Identifying Key Environmental Factors Influencing Spatial Variation of Water Quality in Upper Shitoukoumen Reservoir Basin in Jilin Province,China

Based on the observed data in monitored drainage areas and GIS spatial analysis tools,watershed basic database of Shitoukoumen Reservoir Basin was built.The multivariate analysis and redundancy analysis(RDA) were used to analyze the spatial and temporal variations of water quality,identify the key environmental factors and their patterns influencing the spatial variation of water quality,and determine the main types and forms of the non-point source(NPS) pollutant export controlled by the key environmental factors.The results show that different patterns of environmental factors lead to great changes in water quality at spatial and seasonal scales.All selected environmental factors explain 64.5% and 68.2% of the spatial variation of water quality over dry season and rainy season,respectively,which shows clear seasonal difference.Over dry season,residential land is the most important environmental factor,which possesses 35.4% of the spatial variation,and drainage area is the second key environmental factor,which possesses 17.0% of spatial variation in the total variance.Over rainy season,slope length and drainage area are the key environmental factors,which possess 29.3% of the spatial variation together.Residential land influences nitrogen export by changing NH4+-N and particulate organic nitrogen(PON) discharge over dry season,and drainage area controls phosphorus export by regulating dissolved phosphorus(DP) drainage over dry season and phosphorus associated particulate(PAP) loss over rainy season,respectively.Although slope length is an important environmental factor,it does not influence NPS pollutant export.It is interesting that soil organic matter,as a minor environmental factor,highly determines phosphorus and nitrogen export by enhancing the DP,PAP and PON loss.

State Key Laboratory of Environmental Aquatic Chemistry (SKLEAC) is under construction

A new State Key Laboratory named Environmental Aquatic Chemistry is establishing in the Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. It asso-ciates with other three Iaboratories in universities to make up an Joint State Key Laboratory of Environmental Simulation and Pollution Control. They are supported by Chinese Government with the loan from World Bank for about 2.5 million US dollars and the same amount of RMB.

Impacts of Environmental Factors on the Structure Characteristics of Avian Community in Shanghai Woodlots in Spring

From March to May, 2004, we selected 8 typical parks or green lands in Shanghai downtown as the study sites to conduct a ornithological research. During this study, total 55 species of birds were recorded, which included 31 resident and 24 migratory species. With statistics methodology, we analyzed the avian communities with 10 major environmental factors covering the park area, water percentage, vegetation species, canopy cover, shrub cover, grass cover, hill number, location condition, human quantity, path width, the study results indicated that: (1) the following 7 environmental factors were important to impact the structures of the avian community, they were park area, vegetation species, shrub coverage, grass coverage, hill number, location condition of the parks and path width; (2) the avian community of theses urban parks tended to deteriorate in the bird number and diversity; the man-made lake which was currently promoted in the park designing and planning process would not be good to attract the birds.

Identifying Summer/Autumn Habitat Hotspots of Jumbo Flying Squid (Dosidicus gigas) off Chile

Abundance and distribution of jumbo flying squid(Dosidicus gigas)are evidently influenced by the changes of marine environment.In this study,the maximum entropy(MaxEnt)model was applied to examine the impacts of marine environmental variables on its potential distribution,and identified habitat hotspots of D.gigas in summer and autumn along the coast of Chile.The MaxEnt model was constructed by using the fisheries data of D.gigas from summer to autumn during 2011–2017 combined with critical environmental factors including mixed layer depth(MLD),sea surface salinity(SSS),sea surface height(SSH)and water temperature at depths of 0 m,25 m,50 m,100 m,150 m,200 m,300 m,400 m and 500 m.Results showed that the actual fishing efforts of D.gigas in summer and autumn were mostly distributed in the suitable habitat,indicating that the MaxEnt model can well predict the habitat hotspots of D.gigas off Chile.The key environmental factors and their suitable ranges for D.gigas showed significant intermonthly changes from December to May.The critical environmental factors of D.gigas off Chile were MLD,SSH,water temperature at different depths in summer(Temp_25 m in December,Temp_300 m in January and Temp_400 m in February)and SSH,SSS,Temp_400 m in autumn.Our findings suggest that selecting the key environmental factors is vital to study the potential distribution of D.gigas off Chile in each month to explore its habitat hotspots.

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.