A combined evaluation of the characteristics and antibiotic resistance induction potential of antibiotic wastewater during the treatment process.

Antibiotic wastewater contains a variety of pollutant stressors that can induce and promote antibiotic resistance (AR) when released into the environment. Although these substances are mostly in concentrations lower than those known to induce AR individually, it is possible that antibiotic wastewater discharge might still promote the AR transmission risk via additive or synergistic effects. However, the comprehensive effect of antibiotic wastewater on AR development has rarely been evaluated, and its treatment efficiency remains unknown. Here, samples were collected from different stages of a cephalosporin production wastewater treatment plant, and the potential AR induction effect of their chemical mixtures was explored through the exposure of the antibiotic-sensitive Escherichia coli K12 strain. Incubation with raw cephalosporin production wastewater significantly promoted mutation rates (3.6 × 103-9.3 × 103-fold) and minimum inhibition concentrations (6.0-6.7-fold) of E. coli against ampicillin and chloramphenicol. This may be attributed to the inhibition effect and oxidative stress of cephalosporin wastewater on E. coli. The AR induction effect of cephalosporin wastewater decreased after the coagulation sedimentation treatment and was completely removed after the full treatment process. A Pearson correlation analysis revealed that the reduction in the AR induction effect had a strong positive correlation with the removal of organics and biological toxicity. This indicates that the antibiotic wastewater treatment had a collaborative processing effect of conventional pollutants, toxicity, and the AR induction effect. This study illustrates the potential AR transmission risk of antibiotic wastewater and highlights the need for its adequate treatment.

Naturally aged polylactic acid microplastics stunted pakchoi (Brassica rapa subsp. chinensis) growth with cadmium in soil.

Biodegradable microplastics (BMPs) and cadmium (Cd) are posing threats to agro-systems especially to plants and current studies mostly used virgin BMPs to explore their ecological effects. However, effects of naturally aged BMPs and their combined effects with Cd on pakchoi are yet to be unraveled. Therefore, this study incubated naturally aged polylactic acid (PLA) MPs through soil aging process and investigated the single and combined effects of Cd and PLA MPs (virgin and aged) on pakchoi (Brassica rapa subsp. chinensis) morphology, antioxidant systems and soil microbial activities. Our results found that after being deposited in soil for six months, aged PLA (PLAa) MPs formed with a fractured surface, demonstrating more detrimental effects on pakchoi than virgin ones. PLA/PLAa MPs and Cd stunted pakchoi growth, caused oxidative stress and altered the biophysical environment in soil, separately. Moreover, co-existence of PLA/PLAa MPs and Cd caused greater damages to pakchoi than applied alone. The co-presence of PLAa MPs and Cd inhibited pakchoi biomass accumulation rate by 92.2 % compared with the no-addition group. The results unraveled here emphasized BMPs, especially aged BMPs, could trigger negative effects on agro-systems with heavy metals. These findings will give reference to future holistic assessments of BMPs' ecological effects.

Enhanced denitrification of the AO-MBBR system used for expressway service area sewage treatment: A new perspective on decentralized wastewater treatment.

Decentralized wastewater treatment warrants considerable development in numerous countries and regions. Owing to the unique characteristics of high ammonia nitrogen concentrations and low carbon/nitrogen ratio, nitrogen removal is a key challenge in treating expressway service area sewage. In this study, an anoxic/oxic-moving bed biofilm reactor (A/O-MBBR) and a traditional A/O bioreactor were continuously operated for 115 days and their outcomes were compared to investigate the enhancement effect of carriers on the total nitrogen removal (TN) for expressway service area sewage. Results revealed that A/O-MBBR required lower dissolved oxygen, exhibited higher tolerance toward harsh conditions, and demonstrated better shock load resistance than traditional A/O bioreactor. The TN removal load of A/O-MBBR reached 181.5 g‧N/(m3‧d), which was 15.24% higher than that of the A/O bioreactor. Furthermore, under load shock resistance, the TN removal load of A/O-MBBR still reached 327.0 g‧N/(m3‧d), with a TN removal efficiency of above 80%. Moreover, kinetics demonstrated that the denitrification rate of the A/O-MBBR was 121.9% higher than that of the A/O bioreactor, with the anoxic tank biofilm contributing 60.9% of the total denitrification rate. Community analysis results revealed that the genera OLB8, uncultured_f_Saprospiraceae and OLB12 were the dominant in biofilm loaded on carriers, and OLB8 was the key for enhanced denitrification. FAPROTAX and PICRUSt2 analyses confirmed that more bacteria associated with nitrogen metabolism were enriched by the A/O-MBBR carriers through full denitrification metabolic pathway and dissimilatory nitrate reduction pathway. This study offers a perspective into the development of cost-effective and high-efficiency treatment solutions for expressway service area sewage.

