基于多元统计分析的渭河西咸段水质评价

基于2012年旱季和雨季的水质监测数据,采用主成分分析(PCA)和绝对主成分多元线性回归分析(APCS-MLR)方法对渭河西咸段水体的污染特征进行了综合评价。结果表明,2012年渭河西咸段水体主要以有机污染和富营养化污染为主,同时存在一定的As污染。总体上,研究水体旱季比雨季污染严重,旱季和雨季提取的主成分及大部分断面综合排名不同,说明降雨对水质产生一定的影响。渭河西咸段水体在皂河入渭之前的上游污染相对较轻,污染贡献以干流排污为主;对应的下游水质较差,皂河是其最大的污染源。     

Groundwater pollution source apportionment using principal component analysis in a multiple land-use area in southwestern China

Identification of different pollution sources in groundwater is challenging, especially in areas with diverse land uses and receiving multiple inputs. In this study, principal component analysis (PCA) was combined with geographic information system (GIS) to explore the spatial and temporal variation of groundwater quality and to identify the sources of pollution and main factors governing the quality of groundwater in a multiple land-use area in southwestern China. Groundwater samples collected from 26 wells in 2012 and 38 wells in 2018 were analyzed for 13 water quality parameters. The PCA results showed that the hydro-geochemical process was the predominant factor determining groundwater quality, followed by agricultural activities, domestic sewage discharges, and industrial sewage discharges. Agriculture expansion from 2012 to 2018 resulted in increased apportionment of agricultural pollution. In contrast, economic restructure and infrastructure improvement reduced the contributions of domestic sewage and industrial pollution. Anthropogenic activities were found the major causes of elevated nitrogen concentrations (NO₃^?, NO₂^?, NH₄⁺) in groundwater, highlighting the necessity of controlling N sources through effective fertilizer managements in agricultural areas and reducing sewage discharges in urban areas. The applications of GIS and PCA successfully identified the sources of pollutants and major factors driving the variations of groundwater quality in tested years.

     

长江流域重点断面水质时空变异特征及污染源解析

为明晰长江流域水质时空分布特征并解析污染源,基于长江流域21个水质监测断面2008—2018年的pH、溶解氧(DO)、高锰酸盐指数(COD_Mn)及氨氮质量浓度([NH₃-N])数据,采用M-K趋势检验、相关性分析和层次聚类分析,对流域内水质时空动态变化趋势及特征进行综合识别,并结合绝对主成分回归分析法(APCS-MLR)解析污染物来源。结果表明,研究区内重点断面水质类别以II类为主,占71.39%。在时间上,水质污染程度表现为汛期(5—10月)劣于非汛期(1—4月和11、12月),汛期主要污染指标为DO和COD_Mn,非汛期主要污染指标为[NH₃-N];在空间上,21个监测断面聚类为3组,其水质优劣排序为GⅢ(四川乐山岷江大桥、湖南长沙新港、江西南昌滁搓站点)>GⅡ(中下游及下游)>GⅠ(上游及中上游)。结合主成分分析和多元回归分析得出,在所基于的指标中COD_Mn和NH₃-N是研究区内典型污染物,GⅠ组水体主要受营养盐面源污染和耗氧有机物蓄积污染;GⅡ组水质受工业生产和人类活动影响其营养盐和有机物污染严重,而自然因素影响较弱;GⅢ组站点属局部污染严重,污染源主要是有机物,其次是营养盐。上述研究结果可为长江流域针对性水环境治理、污染控制和改善提供参考。     

Combining the multivariate statistics and dual stable isotopes methods for nitrogen source identification in coastal rivers of Hangzhou Bay,China

