Understanding the spatial representativeness of air quality monitoring network and its application to PM_(2.5)in the China's Mainland

Air pollution has seriously endangered human health and the natural ecosystem during the last decades.Air quality monitoring stations(AQMS)have played a critical role in providing valuable data sets for recording regional air pollutants.The spatial representativeness of AQMS is a critical parameter when choosing the location of stations and assessing effects on the population to long-term exposure to air pollution.In this paper,we proposed a methodological framework for assessing the spatial representativeness of the regional air quality monitoring network and applied it to ground-based PM_(2.5)observation in the mainland of China.Weighted multidimensional Euclidean distance between each pixel and the stations was used to determine the representativeness of the existing monitoring network.In addition,the K-means clustering method was adopted to improve the spatial representativeness of the existing AQMS.The results showed that there were obvious differences among the representative area of 1820 stations in the mainland of China.The monitoring stations could well represent the PM_(2.5)spatial distribution of the entire region,and the effectively represented area(i.e.the area where the Euclidean distance between the pixels and the stations was lower than the average value)accounted for 67.32%of the total area and covered 93.12%of the population.Forty additional stations were identified in the Northwest,North China,and Northeast regions,which could improve the spatial representativeness by 14.31%.

Environmental Benefits for Phase-Out HCFC-22 in the Residential Air-Conditioner Sector in China

China is the largest producer and consumer of hydrochlorofluorocarbons （HCFCs）, and the production of HCFC-22 accounts for more than 80% of all HCFCs. This paper concentrates on the residential air-conditioner industry and analyzes the environmental benefits of accelerating the phase-out of HCFC-22 in China. According to the comparison of the baseline and phase-out scenarios of HCFC-22, the findings show that using HC-290 （propane） as a refrigerant alternative will directly reduce the greenhouse effect, and indirectly reduce the emission of greenhouse gases due to a reduction in the electricity consumption. The comparison of two scenarios of HC-290 and HFC-410A refrigerant alternatives shows that the use of HC-290 refrigerant will produce significantly higher environmental benefits than the HFC-410A refrigerant.

STUDIES ON ENVIRONMENTAL BACKGROUND VALUES IN CHINA

An investigation on environmental background values was made in an area of about 1,140,000 km2, which included temperate and subtropical zones of China. The environmental background values of 142 soil environment units, 18 main soil types, 87 surface water environment units, 8 aquatic organism environment units and 20 underground water environment units were obtained. The rules, causes and effecting factors of regional differentiation of the environmental background values were deduced from over 200,000 various data.

Research on the ecological risk of heavy metals in the soil around a Pb–Zn mine in the Huize County, China

The soil pollution by heavy metals was characterized in the mine tailings and surrounding soils of an old Pb–Zn mine in Huize County. Three hundred and ninety-six samples of agricultural and non-agricultural soil were analyzed for the total metal concentration by acid digestion and sixty-eight selected soil samples were used to determine the chemical fractionation of heavy metals with the modified BCR sequential extraction method. The pollution index of the heavy metals indices for As, Cd, Cr, Cu,Hg, Pb and Zn of non-agricultural soil and agricultural soils in the study area indicated the spreading of heavy metal pollution. Sequential extraction showed that most of Cd existed in an exchangeable form(31.2 %). The available content of Pb, Cu and Zn was mainly distributed in acid extractable fractions and Fe/Mn oxide fractions(27.9, 30 and 27.2 %), and Hg, As and Cr were mainly associated with residual fractions(90.4, 72.9 and 76.8 %). The risks of heavy metals were also evaluated by the risk assessment code(RAC) and potential ecological risk index, respectively. The results of RAC showed a medium and high risk of Cd(45.6 and 54.4 %), medium risk of Zn(100 %), low and medium risk of Cu(41.2 and 58.8 %), largely no risk of Hg(97.1 %), and mainly low risk of As and Pb(92.6and 91.8 %). The range of the potential ecological risk of soil was 58.2–1839.3, revealing a considerably high ecological risk in the study area, most likely related to acid mine drainage and the mining complexes located in the area. The results can be used during the ecological risk screening stage, in conjunction with the total concentrations and metal fractionation values, to better estimate ecological risk.

