Exploring polystyrene weathering behavior: From surface traits to micro(nano)plastics and additives release.

Plastic weathering in the natural environment is a dynamic and complex process, where the release of microplastics, nanoplastics and additives poses potential threats to ecosystems. Understanding the release of different weathering products from plastics is crucial for predicting and assessing the environmental hazards of plastics. This study systematically explored these phenomena by exposing polystyrene (PS) to UV irradiation and mechanical agitation for different durations (1 day, 5 days, 10 days, 20 days). The degree of aging, yellowing, brittleness, and the abundance of carbonyl (CO) functional groups in PS were all gradually increasing over time. The weathering pattern of PS surfaces manifested as initial particle oxidation followed by later cracks or flakes formation. The release of products was positively correlated with the aging degree of plastics, as well as among the various released products. Laser infrared and Raman tests indicated that, for microplastics, the size range of 10-20 µm consistently dominated over time, while the primary size range of nanoplastics shifted towards smaller sizes. Additives and other soluble products were prone to release from weathering plastics, with 20 different chemicals detected after 20 d. The release of plastic additives was closely related to aging time, additive type, and quantity. This study contributes to our understanding of the weathering process of plastics, clarifies the release patterns of products over time, and the relationships among different products. It helps predict and assess the environmental pollution caused by plastics.

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.

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.

Application of spatial Markov chains to the analysis of the temporal-spatial evolution of soil erosion.

Soil and water conservation in the Three Gorges Reservoir Area of China is important, and soil erosion is a significant issue. In the present study, spatial Markov chains were applied to explore the impacts of the regional context on soil erosion in the Xiangxi River watershed, and Thematic Mapper remote sensing data from 1999 and 2007 were employed. The results indicated that the observed changes in soil erosion were closely related to the soil erosion levels of the surrounding areas. When neighboring regions were not considered, the probability that moderate erosion transformed into slight and severe erosion was 0.8330 and 0.0049, respectively. However, when neighboring regions that displayed intensive erosion were considered, the probabilities were 0.2454 and 0.7513, respectively. Moreover, the different levels of soil erosion in neighboring regions played different roles in soil erosion. If the erosion levels in the neighboring region were lower, the probability of a high erosion class transferring to a lower level was relatively high. In contrast, if erosion levels in the neighboring region were higher, the probability was lower. The results of the present study provide important information for the planning and implementation of soil conservation measures in the study area.

Antibiotic intermediates and antibiotics synergistically promote the development of multiple antibiotic resistance in antibiotic production wastewater.

Antibiotic resistance (AR) is a major public health concern. Antibiotic intermediates (AIs) used in the production of semisynthetic antibiotics have the same bioactive structure as parent antibiotics and synthetic antibiotic production wastewater usually contains high concentrations of residual AIs; however, the effects of AIs and their interactive effects with antibiotics on the emergence of AR are unknown. In this study, antibiotic-sensitive E. coli K12 was exposed to five types of ß-lactam AIs and their parent antibiotic ampicillin to analyze their impact on the evolution of multiple AR. The results indicated that AI 6-APA inhibits bacterial growth and stimulates the production of reactive oxygen species, as well as induces AR and antibiotic persistence like the parent antibiotic AMP. Combined exposure to 6-APA and AMP synergistically stimulated the induction of multiple AR and antibiotic persistence. The resistance mutation frequency increased up to 6.1 × 106-fold under combined exposure and the combination index reached 1326.5, indicating a strong synergy of 6-APA and AMP. Phenotypic and genotypic analyses revealed that these effects were associated with the overproduction of reactive oxygen species, enhanced stress response signatures, and activation of efflux pumps. These findings provide evidence and mechanistic insights into AR induction by AIs in antibiotic production wastewater.

[Research Progress on Production and Emission of CH4 and N2O from Urban Rivers].

Methane （CH4） and nitrous oxide （N2O） are concerning greenhouse gases. Urban rivers have been important emission sources of CH4 and N2O in recent years. It is meaningful for city greenhouse gas reduction to provide a systematic analysis of spatiotemporal characteristics, mechanisms, and influencing factors of the production and emission of CH4 and N2O from urban rivers. This study combed measured data of urban river CH4 and N2O dissolution concentrations and emission fluxes from related literature published in the past 20 years and also concluded the spatiotemporal characteristics of urban river CH4 and N2O emissions. This study estimated that CH4 and N2O emissions （expressed by CO2-eq） from urban rivers in Beijing were 234.63 and 59.53 Gg CO2-eq in 2018, whereas CH4 and N2O emissions （expressed by CO2-eq） from urban rivers in Shanghai were 159.86 and 260.24 Gg CO2-eq in 2018, respectively. These results demonstrated that urban rivers have become important CH4 and N2O emission sources. This study summarized the production/consumption processes and import/export pathways of CH4 and N2O in urban rivers. What is more, this study discussed the main influencing factors of urban river CH4 and N2O production and emissions from the perspectives of river environmental conditions and urbanization effects. At last, the present work prospected the future research trends of urban river CH4 and N2O emissions and provides urban rivers with scientific support for greenhouse gas reduction.