Coastal rivers contributed the majority of anthropogenic nitrogen (N) loads to coastal waters, often resulting in eutrophication and hypoxia zones. Accurate N source identification is critical for optimizing coastal river N pollution control strategies. Based on a 2-year seasonal record of dual stable isotopes (\({\updelta}^{15}\mathrm{N}-{\mathrm{NO}}_3^{\hbox{-} }\) and \({\updelta}^{18}\mathrm{O}-{\mathrm{NO}}_3^{\hbox{-} }\)) and water quality parameters, this study combined the dual stable isotope-based MixSIAR model and the absolute principal component score-multiple linear regression (APCS-MLR) model to elucidate N dynamics and sources in two coastal rivers of Hangzhou Bay. Water quality/trophic level indices indicated light-to-moderate eutrophication status for the studied rivers. Spatio-temporal variability of water quality was associated with seasonal agricultural, aquaculture, and domestic activities, as well as the seasonal precipitation pattern. The APCS-MLR model identified soil + domestic wastewater (69.5%) and aquaculture tailwater (22.2%) as the major nitrogen pollution sources. The dual stable isotope-based MixSIAR model identified soil N, aquaculture tailwater, domestic wastewater, and atmospheric deposition N contributions of 35.3 ±21.1%, 29.7 ±17.2%, 27.9 ±14.5%, and 7.2 ±11.4% to riverine \({\mathrm{NO}}_3^{\hbox{-} }\) in the Cao’e River (CER) and 34.4 ±21.3%, 29.5 ±17.2%, 27.4 ±14.7%, and 8.7 ±12.8% in the Jiantang River (JTR), respectively. The APCS-MLR model and the dual stable isotope-based MixSIAR model showed consistent results for riverine N source identification. Combining these two methods for riverine N source identifications effectively distinguished the mix-source components from the APCS-MLR method and alleviated the high cost of stable isotope analysis, thereby providing reliable N source apportionment results with low requirements for water quality sampling and isotope analysis costs. This study highlights the importance of soil N management and aquaculture tailwater treatment in coastal river N pollution control.

     

Groundwater quality assessment and pollution source apportionment in an intensely exploited region of northern China

Deterioration in groundwater quality has attracted wide social interest in China. In this study, groundwater quality was monitored during December 2014 at 115 sites in the Hutuo River alluvial-pluvial fan region of northern China. Results showed that 21.7% of NO₃ ^? and 51.3% of total hardness samples exceeded grade III of the national quality standards for Chinese groundwater. In addition, results of gray relationship analysis (GRA) show that 64.3, 10.4, 21.7, and 3.6% of samples were within the I, II, IV, and V grades of groundwater in the Hutuo River region, respectively. The poor water quality in the study region is due to intense anthropogenic activities as well as aquifer vulnerability to contamination. Results of principal component analysis (PCA) revealed three major factors: (1) domestic wastewater and agricultural runoff pollution (anthropogenic activities), (2) water-rock interactions (natural processes), and (3) industrial wastewater pollution (anthropogenic activities). Using PCA and absolute principal component scores-multivariate linear regression (APCS-MLR), results show that domestic wastewater and agricultural runoff are the main sources of groundwater pollution in the Hutuo River alluvial-pluvial fan area. Thus, the most appropriate methods to prevent groundwater quality degradation are to improve capacities for wastewater treatment and to optimize fertilization strategies.     

Source-specific sewage pollution detection in urban river waters using pharmaceuticals and personal care products as molecular indicators

Environmental Science and Pollution Research - Source-specific elucidation of domestic sewage pollution caused by various effluent sources in an urban river water, as conducted for this study,...     

Groundwater quality in Imphal West district, Manipur, India, with multivariate statistical analysis of data

The aim of this paper was to analyze the groundwater quality of Imphal West district, Manipur, India, and assess its suitability for drinking, domestic, and agricultural use. Eighteen physico-chemical variables were analyzed in groundwater from 30 different hand-operated tube wells in urban, suburban, and rural areas in two seasons. The data were subjected to uni-, bi-, and multivariate statistical analysis, the latter comprising cluster analysis (CA), principal component analysis (PCA), and factor analysis (FA). Arsenic concentrations exceed the Indian standard in 23.3 % and the WHO limit in 73.3 % of the groundwater sources with only 26.7 % in the acceptable range. Several variables like iron, chloride, sodium, sulfate, total dissolved solids, and turbidity are also beyond their desirable limits for drinking water in a number of sites. Sodium concentrations and sodium absorption ratio (SAR) are both high to render the water from the majority of the sources unsuitable for agricultural use. Multivariate statistical techniques, especially varimax rotation of PCA data helped to bring to focus the hidden yet important variables and understand their roles in influencing groundwater quality. Widespread arsenic contamination and high sodium concentration of groundwater pose formidable constraints towards its exploitation for drinking and other domestic and agricultural use in the study area, although urban anthropogenic impacts are not yet pronounced.     

