总氮、总磷监测中存在的有关问题

文章简要介绍了我国部分地表水总氮、总磷的浓度现状和相关标准,重点讨论了总氮、总磷监测中存在的问题并提出相应的解决办法.     

The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin,Brazil

This study sought to evaluate and propose adjustments to the water quality monitoring network of surface freshwaters in the Paraopeba river basin (Minas Gerais, Brazil), using multivariate statistical methods. A total of 13,560 valid data were analyzed for 19 water quality parameters at 30 monitoring sites, over a period of 5 years (2008–2013). The cluster analysis grouped the monitoring sites in eight groups based on similarities of water quality characteristics. This analysis made it possible to detect the most relevant monitoring stations in the river basin. The principal components analysis associated with non-parametric tests and the analysis of violation of the standards prescribed by law, allowed for identifying the most relevant parameters which must be maintained in the network (thermotolerant coliforms, total manganese, and total phosphorus). The discharge of domestic sewage and industrial wastewater, that from mining activities and diffuse pollution from agriculture and pasture areas are the main sources of pollution responsible for the surface water quality deterioration in this basin. The BP073 monitoring site presents the most degraded water quality in the Paropeba river basin. The monitoring sites BP094 and BP092 are located geographically close and they measure similar water quality, so a possible assessment of the need to maintain only one of the two in the monitoring network is suggested. Therefore, multivariate analyses were efficient to assess the adequacy of the water quality monitoring network of the Paraopeba river basin, and it can be used in other watersheds.     

Industrial effluent quality, pollution monitoring and environmental management

Royal Commission Environmental Control Department (RC-ECD) at Yanbu industrial city in Kingdom of Saudi Arabia has established a well-defined monitoring program to control the pollution from industrial effluents. The quality of effluent from each facility is monitored round the clock. Different strategic measures have been taken by the RC-ECD to implement the zero discharge policy of RC. Industries are required to pre-treat the effluent to conform pretreatment standards before discharging to central biological treatment plant. Industries are not allowed to discharge any treated or untreated effluent in open channels. After treatment, reclaimed water must have to comply with direct discharge standards before discharge to the sea. Data of industrial wastewater collected from five major industries and central industrial wastewater treatment plant (IWTP) is summarized in this report. During 5-year period, 3,705 samples were collected and analyzed for 43,436 parameters. There were 1,377 violations from pretreatment standards from all the industries. Overall violation percentage was 3.17%. Maximum violations were recorded from one of the petrochemical plants. The results show no significant pollution due to heavy metals. Almost all heavy metals were within RC pretreatment standards. High COD and TOC indicates that major pollution was due to hydrocarbons. Typical compounds identified by GC-MS were branched alkanes, branched alkenes, aliphatic ketones, substituted thiophenes, substituted phenols, aromatics and aromatic alcohols. Quality of treated water was also in compliance with RC direct discharge standards. In order to achieve the zero discharge goal, further studies and measures are in progress.     

Surface water quality assessment of the Vatinsky Egan River catchment, West Siberia

Stream water chemistry were analyzed across Vatinsky Egan River Catchment (West Siberia). The objective of the study is to reveal the spatial and seasonal variations of the water quality and to assess the anthropogenic chemical inputs into the river system. Stream chemistry were monitored in 24 sampling sites for a period extended from January 2002 to December 2005. Spatial distribution of constituents in the Vatinsky Egan River basin indicated pollution from non-point sources associated with oil development. Data revealed that ion concentrations of river waters are usually negatively correlated with stream discharge. The major spatial variations of the hydrochemistry are related to the salinity. Chloride exhibited wide and high concentration range. A comparison with another rivers of West Siberia reveals that Vatinsky Egan River is the most saline and regional impacts further out in the watershed. The salinity of the river water increases substantially as it crosses Samotlor oil field. Many Cl(-) concentrations in the middle and lower parts of the catchment exceed the world average river values by one or more orders of magnitude. For 38% of sampling events, total petroleum hydrocarbons (TPH) concentrations were above the recommended water quality standards.     

Design of River Water Quality Monitoring Networks: A Case Study

Karoon River, from Gotvand Dam to Persian Gulf with more than 450 km in length and an annual discharge of 11,891 million cubic meters, is the largest river in Iran. Increasing water withdrawal from and wastewater discharge to the river has endangered the aquatic life of this important ecosystem. Furthermore, the drinking and in-stream water quality standards have been violated in many instances. In this paper, a river water quality monitoring network is designed, including determination of sampling frequencies as well as location of water quality monitoring stations. In this regard, two models are developed. The first model is a Genetic Algorithm-based optimization model and the second one is a combination of Kriging method and Analytical Hierarchy Process. The temporal variation of the concentration of water quality variables along Karoon and Dez Rivers are evaluated and the main water quality indicators are selected. Then, thirty five stations are selected and the application of Entropy Theory in calculating the sampling frequency is demonstrated. The results show the significant value of the proposed methodology in the design of monitoring network.     

