Disinfection Byproducts and Their Precursors in Drinking Water Sources:Origins,Influencing Factors,and Environmental Insights

Tracing the contamination origins in water sources and identifying the impacts of natural and human processes are essential for ecological safety and public health.However,current analysis approaches are not ideal,as they tend to be laborious,time-consuming,or technically difficult.Disinfection byproducts(DBPs)are a family of well-known secondary pollutants formed by the reactions of chemical disinfectants with DBP precursors during water disinfection treatment.Since DBP precursors have various origins(e.g.,natural,domestic,industrial,and agricultural sources),and since the formation of DBPs from different precursors in the presence of specific disinfectants is distinctive,we argue that DBPs and DBP precursors can serve as alternative indicators to assess the contamination in water sources and identify pollution origins.After providing a retrospective of the origins of DBPs and DBP precursors,as well as the specific formation patterns of DBPs from different precursors,this article presents an overview of the impacts of various natural and anthropogenic factors on DBPs and DBP precursors in drinking water sources.In practice,the DBPs(i.e.,their concentration and speciation)originally present in source water and the DBP precursors determined using DBP formation potential tests—in which water samples are dosed with a stoichiometric excess of specific disinfectants in order to maximize DBP formation under certain reaction conditions—can be considered as alternative metrics.When jointly used with other water quality parameters(e.g.,dissolved organic carbon,dissolved organic nitrogen,fluorescence,and molecular weight distribution)and specific contaminants of emerging concern(e.g.,certain pharmaceuticals and personal care products),DBPs and DBP precursors in drinking water sources can provide a more comprehensive picture of water pollution for better managing water resources and ensuring human health.

Spatiotemporal Characteristics of Typical Ecosystem Services and Their Spatial Responses to Driving Factors in Ecologically Fragile Areas in Upper Yellow River,China

The identification of dominant driving factors for different ecosystem services(ESs)is crucial for ecological conservation and sustainable development.However,the spatial heterogeneity of the dominant driving factors affecting various ESs has not been adequately elucidated,particularly in ecologically fragile regions.This study employed the integrated valuation of ESs and trade-offs(InVEST)model to evaluate four ESs,namely,water yield(WY),soil conservation(SC),habitat quality(HQ),and carbon storage(CS),and then to identify the dominant driving factors of spatiotemporal differentiation of ES and further to characterize the spatial heterogeneity characteristics of the dominant driving factors in the eco-fragile areas of the upper Yellow River,China from 2000 to 2020.The results demonstrated that WY exhibited northeast-high and northwest-low patterns in the upper Yellow River region,while high values of SC and CS were distributed in central forested areas and a high value of HQ was distributed in vast grassland areas.The CS,WY,and SC exhibited decreasing trends over time.The most critical factors affecting WY,SC,HQ,and CS were the actual evapotranspiration,precipitation,slope,and normalized difference vegetation index,respectively.In addition,the effects of different factors on various ESs exhibited spatial heterogeneity.These results could provide spatial decision support for eco-protection and rehabilitation in ecologically fragile areas.

Quantitative Analysis of Natural and Human Factors of Oasis Change in the Tail of Shiyang River over the Past 60 Years

The human and natural factors complicit in the driving forces of oasis change have always received considerable interest from the international research community. In this study, we used principal component analysis of natural and socio-economic statistical factors to quantitatively analyze the causal relationships and their contributions to the observed periodic expansion or shrinkage of the Minqin Oasis over almost 60 years. Our results show that human factors were the dominant factors governing expansion or shrinkage, with average contributions of 69.38% and 76.16%, respectively. Moreover, policy decisions have been the pivotal human factors. Under the influence of various policies, we have found that water resource utilization, land reclamation, population explosion, ecological protection and economic development have each played leading roles in different periods. This study provides a scientific basis for modelling the dynamics of an oasis for sustainable management.

