk factors of soil in UBRB. The positive matrix factorization model ascertained five potential sources of soil HMs, namely, plastic processing, energy activities, parent material, transportation and agriculture mixed source and industrial manufacturing, with contribution rates of 17%, 7%, 15%, 29% and 32%, respectively. Natural source primarily determined the non-carcinogenic risk for all populations, accounting for about 43% of the total risk. Industrial manufacturing mainly determined the carcinogenic risk, accounting for about 45%. For adults, the risk was acceptable for most of the sample points. For children, potential non-carcinogenic risks were present in 13.19% of the sample sites, which were mainly located in the west, and unacceptable carcinogenic risks were present in 57.21% of the sample sites, which were mainly concentrated in the western and central parts.

Source identification and migration fate of heavy metals of soil-groundwater system in a thousand-year cultivation region.

Pollution of farmland by heavy metals threatens food security and human health. In addition, heavy metals in soil could infiltrate into groundwater to influence the water quality and safety of drinking water. However, the relationship between heavy metal pollution in soil and groundwater is still not clear. In this study, we investigated the soil and groundwater in the Guanzhong Plain region, which is a significant grain production base in China, and determined the spatial distributions, ecological risk, sources, and migration fates of heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn). The results showed that the mean values (0-20cm) in the soil were 19.57mgkg-1 for As, 0.71mgkg-1 for Cd, 69.65mgkg-1 for Cr, 21.97mgkg-1 for Cu, 28.67mgkg-1 for Ni, 17.54mgkg-1 for Pb, and 73.77mgkg-1 for Zn, and the corresponding mean values in groundwater were 1.2, 0.04, 4.69, 0.15, 0.07, 0.3, and 3.6μg L-1, respectively. The mean values for As, Cd, Cr, Pb, and Zn in soil exceeded the background values, and the mean values for As, Cd and Pb exceeded those in groundwater. Positive matrix factorization models identified five sources (fertilizers and organic fertilizers, natural sources, pesticides and herbicides, industrial activities, and sedimentation caused by transportation) for heavy metal pollution in soil and four sources (industry activity, atmospheric sedimentation caused by transportation, natural sources, and agriculture) for heavy metal pollution in groundwater. The soil particle composition and soil organic carbon content were important factors that affected the vertical distribution of heavy metals in the soil. The migration modes (convection and diffusion) were not found for all heavy metals. These results help to understand the relationships between heavy metals in soil and groundwater in farmland ecosystems regionally.

Characteristics and Source Apportionment of Volatile Organic Compounds in a Coastal Industrial Area: A Case Study in the Yangtze River Delta of China.

In recent years, the coastal area in East China has experienced elevated volatile organic compounds (VOCs) levels during specific periods. VOCs have become one of the major atmospheric pollutants in these areas. In this study, 64 compounds including alkanes, alkenes, halohydrocarbons, aromatics, and oxygenated VOCs (OVOCs) were obtained by the TO-15 method through a 12-month campaign in industrial, urban and suburban areas in the Yangtze River Delta of China. The overall trends of total VOC (TVOC) concentrations at eight sampling sites were as follows: winter > autumn > spring > summer. The proportion of VOC categories was various at industrial sites, while OVOCs and halohydrocarbons had high proportions at urban sites and suburban sites, respectively. Coating, vehicle emission, petrochemical source, industrial source, and gasoline volatilization were identified as the major VOC emission sources by the positive matrix factorization model. Petrochemical and coating sources were the prime VOC sources at industrial sites. Aromatics contributed the most ozone formation potential at industrial sites, while OVOCs provided the main contributions at both urban and suburban sites during four seasons. According to the health risk assessment, a high probability of non-carcinogenic risk existed at three industrial sites. Special attention should be given to certain VOCs, such as acrolein and 1,2-dibromoethane in industrial areas.