多元统计分析对再生水河流水质特征分析

对以再生水为补给水源的通惠河进行水质监测,采用模糊综合评价的方法总体评价了通惠河的水质状况,综合评价结果表明,高碑店污水处理厂处理排放人河道的水质达到Ⅱ类水平,对通惠河的污染起到了一定的缓解作用。引入多元统计分析的方法：（1）空间聚类模型将通惠河水质类型分为两类,并具体分析了两种类型的水质18个参数的差别。分析发现第1类水体的主要污染物为硝态氮、亚硝态氮引起的氮污染、磷污染等工业污染,而第2类水体的污染主要以生活污水带来的有机污染为主。（2）运用因子分析解析通惠河的污染来源——主要来源于点源排放的污水产生的氨氮、硝态氮和有机污染。为保持再生水水质,需要对水质差的污染区设立重点监测点并控制偷排现象。     

成都市区、城郊和农村生活垃圾重金属污染特性及来源

以快速发展的城郊地区为切入点,研究了成都市区、城郊和农村三区冬夏两季生活垃圾的物理组成、重金属污染特性和来源。研究发现,成都地区生活垃圾重金属浓度普遍高于当地土壤背景值,且呈现出夏季高于冬季的趋势。无论冬夏,三区垃圾中最主要的污染重金属均为Se(0.3~1.1 mg/kg)、Cd(0.3~0.9 mg/kg)和Cu(24.9~152.6 mg/kg),而其他重金属污染物如Pb、Hg和Cr在三区垃圾中的污染强弱顺序差异较大。通过Pearson相关性分析以及测定垃圾主成分中重金属浓度来研究重金属污染物的来源,结果显示:三区生活垃圾中Cd主要源于餐厨、尘土和塑料,Se可能源于废弃的电子产品,Cu和Zn源于尘土和包装纸;市区垃圾中的Pb主要源于尘土、塑料和包装纸;城郊垃圾中Cr、Se的主要源于尘土,而Hg主要来源于餐厨和尘土。     

Temporal variations of surface water quality in urban, suburban and rural areas during rapid urbanization in Shanghai, China

As the economic and financial center of China, Shanghai has experienced an extensive urban expansion since the early 1980s, with an attendant cost in environmental degradation. We use an integrated pollution index to study the temporal variations of surface water quality in urban, suburban and rural areas between 1982 and 2005. Data on monitored cross-sections were collected from the Shanghai Environmental Monitoring Center. The results indicated that the spatial pattern of surface water quality was determined by the level of urbanization. Surface water qualities in urban and suburban areas were improved by strengthening the environmental policies and management, but were worsening in rural areas. The relationship between economic growth and surface water quality in Shanghai showed an inversed-U-shaped curve, which reflected a similar pattern in most developed countries. This research suggests that decision makers and city officials should be more aware of the recent pollution increases in Shanghai.     

Evaluation of fecal pollution of river sediment by detection of urobilin

In this study, we attempted to establish a new indicator for fecal pollution of river sediment using a sensitive detection method for urobilin. Urobilin contained in sediment was extracted with an alkaline buffer solution. The suitable buffer solution for extraction of urobilin consisted of 0.1 M Tris-HCl buffer (pH 10.0) containing 0.1 m sodium chloride. The ratio of sediment to buffer was 1:10. The distribution of urobilin in river sediment was studied by this method. The amount of urobilin in the river sediment of Tokyo (urban) and the Miura peninsula (rural) area was surveyed. Large quantities of urobilin were detected in the sediments of the urban rivers, but it was scarce in the rural rivers. Urobilin showed a higher content in sediment than in water. Urobilin in river sediment is distributed in large amounts in the lower reaches, where the water is polluted with domestic sewage and industrial waste, but is scarce in the upper streams. The amount of urobilin decreases to the lower layers.     

Principal component analysis of trace substance concentrations in rainwater samples

A total of 197 bulk precipitation samples from different rural and suburban stations in Bavaria, F.R.G., were analysed for the following trace substance concentrations: PAH (fluoranthen, benzo-ghiperylene, benzo-a-pyrene), chlorinated hydrocarbons (α- and γ-BHC, HCB, PCB) and trace metals (Zn, Cd, Pb, Cu, Fe). Data analysis was carried out with multivariate principal component analysis separately for suburban and rural sites, and for summer and winter events. The resulting principal component loadings matrices are characterized by typical patterns indicating differences of the emission of the single pollutants in their temporal and spatial distribution. PAH and Pb are concentrations parameters for the interpretation of the data structure of suburban sites. While Pb concentrations are elevated in the rainwater samples of these stations during all seasons, PAH indicate space-heating by showing elevated levels during winter. Rural sites are characterized by a lower interrelation between the various parameters and chlorinated BHC pesticides as further pollution variables. These substances are highly enriched in rainwater samples from spring and summer events.     