A New Method to Predict Erythrocyte Sedimentation Rate with Natural Geographical Factors and Location by Case-based Reasoning: A Case Study of China

Reference values of erythrocyte sedimentation rate(ESR)are the key to interpret ESR blood test in clinic.The common local reference ESR values are more accuracy in blood test that are established with natural geographical factors by using the multiple linear regression(MLR)model and the artificial neural network(ANN).These knowledge-based methods have limitations since the knowledge domains of ESR and natural geographical factors are limited.This paper presents a new cases-depended model to establish reference ESR values with natural geographical factors and location using case-based reasoning(CBR)since knowledge domain of ESR and geographical factors is weak.Overall 224 local normal ESR values of China that calculated from 13623 samples were obtained,and the corresponding natural geographical factors and location that include altitude,sunshine hours,relative humidity,temperature,precipitation,annual temperature range and annual average wind speed were obtained from the National Geomatics Center of China.CBR was used to predict the unseen local reference ESR values with cases.The average absolute deviation(AAD),mean square error(MSE),prediction accuracy(PA),and Pearson correlation coefficient(r)between the observed and estimated data of proposed model is 33.07%,9.02,66.93% and 0.78,which are better than those of ANN and MLR model.The results show that the proposed model provides higher prediction accuracy than those of the artificial neural network and multiple linear regression models.The predicted values are very close to the observed values.Model results show significant agreement of cases data.Consequently,the model is used to predict the unseen local reference ESR with natural geographical factors and location.In spatial,the highest ESR reference areas are distributed in the southern-western district of China that includes Sichuan,Chongqing,Guangxi and Guizhou provinces,and the reference ESR values are greater than 23 mm/60 min.The higher ESR reference values are distributed in the middle part and northern-eastern of China which include Hubei,Henan,Shaanxi,Shanxi,Jilin and Heilongjiang provinces,and the reference ESR values are greater than 18 mm/60min.The lowest ESR reference values are distributed in the northern-western of China that includes Tibet and Xinjiang,and the reference ESR values are lower than 5 mm/60min.

Statistical Analysis of Influencing Factors of Temporal and Spatial Variation Patterns of Decadal Accumulative Heavy Rainfall in China

Daily precipitation analyses for 659 Chinese meteorological stations from 1951 to 2010 show that the rapid urbanization may have triggered the significant increase of heavy rainfall in China. During the last decades, HRAs （Heavy Rainfall Amounts）, HRDs （Heavy Rainfall Days） and HRI （Heavy Rainfall Intensity） in China have increased. Impressively, the upward trends are not randomly observed among stations, but of robust consistency with quite large regional scale over large widely and significantly. Compared to the 1950s, the HRA, HRD, and HRI increased by 68.71%, 60.15% and 11.52% during the 2000s. The significant increase of accumulative heavy rainfall appears firstly in the southeastern coasts in the early period, and then gradually expands to the central, southwest, north and northeast China. Rapid urbanization is very likely the main cause of large-scale heavy rainfall increase in China. The urbanization indicators including the industrial production output （GDP2）, UP （Urban Population） and annual average HDs （Haze Days） are in good agreement with the heavy rainfall variations, and these indicators can statistically explain the variance of HRA, HRD and HRI by 61.54%, 58.48% and 65.54%, respectively. Meanwhile, the explained variance by leading climate indices including WPSH （Western Pacific Subtropical High）, ENSO （El Nino-Southern Oscillation）, AMO （Atlantic Multi-decadal Oscillation） and AAO （Antarctic Oscillation） are respectively 24.30%, 26.23% and 21.92%, being only about 1/3 of the urbanization-related variance. Panel data analysis of county-level total population and annual average visibility days less than 10 km also show that these two indicators have significant correlation with decadal HRA, HRD ＆ HRI and the spatial correlation coefficient increases gradually with time. These consistent temporal and spatial features strongly suggest that rapid urbanization most likely triggered the steady increase of heavy rainfall over China during the recent decades.

Natural runoff changes in the Yellow River Basin

The driving factors of runoff changes can be divided into precipitationfactor and non-precipitation factor, and they can also be divided into natural factor and humanactivity factor. In this paper, the ways and methods of these driving factors impacting on runoffchanges are analyzed at first, and then according to the relationship between precipitation andrunoff, the analytical method about impacts of precipitation and non-precipitation factors onbasin's natural runoff is derived. The amount and contribution rates of the two factors impacting onnatural runoff between every two adjacent decades during 1956-1998 are calculated in the YellowRiver Basin (YRB). The results show that the amount and contribution rate of the two factorsimpacting on natural runoff are different in different periods and regions. For the YRB, thenon-precipitation impact is preponderant for natural runoff reduction after the 1970s. Finally, bychoosing main factors impacting on the natural runoff, one error back-propagation (BP) artificialneural network (ANN) model has been set up, and the impact of human activities on natural runoffreduction in the YRB is simulated. The result shows that the human activities could cause a 77 x10^8 m^3·a^(-1) reduction of runoff during 1980-1998 according to the climate background of1956-1979.