Evaluation of groundwater quality with multi-source pollution based on source identification and health risks

Groundwater is a crucial water supply source in Chengdu City, western China, a region experiencing significant water scarcity. The sources of inorganic pollutants in groundwater and their potential health risks are of great concern. In this study, based on 156 groundwater samples collected in 2021 in the study area were analyzed for hydrochemical characterization and controlling factors. The Positive Matrix Factorization (PMF) model was used for contaminant source analysis, and Monte Carlo Simulation (MCS) combined with the Health Risk Evaluation Model (HREM) was used to quantify the health risks. The results indicate that the groundwater in the study area is predominantly of the Ca·Na-SO4·HCO3, Ca·Na-HCO3·SO4 and Ca-HCO3·SO4 types, mainly influenced by the combination of evaporation-concentration-crystallization and rock leaching-weathering. K+, Na+, and Cl− mainly originate from the weathering and dissolution of potassium feldspar and rock salt, while Ca2+, Mg2+, HCO3−, and SO42− primarily come from the weathering and dissolution of sulfate minerals. The main sources of groundwater pollution and their contributions are as follows: domestic pollution (25.6 %), dissolution-filtration-evaporation-concentration action (22.8 %), hydrogeochemical evolution (15.8 %), water-rock interactions (12.8 %), primary geologic context (12.1 %), and agricultural non-point source pollution (11.0 %). Cl− and As are the primary contributors to non-carcinogenic and carcinogenic risks, respectively. Non-carcinogenic risks are below USEPA standards, while the average carcinogenic risk for arsenic exceeded the maximum acceptable risk level thresholds by 23 and 109 times for adults and children, respectively. Non-carcinogenic and carcinogenic health risks were mainly influenced by pollutant concentrations. The primary geological background and domestic pollution contributed the most to the non-carcinogenic risk for adults (50.3 %) and children (77.1 %), and 38.2 % and 10.3 %, respectively. This study highlights the necessity of establishing a comprehensive groundwater pollution monitoring system, enhancing industrial waste management practices, and raising public awareness to mitigate contamination and ensure the sustainable use of groundwater resources in Chengdu City.

Impact of vehicles at the roadside of expressway in urban area: Simultaneous measurement of particle size distribution and positive matrix factorization

This study conducted real-time monitoring of size-resolved particle concentrations ranging from 9 nm to 10 μm simultaneously at four sites on the park ground and the roof of a five-story apartment buildings in the upwind and downwind areas of the Olympic Expressway next to apartment complex areas of Seoul, Korea. Using a positive matrix factorization model for source apportionment, eight factors were resolved at each monitoring site: four exhaust emissions of vehicles, one non-exhaust emission of vehicle, two regional sources, and one unknown source. After categorizing monitoring data into three cases by wind conditions, impact and contribution of each vehicle-related source on the local road to the roadside pollution was quantified and characterized by subtracting the urban background concentrations. Throughout the measurement period, the contribution of vehicle-related sources to the particle number concentration at each monitoring site ranged from 61 % to 69 %, while that to the particle mass concentration ranged from 39 % to 87 %. During periods of steady traffic flow and wind blowing from the road to three downwind sites at speeds exceeding >0.5 m/s during working hours, the particle number concentrations at the downwind sites were 2.2–2.5 times higher than the average levels. Among vehicle-related sources, gasoline vehicles with multiple injections or high-emitting diesel vehicles showed the highest contribution to particle number concentrations at all sites. As wind speed increased, the number concentrations of particles from vehicle exhaust and non-exhaust emissions decreased and increased, respectively, probably due to enhanced dilution and transport, respectively. In addition, particle number concentrations showed a parabolic curve-like trend with traffic volumes increasing to approximately 10,000 vehicles/h, and then decreasing for both vehicle exhaust and non-exhaust emissions. These results can be utilized in numerical modeling studies and in establishing traffic-related environmental policies to reduce seasonal and temporal particle exposure near the roadsides.

Source apportionment of PM2.5 and PM10 pollutants near an urban roadside site using positive matrix factorization

This paper presents results from a comprehensive study of source apportionment of particulate matter (PM) of size PM2.5 and PM10 near a busy highway in Sharjah, United Arab Emirates. Source apportionment was carried out using US Environmental Protection Agency (EPA) Positive Matrix Factorization model. Furthermore, backward trajectory analysis and Potential Source Contribution Function were used to assess air mass transport pathways and identify potential source regions, respectively. The results revealed six major sources for PM2.5, including traffic, sea salt, fugitive dust, secondary aerosols, heavy oil combustion and mineral dust. For PM10, four major sources were identified, including secondary aerosols, traffic, sea salt and mineral dust. Traffic emissions were found to be significant contributors to both PM2.5 and PM10 pollution, along with natural sources like sea salt and mineral dust. Backward trajectory analysis indicated the influence of different wind regimes on air mass transport, with contributions from regions like Arabian Gulf, Arabian Sea, Oman and Iran. The Conditional Bivariate Probability Function analysis further explained the impact of local traffic emissions and other sources on PM pollution under varying wind conditions.

