Spatial distribution, compositional characteristics, and source apportionment of legacy and novel per- and polyfluoroalkyl substances in farmland soil: A nationwide study in mainland China

China, as one of the largest global producers and consumers of per- and poly-fluoroalkyl substances (PFASs), faces concerning levels of PFAS pollution in soil. However, knowledge of their occurrence in agricultural soils of China on the national scale remains unknown. Herein, the first nationwide survey was done by collecting 352 soil samples from 31 provinces in mainland China. The results indicated that the Σ24PFASs concentrations were 74.3 - 24880.0 pg/g, with mean concentrations of PFASs in decreasing order of legacy PFASs > emerging PFASs > PFAS precursors (640.2 pg/g, 340.7 pg/g, and 154.9 pg/g, respectively). The concentrations in coastal eastern China were distinctly higher than those in inland regions. Tianjin was the most severely PFASs-contaminated province because of rapid urban industrialization. This study further compared the PFAS content in monoculture and multiple cropping farmland soils, finding the concentrations of PFASs were high in soils planted with vegetable and fruit monocultures. Moreover, a positive matrix factorization (PMF) model was employed to identify different sources of PFASs. Fluoropolymer industries and aqueous film-forming foams were the primary contributors. The contributions from different emission sources varied across the seven geographical regions. This study provides new baseline data for prevention and control policies for reducing pollution.

Hydrogeochemical characteristics, stable isotopes, positive matrix factorization, source apportionment, and health risk of high fluoride groundwater in semiarid region

Chronic exposure to high fluoride (F-) levels in groundwater causes community fluorosis and non-carcinogenic health concerns in local people. This study described occurrence, dental fluorosis, and origin of high F-groundwater using δ2H and δ18O isotopes at semiarid Gilgit, Pakistan. Therefore, groundwater (n = 85) was collected and analyzed for F- concentrations using ion-chromatography. The lowest F- concentration was 0.4 mg/L and the highest 6.8 mg/L. F- enrichment is linked with higher pH, NaHCO3, NaCl, δ18O, Na+, HCO3-, and depleted Ca+2 aquifers. The depleted δ2H and δ18O values indicated precipitation and higher values represented the evaporation effect. Thermodynamic considerations of fluorite minerals showed undersaturation, revealing that other F-bearing minerals viz. biotite and muscovite were essential in F- enrichment in groundwater. Positive matrix factorization (PMF) and principal component analysis multilinear regression (PCAMLR) models were used to determine four-factor solutions for groundwater contamination. The PMF model results were accurate and reliable compared with those of the PCAMLR model, which compiled the overlapping results. Therefore, 28.3% exceeded the WHO permissible limit of 1.5 mg/L F-. Photomicrographs of granite rocks showed enriched F-bearing minerals that trigger F- in groundwater. The community fluorosis index values were recorded at > 0.6, revealing community fluorosis and unsuitability of groundwater for drinking.

Deep optimization of water quality index and positive matrix factorization models for water quality evaluation and pollution source apportionment using a random forest model

Effective evaluation of water quality and accurate quantification of pollution sources are essential for the sustainable use of water resources. Although water quality index (WQI) and positive matrix factorization (PMF) models have been proven to be applicable for surface water quality assessments and pollution source apportionments, these models still have potential for further development in today's data-driven, rapidly evolving technological era. This study coupled a machine learning technique, the random forest model, with WQI and PMF models to enhance their ability to analyze water pollution issues. Monitoring data of 12 water quality indicators from six sites along the Minjiang River from 2015 to 2020 were used to build a WQI model for determining the spatiotemporal water quality characteristics. Then, coupled with the random forest model, the importance of 12 indicators relative to the WQI was assessed. The total phosphorus (TP), total nitrogen (TN), chemical oxygen demand (CODCr), dissolved oxygen (DO), and five-day biochemical oxygen demand (BOD5) were identified as the top five significant parameters influencing water quality in the region. The improved WQI model constructed based on key parameters enabled high-precision (R2 = 0.9696) water quality prediction. Furthermore, the feature importance of the indicators was used as weights to adjust the results of the PMF model, allowing for a more reasonable pollutant source apportionment and revealing potential driving factors of variations in water quality. The final contributions of pollution sources in descending order were agricultural activities (30.26%), domestic sewage (29.07%), industrial wastewater (26.25%), seasonal factors (6.45%), soil erosion (6.19%), and unidentified sources (1.78%). This study provides a new perspective for a comprehensive understanding of the water pollution characteristics of rivers, and offers valuable references for the development of targeted strategies for water quality improvement.