Machine-learning-aided application of high-gravity technology to enhance ammonia recovery of fresh waste leachate.

Stripping is widely applied for the removal of ammonia from fresh waste leachate. However, the development of air stripping technology is restricted by the requirements for large-scale equipment and long operation periods. This paper describes a high-gravity technology that improves ammonia stripping from actual fresh waste leachate and a machine learning approach that predicts the stripping performance under different operational parameters. The high-gravity field is implemented in a co-current-flow rotating packed bed in multi-stage cycle series mode. The eXtreme Gradient Boosting algorithm is applied to the experimental data to predict the liquid volumetric mass transfer coefficient (KLa) and removal efficiency (η) for various rotation speeds, numbers of stripping stages, gas flow rates, and liquid flow rates. Ammonia stripping under a high-gravity field achieves η = 82.73% and KLa = 5.551 × 10-4 s-1 at a pH value of 10 and ambient temperature. The results suggest that the eXtreme Gradient Boosting model provides good accuracy and predictive performance, with R2 values of 0.9923 and 0.9783 for KLa and η, respectively. The machine learning models developed in this study are combined with experimental results to provide more comprehensive information on rotating packed bed operations and more accurate predictions of KLa and η. The information mining behind the model is an important reference for the rational design of high-gravity-field-coupled ammonia stripping projects.

[Spatial Variation and Potential Sources of Microplastics in Rivers in Tongzhou District, Beijing].

Microplastics are emerging contaminants, which can also absorb other contaminants, threatening the health of river ecosystems. However, research on the pollution of microplastics in rivers in northern China is still lacking. In this study, based on the sampling and analysis of water samples in 19 sites in six rivers in Tongzhou district, Beijing, the composition, spatial variation, and potential sources of microplastics were explored. The results showed that all sites were contaminated by microplastics, and the abundance of microplastics in the Xiaozhong River was the highest among all sites (3.50×104 n·m-3), which was 4.04 times that in the Yunchaojian River. The proportion of microplastics with particle sizes smaller than 2000 µm was 90.49%, and microplastics with particle sizes larger than 4000 µm were only found in two out of 19 sampling sites. The microplastics were fiber, film, fragment, and granule shaped. The proportion of fiber microplastics was the highest (90.23%) among all shapes. Most (84.29%) of the microplastics were transparent and blue. Rayon was the most common microplastic in each site, and its proportion in each site was over 66.67%. The proportions of other types of microplastics differed largely among different sites. Spatially, the abundance and types of microplastics in the upper reaches were higher than those in the lower reaches. According to spatial variations in shapes, types, colors, and abundance of microplastics, the potential sources of microplastics were identified. The potential sources of fiber microplastics were washing clothing and using fishing gear and dust-proof nets.

Impact of particle sizes on health risks and source-specific health risks for heavy metals in road dust.