Trends of surface PM_(2.5) over Beijing–Tianjin–Hebei in 2013–2015 and their causes: emission controls vs. meteorological conditions

The PM2.5 （particulate matter with a diameter of less than 2.5 μm） trends during the period 2013- 2015, in 13 cities over the Beijing-Tianjin-Hebei region, and their causes, were investigated using observations at 75 stations and a regional air quality model. It was found that annual PM2.5 in this region experienced a significant decrease in 2014 and 2015, compared with 2013. PM2.s in 2015 almost met the target on air quality in the 13th Five-Year Plan （2012-2017）. In southern cities （e.g. Xingtai, Handan, Shijiazhuang, and Cangzhou）, this PM2.5 decreasing trend was caused by both meteorological conditions and regional emission controls in 2014 and 2015. Contributions from regional emission controls were more significant than meteorological conditions. In Tianjin and Langfang, the impact of regional emission controls was partly offset by the meteorological conditions in 2014. In 2015, meteorological conditions turned favorable for a PM2.s decrease, but emission controls were still the dominant cause. Compared with polluted cities in Hebei and Tianjin, the decreasing trend in Beijing was small （4% and 9% in 2014 and 2015）.This reflects the competition between adverse meteorological conditions and emission controls. In northern cities （Tangshan, Qinhuangdao, and Zhangjiakou）, regional emission controls dominated the PM2.5 decreasing trend in 2014 and 2015, although they were partly offset by meteorological conditions. In all cities during the heating season in 2015, a more significant decreasing trend of high PM2.5 from emission controls was found than low and middle PM2.5. This indicates that air pollution controls are developing towards refined management （e.g. the Heavy Air Pollution Emergency Response Program） in this region.

Identifying factors that affect environmental air quality using geographical detectors in the NKEFAs of China

The establishment of the National Key Ecological Function Areas(NKEFAs)is an important measure for national ecological security,but the current ecological and environmental evaluation of NKEFAs lacks research on the air quality in the NKEFAs.This study presented the current status of the air quality in the NKEFAs and its driving factors using the geographic detector q-statistic method.The air quality in the NKEFAs was overall better than individual cities and urban agglomeration in eastern coast provinces of China,accounting for 9.21%of the days with air quality at Level III or above.The primary air pollutant was PM_(10),followed by PM_(2.5),with lower concentrations of the remaining pollutants.Pollution was more severe in the sand fixation areas,where air pollution was worst in spring and best in autumn,contrasting with other NKEFAs and individual cities and urban agglomerations.The main influencing factors of air quality index(AQI)in the NKEFAs were land use type,wind speed,and relative humidity also weighted more heavily than factors such as industrial pollution and anthropogenic emissions,and most of these influence factors have two types of interactive effects:binary and nonlinear enhancements.These results indicated that air pollution in the NKEFAs was not related with the emission by intensive economic development.Thus,the policies taking the NKEFAs as restricted development zones were effective,but the air pollution caused by PM_(10) also showed the ecological status in the NKEFAs,especially at sand fixation areas was not quite optimistic,and more strict environmental protection measures should be taken to improve the ecological status in these NKEFAs.

Migration mechanism and risk assessment of perand polyfluoroalkyl substances in the Ya'Er Lake oxidation pond area,China

The migration mechanisms,sources,and environmental risks of 29 legacy and emerging perfluorinated and polyfluoroalkyl species present in an oxidation pond(Ya'Er Lake)were investigated for treating sewage based on the analysis of their occurrence and distribution.The concentration of per-and polyfluoroalkyl substances(PFAS)in pond area was between0.30 and 63.2 ng/g dw(dry weight),with the overall average concentration of 8.00 ng/g dw.Notably,the PFAS concentrations in the surface sediments near the sewage outlet in Pond-1(50.2 ng/g dw)and Pond-5(average 15.1 ng/g dw)were 1–2 orders of magnitude higher than those in other areas.In general,the legacy PFAS,i.e.,perfluorooctane sulfonic acid was considered to be the major pollutant in the polluted area,on average,accounting for 73.0%of the total concentration of PFAS pollutants.By evaluating the regional distribution of different PFAS homologs,the short-chain PFAS pollutants with lower K_(ow)were found to migrate farther in both horizontal and vertical directions.The sewage outlets in Pond-1 and Pond-5are the main pollution sources in polluted area and the emerging PFAS pollutants in Pond-5have replaced the legacy PFAS pollutants as the main pollutants.Based on positive matrix factorization analysis,three main industrial sources of PFAS pollutants in the study area were identified:protective coating,fire-fighting,and food packaging sources.Moreover,the environmental risk assessment results showed that most study areas exhibited medium environmental risk(0.01≤Risk quotient(RQ)<1),indicating that the ecological environment risks in this area need further attention.