Source apportionment and suitability evaluation of seasonal VOCs contaminants in the soil around a typical refining-chemical integration park in China

Accurate source apportionment of volatile organic compounds (VOCs) in soil nearby petrochemical industries prevailing globally, is critical for preventing pollution. However, in the process, seasonal effect on contamination pathways and accumulation of soil VOCs is often neglected. Herein, Yanshan Refining-Chemical Integration Park, including a carpet, refining, synthetic rubber, and two synthetic resin zones, was selected for traceability. Season variations resulted in a gradual decrease of 31 VOCs in soil from winter to summer. A method of dry deposition resistance model coupling partitioning coefficient model was created, revealing that dry deposition by gas phase was the primary pathway for VOCs to enter soil in winter and spring, with 100 times higher flux than by particle phase. Source profiles for five zones were built by gas sampling with distinct substance indicators screened, which were used for positive matrix factorization factors determination. Contributions of the five zones were 14.9%, 20.8%, 13.6%, 22.1%, and 28.6% in winter and 33.4%, 12.5%, 10.7%, 24.9%, and 18.5% in spring, respectively. The variation in the soil sorption capacity of VOCs causes inter-seasonal differences in contribution. The better correlation between dry deposition capacity and soil storage of VOCs made root mean square and mean absolute errors decrease averagely by 8.8% and 5.5% in winter compared to spring. This study provides new perspectives and methods for the source apportionment of soil VOCs contamination in industrial sites.

Geochemical characteristics and health risks of heavy metals in agricultural soils and crops from a coal mining area in Anhui province, China

Soil contamination by heavy metals (HMs) in mining areas is a major issue because of its significant impact on the environmental quality and physical health of residents. Mining of minerals used in energy production, particularly coal, has led to HMs entering the surrounding soil through geochemical pathways. In this study, a total of 166 surface soil and 100 wheat grain samples around the Guobei coal mine in southeast China were collected, and trace metal levels were determined via inductively coupled plasma mass spectrometry (ICP-MS). The average HMs (Ni, As, Cr, Cu, Pb, Cd, and Zn) concentrations were lower than the screening values in China (GB 15618-2018) but higher than the soil background values in the Huaibei Bozhou area of Anhui Province (except Zn), indicating HMs enrichment. Based on the geoaccumulation index (Igeo) and ecological risk index (IER), Cd pollution levels were low, while for the other metals the samples were pollution-free, and therefore no ecological risk warning was issued for the mining area. Both Cr and Pb had a higher noncarcinogenic health risks for adults and children. The lifetime carcinogenic risks (LCR) of Cr, Pb, and Cd were within acceptable levels. A positive matrix factorization (PMF) model identified two factors that could explain the HMs sources: factor 1 for Zn, Cd, and Pb, factor 2 for Ni, As, Cr, and Cu. Furthermore, HMs enrichment was observed in surface soil and the Carboniferous-Permian coal seams in the Guobei coal mine, which may suggest that coal mining is an important source for HMs enrichment in surface soil. Overall, this study provides a theoretical basis for undertaking the management and assessment of soil HMs pollution around a coal mine.