Measuring Social Vulnerability to Natural Hazards in Beijing-Tianjin-Hebei Region,China

Social vulnerability in this study represents the differences between the capacity to cope with natural hazards and disaster losses suffered within and between places.The assessment of social vulnerability has been recognized as a critical step in understanding natural hazard risks and enhancing effective response capabilities.This article presents an initial study of the social vulnerability of the Beijing-Tianjin-Hebei(B-T-H) Region in China.The goal is to replicate and test the applicability of the United States Social Vulnerability Index(So VI) method in a Chinese cultural context.Thirty-nine variables adapted from the So VI were collected in relation to two aspects:socioeconomic vulnerability and built environment vulnerability.Using factor analysis,seven factors were extracted from the variable set:the structure of social development,the level of economic and government financial strength,social justice and poverty,family structure,the intensity of space development,the status of residential housing and transportation,and building structure.Factor scores were summed to get the final So VI scores and the most and least vulnerable units were identified and mapped.The highest social vulnerability is concentrated in the northwest of the study area.The least socially vulnerable areas are mainly distributed in the Beijing,Tianjin and Shijiazhuang core urban peripheral and central city areas of the prefecture-level cities.The results show that this method is a useful tool for revealing places that have a high level of vulnerability,in other words,areas which are more likely to face significant challenges in coping with a large-scale event.These findings could provide a scientific basis for policy making and the implementation of disaster prevention and mitigation in China.

2013 SCI Impact Factor being 1.788 for Journal of Natural Gas Chemistry

The SCI impact factor of Journal of Natural Gas Chemistry （JNGC） is 1.788, according to the ＂2013 Journal Citation Reports （JCR） Science Edition＂. This is the highest SCI impact factor for Journal of Natural Gas Chemistry since the journal was included in the Science Citation Index Expanded （SCIE） in 2007, and it ranks first among chemistry journals in China. Over the past decade, the Journal of Natural Gas Chemistry has become more and more international and has received large numbers of manuscripts concerning energy chemistry. In deed, nowadays enerzy chemistry is becoming one of the hot topics.

Investigating the Effect of Climatic Factors of Roshtkhar Town (Khorasan Razavi, Iran) on the Development and Cultivation of Pistachio Using GIS Software

The use of Geographic Information System (GIS) has significantly helped managers provide optimal models of sustainable agricultural development, identify local features related to agricultural production and their proper zoning, identify agricultural needs and constraints and finally provide the appropriate structure of land use. The main purpose of this study was to determine areas capable of cultivating Pistachio according to the parameters affecting the Pistachio cultivation in Roshtkhar town. Statistics of meteorological stations of the town were taken from Meteorology Organization of Khorasan Razavi for the period of 1989-2010 in order to determine climatic parameters required to cultivate Pistachio. For mapping surface elevation, slope, aspect, and TIN of the geographic organization of armed forces with a scale of 1:250,000 topographic maps were used. For mapping vegetation and land use in the area under study, land capability map of the area on a scale of 1:250,000 from the institute of soil and water was used. Also information on cultivation and annual production of agricultural statistics, published by Agriculture was used. Finally, it was concluded that the northeast and southwest of Roshtkhar town are the most prone areas to cultivate Pistachio.

2011 SCI Impact Factor being 1.348 for Journal of Natural Gas Chemistry

The SCI impact factor of Journal of Natural Gas Chemistry （JNGC） is 1.348, according to the ＂2011 Journal Citation Reports （JCR） Science Edition＂. This is the highest SCI impact factor for Journal of Natural Gas Chemistry since the journal was included in the Science Citation Index Expanded （SCIE） in 2007, and it ranks first among chemistry journals in China.

Assessing the vulnerability of changing coasts,Hainan Island,China

Knowledge of coastline changes and vulnerability is of great importance to local government departments that are responsible for the management and development of coastal zones.To study the nature of change and vulnerability along the coasts of the Hainan Island,we collected a large number of sediment samples through the last few years,and reconstructed the changes of the coastline by combining the data of sediment grain-size analysis and the nautical charts/TM RS imaginary.Contrary to being almost free from erosion（as expected from the findings that the coastlines are in a relatively stable state）,four major cities in Hainan（i.e.,Haikou,Wenchang,Sanya and Changjiang） turned out to be suffered from a moderate coastal vulnerability primarily because of the large populations that impose considerable pressure on the coastlines.Thus,the assessment methodology utilized in this study,including both anthropogenic and natural factors,serves as a useful tool to obtain a comprehensive understanding of coastline vulnerability for local government,in terms of coastal management and adaptation.