Automatic mapping of gully from satellite images using asymmetric non-local LinkNet: A case study in Northeast China

Gully erosion can lead to the destruction of farmland and the reduction in crop yield.Gully mapping from remote sensing images is critical for quickly obtaining the distribution of gullies at regional scales and arranging corresponding prevention and control measures.The narrow and irregular shapes and similar colors to the surrounding farmland make mapping erosion gullies in sloping farmland from remote sensing images challenging.To implement gully erosion mapping,we developed a small training samples-oriented lightweight deep leaning model,called asymmetric non-local LinkNet(ASNL-LinkNet).The ASNL-LinkNet integrates global context information through an asymmetric non-local operation and conducts multilayer feature fusion to improve the robustness of the extracted features.Experiment results show that the proposed ASNL-LinkNet achieves the best performance when compared with other deep learning methods.The quantitative evaluation results in the three test areas show that the F1-score of erosion gully recognition varies from 0.62 to 0.72.This study provides theoretical reference and practical guidance for monitoring erosion gullies on slope farmland in the black soil region of Northeast China.

Trends in particulate matter and its chemical compositions in China from 2013–2017

Accurate determination of the atmospheric particulate matter mass concentration and chemical composition is helpful in exploring the causes and sources of atmospheric enthalpy pollution and in evaluating the rationality of environmental air quality control strategies.Based on the sampling and chemical composition data of PM2.5 in different key regions of China in the CARE-China observation network,this research analyzes the environmental air quality data released by the China National Environmental Monitoring Centre during the studied period to determine the changes in the particulate matter mass concentration in key regions and the evolution of the corresponding chemical compositions during the implementation of the Action Plan for Prevention and Control of Air Pollution from 2013-2017.The results show the following.(1)The particulate matter mass concentration in China showed a significant downward trend;however,the PM2.5 annual mass concentration in 64%of cities exceeds the New Chinese Ambient Air Quality Standard(CAAQS)GradeⅡ(GB3095-2012).The region to the east of the Taihang Mountains,the Fenhe and Weihe River Plain and the Urumqi-Changji regions in Xinjiang,all have PM2.5 concentration loading that is still high,and heavy haze pollution occurred frequently in the autumn and winter.(2)During the heavy pollution in the autumn and winter,the concentrations of sulfate and organic components decreased significantly.The mean SO42-concentration in PM2.5 decreased by 76%,12%,81%and 38%in Beijing-Tianjin-Hebei(BTH),the Pearl River Delta(PRD),the Sichuan-Chongqing region(SC)and the Fenhe and Weihe River Plain,respectively.The mean organic matter(OM)concentration decreased by 70%,44%,48%and 31%,respectively,and the mean concentration of NH4+decreased by 68%,1.6%,38%and 25%,respectively.The mean elemental carbon(EC)concentration decreased by 84%and 20%in BTH and SC,respectively,and it increased by 61%and 11%in the PRD and Fenhe and Weihe River Plain,respectively.The mean concentration of mineral and unresolved chemical components(MI)dropped by 70%,24%and 13%in BTH,the PRD and the Fenhe and Weihe River Plain,respectively.The change in the PM2.5 chemical composition is consistent with the decrease of the PM2.5mass concentration.(3)In 2015,the mean OM concentration contributions to fine particles and coarse particles were 13-46%and 46-57%,respectively,and the mean MI concentration contributions to fine particles and coarse and particles were 31-60%and 39-73%,respectively;these values are lower than the 2013 values from the key regions,which is the most important factor behind the decrease of the particulate matter mass concentration.From 2013 to 2015,among the chemical components of different particle size fractions,the peak value of the coarse particle size fraction decreased significantly,and the fine particle size fractions of SO42-,NO3-,and NH4+decreased with the decrease of the particulate matter mass concentration in different particle size fractions.The fine-particle size peaks of SO42-,NO3-and NH4+shifted from 0.65-1.1μm to the finer size range of0.43-0.65μm during the same time frame.