Spatio-temporal distribution and source identification of antibiotics in suspended matter in the Fen River Basin

In this study, 26 typical antibiotics in the suspended matter of the Fen River basin were analyzed during the wet and dry seasons, and the main sources of antibiotic contamination were further identified. The results showed that the concentrations of antibiotics in the suspended matter varied seasonally. Sixteen antibiotics were detected in the suspended matter during the wet season with an average concentration of 463.56 ng/L. However, a total of 21 antibiotics were detected in the dry season, with an average concentration of 106.00 ng/L. The concentration of chloramphenicol antibiotics was outstanding in the wet season and dry season. The spatial distribution of the antibiotics in suspended matter showed little spatial discrepancy during the wet season. During the dry season, nevertheless, the concentration was higher upstream than midstream and downstream. The main sources of antibiotics in the Fen River Basin were livestock and poultry breeding, wastewater from wastewater treatment plants (WWTPs), agricultural drainage, domestic sewage, and pharmaceutical wastewater. Wastewater from WWTPs and domestic sewage were identified as two primary sources in the suspended matter during the wet season, with wastewater from WWTPs contributing the most accounting for 37%. While the most significant source of antibiotics in the suspended matter in the dry season was pharmaceutical wastewater, accounting for 36%. In addition, the contribution proportion of sources for antibiotics exhibited discrepant spatial distribution characteristics. In the wet season, wastewater from WWTPs dominated in the upstream and midstream, and livestock and poultry breeding was prominent in the midstream and downstream. Pharmaceutical wastewater was the main source in the midstream and downstream regions during the dry season.

Source apportionment and health impact assessment of atmospheric particulate matter in the city of São Carlos, Brazil

In this study, positive matrix factorization method was used for source apportionment of PM₁₀ in the city of São Carlos from 2015 to 2018. The annual mean concentrations of PM₁₀, 15 PAHs, 4 oxy-PAHs, 6 nitro-PAHs, 21 saccharides, and 17 ions in these samples were in the ranges 18.1 ± 6.99 to 25.0 ± 11.3 μg m^-3 for PM₁₀, 9.80 × 10^-1 ± 2.06 to 2.03 ± 8.54 × 10^-1 ng m^-3 for ΣPAHs, 83.9 ± 35.7 to 683 ± 521 pg m^-3 for Σoxy-PAHs, 1.79 × 10^-2 ± 1.23 × 10^-1 to 7.12 ± 4.90 ng m^-3 for Σnitro-PAHs, 83.3 ± 44.7 to 142 ± 85.9 ng m^-3 for Σsaccharides, and 3.80 ± 1.54 to 5.66 ± 4.52 μg m^-3 for Σions. For most species, the concentrations were higher in the dry season than in the rainy. This was related not only to the low rainfall and relative humidity characteristic of the dry season but also to an increase in fire spots recorded in the region between April and September every year from 2015 to 2018. A 4-factor solution provided the best description of the dataset, with the four identified sources of PM₁₀ being soil resuspension (28%), biogenic emissions (27%), biomass burning (27%), and vehicle exhaust together with secondary PM (18%). Although the PM₁₀ concentrations were not above the limit established by local legislation, the epidemiological study showed that by reducing PM_2.5 concentrations to the level recommended by the WHO, approximately 35 premature deaths per 100,000 population could be avoided annually. The results revealed that biomass burning continues to be one of the main anthropic sources of emissions to the atmosphere in the region, so it needs to be incorporated into the existing guidelines and policies to reduce the concentration of particulate matter to within the limits recommended by the WHO, in order to avoid premature deaths.

An integrated approach for quantifying source apportionment and source-oriented health risk of heavy metals in soils near an old industrial area