北方地区典型城郊型村镇生活污水排放特征

近年来,随着城镇化的快速发展,城郊型村镇作为一类典型的农村地区,由于较普通农村地区发展更加迅速、人口分布更加集中、产业类型更加多样,正面临日益严重的环境问题,逐渐成为农村污水治理研究的重点。本研究区以北方地区黄河流域下的一个典型城郊型村镇为研究对象,探讨研究区农村生活污水的排污特征,补充该类典型农村地区生活污水治理的基础数据,帮助更科学的开展城郊型村镇污水治理工作。结果表明,研究区排放的生活污水水温全年基本保持在10 ℃以上,非雨季人均每日生活污水排放量为91~136 L·(人·d)⁻¹,污水总排放量为150~600 m³·d⁻¹,TN、NH₄⁺-N、TP、COD 4项污染物的平均浓度分别为36.4、34.0、2.5和131.0 mg·L⁻¹,其作为城郊型村镇具有产生污水水量较大、污染物浓度较低且波动范围较广的特点,适用于单一生态或生物与生态相结合的生活污水处理技术。     

Assessment and rationalization of water quality monitoring network: a multivariate statistical approach to the Kabbini River (India)

The establishment of an efficient surface water quality monitoring (WQM) network is a critical component in the assessment, restoration and protection of river water quality. A periodic evaluation of monitoring network is mandatory to ensure effective data collection and possible redesigning of existing network in a river catchment. In this study, the efficacy and appropriateness of existing water quality monitoring network in the Kabbini River basin of Kerala, India is presented. Significant multivariate statistical techniques like principal component analysis (PCA) and principal factor analysis (PFA) have been employed to evaluate the efficiency of the surface water quality monitoring network with monitoring stations as the evaluated variables for the interpretation of complex data matrix of the river basin. The main objective is to identify significant monitoring stations that must essentially be included in assessing annual and seasonal variations of river water quality. Moreover, the significance of seasonal redesign of the monitoring network was also investigated to capture valuable information on water quality from the network. Results identified few monitoring stations as insignificant in explaining the annual variance of the dataset. Moreover, the seasonal redesign of the monitoring network through a multivariate statistical framework was found to capture valuable information from the system, thus making the network more efficient. Cluster analysis (CA) classified the sampling sites into different groups based on similarity in water quality characteristics. The PCA/PFA identified significant latent factors standing for different pollution sources such as organic pollution, industrial pollution, diffuse pollution and faecal contamination. Thus, the present study illustrates that various multivariate statistical techniques can be effectively employed in sustainable management of water resources. Highlights ? The effectiveness of existing river water quality monitoring network is assessed ? Significance of seasonal redesign of the monitoring network is demonstrated ? Rationalization of water quality parameters is performed in a statistical framework     

生物生态耦合系统对分散式农村生活污水的深度净化

针对分散式农村生活污水排放标准的提升,通过集约式立体生物生态耦合系统对农村生活污水二级处理出水进行深度净化,采用国家标准方法对系统进出水中的COD、氨氮、TN和TP进行了测定,评价了系统对各污染物质的去除效果。结果表明：在实验进水COD,氨氮,TN和TP均属于《城镇污水处理厂污染物排放标准》(GB 18918-2002)一级B标准时,系统稳定后实验出水的COD,氨氮,TN和TP的浓度分别可降至9~35、1~7、8.0~14.9、0.20~0.47 mg·L^-1,均满足一级A标准。随着流水分区不同,COD,氨氮,TN和TP的浓度逐渐降低。采用集约式立体生物生态耦合系统可使农村生活污水二级处理出水水质达到一级A排放标准,实现深度净化的需求。     

聊城市城区河湖水中Hg、As浓度分布特征及健康风险评价

为了解聊城市城区河湖水中Hg、As浓度分布,于2010年12月19日采集、分析了20个表层水样中Hg、As浓度,并采用美国环境保护署推荐的健康风险评价模型对其进行了初步评价.结果表明:城区河湖水中Hg、As的质量浓度分别为0.016～0.366、0.494～23.438 μg/L,各主要河湖水中Hg的平均浓度大小为周公河＞东昌湖＞小运河＞徒骇河;As的平均浓度大小为周公河＞徒骇河＞小运河＞东昌湖;东昌湖Hg浓度超过《地表水环境质量标准》(GB 3838-2002)的Ⅲ类水标准值,超标率为71.4％.各主要河湖水中Hg、As浓度的空间分布差异显著,Hg主要来源于大气沉降和沿岸生活污水的排放,As主要来源于工业废水,两者均受到上游来水的影响.As通过饮水途径产生的健康风险值在10-6～10-4 a-1,是Hg的103～106倍,高于部分机构推荐的最大可接受风险水平(1.0×10-6 a-1).建议有关部门应加强对聊城市城区河湖水中Hg、As的监测和环境风险管理.     