Development of a static test apparatus for evaluating the performance of three PM2.5 separators commonly used in China

PM2.5 separator directly affects the accuracy of PM2.5 sampling.The specification testing and evaluation for PM2.5 separator is particularly important,especially under China’s wide variation of terrain and climate.In this study,first a static test apparatus based on polydisperse aerosol was established and calibrated to evaluate the performance of the PM2.5 separators.A uniform mixing chamber was developed to make particles mix completely.The aerosol concentration relative standard deviations of three test points at the same horizontal chamber position were less than 0.57%,and the particle size distribution obeyed logarithmic normal distribution with an R2 of 0.996.The flow rate deviation between the measurement and the set point flow rate agreed to within±1.0%in the range of-40 to 50℃.Secondly,the separation,flow and loading characteristics of three cyclone separators(VSCC-A,SCC-A and SCC112)were evaluated using this system.The results showed that the 50%cutoff sizes(D50)of the three cyclones were 2.48,2.47 and 2.44μm when worked at the manufacturer’s recommended flow rates,respectively.The geometric standard deviation(GSD)of the capture efficiency of VSCCA was 1.23,showed a slightly sharper than SCC-A(GSD=1.27),while the SCC112 did not meet the relevant indicator(GSD=1.2±0.1)with a GSD=1.44.The flow rate and loading test had a great effect on D50,while the GSD remained almost the same as before.In addition,the maintenance frequency under different air pollution conditions of the cyclones was summarized according to the loading test.

City level CO_(2) and local air pollutants co-control performance evaluation: A case study of 113 key envir on mental protection cities in China

‘Co-control',or synergistically reducing CO_(2)and local air polluta nt emissions,is an important strategy for cities to achieve'low carb on'and'blue sky'simultaneously.However,there were few studies to evaluate and compare the level of co-control of CO_(2) and local air pollutants in cities year.The present study proposed qualitative and quantitative methods to evaluate the level of co-control of CO_(2)and three local air pollutant(SO_(2).NOX,and particulate matter PM)emissions in key environmental protection cities in China over two periods(2012-2015 and 2015-2018).Statistical analysis found that,though three local air pollutant emissions positively correlated with CO_(2) emission,no significantly positive correlation was found between local air pollutants emission reductions and CO_(2) emission reductions,indicating that co-control effects were poor in general.By using the co-control effect coordinate system,qualitative evaluation showed that less than half of the sample cities could achieve co-control of the total amount of CO_(2) and local air pollutants.By employing the indicator of emission reduction equivalence(EReq),quantitative evaluation showed that the co-control level of the sample cities improved in 2015-2018 compared with 2012-2015.Further regression analysis showed that,reducing coal consumption and economic development significantly enhanced the co-control performance of the observed cities.The present case study proved that the proposed methods for evaluation and comparison of the city co-control performance works well,and can be used in other countries and regions to promote global cities racing to carbon and local air pollutants co-control.

Characteristics of the phytoplankton community and bioaccumulation of heavy metals during algal blooms in Xiangjiang River (Hunan,China)

The frequency of algal blooms has increased in the mid and downstream reaches of the Xiangjiang River （Hunan, China）, one of the most heavily polluted rivers in China. We identified the bloom-forming species in a bloom that occurred mid-late September 2010. In addition, we determined the extent of metal bioaccumulation in the algae and measured the toxicity of the algae using a mouse bioassay. Water samples were collected at upstream （Yongzhou）, midstream （Hengyang）, and downstream （Zhuzhou, Xiangtan, and Changsha） sites. The dominant species was Aulacoseira granulata, formerly known as Melosira granulata. The heaviest bloom occurred at Xiangtan and Changsha, where the number ofA. granulata peaked at 1.3×10^5 filaments L-1 and chlorophyll a at 0.04 mg L-1. Concentrations of A1, Fe, and Mn were 4.4×10^3, 768.4, and 138.7 mg kg-1 dry weight in the phytoplankton. The bioaccumulation factor was 4.0×10^5, 7.7×10^5, and 3.2×10^3, respectively. The heavy metal Pb had the greatest tendency to bioaccumulate among the highly toxic heavy metals, with a concentration of 19.2 mg kg-1 dry weight and bioaccumulation factor of 9.6×10^3. The mouse bioassay suggested the bloom was toxic. The LD50 was 384 mg kg-1 and all surviving mice lost weight during the first 72 h after exposure. Our results demonstrate that blooms ofA. granulata in rivers contaminated with heavy metals pose a threat to freshwater ecosystems and human health. Thus, measures should be taken to control eutrophication and heavy metal pollution in such rivers.