Soil contamination of heavy metals (HMs) caused by the long-term industrial activities has become a major environmental issue due to its adverse effects on human health and ecosystem. In this paper, 50 soil samples were analyzed to evaluate the contamination characteristics, source apportionment and source-oriented health risk of HMs in soils near an old industrial area in NE China by applying an integrated approach of Pearson correlation analysis, Positive matrix factorization (PMF) model and Monte Carlo simulation. The results showed that the mean concentrations of all HMs greatly exceeded the soil background values (SBV), and the surface soils in the study area were heavily polluted with HMs, displaying a very high ecological risk. The toxic HMs emitted from the bullet production were identified as the primary source of HMs contamination in soils, with a contribution rate of 33.3%. The human health risk assessment (HHRA) suggested that the Hazard quotient (HQ) values of all HMs for children and adults are within the acceptable risk level (HQ < 1). The carcinogenic risk (CR) values of HMs for children and adults significantly exceeded the acceptable threshold of 1E-6 with a basic trend: As > Pb > Cr > Co > Ni, indicating a high cancer risk. For source-oriented health risk, the CR of four pollution sources for children and adults shows a same trend: Factor 4 > Factor 3 > Factor 2 > Factor 1. Among those, the source of HMs pollution from bullet production is the largest contributor to cancer risk, and As and Pb are the most important HMs pollutants that cause cancer risk to humans. The present study sheds some light on the contamination characteristics, source apportionment and source-health risk assessment of HMs in industrially contaminated soils, which helps improve the management of environmental risk control, prevention and remediation.

Source-oriented probabilistic health risk assessment of soil potentially toxic elements in a typical mining city

Identifying potential sources of soil potentially toxic elements (PTEs) and developing source-oriented health risk assessments in typical mining cities are key for pollution prevention and risk management. To this end, a case study was conducted to explore the pollution characteristics, potential sources, and human health risks of PTEs in Daye City, China. Indices, including the pollution factor (PF), pollution load index (PLI), and geo-accumulation index (I_geo), were applied to assess PTE pollution. Cd had the highest value among the detected PTEs, and 82.93% of the sampling sites had moderate pollution levels, with the highest mean I_geo value for Cd (2.30). Four potential sources were determined. Cr and Ni originated mainly from natural sources. Zn (91.5%) was exclusively and then Cd (33.1%) was moderately derived from industrial activities. The mixed source of various mineral exploitation smelting, and coal-fired traffic emissions leaded to the accumulation of As, Cd, and Pb. Cu was associated with Cu-related mining and smelting activities. The probabilistic health risk assessment indicated that the non-carcinogenic risks for populations were negligible. Overall, this work provides scientific information for environmental managers to manage soil PTE pollution through the effective management of anthropogenic sources with limited resources and costs.

Dissolved polycyclic aromatic hydrocarbons (PAHs-d) in response to hydrology variation and anthropogenic activities in the Yangtze River, China

Owing to their bioavailability and toxicity, the dissolved polycyclic aromatic hydrocarbons (PAHs-d) loaded in rivers are harmful to both inland and marine ecosystems. Thus, exploring the changes in PAHs-d levels and sources is important for controlling PAHs pollution. In this study, the concentration of PAHs-d in the mainstream of the Yangtze River during dry and wet seasons was investigated and the source was analyzed using the positive matrix factorization (PMF) model to assess the response of PAHs-d to hydrological and anthropogenic activities changes. The concentration of PAHs-d in the wet season (166.2 ± 52.51 ng/L) was significantly higher than that in the dry season (89.05 ± 20.89 ng/L) (ANOVA, P < 0.001), and the sampling sites with high pollution were mainly distributed in the downstream urban agglomeration. Herein, 2-3 rings were identified to play a dominant role in the composition of PAHs-d. Compared with the dry season, the proportion of the low molecular weight (LMW) PAHs-d were relatively depleted and the high molecular weight (HMW) PAHs-d were accumulated in the wet season. Coal and coke combustion were identified as the main sources of PAHs-d (65.9% in the dry season and 59.2% in the wet season), followed by vehicle emissions, petroleum sources, and biomass combustion. Owing to the change in energy consumption structure and climate characteristics, the sources of PAHs-d displayed seasonal variation and spatial heterogeneity. Further, flow was identified as the most important factor affecting PAHs-d in the hydrological parameters. Increases of flow, pH, and SPM decreased the proportion of LMW PAHs-d, and increased that of HMW PAHs-d. The increase in anthropogenic activities intensified the residual levels of 2-3rings and 5-6 rings in water, but had no significant impact on the levels of 4 rings.