Using multivariate analyses and GIS to identify pollutants and their spatial patterns in urban soils in Galway, Ireland

Galway is a small but rapidly growing tourism city in western Ireland. To evaluate its environmental quality, a total of 166 surface soil samples (0-10 cm depth) were collected from parks and grasslands at the density of 1 sample per 0.25 km2 at the end of 2004. All samples were analysed using ICP-AES for the near-total concentrations of 26 chemical elements. Multivariate statistics and GIS techniques were applied to classify the elements and to identify elements influenced by human activities. Cluster analysis (CA) and principal component analysis (PCA) classified the elements into two groups: the first group predominantly derived from natural sources, the second being influenced by human activities. GIS mapping is a powerful tool in identifying the possible sources of pollutants. Relatively high concentrations of Cu, Pb and Zn were found in the city centre, old residential areas, and along major traffic routes, showing significant effects of traffic pollution. The element As is enriched in soils of the old built-up areas, which can be attributed to coal and peat combustion for home heating. Such significant spatial patterns of pollutants displayed by urban soils may imply potential health threat to residents of the contaminated areas of the city.     

Identifying natural and anthropogenic sources of metals in urban and rural soils using GIS-based data,PCA, and spatial interpolation

Determining sources of neurotoxic metals in rural and urban soils is important for mitigating human exposure. Surface soil from four areas with significant clusters of mental retardation and developmental delay (MR/DD) in children, and one control site were analyzed for nine metals and characterized by soil type, climate, ecological region, land use and industrial facilities using readily available GIS-based data. Kriging, principal component analysis (PCA) and cluster analysis (CA) were used to identify commonalities of metal distribution. Three MR/DD areas (one rural and two urban) had similar soil types and significantly higher soil metal concentrations. PCA and CA results suggested that Ba, Be and Mn were consistently from natural sources; Pb and Hg from anthropogenic sources; and As, Cr, Cu, and Ni from both sources. Arsenic had low commonality estimates, was highly associated with a third PCA factor, and had a complex distribution, complicating mitigation strategies to minimize concentrations and exposures.     

Source apportionment of sediment-associated aliphatic hydrocarbon in a eutrophicated shallow lake, China

Chaohu Lake, one of the most eutrophicated lakes in China, has been suffering from long-term outside pollution, urban sewage, river outflows, and agricultural runoff which expectedly have been the main contributors of hydrocarbons. However, the contributions from these various sources have not been specified. The present study is aimed at identifying the potential sources of hydrocarbons in surface sediment around the whole lake and assessing the relative contributions using principal components analysis?Cmultiple linear regression (PCA-MLR). Sixty-one surface sediments covering the whole Chaohu Lake and three main estuaries of inflowing rivers were collected, dried, extracted, and analyzed for 27 normal alkanes (n-alkanes, from C₁₂ to C₃₈, defined ??₂₇AH) and unresolved complex mixture (UCM) by GC/MS. Diagnostic ratios and PCA-MLR were utilized to apportion their sources. The concentrations of ??₂₇AH and UCM ranged from 434 to 3,870?ng/g and 11.9 to 325???g/g dry weight, respectively, for all samples. The concentrations of ??₂₇AH in western region and estuary of Nanfei River were slightly higher but without statistical significance than those from eastern region and estuaries of Yuxi River and Hangbu River. The concentration of UCM from western region was significantly higher than that obtained from eastern region. These results reflect the importance of input of urban runoff by Nanfei River and serious eutrophication in western region. Aliphatic hydrocarbons in Chaohu Lake were mainly derived from high plant wax with mixed sources of phytoplankton and petroleum. Weak microbial decomposition of n-alkanes would be expected to occur from the low ratios of isoprenoid hydrocarbons pristine (pri) and phytane (phy) to n-C₁₇ and n-C₁₈, respectively. Higher plant, fossil combustion, petroleum residue, and phytoplankton were proposed as the main origines of aliphatic hydrocarbons by PCA while the contributions of individual n-alkane homologues, pri and phy from the identified sources (31?% from higher plant, 30?% from fossil combustion, 26?% from petroleum, and 19?% from phytoplankton) were well predicted using MLR. The distribution profile and corresponding diagnostic ratios of normal alkanes show the promising potential as a useful proxy for estimating the source and loading of pollutants in Chaohu Lake.     

射阳河水环境综合整治对策研究与分析

对射阳河的水质现状和生活、农业、工业污染源进行了全面调查,分析了射阳河流域的水质特征、污染特征等情况,并在此基础上提出了相应的综合整治对策,促进沿海开发建设与环境保护工作的协调发展。