Abstract:The adverse effects of endocrinedisrupting compounds（EDCs） in wastewater on ecosystems have garnered great concerns， necessitating stricter management to mitigate downstream ecological risks. The identification of EDCs in wastewater is a prerequisite for risk assessment and control. However， the current methods for addressing this issue are not well-established. This article presents a comprehensive overview of two strategies for EDC identification： a top-down approach that starts with compound structure identification and proceeds to evaluate their endocrine-disrupting effects， and a bottom-up approach that begins with effect-directed analysis and then determines the structure of compounds. For the top-down strategy， screening methods for suspected compounds and non-targeted screening techniques are the primary means to identify unknown compounds. Building a list of suspects is crucial， and the integration of various non-targeted screening software aids in recognizing unidentified compounds in environmental samples. The bottomup approach relies on effectdirected analysis， which is a mature and widely used method. Recently， machine learning algorithms have advanced to directly predict EDC activity classifications from environmental sample mass spectrometry data， streamlining the effectdirected analysis processes. The present review provides a reference for the comprehensive identification of EDCs in wastewater， which is beneficial to effective control EDCs in wastewater.

Abstract:Environmental endocrine disruptors（EDCs）， also known as environmental hormones， exhibit structures and effects similar to natural hormones， potentially disrupting the endocrine systems of organisms and posing significant health risks to both humans and animals.This paper focuses on the microbial degradationof typical phenolic EDCs， specifically alkylphenols（APs）， bisphenols（BPs）， and chlorophenols（CPs）. Effective degrading bacteria and fungi have been identified in contaminated soils， rivers， sediments， and activated sludge. These microorganisms hold great potential for bioremediation of polluted soils and water bodies， as well as for the removal of phenolic EDCs from wastewater. This paper systematically reviews the degrading microbes and their metabolic pathways under both aerobic and anaerobic conditions. It summarizes the degrading enzymes and functional genes involved， including monooxygenases and hydroxylases for hydroxylation， dioxygenases for ring cleavage， and reductive dehalogenases for reductive dechlorination. The aim is to provide a scientific basis for the innovation of microbial methods aimed at the efficient reduction of phenolic EDCs.

Abstract:Environmental microorganisms are the primary decomposers in the environment and play a pivotal role in the degradation of malachite green. The lack of costeffective alternatives has resulted in the continued release of malachite green into the environment. Consequently， there has been considerable attention paid to its environmental distribution and potential effects on human health. This paper presents a review of the malachite green-degrading bacteria and fungi， including an examination of their optimal degradation conditions， degradation pathways， and degradation enzymes. Furthermore， it provides an overview of the current developments in malachite green degradation through immobilization and omics studies. Finally， it identifies potential future research directions in the field of microbial malachite green degradation. This review offers a rapid and comprehensive understanding of recent research progress in microbial malachite green degradation， providing valuable scientific arguments for further mechanistic studies and technological applications.

Abstract:To investigate the characteristics， sources， and ecological risks of polycyclic aromatic hydrocarbons（PAHs） in the soil of the Xiaoqing River Basin in Shandong Province， 30 soil samples along the river were collected in June to July， 2021. The content of 16 priority-controlled PAHs was determined using gas chromatography-mass spectrometry（GC-MS）. The sources of PAHs were analyzed through characteristic composition ratio method and principal component analysis method， and risk quotient method was used for ecological risk assessment. The results showed that all 16 PAHs were detected in all samples， total concentrations ranged from 59.07 to 800.86 ng/g， with an average of 194.64 ng/g. High-ring PAHs dominated the composition， with an average proportion of high-ring（45.70%）>medium-ring（30.24%）>low-ring（24.06%）. Fossil fuel， coal， and biomass combustion were the main contributors to PAHs in the samples. Seven carcinogenic PAHs were the primary sources of ecological risk， with BaP and DBA contributing the most. Compared to other studies， the ecological risk of PAHs in the soil of the study area was relatively low， but some individual sampling points showed heavier contamination. More attention should be paid to potential ecological risk due to the reorientation plan on Xiaoqing River.