To analyze the impact of particle sizes on sources and related health risks for heavy metals, road dust samples in Beijing were collected and sifted into five particle sizes. The positive matrix factorization (PMF), human health risk assessment model (HHRA), and Monte Carlo simulation were used in the health risk assessment and source apportionment. Results showed that mass of particles < 74 µm occupied about 50% of the total particles, while only 8.48% of the particles were > 500 µm. Mass distribution and concentrations of heavy metals in each particle size changed in temporal. Over 85.00% of carcinogenic risks (CR) were from particles <74 µm, whereas CR from particles >250 µm were ignorable. Sources for health risks in each particle size were traffic exhaust, fuel combustion, construction, and use of pesticides and fertilizers. Proportions of sources to CR differed among particle sizes. Traffic exhaust and fuel combustion contributed over 90% to CR in particles <74 µm, whereas construction contributed the highest (31.68-54.14%) among all sources in particles 74-250 µm. Furthermore, the difference between health risks based on sifted road dust and that based on unsifted road dust was quantitatively analyzed. Source-specific health risk apportionment based on unsifted road dust was not presentative to all particle sizes, and true value of health risks could be over 2.5 times of the estimated value based on unsifted road dust, emphasized the importance of sifting of road dust.

[Temporal and Spatial Distribution Characteristics and Source Apportionment of Runoff Pollution in Langfang City].

Urban runoff pollution can carry pollutants into the receiving water through scouring and leaching, causing black color and odor or eutrophication. Understanding and mastering the characteristics of runoff pollution is a prerequisite for the effective control of runoff pollution. This study aimed to comprehensively analyze the temporal and spatial distribution characteristics of runoff pollution and the correlation between pollutants in the urban area of Langfang City. Rainfall runoff samples were collected seven times by setting up 14 sampling sites within the urban area. The suspended solids (SS), chemical oxygen demand (COD), N, P, fecal E. coli, anionic surfactants, volatile phenols, and Zn, Cr6+, As, Cu, etc. were analyzed. The source and distribution of pollutants were summarized and analyzed through principal component analysis and cluster analysis. The results showed that the concentration of pollutants in runoff in Langfang City varied greatly at different times and locations. The average ρ(SS) at each point ranged from 150-500 mg·L-1, and the average concentrations of COD, N, P, and fecal E. coli all exceeded those of the surface water standard Ⅴ. The average concentration of anionic surfactants, petroleum, and volatile phenols were between those of the surface water standard Ⅰ and standard Ⅳ. The concentrations of metal pollutants were relatively low. NH4+-N had a positive correlation with total nitrogen (TN), volatile phenols, and As. COD had a certain positive correlation with TN, total phosphorus (TP), Cr6+, and As, whereas fecal E. coli had a certain negative correlation with Zn and Cu. The organic matter, P, Cu, and SS were probably derived from vehicle tires and road surfaces. All sampling sites could be roughly divided into four types according to the features of pollution:mainly commercial service areas, residential areas, larger arterial roads, and small roads between communities. The pollution of runoff in Langfang City was relatively serious, especially that of COD, N, and P. This research provides important reference values for the control and regulation of runoff pollution in urban areas and other northern cities.

Prediction of tempo-spatial patterns and exceedance probabilities of atmospheric corrosion of Q235 carbon steel across China.

To reduce the losses caused by the atmospheric corrosion of carbon steels, it is important to establish a prediction model to determine the corrosion rate of carbon steels in natural environments. In this study, a prediction model of atmospheric corrosion of Q235 carbon steel (PMACC-Q235) in China was established by coupling the mean impact value algorithm and back propagation artificial neural network. Tempo-spatial patterns of corrosion rates in five long-exposure time categories across China were analyzed. Ten main factors affecting the atmospheric corrosion of Q235 were identified. The corrosion rates in a single year were similar (approximately 30 µm/a) and larger than those for 2 (25.30 µm/a) and 3 years (21.66 µm/a). The spatial corrosion rates in the northwestern areas were primarily lower than those in southeastern coastal areas. This could be influenced by climatic factors, such as temperature, humidity, and precipitation. All corrosion rates reached the C2 level (>1.3 µm/a), and there was some possibility that they reached higher corrosion levels. The largest probability for the C3 level in all periods was an average of 0.91, and that for the C4 level was 0.83. Spatially, higher probabilities were mainly located in the southern area, especially in Hainan, located in the south and surrounded by sea. Corrosion rates largely varied among climatic zones, and mean corrosion rates in the tropical monsoon climate zone were the largest (average of three periods 33.39 µm/a). SO2 and soluble-dust fall had the largest impact on the variations in the corrosion rates among different climatic zones.