Single and combined effect of polyethylene microplastics (virgin and naturally aged) and cadmium on pakchoi (Brassica rapa subsp. chinensis) under different growth stages.

To protect agro-systems and food security, study on the effect of microplastics and heavy metals on edible plants is of great significance. Existing studies mostly used virgin microplastics to evaluate their effects on plants, effects of naturally aged microplastics and their combined effects with heavy metals are rarely explored. In this study, single and combined effect of polyethylene microplastics (PE, both virgin and naturally aged) and cadmium (Cd) on pakchoi under seedling and mature stages were analyzed from perspectives of growth inhibition, oxidative damage, nutrition content and soil enzyme activities. Results showed that inhibiting effects of naturally aged PE (PEa) on the growth of pakchoi were stronger than virgin PE (PEv), whereas co-contamination of PEa and Cd was less toxic than that of PEv and Cd. The co-contamination of PE and Cd could inhibit pakchoi dry biomass by over 85 %. Both single and combined contamination of PE and Cd promoted soil fluorescein diacetate hydrolase (FDA) activities, which were 1.11 to 2.04 times of that in control group. Soluble sugar contents under co-contamination of PEa and Cd were 14 % to 22 % higher than those in control group. PEa and PEv showed different effects on oxidative damage of pakchoi. Compared with PEv, catalase (CAT) activities were more sensitive with PEa, whereas PEa had lower effect on superoxide dismutase (SOD) activities. The response of pakchoi to PE and Cd changed with growth stage. Chlorophyll contents in pakchoi under seedling stage were generally higher than those under mature stage. For Cd contaminated soils, PE benefited pakchoi growth under seedling stage, i.e. antagonistic effect between Cd and PE but hindered their growth under mature stage, i.e. synergistic effect. The results unraveled here emphasized PE, especially PEa, could trigger negative effects on agro-systems, whereas PE could be beneficial for heavy metal contaminated agro-systems under specific situations.

The difference between tire wear particles and polyethylene microplastics in stormwater filtration systems: Perspectives from aging process, conventional pollutants removal and microbial communities.

Tire wear particles (TWPs) in stormwater runoff have been widely detected and were generally classified into microplastics (MPs). TWPs and conventional MPs can be intercepted and accumulated in stormwater filtration systems, but their impacts on filtration, adsorption and microbial degradation processes of conventional pollutants (organic matters, nitrate and ammonium) have not been clarified. TWPs are different from MPs in surface feature, chemical components, adsorption ability and leaching of additives, which might lead to their different impacts on conventional pollutants removal. In this study, five different levels of aged polyethylene MPs (PEMPs) and aged TWPs contamination in stormwater filtration systems were simulated using thirty-three filtration columns. Results showed that ultraviolet aging treatment was less influential for the aging of TWPs than that of PEMPs, the specific surface area of aged PEMPs (1.603 m2/g) was over two times of unaged TWPs (0.728 m2/g) in the same size. Aged PEMPs and aged TWPs had different impacts on conventional pollutants removal performance and microbial communities, and the difference might be enlarged with exposure duration. The intensified aged PEMPs contamination generally promoted conventional pollutants removal, whereas aged TWPs showed an opposite trend. Mild contamination (0.01% and 0.1%, wt%) of aged PEMP/TWPs was beneficial to the richness and diversity of microbial communities, whereas higher contamination of aged PEMPs/TWPs was harmful. Aged PEMPs and TWPs had different impact on microbial community structure. Overall, the study found that TWPs were more detrimental than PEMPs in filtration systems. The research underscores the need for more comprehensive investigation into the occurrence, effects and management strategies of TWPs, as well as the importance of distinguishing between TWPs and MPs in future studies.

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.

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.

Propagation of spiking regularity and double coherence resonance in feedforward networks.

We investigate the propagation of spiking regularity in noisy feedforward networks (FFNs) based on FitzHugh-Nagumo neuron model systematically. It is found that noise could modulate the transmission of firing rate and spiking regularity. Noise-induced synchronization and synfire-enhanced coherence resonance are also observed when signals propagate in noisy multilayer networks. It is interesting that double coherence resonance (DCR) with the combination of synaptic input correlation and noise intensity is finally attained after the processing layer by layer in FFNs. Furthermore, inhibitory connections also play essential roles in shaping DCR phenomena. Several properties of the neuronal network such as noise intensity, correlation of synaptic inputs, and inhibitory connections can serve as control parameters in modulating both rate coding and the order of temporal coding.

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.

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.

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.

[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.

Vibrational resonance in feedforward network.

This paper investigates vibrational resonance in multi-layer feedforward network (FFN) based on FitzHugh-Nagumo (FHN) neuron model. High-frequency stimuli can improve the input-output linearity of firing rates, especially for the inputs with low firing rate. For FFN network, it is found that high-frequency disturbances play important roles in enhancing the propagation of weak signal through layers. Synfire-enhanced phenomenon of signal propagation is also observed in multi-layers network, when the signal transmission is affected by high-frequency disturbances. Network connections are found to be important for the propagation of weak signal. Besides that, the characteristics of high-frequency stimuli such as heterogeneity and frequency can also modulate the propagation of neural code through layers.

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.

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.