Abstract:This study investigated pollution source of abnormal influent of a wastewater treatment plant（treatment capacity of 60 000 t/d） in a southern town with the help of the pollution discharge source identification technology based on aqueous fluorescence fingerprint. The comparison results of the aqueous fluorescence fingerprint indicated that the suspected source of the abnormal influent was plastic/rubber industry and the abnormal influent was from underground pipes（P1） of the 10# location in the sewage pipe network， where the chemical oxygen demand of the water sample was 772 mg/L， being higher than the Class III of the Integrated Wastewater Discharge Standard（GB 8978—1996） by 0.54 times. Then， a plastic/rubber enterprise was identified as pollution source based on the high similarity（99%） of aqueous fluorescence fingerprint between the raw wastewater of the enterprise and the sewage from P1， and the high -chemical oxygen demand of the raw wastewater of 11 551 mg/L. Since the water quality of the wastewater from the enterprise’s legal sewage discharge outlet was better than the discharge standard， thus it was clear that the enterprise illegally discharged raw wastewater into the sewage pipe network. It took 5.5 hours to conduct the pollution source identification process. Due to the fast and precise identification， the pollution discharge was timely stopped to avoid further deterioration of influent’s water quality and treatment plant’s operation. This practical research demonstrated that the identification technology can achieve rapid and precise pollution source identification under strong disturbance of complex wastewater.

Abstract:This study developed a stereoscopic network monitoring system that integrates satellite-based remote sensing， unmanned aerial vehicle（UAV） observations， and ship-based surveys to monitor the water quality of Dianshan Lake. The spatial distribution of water quality parameters was monitored and analyzed. The results demonstrated the followings：（1） The constructed water quality inversion model achieved high precision， with root mean square errors（RMSE） of 0.019 1 mg/L（R²=0.64，P<0.001） for total phosphorus and 0.036 0 mg/L（R²=0.83，P<0.001） for total nitrogen concentrations.（2） Characteristics of spatial distribution of water quality： The total phosphorus and ammonia nitrogen in Dianshan Lake are higher in the northwest and lower in the central， eastern， and western regions; the Chlorophyll-a shows a spatial distribution characterized by higher levels in the north and east， lower levels in the south and west， and higher concentrations along the shores and lower in the center.（3） Trace analysis using a generalized linear mixing model revealed significant impacts from inflowing tributaries， motorized boats， farmland， and aquatic plants on the distribution patterns of total phosphorus， ammonia-nitrogen concentrations， and chlorophyll-a concentration， with inflowing tributaries having the most substantial influence. These research findings provide essential references and scientific foundations for stereoscopic network monitoring of the water environment in Shanghai.

Abstract:The Mao River Basin in the Pengshan District of Meishan， Sichuan Province was used as an example to analyse pollution traceability comprehensively and accurately. Based on the consideration of changes in hydrological conditions and the spatial distribution of pollution sources， a mathematical model of the basin water environment was established to analyse the weight of pollution sources during different periods by pollution contribution fluxes and equivalent pollution load ratios. The results indicate that：（1） Pollution from urban domestic sewage in the Mao River basin is the main contributor to chemical oxygen demand（COD） and ammonia nitrogen（NH₄⁺-N） river inflow， accounting for 52.14% and 50.74%， respectively. This pollution is mainly located in the old urban area of Pengshan. Farming is the main contributor to the amount of total phosphorus（TP） in the river， accounting for 51.32%， and is distributed in Tongji weir irrigation district and other pollution source areas. Industrial pollution sources contributed the least to the amount of COD， NH₄⁺-N and TP in the river， accounting for no more than 2%. The simulation results of a one-dimensional non-stationary model in the Mao River Basin showed that the percent biases（PBIAS） of COD， NH₄⁺-N and TP in each period were less than or equal to 25%， which was more consistent with the actual values.（3） During the overflow influence period， the pollution sources in Pengshan urban area have the greatest impact on the water quality of the Qiaojiangqiao section. The weights of water quality influence are 67.2% for COD， 67.3% for NH₄⁺-N， and 51.7% for TP， respectively. The pollution characteristics during the rainfall period and overflow influence period are similar. However， the dilution effect of heavy rainfall makes the water quality avoid exceeding the standard. During the irrigation recession period， the primary source of pollution is agricultural. The Tongji weir irrigation area contributes the most to the total pollution（37.6%） at the Qiaojiangqiao section.