A four-way model (FEST) for source apportionment: Development, verification, and application.

In studying the spatial, temporal, and particle size variations heavy metal sources, a source apportionment model for a four-way array of data is required. In this study, referencing two-way and three-way models, a four-way (particle fractions, elements, sites, and time) source apportionment model (FEST) was developed. Errors in the three-way models solving four-way problems verified the necessity of developing the FEST model. The results showed that the FEST model had a higher accuracy than the existing models, which was probably because of more constraints and input data in the FEST model. Based on the sampled data in Beijing, sources were apportioned for the four-way array of data using the FEST model, and the spatial, temporal, and particle size variations of sources were evaluated. The main sources of heavy metals were similar to those in our prior studies, whereas the contributions of sources to specific heavy metals differed. Traffic exhaust and fuel combustion contributed more to fine particles than coarse particles, indicating that the two should be controlled preferentially among all sources. The management of traffic exhaust should be focused on the central and northern areas in each season, and the control of fuel combustion should be strengthened in the southern area in winter.

Multiscale spatiotemporal characteristics of landscape patterns, hotspots, and influencing factors for soil erosion.

Soil erosion is an increasingly serious eco-environmental problem, and effective control of soil erosion is an important part of soil resource protection and ecological restoration. In this study, the multi-scale characteristics and influencing factors of soil erosion were analyzed in the Beijing-Tianjin-Hebei (BTH) region from 2000 to 2015. The results showed that the average soil erosion in the study area was 3500 t/(km2·a), in which the severe erosion areas accounted for 10% of the total area. Although the total soil erosion rate decreased by 60% from 2000 to 2015, the rate of current soil erosion was higher than the soil loss tolerance. The severe erosion area had the highest aggregation index, making it the most suitable for centralized treatment. Meanwhile, the fractal dimension index of severe erosion showed a downward trend from 2000 to 2015. This decrease in complexity led to a more optimistic conservation situation. The hotspot areas overlapped with the relatively high erosion zones and were aggregated as three large patches in the northern, southwestern, and southern BTH regions. Soil erosion distribution depends on both anthropogenic activities and natural conditions. The slope factor, which reflects the impact of natural factors on soil erosion, was the most dominant factor on soil erosion from 2000 to 2010. Conversely, the land use factor, which is mainly controlled by humans, became the dominant factor in 2015. The distribution characteristics and influencing factors of soil erosion both had scale effects. As the scale decreased from city to town, the patches of high and severe erosion classes became more regular and aggregated, the hotspot area had the most concentrated and severe soil erosion rate at the town scale, and human impacts became dominant. Conservation targeting hotspot areas measured at the town scale, which was 20% of the total area, could reduce the total soil loss by 38%. For a region with a complex structure, the main influencing factors showed strong spatial dependence.

Spatial-temporal characteristics, source-specific variation and uncertainty analysis of health risks associated with heavy metals in road dust in Beijing, China.

Based on the concentrations of ten heavy metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn, Fe) in 144 road dust samples collected from 36 sites across 4 seasons from 2016 to 2017 in Beijing, this study systematically analyzed the levels and main sources of health risks in terms of their temporal and spatial variations. A combination of receptor models (positive matrix factorization and multilinear engine-2), human health risk assessment models, and Monte Carlo simulations were used to apportion the seasonal variation of the health risks associated with these heavy metals. While non-carcinogenic risks were generally acceptable, Cr and Ni induced cautionary carcinogenic risks (CR) to children (confidence levels was approximately 80% and 95%, respectively).. Additionally, fuel combustion posed cautionary CR to children in all seasons, while the level of CR from other sources varied, depending on the seasons. Heavy metal concentrations were the most influential variables for uncertainties, followed by ingestion rate and skin adherence factor. The values and spatial patterns of health risks were influenced by the spatial pattern of risks from each source.

Temporal variations of levels and sources of health risk associated with heavy metals in road dust in Beijing from May 2016 to April 2018.