Abstract:Based on the monthly monitoring data of gross β activity concentration of aerosol around Fuqing nuclear power plant from May 2015 to December 2022， the correlation between monitoring points and between monitoring points and control points was discussed by statistical Spearman rank correlation coefficient method. The relationship between gross β and rainfall was analyzed by linear regression method. The monitoring value of gross β activity concentration was negatively correlated with rainfall， and there was no obvious seasonality. The gross β radioactivity levels in aerosols around PWR nuclear power plants in China and the United States were investigated and compared. The application of integrated moving average autoregressive model（ARIMA） in the analysis and prediction of gross β activity concentration in aerosol aroundnuclear power plant was discussed. The prediction model ARIMA（2，1，1）（0，1，1） suitable for the prediction of gross β activity concentration in aerosol around Fuqing nuclear power plant was established and optimized， which will be helpful for the prediction and early warning of gross β activity concentration in aerosol around Fuqing nuclear power plant.

Abstract:Based on the PM_2.5 and O₃ monitoring data and NCEP-FNL data（i.e geopotential height and u、v wind at 925 hPa） in the fall and winter（i.e.， January， February， November， and December） and the warm season（i.e.，April-October） in the centraleastern region of China from 2014 to 2019， typical atmospheric circulation types（CTs） were recognized via Tmode PCA classification method. The results showed that during the research period， seventeen CTs affected air quality in the Yangtze River Delta region （YRD region）， and the CTs that were prone to the occurrence of PM_2.5 and O₃ pollution were furtherly identified. High PM_2.5 concentration in autumn and winter（i.e.， January， February， November， and December） were usually related to cold front（AW_CT2） and High Pressure Moving to Sea（AW_CT3 and AW_CT5） weather system. Atmospheric circulation conditions may be conductive for upstream pollutant transport for AW_CT2 and local accumulation for AW_CT3 and AW_CT5 respectively. While high ozone concentration in warm season（i.e.， from April to October） were associated to subtropical high control（Spring_CT1 and Summer_CT1） and uniform pressure field（Summer_CT3 and Autumn_CT2）， but there may be differences in the impacts of meteorological characteristics and photochemical processes for O₃ pollution. The O₃ polluted days and MDA8 O₃ concentrations in the five cities of the YRD region were higher than those controlled by other CTs in the same seasons. Moreover， double high pollution was frequently occurred in Shanghai， Hangzhou and Nanjing under subtropical high control and uniform pressure field.

Abstract:In order to investigate the current pollution levels， sources， health risks and trends of heavy metals in atmospheric PM_2.5 in Urumqi， continuous monitoring of heavy metals in PM_2.5 in four seasons in a typical representative area of Urumqi was conducted to analyse the pollution characteristics， sources and health risks of heavy metals in PM_2.5 . The results show that the annual average value of PM_2.5 in 2020 exceeded the class II limit value of 35 μg/m³ set by China’s Ambient Air Quality Standard（GB3095—2012）. The concentration of each element was the highest in winter and the lowest in summer. Cu， Cr， Zn， Mn were the most abundant elements in PM_2.5. The total content of heavy metals in the monitoring points of #1（traffic road area）， #2（industrial concentration area）， and #3（agricultural area） accounted for 1.57%， 2.48%， and 0.68% of the mass concentration of PM_2.5， respectively， i.e.， the heavy metal content in PM_2.5 in the three monitoring points ranged in descending order as 2# monitoring point>1# monitoring point>3# monitoring point. The ILCR of Cr is>10^-4， which shows a carcinogenic risk for the whole group of people. The ILCR of Cd is in the range of 10^-6~10^-4， indicating acceptable levels， and the carcinogenic risk is negligible. The HQs of Mn and Cr are both>1， showing noncarcinogenic risk. The HQs of the 7 heavy metals range as children>male adults>female adults， with all values less than 1， the non-carcinogenic risk is low and negligible.

Abstract:An improved YOLOv5s algorithm of smoky vehicle detection has been established to address the issue of low resolution and too small target to test. Firstly， the smoke vehicle dataset is constructed using public network data and real road photography to solve the problem of a limited dataset. Secondly， the introduction of Coordinate has further optimized the model. In addition， the paper introduces Coordinate and improves the regression loss function of the bounding box into GIOU to improve the location precision of the bounding box. Experiments show that the proposed model is effective in detecting small targets over a long distance， and it can solve the problem of false negative and false alarm. A comparison with the original YOLOv5s model reveals an increase of 3.1% in the average detection accuracy（mAP） and a 4.9% enhancement in the detection accuracy of the black smoke category（AP）， the model exhibits strong generalization ability in small target scenarios.