Abstract:The high spatial resolution and short revisit cycle of Sentinel2 multispectral imager（MSI） data make it highly suitable for water quality inversion in small to mediumsized lakes like Gaoyou Lake. In this study， we fitted the Sentinel-2 MSI data with measured water spectra to establish models for chlorophyll-a concentration（Chl.a） and total suspended matter（TSM） concentration inversion in Gaoyou Lake. After verification， the root mean square error（RMSE） of Chla inversion was found to be 8.02 μg/L with a mean relative error（MRE） of 18.4%， while the RMSE of TSM concentration inversion was 16.2 mg/L with an MRE of 23.3%， indicating excellent accuracy of this model. By utilizing Sentinel-2 MSI satellite imagery along with this established inversion model， we can obtain spatiotemporal distributions of Chla and TSM concentration in Gaoyou Lake. Preliminary analysis revealed that these two water quality parameters are influenced by net farming activities and runoff into the lake.

Abstract:Cyanobacterial blooms rapidly degrade water quality， impacting aquatic ecosystem stability and drinking water safety. The accurate， rapid， and effective monitoring and early warning of cyanobacteria bloom are of utmost importance. To address this， our study selected a typical area in the northwest of Lake Taihu where Microcystis blooms occurred in 2020. Artificial intelligence techniques were used to analyze 501 samples collected from March to October， obtaining extensive statistical information on algal community structure and morphology. The research findings indicate the following：Microcystis spp. is the first dominant genus during the study period，accounting for 57% of the total； There is significant largescale periodicity within the Microcystis-genus， particularly evident in the succession of Microcystis species characterized by larger cell diameters and high-temperature resistance in the summer and autumn， such as Microcystis wesenbergii and Microcystis aeruginosa； A smaller periodicity in Microcystis cell density is observed， with a reproductive cycle of 2～5 days showing a distinct daily fluctuation pattern. By establishing accurate， rapid， and effective artificial intelligence-based monitoring techniques for algae， we can swiftly analyze algal community structure in water bodies and utilize big data mining to understand the succession and growth patterns of Microcystis . This is of great significance for the early warning of cyanobacterial bloom with higher precision.

Abstract:The component characteristics of PM_2.5 were analysed by online monitoring systems in the urban area of Suzhou—the typical city of the Yangtze River Delta from January to December in 2021. The results showed that the annual average of PM_2.5 was 28μg·m^-3， showing obvious order of winter＞spring>autumn >summer during the observation period. Overall， the most abundant component was organicmatter（OM， 28.3%）， followed by NO₃^-（23.0 %）， SO₄^2-（19.4 %）， NH₄⁺（15.6%）， EC（4.1%）， Ca²⁺（3.4%）， Cl^-（3.2%）， Na⁺（1.3%）， K⁺（0.9%） and Mg²⁺（0.7%）. On year-average， NO₃^- was the highest inorganic component in major PM_2.5 species， and the secondary inorganic ions including NH₄⁺， NO₃^- and SO₄^2-，accounted for more than 50%. Based on the research results above， an disease burden assessment was conducted with the Integrated Exposure Respone model（IER） and Global Exposure Mortality Model（GEMM）， mainly for the relative risk（RR） and the attributable fraction（AF） of the five diseases， such as chronic obstructive pulmonary disease（COPD）， lung cancer（LC）， Stroke， ischemic heart disease（IHD） and lower respiratory infection（LRI） attributed to long-term exposure to PM_2.5. Results showed the relative risks of the five diseases for the IER model were 1.14， 1.18， 1.39， 1.26 and 1.21， with the attributable fractions of 12.3%， 15.3%， 28.1%， 20.6% and 17.1%， respectively. The relative risks of the five diseases for the GEMM model were 1.31， 1.36， 1.30， 1.59 and 1.93， with the attributable fractions of 23.7%， 26.5%， 23.1%， 37.1% and 48.%， respectively. The evaluation results of the GEMM model were higher than that of the IER model（except for Stroke）.