To analyze the temporal variations of heavy metals, health risk, and source-specific health risk, 24 road dust samples were collected from Beijing in each month in two years. The temporal variations of Hg, Pb, and Ni were higher than other heavy metals. Most heavy metals reached their highest concentrations either in winter or in spring, then the concentrations decreased and reached the lowest values in autumn. Human health risk assessment (HHRA) model showed that As, Cr, and Ni might pose cautionary carcinogenic risk (CR) to children (CR > 10-6). CR for adults were only 0.15 to 0.19 times of that for children. Four sources were identified based on positive matrix factorization model and HHRA model, they were traffic exhaust, fuel combustion, construction, and use of pesticides and fertilizers. Influenced by the difference of carcinogenicity of heavy metals, traffic exhaust contributed the largest to heavy metals (36.02%, over 42.24% higher than other sources), while contributions of fuel combustion to CR (36.95%) was similar to traffic exhaust (37.17%). Monte-Carlo simulation showed that the 95th percentile of probability density functions of CR posed by Cr and Ni from each source were 9.90 × 10-5 to 2.64 × 10-4, posing cautionary carcinogenic risk to children. The seasonal change of CR varied among different sources. CR from use of pesticides and fertilizers in spring was 35.06 times of that in winter, and that from fuel combustion in winter was 1.15-2.40 times of that in other seasons. CR from each source was sensitive to ingestion rate and skin adherence factor.

Source-specific ecological risk analysis and critical source identification of heavy metals in road dust in Beijing, China.

To explore the spatial variation of source-specific ecological risks and identify critical sources of heavy metals in road dust, 36 road dust samples collected in Beijing in March 2017 were analyzed for heavy metals. A new method that takes into consideration the heavy-metal toxic response and is flexible to changes in the number of calculated heavy metals, called the Nemerow integrated risk index (NIRI), was developed for ecological risk assessment. The NIRI indicated that heavy metals posed considerable to high risks at the majority of sites, and 22 % of the sites suffered extreme risk in spring (NIRI > 320). Four main sources were identified based on positive matrix factorization (PMF): traffic exhaust, fuel combustion, construction, and use of pesticides and fertilizers. Owing to the lower toxic response factors of representative heavy metals of fuel combustion than those of other sources, although fuel combustion had the highest contribution (34.21 %) to heavy metals in spring, it only contributed 5.57 % to ecological risks. Critical sources and critical source areas were determined by considering the contributions to both heavy metals and ecological risks. The use of pesticide and fertilizer and traffic-related exhaust were identified as critical sources of heavy metals in spring. Source-specific ecological risks and critical sources of heavy metals changed with the changing seasons, which suggests that different strategies should be adopted in different seasons.

Spatial-temporal variation of heavy metals' sources in the surface sediments of the Yangtze River Estuary.

In this study, positive matrix factorization, multilinear engine 2, and geographic information systems were used to characterize the spatial-temporal patterns of sources for nine heavy metals in the surface sediments of the Yangtze River Estuary in different seasons. Results showed that six sources were identified: agricultural pesticide, marine transportation, chemical factory wastewater, metal smelter waste, atmospheric deposition, and agricultural fertilizer. The proportions of sources were similar during the entire year but varied among the seasons. The differences in the proportions of agricultural pesticide between winter and other seasons were greater than 12%. Over 40% of the Cd concentration in most seasons was attributed to atmospheric deposition, while less than 5% in autumn. The impact strength of most sources, except marine transportation and metal smelter waste, decreased from the inner regions to the adjacent sea. The difference in the impact strength of agricultural pesticide was the largest throughout the study area.

Uncertainty analysis in source apportionment of heavy metals in road dust based on positive matrix factorization model and geographic information system.