Importance and vulnerability of lakes and reservoirs supporting drinking water in China

Drinking water is closely related to human health,disease and mortality,and contaminated drinking water causes 485,000 deaths from diarrhea each year worldwide.China has been facing increasingly severe water scarcity due to both water shortages and poor water quality.Ensuring safe and clean drinking water is a great challenge and top priority,especially for China with 1.4 billion people.In China,more than 4000 centralized drinking water sources including rivers,lakes and reservoirs,and groundwater have been established to serve urban residents.However,there is little knowledge on the percentage,serving population and water quality of three centralized drinking water source types.We collected nationwide centralized drinking water sources data and serving population data covering 395 prefecture-level and county-level cities and water quality data in the two most populous provinces(Guangdong and Shandong)to examine their contribution and importance.Geographically,the drinking water source types can be classified into three clear regions exhibiting apparent differences in the respective contributions of rivers,lakes and reservoirs,and groundwater.We further found that overall,lakes and reservoirs account for 40.6%of the centralized drinking water sources vs.river(30.8%)and groundwater(28.6%)in China.Lakes and reservoirs are particularly important in the densely populated eastern region,where they are used as drinking water sources by 51.0%of the population(318 million).Moreover,the contribution to the drinking water supply from lakes and reservoirs is increasing due to their better water quality and many cross-regional water transfer projects.These results will be useful for the government to improve and optimize the establishment of centralized drinking water sources,which provide safe and clean drinking water in China to safeguard people's lives and health and realize sustainable development goals.

Heavy haze pollution during the COVID-19 lockdown in the Beijing-Tianjin-Hebei region,China

To investigate the characteristics of particulate matter with an aerodynamic diameter less than 2.5μm(PM_(2.5))and its chemical compositions in the Beijing-Tianjin-Hebei(BTH)region of China during the novel coronavirus disease(COVID-19)lockdown,the ground-based data of PM_(2.5),trace gases,water-soluble inorganic ions,and organic and elemental carbon were analyzed in three typical cities(Beijing,Tianjin,and Baoding)in the BTH region of China from 5-15 February 2020.The PM_(2.5)source apportionment was established by combining the weather research and forecasting model and comprehensive air quality model with extensions(WRF-CAMx).The results showed that the maximum daily PM_(2.5)concentration reached the heavy pollution level(>150μg/m^(3))in the above three cities.The sum concentration of SO_(4)^(2-),NO_(3)^(-)and NH_(4)^(+)played a dominant position in PM_(2.5)chemical compositions of Beijing,Tianjin,and Baoding;secondary transformation of gaseous pollutants contributed significantly to PM_(2.5)generation,and the secondary transformation was enhanced as the increased PM_(2.5)concentrations.The results of WRF-CAMx showed obviously inter-transport of PM_(2.5)in the BTH region;the contribution of transportation source decreased significantly than previous reports in Beijing,Tianjin,and Baoding during the COVID-19 lockdown;but the contribution of industrial and residential emission sources increased significantly with the increase of PM_(2.5)concentration,and industry emission sources contributed the most to PM_(2.5)concentrations.Therefore,control policies should be devoted to reducing industrial emissions and regional joint control strategies to mitigate haze pollution.