Abstract:This paper established an onsite monitoring method for four odor substances（geosmin， 2-methylisoborneol， dimethyl disulfide， dimethyl trisulfid） in water by using portable solid phase microextraction-gas chromatography mass spectrometry（SPME-GCMS） combined with select ion storage（SIS） technology. Compared with the full scan（SCAN） or selected ion monitor（SIM） technology， SIS showed great sensitivity with highest signal to noise ratios， surpassing those in the SIM mode by 1.6~3.6 times. Under the established experimental conditions， the detection limit of the four odor substances was between 0.6 and 1.5 ng/L， with linear coefficients greater than 0.999 and relative standard deviations ranging from 3.7% to 8.1%. The recoveries from real surface water samples fell within the range of 82.4% to 97.8%. Monitoring on geosmin and 2-methylisoborneol in surface water sampled in CC River in Jiangsu Province between June and September in 2023 using this method unveiled concentration variations at different sampling locations. Consistent temporal trends in geosmin and 2-methylisoborneol concentrations were observed at each site， providing evidence of satisfactory monitoring efficacy. Pearson correlation coefficient analysis showed that there was no significant correlation between odor substance（geosmin， 2-methylisoborneol） concentrations and water quality parameters（water temperature， ammonia nitrogen， total phosphorus， total nitrogen， and turbidity）. This method is easy to operate and efficient， and is capable to achieve swift on-site monitoring of four odor compounds in water.

Abstract:In order to illustrate the main source and environmental behavior of organophosphate esters（OPEs） in the surface water of Jiangsu reach of the Yangtze River Basin， we collected the surface water samples from different receiving water， and further determined the distribution characteristics of 13 OPEs by ultra performance liquid chromatographymass spectrometry（UPLC-MS/MS）. Results showed that total concentrations of the 13 OPEs in the surface water of Jiangsu reach of the Yangtze River Basin ranged from 74.3 to 4 776 ng/L， with an average concentration of 354 ng/L. OPEs in main streams and drinking water sources were at the lowest concentration levels， followed by agricultural runoff， whereas tributaries had higher concentration of OPEs， and wastewater treatment plants had highest concentration of OPEs. In winter， the OPEs concentration of main streams， tributaries， drinking water sources， and wastewater treatment plants were lower than that in summer. Tris（2-chloropropyl） phosphate（TCPP）， Tris（2-chloroethyl） phosphate（TCEP）， and Triphenylphosphine oxide（TPPO） were the main OPEs pollutants in surface water. Wastewater treatment plants are the greatest source of OPEs to surface water.

Abstract:According to the water quality characteristics of groundwater containing perchloride and ferric ions in coastal area of the Pearl River Delta， the applicability of automatic monitoring for water quality parameters such as ammonia nitrogen， oxygen consumption（COD_Mn）， manganese and chloride in groundwater was verified by comparison the results of automatic instruments with manual methods. The results show that the monitoring results of ammonia nitrogen in groundwater by automatic instrument of distillation pretreatment and salicylic acid spectrophotometry are in good agreement with those of manual methods. The relative errors of phreatic wells are 2.15%~22.7%， and those of confined wells are 2.8%~9.45%. The monitoring results of oxygen consumption in phreatic water by automatic instrument using permanganate titration are in good agreement with those of manual method. The relative errors of phreatic wells are 9.17%~12.9%. The monitoring results of manganese in groundwater by automatic instrument using periodate titration are in good agreement with those of manual method. The relative errors of phreatic wells are 5.78%~23.2%， and those of confined wells are 8.94%~35.1%. The monitoring results of manganese in groundwater by automatic instrument uisng ion selective electrode method are in good agreement with those of manual method. The relative errors of phreatic wells are 3.01%~29.4%， and those of confined wells are 0.61%~9.95%. It can provide experience and reference for establishing a unified and standardized groundwater quality automatic monitoring technical system.