The spatial relationship between salt marsh vegetation patterns,soil elevation and tidal channels using remote sensing at Chongming Dongtan Nature Reserve, China

The analysis of vegetation-environment relationships has always been a study hotspot in ecology. A number of biotic, hydrologic and edaphic factors have great influence on the distribution of macrophytes within salt marsh.Since the exotic species Spartina alterniflora（S. alterniflora） was introduced in 1995, a rapid expansion has occurred at Chongming Dongtan Nature Reserve（CDNR） in the Changjiang（Yangtze） River Estuary, China.Several important vegetation-environment factors including soil elevation, tidal channels density（TCD）,vegetation classification and fractional vegetation cover（FVC） were extracted by remote sensing method combined with field measurement. To ignore the details in interaction between biological and physical process,the relationship between them was discussed at a large scale of the whole saltmarsh. The results showed that Scirpus mariqueter（S. mariqueter） can endure the greatest elevation variance with 0.33 m throughout the marsh in CDNR. But it is dominant in the area less than 2.5 m with the occurrence frequency reaching 98%. S. alterniflora has usually been found on the most elevated soils higher than 3.5 m but has a narrow spatial distribution. The rapid decrease of S. mariqueter can be explained by stronger competitive capacity of S. alterniflora on the high tidal flat. FVC increases with elevation which shows significant correlation with elevation（r=0.30, p〈0.001）. But the frequency distribution of FVC indicates that vegetation is not well developed on both elevated banks near tidal channels from the whole scale mainly due to tidal channel lateral swing and human activities. The significant negative correlation（r=–0.20, p〈0.001） was found between FVC and TCD, which shows vegetation is restricted to grow in higher TCD area corresponding to lower elevation mainly occupied by S. mariqueter communities. The maximum occurrence frequency of this species reaches to 97% at the salt marsh with TCD more than 8 m/m2.

Contents and spatial distribution patterns of heavy metals in the hinterland of the Tengger Desert,China

The desert in northern China is one of important sources of loess and one significant source of material for sandstorms in Asia.The sand/dust that is transported from desert when sandstorms occur can destroy the growth of crops,cause serious losses and great harm to the economic construction and life safety,and cause natural environment pollution.Hence,it is very important to deepen the research into heavy metals in surface deposits at vulnerable ecological region of arid land of northern China to guide local industrial and agricultural development and improve environmental protection.In this research,10 heavy metal elements(Cr,Mn,Fe,Co,Ni,Cu,Zn,Cd,Pb,and Th)were tested and analyzed in 33 soil sample sites collected from the hinterland of the Tengger Desert,northern China.The results showed that the average abundance of Th exceeded its background soil value of China by more than 5.2 times,which suggests that the Tengger Desert is polluted by Th.In addition,based on principal component analysis,spatial differentiation,and correlation analysis,we identified the source of element with a coefficient of variation in abundance of greater than 0.5 or exceeding the background soil value of China.Principal component analysis and correlation analysis showed that the sources of heavy metals of Cr,Mn,Fe,Co,Ni,Cu,and Cd were similar,while those of Th and Zn were different.Moreover,based on the contents and spatial distribution characteristics of those heavy metal elements,we found that the formation of heavy metal elements enrichment areas is caused by industrial pollution,development of irrigated agricultural,geological,and geomorphic conditions,and the sedimentary environment in the study area.Our result can provide information on the environmental background values of soils in the hinterland of the Tengger Desert.

Modeling groundwater nitrate concentrations using spatial and non-spatial regression models in a semi-arid environment

Nitrate nitrogen(NO_(3)^(-)N)from agricultural activities and in industrial wastewater has become the main source of groundwater pollution,which has raised widespread concerns,particularly in arid and semi-arid river basins with little water that meets relevant standards.This study aimed to investigate the performance of spatial and non-spatial regression models in modeling nitrate pollution in a semi-intensive farming region of Iran.To perform the modeling of the groundwater's NO_(3)^(-)N concentration,both natural and anthropogenic factors affecting groundwater NO_(3)^(-)N were selected.The results of Moran's I test showed that groundwater nitrate concentration had a significant spatial dependence on the density of wells,distance from streams,total annual precipitation,and distance from roads in the study area.This study provided a way to estimate nitrate pollution using both natural and anthropogenic factors in arid and semi-arid areas where only a few factors are available.Spatial regression methods with spatial correlation structures are effective tools to support spatial decision-making in water pollution control.