Abstract:Cyclic volatile methylsiloxanes（cVMSs） are highly volatile， making their monitoring subject to high background interference， which affects data accuracy. By comprehensively optimizing factors such as injection septum， injection bottle insert， and sample preservation methods， the optimal pretreatment conditions were determined. An analytical method for detecting trace amounts of octamethylcyclotetrasiloxane（D4）， decamethylcyclopentasiloxane（D5）， and dodecamethylcyclohexasiloxane（D6） in water using gas chromatography–mass spectrometry（GC–MS） was established and applied to the detection of D4， D5， and D6 concentrations in actual domestic wastewater. The results showed that the method detection limits ranged from 1.43 to 3.14 ng/L， with average recoveries of 92.2% to 110.6% and 75.1% to 91.2% at spiked concentrations of 5 and 0.5 μg/L， respectively. The detection results for actual domestic wastewater indicated that the average concentrations of D5 and D6 in influent were 1 071 and 524 ng/L， respectively， with D4 not detected； D4， D5， and D6 were not detected in any effluent samples. The sample pretreatment and GC-MS detection method is simple and can significantly reduce background interference， providing a reference method for the detection and analysis of cVMSs in wastewater and supporting decisionmaking for environmental regulatory agencies.

Abstract:To evaluate the comprehensibility of monitoring data obtained from different standard analysis methods in the environmental and agricultural fields during soil monitoring，this study used multiple statistical methods to analyze the equivalence of standard analysis methods used for 11 monitoring indicators，including soil pH value，organic matter，cation exchange capacity，copper，zinc，lead，nickel，cadmium，chromium，mercury，and arsenic. The comparison results of technical specifications show that in the fields of environment and agriculture，the technical specifications used in the sampling，preservation，and preparation of soil samples have little impact on the analysis results. The results of method performance indicators show that there is no significant difference in precision between the two types of standard analysis methods. The significance test results show that except for pH value and mercury，there are significant differences in the other 9 indicators. When the equivalence boundary is ±20%，the results of equivalence evaluation show that the two standard analysis method sets for measuring pH value，organic matter，cation exchange capacity，copper，zinc，nickel，mercury，and arsenic are equivalent，and the monitoring data obtained can be shared. The performance evaluation and significance testing of methods cannot quantitatively determine the range of differences between method sets，while the double unilateral test compensates for this deficiency and avoids misjudgment of significance caused by insufficient sample size or high precision. Therefore，the evaluation results of this study can be used to integrate and manage the soil environmental quality monitoring network in the environmental and agricultural fields，which can achieve a more comprehensive understanding of the pollution status of agricultural soil environment.

Abstract:This paper introduces a set of highly sensitive system based on portable cantilever beam microphone photoacoustic spectroscopy to monitor the concentration of greenhouse gases in the atmospheric environment. The pulsed infrared light source is used to form multiple spectral bands in the midinfrared region through a narrowband optical filter. Combined with the optical cantilever beam microphone technology， it has ultrahigh sensitivity and can remove background gas interference to achieve simultaneous monitoring of multiple gases. By measuring the concentrations of greenhouse gases， it was verified that the method detection limit of CH₄ is 0.226×10^-6， and the method detection limit of CO₂ is 2.624×10^-6. The detection limits of other greenhouse gases were as low as CF₄ （0.052×10^-6） and as high as NF₃（0.164×10^-6）. The long-term repeatability was verified， with 1 time the standard deviation of CO₂ being 0.405 5 and the maximum drift being 1.775 6×10^-6； 1 time the standard deviation of CH₄ being 9.162 0 and the maximum drift being 36.261 1×10^-9. It was verified that the maximum indication deviation of the instrument for CO₂ is -0.04×10^-6， and for CH₄ is 1.48×10^-9. The relative standard deviations of greenhouse gases are all <2%； the average response time of CO₂ and CH₄ is verified to be 2 min 40 s； the R² of CO₂ and CH₄ is verified to be>0.999 9， the CO₂ fitting residual is within ±0.05×10^-6， and the CH₄ fitting residual is within ±1×10^-6.