Abstract:The Yellow River estuary is one of the three major estuaries in China. Analyzing the contamination characteristics of halogenated compounds in the sediment environment of the region and discovering their unknown halogenated compounds can help to correctly assess the potential risk of such substances to the environment of the region. Fortysix marine surface sediments from the Yellow River estuary were collected in June 2021 to analyze the concentration composition and distribution characteristics of 32 polychlorinated biphenyls（PCBs）， 27 polybrominated diphenyl ethers（PBDEs）， and 16 emerging halogenated flame retardants（EHFRs） in the samples， and then based on the full two-dimensional gas chromatography-time-of-flight high-resolution mass spectrometry（GC×GC/HR-TOF/MS）， a non-targeted screening was carried out for the samples. Unknown halogenated compounds were non-targeted screened.The results showed that the ranges of ω（PCBs），ω（PBDEs） and ω（EHFRs） in the sediment were ND（not detected）～976.1 pg/g（dw）， ND～2，045.5 pg/g（dw） and ND～1，625.8 pg/g（dw）， respectively. PCBs were dominated by pentachlorobiphenyl（Penta-PCB）， trichlorobiphenyl（Tri-PCB） and tetrachlorobiphenyl（Tetra-PCB）； decabromodiphenyl ether（BDE-209） was the main pollutant of PBDEs and showed obvious regional differences， with the significance of the region to the south of the estuary higher than that in the northern region； among the EHFRs， the pollutants were anti Dechlorane Plus（anti-DP）， syn Dechlorane Plus（syn-DP）， pentabromotoluene（PBT）， pentabromobenzene（PBBz） and hexabromobenzene（HBBz）. Hexabromobenzene（HBBz） were the main detected contaminants， especially anti-DP and syn-DP were commonly detected in the sediments， and the ratio（anti） of anti-DP to total degron（ΣDP） was consistent with that of industrial products， indicating that DP was not degraded significantly in the sediments；Based on the GC×GC/HR-TOF/MS， 11 emerging halogenated compounds other than the target compounds were identified in the sediment samples， of which 8 were internal standard compounds added for quantitative analysis， and the chemical structures of the remaining 3 still need to be further analyzed and confirmed. The results of the environmental risk assessment indicate that PBDEs and DPs at most points do not pose a risk to the local environment； BDE-209 may pose a low to medium risk and should be emphasized. PCBs will not have an adverse impact on the ecological environment of the Yellow River estuary.

Abstract:Ammonia escape from industrial flue gas has been widely concerned under the background of ultra-low NO_X emission control. In order to investigate the current situation of ammonia escape and its impact on air quality， NH₃ emission monitoring was conducted in 7 industries in Jiangsu Province from March to June 2022， and the emission characteristics of condensable particulate matter（CPM）was tested in 4 production lines with serious ammonia escape. The results showed that the NH₃ emission concentration were between 0.7～65.4 mg/m³. Ammonia escape in thermoelectric and glass industries was prominent， the average concentration was 37.4 and 39.2 mg/m³， respectively. The NH₃ emission concentration from industrial flue gas using SNCR denitrification facilities was 1.4～2.4 times higher than that using SCR and SNCR+SCR technologies. The CPM concentration in production lines with serious ammonia escape reached 717～1 322 mg/m³， which offset the emissions reduction brought about by desulfurization， denitrification and dust removal and made a direct contribution to PM_2.5. The results can provide support for the source and control direction of secondary particulate matter in China.