Spatial Heterogeneity Analysis and Risk Assessment of Potentially Toxic Elements in Soils of Typical Green Tea Plantations

The spatial heterogeneity of potentially toxic elements (PTEs) in a typical green tea-producing area in Zhejiang was investigated with application of geostatistics. The positive matrix factorization (PMF) was conducted for analysis of pollution sources and risk assessment of the soil of the tea garden. The results revealed that 93.52% of the study area did not exceed the PTEs risk screening value in the soil pollution risk control standard of agricultural land. The results of the spatial heterogeneity analysis showed that Cd and Pb had moderate spatial auto-correlation, exhibiting similar spatial distribution patterns. The high-value locations were distributed in the southeast of the study area, while low-value locations were distributed in the southwest of the study area. The Cr, As, and Hg had strong spatial auto-correlation, while Cr and As had similar spatial distribution patterns whose high-value areas and low-value areas were concentrated in the west and center of the study area, respectively. The Cd, Pb, and As originated from the agricultural source, transportation source, and industrial source, respectively, while Cr and Hg were from the natural source on the basis of the results of the PMF model. The results of a potential ecological risk assessment revealed that five PTEs in the study area were of low potential risk. The single-factor ecological risk ranking was Cd > As > Hg > Cr > Pb. The overall ecological risk in the study area was slight. The human health risk model indicates that there was a non-carcinogenic risk for children in the study area, and the high-value area was concentrated in the northwest of the study area. It is concluded that emphasis shall be given to excessive Cd caused by agricultural sources in the southeast of the study area, and control and monitoring will be strengthened in the northwestern part of the study area. The relevant measures for prevention of soil pollution must be conducted.

Long-term change in winter aerosol composition and sources in Guiyang Southwest China (2003–2020)

This study presents a comprehensive analysis of air quality in China, Southwest China, over four winter seasons: 2003–2004, 2004–2005, 2017–2018 and 2019–2020. We initially collected Total Suspended Particles (TSP) samples during the earlier periods and PM2.5 samples during the later periods. Our goal was to illustrate the changes in sources of atmospheric pollutants over time. By focusing on the chemical composition of water-soluble inorganic ions (WSIIs), we highlighted significant long-term changes in air quality and pollution sources in Guiyang alongside the effectiveness of recent pollution treatment strategies. Historically affected by acid rain and acid pollution, Guiyang has shown notable improvements in air quality. Notably, sulfate pollution, primarily from coal combustion, has significantly decreased, with the sulfates concentration declining from an estimated 19.04 μg m−3 to 30.46 μg m−3 during the winter of 2003–2004, to just 7.37 μg m−3 in PM2.5 during the winter of 2019–2020. Additionally, the mean mass concentration of PM2.5 dropped by 18% between the 2017–2018 and 2019–2020 winters. An increasing ratio of nitrate to sulfate in the aerosols indicates a shift in pollution sources, with secondary nitrate pollution, largely from vehicle emissions, becoming increasingly prevalent. Positive Matrix Factorization (PMF) model analysis identified five major pollution sources, highlighting a transition from secondary sulfate to secondary nitrate as the primary contributors to air pollution in Guiyang, and secondary nitrate pollution mainly from vehicles emission was increasingly severe meanwhile the significance of ammonium should not be overlooked. The results stress the importance of local pollution sources and suggest a need for revised pollution control policies that address the evolving characteristics of aerosols and prioritize the major pollutants in Guiyang, especially during winter months.

Contamination Characteristics and Source Apportionment of Heavy Metal in the Topsoil of a Small Watershed in South Taihang