Abstract:Taking 12 water quality monitoring sections of the eastern route of the South-to-North Water Diversion Project as the research object， according to the monitoring results of 9 indexes such as dissolved oxygen， permanganate index， ammonia nitrogen， total phosphorus， heavy metals（copper， zinc， lead and cadmium） and fecal coliform group， four water quality evaluation methods such as single factor evaluation method， Nemero index method， comprehensive water quality identification index method and fuzzy comprehensive matrix evaluation method are used to evaluate and analyze the water quality of 12 sections. The results show that the water quality of 12 sections is good. The water quality of Laoshan Township section（Lake and reservoir） is identified as class V using the single factor evaluation method， and the main exceeding factor is total phosphorus. The water quality of other sections was evaluated as Class III or Class II using either of the four methods. Compared with the other three methods， the single-factor evaluation method is simple to calculate， and the water quality category obtained is the worst overall due to its strict assessment standard. In the specific application practice， a more appropriate evaluation method should be adopted according to the evaluation purpose and section function， so as to provide a more objective basis for the environmental management of the South-to-North Water Diversion.

Abstract:As a typical subtropical oligotrophic reservoir， Xinfengjiang Reservoir is an important drinking water source for Guangdong-HongKong-Macao Greater Bay Area. Dissolved oxygen(DO) is usually considered as the only key indicator that determines the water quality type of Xinfengjiang Reservoir. To understand the monthly and seasonal variation characteristics of DO and its influencing factors， five approaches including continuous wavelet transform(CWT)， cross wavelet transform(XWT)， maximum information coefficient(MIC)， correlation coefficient(CC) and multiple linear regression(MLR) were applied based on five consecutive years data obtained from Apr. 2018 to Nov. 2022. The results showed that DO monthly concentration were between 6.94 mg/L and 9.48 mg/L and all met class Ⅰ or class Ⅱ set by the “Surface Water Environmental Quality Standard” GB 3838—2002). The DO changed in a cycle of 11~12 months and 35~37 months from 2018 to 2022 a V-shaped change presented on temporal distribution， and the low DO values appeared in September or October. The DO spatial variation was small and all met class Ⅰ set by the “Surface Water Environmental Quality Standard”(GB 3838—2002). The annual average concentration of DO was between 7.95 mg/L and 8.16 mg/L at six stations， the difference of maximum and minimum value was only 0.2 mg/L. DO concentration gradually decreased from upstream to downstream. MIC， XWT， CC and MLR analysis between DO and environmental factors showed that DO were subjected to a comprehensive influence of multiple factors， among them， water temperature was the key factor affecting DO， followed by pH value. The present study has great significance for further understanding the impacts and mechanisms of DO change in oligotrophic reservoir.

Abstract:The landform types in the central urban area of Zhengzhou are divided into Yellow River alluvial plain， mountain front alluvial plain， and loess hills. Different landform types have different hydrogeological characteristics. Based on the distribution characteristics of three landform types and their pollution sources， groundwater sampling points are set up to study the relationship between the “three nitrogen” content in shallow groundwater and the distribution of pollution sources， the depth of groundwater level， the lithology of the aeration zone， and the hydrochemical environment. The results show that the groundwater quality in the central urban area of Zhengzhou is greatly affected by the content of nitrate nitrogen and ammonia nitrogen， and is less affected by the content of nitrite nitrogen. The range of nitrate nitrogen content exceeding the standard in 2023 has significantly decreased compared to 2020， and there has been a local increase in ammonia nitrogen content. The changes in “three nitrogen” content， especially ammonia nitrogen content， in the Yellow River alluvial plain area should be taken seriously. The changes in the acidbase and redox environments of groundwater can to some extent cause changes in the “three nitrogen” content in groundwater. When groundwater is in an oxidizing environment， the nitrate nitrogen content in groundwater increases while the ammonia nitrogen content decreases.

Abstract:In this study， the hourly meteorological data， PM_2.5 and components data in Suzhou city during the Spring Festival in Suzhou in 2022（January 31 to February 6） were used to analyze the impacts of firework consumption on PM_2.5 and its components. The results showed： the average concentration of sulfate ion（SO₄^2-）， chloride ion（Cl^-）， potassium ion（K⁺）， magnesium ion（Mg²⁺）， organic carbon（OC）and elemental carbon（EC） have a large rising during the centralized discharge of fireworks， and increased by 90.6%，783.3%，350.0%，371.4%，137.5% and 150.0%， respectively， compared with the non-centralized fire period. The significant increase in concentration were Barium（Ba）， copper（Cu）， chromium（Cr）， potassium（K）， lead（Pb）， tin（Sn）， manganese（Mn）， antimony（Sb）， silicon（Si）， zinc（Zn）， iron（Fe）， arsenic（As）， gallium（Ga）（in descending order of increase）， the peak concentration of Ba⁺ which is one of the fireworks feature ion were more than 34.9 times during the centralized discharge of fireworks compared with the non-centralized fire period. And the peak concentration of other characteristic ions were more than 8 times that of non-concentrated discharge period. The centralized discharge of fireworks increases the concentration of gaseous pollutants significantly and two pollution peaks were formed on New Year‘s Eve and the day of the God of Wealth. The ratio method（M/CO） was used for quantitative evaluation and the result showed that the contribution rate of PM_2.5 was 50.4% in urban area of Suzhou， which was significantly lower than that of the counties under the jurisdiction of Suzhou. It shows that the ban on setting off fireworks has a certain effect. The variation characteristics of water-soluble ions concentrations and OC concentrations and fireworks feature heavy metals concentrations and were consistent with PM_2.5 concentrations. The results of online source profiles analysis also showed that the air quality in Suzhou during the Spring Festival was affected by centralized discharge of fireworks significantly.