Abstract:From November 2021 to September 2022， the atmospheric gaseous elemental mercury（GEM） concentrations in different regions of Urumqi had been monitoring for one week per quarter， meanwhile the surrounding coal-fired boilers were sampled， and the vertical distribution of pollutants in winter and summer in Urumqi was further explored by Lidar detection technology， and the temporal and spatial variation characteristics of atmospheric GEM concentrations in Urumqi were comprehensively analyzed. The results showed that the average concentrations of GEM in the atmosphere was 4.45±1.38 ng/m³， which was higher than the background concentrations in the Northern Hemisphere， and the atmospheric GEM concentrations in winter was higher than that in summer， with significant seasonal variation characteristics， and the diurnal variation characteristic showed that the GEM concentrations of the atmosphere in the night were higher than those in the daytime．In this paper， the atmospheric GEM concentrations in Urumqi were monitored for the first time， which provides scientific support for the furture control of atmospheric mercury in Urumqi.

Abstract:Based on NO₂ ground monitoring data and combined with the observation results of TROPOMI satellite， the characteristics of NO₂ pollution in Jiangsu Province during the covid-19 pandemic from 2020 to 2021 were analyzed. Using WRF-CMAQ-ISAM system model，the characteristics of NO₂ were analyzed. The results showed that： The NO₂ concentration in Jiangsu province was 29 μg/m³ in 2020 and 2021， showing a significant decrease of 21.6% compared with that in 2014—2019. However， autumn and winter（November-December） are still a difficult period for NO₂ control. TROPOMI satellite and ground observations showed that high NO₂ values in autumn and winter were concentrated in 8 cities along the Yangtze River. From November to December 2021， the number of days of NO₂ primary pollutants exceeded the same period in 2019， which showed that pollution by NO₂ as the primary pollutant in autumn and winter still rebounding. The WRF-CMAQ model indicated that both meteorological and anthropogenic factors in autumn and winter of 2021 jointly contributed to the increase in NO₂ concentration across Jiangsu Province. Compared with that in 2020， meteorological and human-related factors have increased the concentration of NO₂ by 3.1 and 0.9 μg/m³， respectively. In the 8 cities located along the Yangtze River， the anthropogenic influence on the NO₂ concentration is predominantly positive， ranging from -0.6 to 6.7 μg/m³. Conversely， in the 5 cities in northern Jiangsu， the anthropogenic impact is predominantly negative， with contribution values ranging from -4.6 to 1.7 μg/m³. The contribution results of different industries showed that the NO₂ sources were mainly road mobile sources， industrial sources and non-road mobile sources， accounting for 39.2%， 33.0% and 20.8% respectively， and ships and residential sources accounted for 3.5%.

Abstract:By analyzing the hourly observation data of ozone（O₃） near the ground in Xingtai from 2018 to 2022， the meteorological data and satellite remote sensing data of the same period， the characteristics of O₃ pollution near the ground in Xingtai and its relationship with meteorological factors， as well as the sensitivity of O₃ generation， were studied. The results indicated that the value of the 90th percentile of the daily maximum 8-hour O₃ mass concentration ［ρ（O₃-8h-90 per）］ in Xingtai fluctuated downward from 2018 to 2022， with an average annual decrease of 4.24 μg/m³. Seasonally， the annual average ρ（O₃） followed a trend of summer > spring > autumn > winter， peaking in June and reaching its nadir in December. The diurnal variation of ρ（O₃） showed an obvious ‘single peak’ structure， with the lowest values concentrated between 06：00 and 07：00 and peaking between 15：00 and 16：00. The hourly ρ（O₃） values were positively correlated with air temperature. When the temperature exceeded 20℃， the hourly O₃ exceedance rate increased rapidly with rising temperatures. The hourly O₃ exceedance rate peaked at 6.02% when the relative humidity ranged from 40% to 50%. Under a southeast wind， the hourly O₃ exceedance rate was the highest， followed by easterly and southerly winds. Satellite remote sensing data revealed that the annual mean tropospheric NO₂ column concentration in Xingtai decreased by 0.24×10^-5 mol/m²·a from April to September during 2019—2022， with a downward trend observed in urban areas， northern and southern transmission corridor counties， while an upward trend was noted in western and centraleastern regions. The tropospheric formaldehyde（HCHO） column concentration showed an overall downward trend， decreasing by 1.12×10^-5 mol/m² annually. In Xingtai， the volatile organic compounds（VOCs） control areas were primarily concentrated in urban areas， Shahe in the south and some areas of Neiqiu and Lincheng in the north， while other regions were designated as VOCs and nitrogen oxides（NO_X） collaborative control areas.