With the rapid development of industrialization and urbanization, the issue of soil environmental pollution is becoming more and more prominent, especially concerning heavy metal contamination, which has garnered significant scholarly attention. The surface watershed formed by waterline is influenced by various factors such as topography, industrial emissions, and agricultural runoff, resulting in a complex process of migration and accumulation of heavy metal elements from multiple sources. In this study, the pollution characteristics and sources of heavy metal elements Hg, As, Pb, Ni, Cd, Cr, Cu and Zn in 165 surface soil samples from the Manghe River watershed in Jiyuan City were comprehensively analyzed using a variety of methods, including statistics, geostatistics, enriched factor analysis and the Positive Matrix Factorization Model (PMF). The results showed that the concentrations of Hg, Cd, As, Cu, Pb and Zn exceeded their corresponding background values with varying degrees of enrichment. Notably, the average contents of Cd, Hg and Pb were 26.70 times, 3.69 times and 4.49 times higher than those in Chinese soils on average, respectively, showing obvious enrichment characteristics. Moreover, there were distinct spatial distribution patterns for each heavy metal element; Ni and Cr exhibited similar trends mainly controlled by the parent material, while human activities significantly affect the other six elements forming high-value areas around mining and related industries. It is noteworthy that Cu, Hg and Zn were influenced by dominant wind direction in autumn and winter, forming sub-high-value zones in southern forested areas; meanwhile, Cu and Zn were also influenced by agricultural fertilizer application as well as surface runoff, leading to secondary high-value areas in the dryland areas. Further analysis revealed a significant positive correlation among these heavy metal elements, suggesting that they may share common sources. Through the PMF Model, four main factors were identified, with factor 2 (36.25%), factor 1 (23.00%), factor 3 (21.20%) and factor 4 (19.55%) ranked in descending order of contribution rate. The heavy metal pollution in the study area was attributed to anthropogenic activities and natural factors, accounting for 63.75% and 36.25%, respectively. Coal mining, chemical industry smelting, vehicle emissions and excessive use of agrochemicals were identified as the main sources of heavy metal pollution. These pollutants entered the soil through direct emissions, atmospheric deposition, transportation and agricultural activities, exerting a significant impact on the soil environment. Therefore, delving into the spatial distribution pattern of soil heavy metal pollution and precise analysis of its sources are of great importance for effective treatment and remediation of soil heavy metal pollution in small watersheds, maintaining healthy soil ecology and safeguarding human health.

Distribution Characteristics, Risk Assessment, and Source Analysis of Heavy Metals in Farmland Soil of a Karst Area in Southwest China

Soil environmental quality related to the residents’ life, health, and safety, has been the hotspot issues in science of ecological environment protection. Evaluating the distribution characteristics, ecological risk, and source of heavy metals in farmland is important for protecting soil resources. The agricultural area of Lianhua town, Gongcheng County, Guilin is a typical karst landform. In response to the problem of heavy metal pollution and complex sources in the soil of this area, the characteristics and sources of heavy metal pollution in the soil profiles from farmland, abandoned land, and forest were studied using the single-factor index method, the geoaccumulation index (Igeo) principal component analysis (PCA) and positive matrix factorization (PMF) model. The results showed that: (1) that the contents of cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) in the soil profile of the study area were higher than that of the soil elements background values in Guangxi. The total and available forms contents of all heavy metal elements exhibited the characteristics of accumulation in the surface profile; (2) among the six heavy elements, the contents of Cd were in a moderately to heavily polluted state. The contents of Cd in some soil profiles exceeded the control standard for agricultural land soil pollution. The contents of Zn and Ni were from slightly to moderately polluted in areas with frequent agricultural activities; (3) according to the PCA and PMF model, there were three main sources of heavy metals in the study area. Among them, Cd, Cu, Ni, and Zn are related to agricultural activities; the elements As, Cd, Cr, and Hg are closely related to geological background; Pb and Zn are mainly affected by atmospheric sedimentation of transportation. Agricultural activities and natural geological background are the main contribution sources of heavy metals in soil. Human activities are the main factors that cause the accumulation of heavy metals in soil. This research has theoretical guidance and practical significance for the prevention and control of soil heavy metal pollution and the protection of farmland environmental quality in the region.

Unveiling nitrate origins in semiarid aquifers: A comparative analysis of Bayesian isotope mixing models using nitrate and boron isotopes and a Positive Matrix Factorization model

Nitrate contamination of groundwater is a pressing global concern, affecting over 80 million people worldwide, with agricultural activities being the primary contributor to nitrogen inputs into aquifers. The primary objective of this study was to identify the predominant sources of nitrate pollution and biogeochemical transformations in the semiarid region of the Meoqui-Delicias aquifer, Mexico. In this region, the uncontrolled use of chemical fertilizers and manure leads to excessive nutrient input, which accelerates the deterioration of groundwater quality. This study introduces an innovative dual-model approach (δ15NNO3 vs. δ11B) to compare the Bayesian Isotope Mixing Model (BIMM) with Positive Matrix Factorization (PMF) for nuanced source apportionment. This approach enhanced the differentiation between manure and sewage as nitrate sources. Results from the δ15NNO3 vs. δ11B model revealed that manure (52.4%) was the most significant source of nitrate pollution in the aquifer, followed by soil (37.4%), chemical fertilizers (5.5%), and sewage (4.7%). The PMF model corroborated this finding and indicated that 60.2% of the NO3–-N pollution in the aquifer was attributed to manure and sewage, confirming the superior performance of the proposed BIMM in source differentiation. Our findings enhance the understanding of nitrate dynamics in semi-arid regions and can serve as a scientific evidence base for targeted interventions in nutrient management in the study area and elsewhere.