Abundance, spatial variation, and sources of rare earth elements in soils around ion-adsorbed rare earth mining areas

Rare earth elements (REEs) concentrated in soils have attracted increasing attention about their impact on soil health as emerging contaminants. However, the sources of REEs enriched in soils are diverse and need to be further investigated. Here, surface soil samples were collected from southern Jiangxi Province, China. REEs contents and soil physicochemical properties were determined, and cerium (Ce) and europium (Eu) anomalies were calculated. Moreover, we established a model to further identify the main sources of REEs accumulation in the studied soils. Results show that the abundance of soil REEs reveals larger spatial variation, suggesting spatially heterogeneous distribution of REEs. The median content of light REEs in soils (154.5 mg kg^-1) of the study area was higher than that of heavy REEs and yttrium (35.8 mg kg^-1). In addition, most of the soil samples present negative Ce anomalies and all the soil samples present negative Eu anomalies implying the combined effect of weathering and potential exogenous inputs on soil REEs. Positive matrix factorization modeling reveals that soil REEs content is primarily influenced by soil parent materials. Potential anthropogenic sources include mining-related leachate, traffic exhaust, and industrial dust. These results demonstrate that the identification of sources of soil REEs is an important starting point for targeted REEs sources management and regulation of excessive and potentially harmful REEs levels in the soil.

Seasonal trend and source identification of polycyclic aromatic hydrocarbons associated with fine particulate matters (PM2.5) in Isfahan City, Iran, using diagnostic ratio and PMF model

Particulate matters (PMs) and their associated chemical compounds such as polycyclic aromatic hydrocarbons (PAHs) are important factors to evaluate air pollution and its health impacts particularly in developing countries. Source identification of these compounds can be used for air quality management. The aim of this study was to identify the sources of PM_2.5-bound PAHs in Isfahan city, a metropolitan and industrialized area in central Iran. The PM_2.5 samples were collected at 50 sites during 1 year. Source identification and apportionment of particle-bound PAHs were carried out using diagnostic ratios (DRs) of PAHs and positive matrix factorization (PMF) model. The results showed that the concentrations of PM_2.5 ranged from 8 to 291 μg/m³ with an average of 60.2 ± 53.9 μg/m³, whereas the sum of concentrations of the 19 PAH compounds (ƩPAHs) ranged from 0.3 to 61.4 ng/m³ with an average of 4.65 ± 8.54 ng/m³. The PAH compounds showed their highest and lowest concentrations occurred in cold and warm seasons, respectively. The mean concentration of benzo[a]pyrene (1.357 ng m^-3) in December-January, when inversion occured, was higher than the Iranian national standard value showing the risk of exposure to PM_2.5-bound PAHs. Applying DRs suggested that the sources of the PAHs were mainly from fuel combustion. The main sources identified by the PMF model were gasoline combustion (23.8 to 33.1%) followed by diesel combustion (20.6 to 24.8%), natural gas combustion (9.5 to 28.4%), evaporative-uncombusted (9.5 to 23.0%), industrial activities (8.4 to 13.5%), and unknown sources (2.8 to 15.7%). It is concluded that transportation, industrial activities, and combustion of natural gas (both in residential-commercial and industrial sectors) as the main sources of PAHs in PM_2.5 should be managed in the metropolitan area, particularly in cold seasons.

Dissolved polycyclic aromatic hydrocarbons from the Northwestern Pacific to the Southern Ocean: Surface seawater distribution, source apportionment, and air-seawater exchange