Abstract:Based on the observation data of air quality and meteorology， ERA5 reanalysis data， and online monitoring data of single particle aerosol mass spectrometer， this study analyzes the meteorological causes， sources， and chemical composition changes of PM_2.5 pollution in Shantou， Guangdong during the 2023 Spring Festival， discusses the impact of fireworks on air quality， and quantifies the contribution of fireworks during the Spring Festival period to PM_2.5 concentration in Shantou and various districts and counties using the random forest algorithm. The results show that the combination of fireworks and adverse meteorological conditions caused an overall increase in PM_2.5 concentration in Shantou during the 2023 Spring Festival， resulting in severe PM_2.5 pollution for three consecutive hours. PM_2.5 source apportionment analysis shows that fireworks have the largest contribution to PM_2.5during the Spring Festival period（35%）， followed by dust sources（14%）， mobile sources（12%）， and secondary inorganic sources（12%）. The concentration of characteristic ions during the concentrated burning period increased significantly， with an increase ranging from 3.5 to 39.3 times compared with nonconcentrated periods. The increase in the characteristic ion Ba⁺ was most significant during the concentrated burning period. The quantitative evaluation of the random forest model shows that the irregular human impact of PM_2.5 concentration， represented by fireworks during the 2023 Spring Festival， has increased significantly， with a contribution rate of 36.9% to PM_2.5 concentration. Compared with the eastern and northern regions of Shantou， the contribution of fireworks during the 2023 Spring Festival to the western and southern regions of Shantou is greater. In conclusion， it is recommended that Shantou continue to strengthen the regulation of fireworks during the Spring Festival， carry out inspections and rectification against illegal and irregular operations and use of fireworks， and scientifically divide the prohibited fireworks area and the concentrated burning area based on the degree of impact of fireworks on air quality in each district and county， in order to further improve the urban environment and air quality.

Abstract:This paper investigated the remote sensing ecological index（RSEI） over Urumqi from 2003 to 2022 based on MODIS remote sensing data and the Google Earth Engine（GEE） platform. Then， the Theil-Sen Median and Mann-Kendall methods were used to analyze spatio-temporal variations of RSEI. The results showed that：（1） The average RSEI of Urumqi from 2003 to 2022 was 0.37， suggesting a slightly lower level of overall environmental quality. The RSEI exhibited significant spatial differences， with a spatial trend of gradual decrease from south to north.（2） From 2003 to 2022， the overall RSEI of Urumqi showed a trend of increasing by 0.02 every 10 years. Specifically， the increasing trend occurred mainly in the period of 2003—2016， with a rate of 0.07 per 10 years.（3） During the period from 2003 to 2022， the RSEI of Urumqi exhibited a decrease in the southern region（southern edge of Urumqi County） and the eastern region（northeastern part of Dabancheng）， and an increase in the central and northern regions（Midong）. However， from 2016 to 2022， the RSEI showed a decreasing trend in the central and northern regions， calling for attention on improving the ecological environment in these areas in the future.