Distribution, risk evaluation, and source allocation of cesium and strontium in surface soil in a mining city.

Radioactive nuclides cesium (Cs) and strontium (Sr) possess long half-lives, with 135Cs at approximately 2.3 million years and 87Sr at about 49 billion years. Their persistent accumulation can result in long-lasting radioactive contamination of soil ecosystems. This study employed geo-accumulation index (Igeo), pollution load index (PLI), potential ecological risk index (PEPI), health risk assessment model (HRA), and Monte Carlo simulation to evaluate the pollution and health risks of Cs and Sr in the surface soil of different functional areas in a typical mining city in China. Positive matrix factorization (PMF) model was used to elucidate the potential sources of Cs and Sr and the respective contribution rates of natural and anthropogenic sources. The findings indicate that soils in the mining area exhibited significantly higher levels of Cs and Sr pollution compared to smelting factory area, agricultural area, and urban residential area. Strontium did not pose a potential ecological risk in any studied functional area. The non-carcinogenic health risk of Sr to the human body in the study area was relatively low. Because of the lack of parameters for Cs, the potential ecological and human health risks of Cs was not calculated. The primary source of Cs in the soil was identified as the parent material from which the soil developed, while Sr mainly originated from associated contamination caused by mining activities. This research provides data for the control of Cs and Sr pollution in the surface soil of mining city.

Volatile Organic Compounds on Rhodes Island, Greece: Implications for Outdoor and Indoor Human Exposure.

Volatile organic compounds (VOC) are considered a class of pollutants with a significant presence in indoor and outdoor air and serious health effects. The aim of this study was to measure and evaluate the levels of outdoor and indoor VOCs at selected sites on Rhodes Island, Greece, during the cold and warm periods of 2023. Spatial and seasonal variations were evaluated; moreover, cancer and non-cancer inhalation risks were assessed. For this purpose, simultaneous indoor-outdoor air sampling was carried out on the island of Rhodes. VOCs were determined by Thermal Desorption-Gas Chromatography/Mass Spectroscopy (TD-GC/MS). Fifty-six VOCs with frequencies ≥ 50% were further considered. VOC concentrations (∑56VOCs) at all sites were found to be higher in the warm period. In the warm and cold sampling periods, the highest concentrations were found at the port of Rhodes City, while total VOC concentrations were dominated by alkanes. The Positive Matrix Factorization (PMF) model was applied to identify the VOC emission sources. Non-cancer and cancer risks for adults were within the safe levels.

Sustainability Assessment and Source Apportionment of Soil Heavy Metals in a Mineral Aggregation Area of Datian County, South China

Heavy metal pollution in soils, especially in mineral aggregation areas, presents significant sustainability challenges affecting ecosystem health and human well-being. This study conducted source apportionment and risk analysis of soil heavy metals in Datian County, South China, to promote sustainable land use and pollution mitigation. We collected 103 surface soil samples (0–20 cm) from a typical mineral aggregation area and analyzed the concentration distributions of heavy metals using geostatistical methods. The geoaccumulation index (Igeo) and potential ecological risk index (RI) were employed to evaluate pollution levels and ecological risks. Our findings reveal that heavy metal concentrations substantially exceeded Fujian Province’s background values, with Cd exhibiting severe pollution levels. Cd, Pb, and Cu pose moderate to high ecological risks. Major pollution sources include metal smelting enterprises, soil parent materials, mixed sources of mineral extraction and traffic pollution, atmospheric deposition, and agricultural pollution. Their contribution rates were found to be 15.66%, 17.72%, 38.32%, 8.25%, and 20.05%, respectively. Utilizing principal component analysis (PCA) and positive matrix factorization (PMF) models integrated with geostatistical methods, this study provides robust source identification and highlights sustainable practices for soil management. The results offer a scientific basis for developing strategies to mitigate heavy metal pollution and enhance environmental sustainability in the region.