Polycyclic aromatic hydrocarbons (PAHs) as a group of toxic and carcinogenic compounds are large scale globally emitted anthropogenic pollutants mainly emitted into the atmosphere. However, atmospheric transport cannot fully explain the spatial variability of PAHs in the marine atmosphere and seawater. It is hypothesized that PAHs accumulated in seawater and ocean circulation can also influence PAHs observed in air above the ocean. In order to investigate PAHs in seawater as a potential secondary source to air, we collected paired air and seawater samples during a research cruise from China to the Antarctic in 2018-2019, covering the Pacific Ocean, the Indian Ocean, and the Southern Ocean. Summed concentrations of 28 analyzed PAHs in seawater were highest in the Pacific Ocean (4000 ± 1400 pg/L), followed by the Indian Ocean (2700 ± 1000 pg/L), and the Southern Ocean (2300 ± 520 pg/L). Three-ringed PAHs dominated the composition profile. We found that PAH levels in the Pacific and Indian Oceans were strong inversely correlated with salinity and distance to the coastline. This suggests that riverine inputs and continental discharges are important sources of PAHs to the marine environment. Derived air-seawater fugacity ratios suggest that net fluxes of PAHs were from seawater to the air in the Pacific and Indian Oceans at 9.0-8100 (median: 1600) ng/m²/d and 290-2000 (median: 1300) ng/m²/d, respectively. In the Southern Ocean, the net flow of PAHs was from air to seawater with a flux of -1000-450 (median: -82) ng/m²/d. Source apportionment from two different models suggested that the largest contribution to total PAHs was from petrogenic sources (44-57%), followed by coal/wood combustion (30-31%), fossil fuel combustion (15%), and engine combustion emissions (2.8-9.5%). Higher contributions from petrogenic sources were found at sites close to coastal regions. Both coal/wood combustion and petrogenic sources are responsible for the PAH concentrations detected in the Indian and Southern Oceans.

Establishment and verification of anthropogenic volatile organic compound emission inventory in a typical coal resource-based city

A few studies on volatile organic compound (VOC) emission inventories in coal resource-based cities have been reported, and previous emission inventories lacked verification. Herein, using Yangquan as a case study, emission factor (EF) method and "(tracer ratio) TR - positive matrix factorization (PMF)" combined method based on atmospheric data were used to establish and verify the VOC emission inventory in coal resource-based cities, respectively. The total VOC emissions in Yangquan were 9283.2 t [-40.0%, 62.1%] in 2018, with industrial processes being the major contributors. Alkanes (35.8%), aromatics (25.0%), and alkenes (19.8%) were the main compounds in the emission inventory. The verification results for both species emission and source structure were in agreement, indicating the accuracy of VOC emission inventory based on EF method to a certain extent. However, for some species (ethane, propane, benzene, and acetylene), the EF method indicated emissions lower than those obtained from the TR results. Furthermore, the summer-time emission contribution from fossil fuel combustion indicated by the EF method (23.4%) was lower than that obtained from the PMF results (38.4%). Overall, these discrepancies could be attributed to the absence of a coal gangue source in the EF method. The verification results determined the accuracy of the VOC emission inventory and identified existing problems in the estimation of the VOC emission inventory in coal resource-based cities. In particular, not accounting for the coal gangue emissions may result in an underestimation of VOC emissions in coal resource-based cities. Thus, coal gangue emissions should be considered in future research.

Variation in PM2.5 sources in central North China Plain during 2017-2019: Response to mitigation strategies

Central North China Plain (NCP) is one of the most important source region of air pollutants over the Beijing-Tianjin-Hebei (BTH) region. The national government has issued abatement measures to improve the air quality in this area from 2017. To examine the effects of control measures, observational analysis on PM_2.5 characteristics was performed in a city of central NCP during 2017-2019 to investigate the variation in mass concentration, chemical composition, and emission source of PM_2.5. Annual PM_2.5 concentration significantly reduced by 16% from 2017 to 2019, implying substantial improvements in air quality. PM_2.5 enriched in autumn-winter seasons was dominated by SNA (sum of sulfate, nitrate and ammonium; ~38%), followed by organic carbon matters (OM; ~24%) and fine soil (FS; ~12%). This chemical composition was different from that in a megacity in NCP (Beijing) where OM accounted for a comparable fraction to SNA. Approximately half of SNA was attributed to nitrate, indicating that SNA changed from sulfate-driven to nitrate-driven, and the considerable effects of coal combustion cutoff, in which sulfate was concentrated. Decreased mass fraction of SNA and increased OM fraction in PM_2.5 were observed in 2018-2019 partly contributed to the decrease in PM_2.5. A progressive increase in the contribution of heterogeneous formed SNA whilst a decrease in OM was observed as the pollution elevated from clean to heavily polluted. Six sources (soil dust, biomass burning, secondary emission, road traffic, coal combustion and industry) were identified by the Positive Matrix Factorization (PMF) model in both years and dominated by secondary aerosols, respectively contributing 39% and 41% to PM_2.5. The decreasing concentrations (with reductions of 17%-61%) of the secondary source, coal combustion, soil dust and biomass burning largely accounted for the reduction in PM_2.5, as a consequence of the recent abatement measures. By contrast, contributions of vehicle-related emissions, similar to the increasing contribution of vehicles at sites in NCP after 2013, should receive increased attention.