Abstract:Based on the hourly concentration data of various pollutants during the Spring Festival in Yongzhou City from 2018 to 2022， this study further analyzed the impact of fireworks on ambient air quality through concentration analysis， component analysis， correlation analysis and relative ratio analysis. The results showed that the pollution weather during the Spring Festival in Yongzhou City from 2018 to 2022 was mainly concentrated on the New Year’s Eve and the first day of the year. The rising time of pollutant concentration is consistent with fireworks setting off time. The hourly maximum concentration of PM_2.5 was as high as 184 μg/m³， with the highest increase of 1 410%. During the discharge period， K⁺， Mg²⁺， Ca²⁺and Cl^- plasma increased significantly， and were related to the high concentration of particulate matter. Among them， the maximum concentration of K⁺， a characteristic ion set off by fireworks and firecrackers， reached 21.6 μg/m³， which was about 7 times that of conventional clean weather. The results of relative ratio analysis showed that the contribution of fireworks and firecrackers to the increase of particulate matter concentration is greater， and the contribution of fireworks and firecrackers to PM_2.5 and PM₁₀ concentration during the concentrated discharge period in 2022 was 6.2%~52.7% and 0.9%~52.0%， respectively. The concentration of particulate matter contributed by fireworks and the measured concentration showed a high consistency in the hourly variation trend， and the fireworks and firecrackers display was the main reason affecting the air quality in Yongzhou during the Spring Festival.

Abstract:This paper takes a modern business park in Northern China as an example to conduct a carbon peak study. Firstly，the energy consumption and carbon emissions of the park from 2018 to 2022 are sorted out. Then LMDI method was used to study the contribution of each driving factor to carbon emission. Based on LEAP model，the carbon emission of the park is predicted and the emission reduction potential of the park is explored. The results show that：at present，the carbon emission of the park is still in the growth stage，and the energy consumption and carbon emission of the park is dominated by business. The expansion of economic scale and the increase of population density continue to promote the increase of carbon emissions，while energy intensity and energy structure are the leading factors to promote the emission reduction. Under the enhanced emission reduction scenario，time to peak will be on time in 2030，and then carbon emissions will begin to decline and gradually become carbon neutral. In the future，the park will reach carbon peak on schedule by constructing a hybrid low-carbon micro-network and low-carbon smart buildings，and strengthening the optimal allocation of flexible resources.

Abstract:Under the background of Chinas peak carbon emissions and carbon neutrality goals， based on the data of 30 provinces in China from 2018 to 2021， this paper used the method given by the Intergovernmental Panel on Climate Change（IPCC） to calculate carbon emissions using energy consumption data and emission factors， analyzed the spatiotemporal evolutionary characteristics of China‘s carbon dioxide（CO₂ ） emissions， and used the emission reduction synergy effect quantitative evaluation method to evaluate the synergistic effects of pollution reduction and carbon reduction in various provinces and cities. The results show that： China's total carbon emissions are increasing year by year， but the growth rate has begun to slow down since 2021； A highvalue carbon emission area centered on North China and South China has been formed， roughly showing a “low in the south and high in the north” pattern， the carbon emissions and growth rates in most provinces and cities are still increasing； About 70% of the provinces and cities have not yet formed a synergistic effect between carbon emissions and air pollution/air quality， and local governments should strengthen the control of carbon emissions. Therefore， it is recommended that all provinces and cities in China improve the utilization rate of clean energy， develop low-carbon technologies according to local conditions， so as to reduce carbon emissions and achieve synergy in pollution reduction and carbon reduction.