Based on 36 road dust samples from an urbanized area of Beijing in September 2016, the information about sources (types, proportions, and intensity in spatial) of heavy metals and uncertainties were analyzed using positive matrix factorization (PMF) model, bootstrap (BS), geographic information system (GIS) and Kriging. The mean concentration of most heavy metals was higher than the corresponding background, and mean concentration of Cd was six times of its background value. Types and proportions of four sources were identified: fuel combustion (33.64%), vehicle emission (25.46%), manufacture and use of metallic substances (22.63%), and use of pesticides, fertilizers, and medical devices (18.26%). The intensity of vehicle emission and the use of pesticides, fertilizers, and medical devices were more homogeneous in spatial (extents were 1.285 and 0.955), while intensity of fuel combustion and the manufacture and use of metallic substances varied largely (extents were 4.172 and 5.518). Uncertainty analysis contained three aspects: goodness of fit, bias and variability in the PMF solution, and impact of input data size. Goodness of fit was assessed by coefficient of determination (R2) of predicted and measured values, and R2 of most species were higher than 0.56. Influenced by an outlier, R2 of Ni decreased from 0.59 to 0.11. Result of bootstrap (BS) showed good robust of this four-factor configuration in PMF model, and contributions of base run of factors to most species were contained in the small interquartile range and close to median values of bootstrap. Size of input data also had influence on results of PMF model. Residuals changed largely with the increase of number of site, it varied at first and then kept stable after number of site reached 70.

Quantifying and simulating landscape composition and pattern impacts on land surface temperature: A decadal study of the rapidly urbanizing city of Beijing, China.

The increase in impervious surfaces due to the urbanization has caused many adverse effects on urban ecological systems, including the urban heat environmental risk. Revealing the relationship between landscape composition and pattern and land surface temperature (LST) gives insight into how to effectively mitigate the urban heat island (UHI) effect. It is also essential to simulate and optimize the distribution of impervious surfaces in urban planning. In this study, the multi-scale relationship between impervious surface and LST in Beijing was analyzed. Different distributions of land cover types and the corresponding LSTs were simulated under two development scenarios. Various geospatial approaches, including geographic information system (GIS), remote sensing, and the Conversion of Land Use and its Effects at Small regional extent (CLUE-S), were used to facilitate the analysis. The results showed that (1) impervious surfaces increased from 36.76% to 44.95% of the total area between 2005 and 2015 and the mean LST of impervious surfaces was approximately 2 °C higher than that of the areas with vegetation cover; (2) impervious surfaces had a positive logarithmic correlation with LST, while the vegetation coverage had a negative linear correlation with LST; (3) as the grid size increased, the correlation coefficients between the impervious surface density and mean LST increased at different magnitudes, and the correlation coefficients stabilized after the scale of 900 × 900 m; (4) large and contiguous patches of impervious surfaces aggravated the UHI effect when the total percentage of impervious surface remained the same; and (5) to achieve an improved and healthier urban living environment, populations controls should be considered to decrease future impervious surface demands by 7.69%-which corresponds to an average LST decrease of 1.1 °C. Landscape distribution and configuration should also be better integrated into landscape and urban planning.

The impact of seasonal varied human activity on characteristics and sources of heavy metals in metropolitan road dusts.

Due to significant human activity, road dust is becoming contaminated by heavy metals in many cities. To comprehensively investigate the variation of contamination level and sources of heavy metals in road dust, 10 heavy metals in road dust samples from Beijing, China, in both summer and winter, were evaluated by spatial analysis using geographic information system (GIS) mapping technology and the positive matrix factorization (PMF) Model. Although the concentrations of some heavy metals between summer and winter had similarities, the differences of others and spatial distributions of heavy metals between summer and winter were considerable. The mean concentrations of As, Cd, Cr, Cu, and Fe were lower in winter, while those of Hg, Mn, Ni, Pb, and Zn were higher. According to the values of the Pollution Index (PI) and Nemerow Integrated Pollution Index (NIPI), there were no obvious differences between summer and winter, but the range between different sites in winter was nearly twice that of summer. Based on the PMF model, four sources of heavy metals in the dust samples were identified. Although the types of sources were consistent, the relative contributions of each source differed between summer and winter. Non-exhaust vehicle emissions was the most important source in summer (34.47 wt%), while fuel combustion contributed the largest proportion to the total heavy metals in winter (32.40 wt%). The impact of each source also showed spatial variation different trends in summer and winter. With the alteration of seasons, intensity of human activities also changed, such as the number of tourists, energy needs for building temperature regulation, construction, and the amount of pesticides and fertilizer. That might be the reason for the variation of heavy metal concentrations and relative contribution of their sources between summer and winter.