Several major issues concerning the environmental transmission and risk prevention of SARS-CoV-2

Coronavirus disease 2019(COVID-19) is the most serious infectious disease pandemic in the world in a century, and has had a serious impact on the health, safety, and social and economic development of all mankind. Since the earth entered the“Anthropocene”, human activities have become the most important driving force of the evolution of the earth system. At the same time, the epidemic frequency of major human infectious diseases worldwide has been increasing, with more than 70% of novel diseases having zoonotic origins. The review of several major epidemics in human history shows that there is a common rule, i.e., changes in the natural environment have an important and profound impact on the occurrence and development of epidemics. Therefore, the impact of the natural environment on the current COVID-19 pandemic and its mechanisms have become scientific issues that need to be resolved urgently. From the perspective of the natural environment, this study systematically investigated several major issues concerning the environmental transmission and risk prevention of Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2). From a macroscopic temporal and spatial scale, the research focus on understand the impact of the destruction of the natural environment and global changes on the outbreak of infectious diseases;the threat of zoonotic diseases to human health;the regularity for virus diffusion, migration and mutation in environmental media;the mechanisms of virus transmission from animals and environmental media to humans;and environmental safety, secondary risk prevention and control of major epidemics. Suggestions were made for future key research directions and issues that need attention, with a view to providing a reference for the prevention and control of the global coronavirus disease 2019, and to improving the ability of response to major public health emergencies.

Air pollution health burden embodied in China's supply chains

Product trade plays an increasing role in relocating production and the associated air pollution impact among sectors and regions.While a comprehensive depiction of atmospheric pollution redistribution through trade chains is missing,which may hinder targeted clean air cooperation among sectors and regions.Here,we combined five state-of-the-art models from physics,economy,and epidemiology to track the anthropogenic fine particle matters(PM_(2.5))related premature mortality along the supply chains within China in 2017.Our results highlight the key sectors that affect PM_(2.5)-related mortality from both production and consumption perspectives.The consumption-based effects from food,light industry,equipment,construction,and services sectors,caused 2e22 times higher deaths than those from a production perspective and totally contributed 63%of the national total.From a cross-boundary perspective,25.7%of China's PM_(2.5)-related deaths were caused by interprovincial trade,with the largest transfer occurring from the central and northern regions to well-developed east coast provinces.Capital investment dominated the cross-boundary effect(56%of the total)by involving substantial equipment and construction products,which greatly rely on product exports from regions with specific resources.This supply chain-based analysis provides a comprehensive quantification and may inform more effective joint-control efforts among associated regions and sectors from a health risk perspective.

Knowledge-guided machine learning reveals pivotal drivers for gasto-particle conversion of atmospheric nitrate

Particulate nitrate,a key component of fine particles,forms through the intricate gas-to-particle conversion process.This process is regulated by the gas-to-particle conversion coefficient of nitrate(ε(NO_(3)^(-))).The mechanism betweenε(NO_(3)^(-))and its drivers is highly complex and nonlinear,and can be characterized by machine learning methods.However,conventional machine learning often yields results that lack clear physical meaning and may even contradict established physical/chemical mechanisms due to the influence of ambient factors.It urgently needs an alternative approach that possesses transparent physical interpretations and provides deeper insights into the impact ofε(NO_(3)^(-)).Here we introduce a supervised machine learning approachdthe multilevel nested random forest guided by theory approaches.Our approach robustly identifies NH4 t,SO_(4)^(2-),and temperature as pivotal drivers forε(NO_(3)^(-)).Notably,substantial disparities exist between the outcomes of traditional random forest analysis and the anticipated actual results.Furthermore,our approach underscores the significance of NH4 t during both daytime(30%)and nighttime(40%)periods,while appropriately downplaying the influence of some less relevant drivers in comparison to conventional random forest analysis.This research underscores the transformative potential of integrating domain knowledge with machine learning in atmospheric studies.

Water temperature governs organophosphate ester dynamics in the aquatic food chain of Poyang Lake