Disturbance mechanisms of lacustrine organic carbon burial: Case study of Cuopu Lake, Southwest China

Lakes are important organic carbon (OC) traps in the global carbon cycle. Recent studies have shown that the rate of OC burial in lacustrine sediments is influenced by factors such as climate change, land-use change, and eutrophication. In this study, we use multiproxy methods to reveal the mechanisms of lacustrine sediment OC burial in an alpine lake (Cuopu Lake), in southwest China. Combined with the dating from ²¹⁰Pb_ex and n-alkanes distribution analysis using the Positive Matrix Factorization model, the sedimentary history was divided into five stages: religious activity (the 1840s-1880s), earthquake (the 1880s-1910s), garrison (the 1910s-1960s), transition (the 1960s-1990s), and ecotourism (the 1990s-2010s). During the earthquake stage, OC burial was dominated by terrestrial solids (>40%) and co-precipitated algae (>30%), with a rapid deposition rate (>4 mm a^-1) and low OC concentration (<4 mg g^-1). During the other stages, when the level of disturbance was relatively low, a change in nutrient conditions either promoted or inhibited plant growth, which influenced the type of buried OC. The contribution of OC derived from combustion sources varied from stage to stage. Severe anthropogenic disturbances have led to a significant increase in nutritional levels in the lake water, leading to an increase in the OC burial rate. Climate change, which leads to changes in temperature and rainfall, did not significantly influence OC burial, whereas nitrogen deposition (and associated ecological changes) was a significant determinant. When the general mechanism is dominant, the total nitrogen to inorganic phosphorus ratio is an effective indicator of OC burial due to its selective promotion of different plant types. In conclusion, our results suggest that lacustrine sediment OC burial is closely linked to physical and anthropogenic factors in Cuopu Lake, as well as similar montane lakes.

Insights into the long-term pollution trends and sources contributions in Lake Taihu, China using multi-statistic analyses models

Eutrophication pollution seriously threatens the sustainable development of Lake Taihu, China. In order to identify the primary parameters of water quality and the potential pollution sources, the water quality dataset of Lake Taihu (2010-2014) was analyzed with the water quality index (WQI) and multivariate statistical analysis methods. Principle component analysis/factor analysis (PCA/FA) and correlation analysis screened out five significant water quality indicators, i.e. potassium permanganate index (COD_Mn), total nitrogen (TN), total phosphorus (TP), chloride ion (Cl^-) and dissolved oxygen (DO), to represent the whole datasets and evaluate the water quality with WQI. Since northwestern of Lake Taihu was the most heavily polluted area, the parameters of the water quality were analyzed to further explore the potential sources and their contributions. Five potential pollution sources of northwestern lake were identified, and the contribution rate of each pollution source was calculated by the absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models. In brief, the PMF model was more suitable for pollution source apportionment of the northwestern lake, and the contribution rate was ranked as agricultural non-point source pollution (26.6%) > domestic sewage discharge (23.5%) > industrial wastewater discharge and atmospheric deposition (20.6%) > phytoplankton growth (16.0%) > rainfall or wind disturbance (13.4%). This study might provide useful information for the optimization of water quality management and pollution control strategies of Lake Taihu.