Pollution characteristics, risk assessment, and source apportionment of heavy metals in road dust in Beijing, China.

To analyze the spatial distribution patterns, risks, and sources of heavy metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn, Fe), 36 road dust samples were collected from an urbanized area of Beijing in June 2016. The mean concentration of most metals, except As and Mn, exceeded their corresponding background values, with the mean concentration of Cd being 8 times that of its background. Spatially, for most heavy metals, except As and Mn, the high concentration areas were mainly within the 5th ring road, especially the northern area. The geo-accumulation index of Cd and Cu indicated moderate contamination at many sites. The entire study area was prone to potential ecological risks, with higher risks within the 4th ring road. Cd caused high potential ecological risk at most sites. According to the health risk assessment results, the non-carcinogenic risks that human beings suffered from heavy metals were insignificant. However, the carcinogenic risks due to Ni and Cr exceeded the acceptable level. Based on the source apportionment using positive matrix factorization, four factors were defined for the heavy metals. Factor 1, which was traffic-related exhaust, accounted for 34.47% of the concentration of heavy metals. The contributions of Factors 2 and 3 were approximately 25% each. Factor 2 was potentially related to coal combustion, while Factor 3 could be related to the manufacture and use of metal components. Factor 4, which could be related to the use of pesticides, fertilizers, and medical devices, accounted for 14.88%, which was the lowest.

Uncertainty in positive matrix factorization solutions for PAHs in surface sediments of the Yangtze River Estuary in different seasons.

To examine the variabilities of source contributions in the Yangtze River Estuary (YRE), the uncertainty based on the positive matrix factorization (PMF) was applied to the source apportionment of the 16 priority PAHs in 120 surface sediment samples from four seasons. Based on the signal-to-noise ratios, the PAHs categorized as "Bad" might drop out of the estimation of bootstrap. Next, the spatial variability of residuals was applied to determine which species with non-normal curves should be excluded. The median values from the bootstrapped solutions were chosen as the best estimate of the true factor contributions, and the intervals from 5th to 95th percentile represent the variability in each sample factor contribution. Based on the results, the median factor contributions of wood grass combustion and coke plant emissions were highly correlated with the variability (R2 = 0.6797-0.9937) in every season. Meanwhile, the factor of coal and gasoline combustion had large variability with lower R2 values in every season, especially in summer (0.4784) and winter (0.2785). The coefficient of variation (CV) values based on the Bootstrap (BS) simulations were applied to indicate the uncertainties of PAHs in every factor of each season. Acy, NaP and BgP always showed higher CV values, which suggested higher uncertainties in the BS simulations, and the PAH with the lowest concentration among all PAHs usually became the species with higher uncertainties.

Spatial-temporal distribution and risk assessment of mercury in different fractions in surface sediments from the Yangtze River estuary.

The temporal and spatial distributions of mercury in different fractions and its potential ecological risk were investigated in sediments from the Yangtze River estuary (YRE) by analyzing data collected from the study area. The results showed that mercury in the organic and residual fractions had dominant proportions, from 15.2% to 48.52% and from 45.96% to 81.59%, respectively. The fractions were more susceptible to seasonal changes than other fractions. Higher proportions of mercury in organic fraction were found in wet seasons; the opposite was true for mercury in residual fraction. With respect to the spatial distribution, the concentration mercury in exchangeable, carbonate and Fe-Mn oxide fractions showed a decreasing trend from the inner estuary to the outer estuary, but no obvious trends were found in the distributions of mercury in the organic and residual fractions. The risk assessment code (RAC) was used to evaluate the potential ecological risk in the study area based on the proportions of exchangeable and carbonate fractions. The average RAC values during the four periods were 6.00%, 2.20%, 2.83%, and 0.61%. Although these values show that the risk in the study area is generally low, the distribution of RAC values indicates that the inner estuary has a medium risk, with a value up to 10%.