Organophosphate esters(OPEs)are increasingly recognized as pervasive environmental contaminants,primarily from their extensive application in flame retardants and plasticizers.Despite their widespread presence,the intricacies of OPE bioaccumulation within aquatic ecosystems remain poorly understood,particularly the environmental determinants influencing their distribution and the bioaccumulation dynamics across aquatic food chains.Here we show that water temperature plays a crucial role in modulating the dispersion of OPE in the aquatic environment of Poyang Lake.We quantified OPE concentrations across various matrices,uncovering levels ranging from 0.198 to 912.622 ng L^(-1) in water,0.013e493.36 ng per g dry weight(dw)in sediment,0.026e41.92 ng per g wet weight(ww)in plankton,0.13e2100.72 ng per g dw in benthic invertebrates,and 0.31e3956.49 ng per g dw in wild fish,highlighting a pronounced bioaccumulation gradient.Notably,the intestines emerged as the principal site for OPE absorption,displaying the highest concentrations among the seven tissues examined.Among the various OPEs,tris(chloroethyl)phosphate was distinguished by its significant bioaccumulation potential within the aquatic food web,suggesting a need for heightened scrutiny.The propensity for OPE accumulation was markedly higher in benthic invertebrates than wild fish,indicating a differential vulnerability within aquatic biota.This study lays a foundational basis for the risk assessment of OPEs as emerging contaminants and underscores the imperative to prioritize the examination of bioaccumulation effects,particularly in benthic invertebrates,to inform future environmental safeguarding strategies.

Land use and river-lake connectivity: Biodiversity determinants of lake ecosystems

Lake ecosystems confront escalating challenges to their stability and resilience,most intuitively leading to biodiversity loss,necessitating effective preservation strategies to safeguard aquatic environments.However,the complexity of ecological processes governing lake biodiversity under multi-stressor interactions remains an ongoing concern,primarily due to insufficient long-term bioindicator data,particularly concerning macroinvertebrate biodiversity.Here we utilize a unique,continuous,and in situ biomonitoring dataset spanning from 2011 to 2019 to investigate the spatio-temporal variation of macroinvertebrate communities.We assess the impact of four crucial environmental parameters on Lake Dongting and Lake Taihu,i.e.,water quality,hydrology,climate change,and land use.These two systems are representative of lakes with Yangtze-connected and disconnected subtropical floodplains in China.We find an alarming trend of declining taxonomic and functional diversities among macroinvertebrate communities despite improvements in water quality.Primary contributing factors to this decline include persistent anthropogenic pressures,particularly alterations in human land use around the lakes,including intensified nutrient loads and reduced habitat heterogeneity.Notably,river-lake connectivity is pivotal in shaping differential responses to multiple stressors.Our results highlight a strong correlation between biodiversity alterations and land use within a 2e5 km radius and 0.05e2.5 km from the shorelines of Lakes Dongting and Taihu,respectively.These findings highlight the importance of implementing land buffer zones with specific spatial scales to enhance taxonomic and functional diversity,securing essential ecosystem services and enhancing the resilience of crucial lake ecosystems.

Emission factors, ozone and secondary organic aerosol formation potential of volatile organic compounds emitted from industrial biomass boilers

To evaluate the potential benefits of biomass use for air pollution control, this paper identified and quantified the emissions of major reactive organic compounds anticipated from biomass-fired industrial boilers. Wood pellets(WP) and straw pellets(SP) were burned to determine the volatile organic compound emission profiles for each biomass-boiler combination. More than 100 types of volatile organic compounds(VOCs) were measured from the two biomass boilers. The measured VOC species included alkanes, alkenes and acetylenes, aromatics, halocarbons and carbonyls. A single coal-fired boiler(CB) was also studied to provide a basis for comparison. Biomass boiler 1(BB1) emitted relatively high proportions of alkanes(28.9%–38.1% by mass) and alkenes and acetylenes(23.4%–40.8%),while biomass boiler 2(BB2) emitted relatively high proportions of aromatics(27.9%–29.2%)and oxygenated VOCs(33.0%–44.8%). The total VOC(TVOC) emission factors from BB1(128.59–146.16 mg/kg) were higher than those from BB2(41.26–85.29 mg/kg). The total ozone formation potential(OFP) ranged from 6.26 to 81.75 mg/m^3 with an average of 33.66 mg/m^3 for the two biomass boilers. The total secondary organic aerosol potential(SOAP) ranged from 61.56 to 211.67 mg/m^3 with an average of 142.27 mg/m^3 for the two biomass boilers.The emission factors(EFs) of TVOCs from biomass boilers in this study were similar to those for industrial coal-fired boilers with the same thermal power. These data can supplement existing VOC emission factors for biomass combustion and thus enrich the VOC emission inventory.