Regional Ecological Vulnerability Assessment of the Guangxi Xijiang River Economic Belt in Southwest China with VSD Model

The interactive effects of natural and human factors on ecosystems have been well studied, and the quantitative assessment of large-scale ecological vulnerability caused by natural and human factors is now one of the most active topics in the ifeld. Taking the Guangxi Xijiang River Economic Belt in southwest China （GXEB） as a case study, we assess ecological vulnerability based on the Vulnerability Scoping Diagram （VSD） model. The indices system is decomposed into three sub objects, ten elements and 25 indicators layer by layer, which included factors from both natural and human ifelds. Results indicate that zones with lower, middle-lower, middle, middle-higher and higher vulnerability account for 11.31%, 22.63%, 27.60%, 24.39%, and 14.07%, respectively. The western and eastern parts of GXEB are more vulnerable than the central part and the mountain and urban areas are of higher vulnerability than the basins and river valleys. Compared with a vulnerability assessment based on natural factors only, it is concluded that human activities indeed cause the transition from naturally stable zones to vulnerable zones. The nature-dominated vulnerable zones are different with human-dominated ones in size and distribution, the latter being smaller, more scattered and distributed in urban areas and their surroundings. About 53%of total construction land is distributed in zones with middle and middle-higher ecological vulnerability;less vulnerable zones should attract construction in the future. Relevant suggestions are proposed on how to reduce vulnerability according to inducing factors. The VSD model has a signiifcant advantage in the quantitative evaluation of ecological vulnerability, but is insufficient to distinguish nature- or human-dominated vulnerability quantitatively.

Impact of global change on transmission of human infectious diseases

Global change,which refers to large-scale changes in the earth system and human society,has been changing the outbreak and transmission mode of many infectious diseases.Climate change affects infectious diseases directly and indirectly.Meteorological factors including temperature,precipitation,humidity and radiation influence infectious disease by modulating pathogen,host and transmission pathways.Meteorological disasters such as droughts and floods directly impact the outbreak and transmission of infectious diseases.Climate change indirectly impacts infectious diseases by altering the ecological system,including its underlying surface and vegetation distribution.In addition,anthropogenic activities are a driving force for climate change and an indirect forcing of infectious disease transmission.International travel and rural-urban migration are a root cause of infectious disease transmission.Rapid urbanization along with poor infrastructure and high disease risk in the rural-urban fringe has been changing the pattern of disease outbreaks and mortality.Land use changes,such as agricultural expansion and deforestation,have already changed the transmission of infectious disease.Accelerated air,road and rail transportation development may not only increase the transmission speed of outbreaks,but also enlarge the scope of transmission area.In addition,more frequent trade and other economic activities will also increase the potential risks of disease outbreaks and facilitate the spread of infectious diseases.

Spatiotemporal variation and hotspots of climate change in the Yangtze River Watershed during 1958-2017

The Yangtze River Watershed in China is a climate change hotspot featuring strong spatial and temporal variability;hence, it poses a certain threat to social development. Identifying the characteristics of and regions vulnerable to climate change is significantly important for formulating adaptive countermeasures. However, with regard to the Yangtze River Watershed, there is currently a lack of research on these aspects from the perspective of natural and anthropogenic factors. To address this issue, in this study, based on the temperature and precipitation records from 717 meteorological stations, the RClim Dex and random forest models were used to assess the spatiotemporal characteristics of climate change and identify mainly the natural and anthropogenic factors influencing climate change hotspots in the Yangtze River Watershed for the period 1958-2017. The results indicated a significant increasing trend in temperature, a trend of wet and dry polarization in the annual precipitation, and that the number of temperature indices with significant variations was 2.8 times greater than that of precipitation indices. Significant differences were also noted in the responses of the climate change characteristics of the sub-basins to anthropogenic and natural factors;the delta plain of the Yangtze River estuary exhibited the most significant climate changes, where 88.89% of the extreme climate indices varied considerably. Furthermore, the characteristics that were similar among the identified hotpots, including human activities(higher Gross Domestic Product and construction land proportions) and natural factors(high altitudes and large proportions of grassland and water bodies), were positively correlated with the rapid climate warming.

Causes of Lake Area Changes in Poland

The northern part of Poland is occupied by numerous lakes formed during the last glaciation as a result of the Scandinavian ice sheet. Studies carried out in the lake district areas show progressive reduction of the surface area of the lakes, which leads to their eventual disappearance. The paper discusses the degree of the observed changes and points out main natural and anthropogenic factors influencing changes of lake area in Poland, including climate change, depth of lake basins, biomass growth, deforestation, hydrotechnical works, use of fertilizers and discharge of wastewater.