前处理方法对水体总磷测定值的影响研究

研究了水样静置30 min和全部混合立即测定2种前处理方法对江苏省环太湖15条主要出入湖河流总磷测定值的影响,结果表明,采样后静置30 min测定的总磷浓度较低,仅为全部混匀立即测定总磷浓度的46%～80%;水体中漂浮水华蓝藻数量是影响2种前处理方法总磷测定结果差异性的重要因素,去除漂浮水华蓝藻较多的7条入湖河流监测数据后,静置30 min测定的总磷浓度为全部混匀立即测定总磷浓度的71%～80%。提出,基于不同的测定目的,应有针对性地选择总磷前处理方法,在水环境质量状况评估时,可参照国家标准或最新技术规定的前处理方法执行,以保证总磷浓度的可比性;在进行总磷入湖通量研究时,建议采用全部混合立即测定的前处理方法,以反映水体中实际总磷浓度;在不同国家水体总磷浓度比较时,建议采用相同的前处理方法进行总磷浓度测定。     

Optimizing the flow adjustment of constituent concentrations via LOESS for trend analysis

Trend analysis of stream constituent concentrations requires adjustment for exogenous variables like discharge because concentrations often have variable relations with flow. To remove the influence of flow on stream water quality data, an accurate characterization of the relationship between the constituent and streamflow is needed. One popular method, locally weighted regression (LOESS), provides an effective means for flow-adjusting concentrations. The LOESS fit can be tailored to the data via the smoothing parameter (f), so that the user can avoid overfitting or oversmoothing the data. However, it is a common practice to use a single f value when flow-adjusting water quality data for trend analysis. This study provides a robust, automated method for determining the optimal f value (f_opt) for each dataset via an iterative K-fold cross-validation procedure that minimizes prediction error in LOESS. The method is developed by analyzing datasets of seven different constituents across 17 sites (119 datasets total) from a stream monitoring program in northwest Arkansas (USA). We recommend using 10 iterations of 10-fold cross-validation (10?×?10 CV) in order to select f_opt when flow-adjusting water quality data with LOESS. The use of a default f value did not produce different trend interpretations for the data used here; however, the proposed approach may be helpful in other water quality studies which employ similar statistical fitting methods. Additionally, we provide an implementation of the method in the R statistical computing environment.     

A multi-variate methodology for analyzing pre-existing lake water quality data

Environmental agencies are given the task of monitoring water quality in rivers, lakes, and other bodies of water, for the purpose of comparing the results with regulatory standards. Monitoring follows requirements set by regulations, and data are collected in a systematic way for the intended purpose. Monitoring enables agencies to determine whether water bodies are polluted. Much effort is spent per monitoring event, resulting in hundreds of data points typically used solely for comparison with regulatory standards and then stored for little further use. This paper devises a data analysis methodology that can make use of the pre-existing datasets to extract more useful information on water quality trends, without new sample collection and analysis. In this paper, measured lake water quality data are subjected to statistical analyses including Principal Component Analysis (PCA) to deduce changes in water quality spatially and temporally over several years. It was found that the lake as a whole changed temporally by season, rather than spatially. Storm events caused the greatest shifts in water quality, though the shifts were fairly consistent across sampling stations. This methodology can be applied to similar datasets, especially with the recent emphasis by the U.S. EPA on protection of lakes as water sources. Water quality managers using these techniques may be able to lower their monitoring costs by eliminating redundant water quality parameters found in this analysis.     

改进密切值法在阳澄湖水质评价中的应用

以阳澄湖水质分析为例,利用改进密切值法分别对其东、中、西3个湖区湖体水质进行评价。结果表明,在复杂的湖泊生态系统水质评价中,该方法不仅具有模型构建简便灵活、计算量小、结果直观的特点,而且区别于以往笼统的将不同时段、不同区域湖体水质判断为某一类标准的评价模式,能够客观准确地分析不同时空的水质分布规律,预判水质变化趋势,同时区别于将污染指标等权处理或忽略指标权重的评价方式,通过引进熵权法计算权重判断主要污染因子,使湖泊生态系统水质评价结果更真实合理。     

滇池水环境质量综合评价指标优选

在研究2000—2014年滇池流域水污染排放的时空变化、水环境质量时空变化和生态环境时空演替基础上,结合滇池目前水环境质量监测工作要求,采用模型计算、指标特性分析、专家调查等方法,筛选出36个评价指标,分别表征滇池水环境质量的物理、化学、生物、营养、重金属、有机污染等特性,将滇池湖体4个监测点位优选出的评价指标监测数据输入水生态健康评价系统。结果表明,优选指标和评价体系能全面、准确、宏观地反映滇池水环境质量状况。将滇池评价指标由现有的94个压缩至36个,极大节省人力、物力,且更符合滇池水环境特点。     

Integrating sentinel watershed-systems into the monitoring and assessment of Minnesota’s (USA) waters quality

Section 303(d) of the Clean Water Act requires States and Tribes to list waters not meeting water quality standards. A total maximum daily load must be prepared for waters identified as impaired with respect to water quality standards. Historically, the management of pollution in Minnesota has been focused on point-source regulation. Regulatory effort in Minnesota has improved water quality over the last three decades. Non-point source pollution has become the largest driver of conventional 303(d) listings in the 21st century. Conventional pollutants, i.e., organic, sediment and nutrient imbalances can be identified with poor land use management practices. However, the cause and effect relationship can be elusive because of natural watershed-system influences that vary with scale. Elucidation is complex because the current water quality standards in Minnesota were designed to work best with water quality permits to control point sources of pollution. This paper presents a sentinel watershed-systems approach (SWSA) to the monitoring and assessment of Minnesota waterbodies. SWSA integrates physical, chemical, and biological data over space and time using advanced technologies at selected small watersheds across Minnesota to potentially improve understanding of natural and anthropogenic watershed processes and the management of point and non-point sources of pollution. Long-term, state-of-the-art monitoring and assessment is needed to advance and improve water quality standards. Advanced water quality or ecologically-based standards that integrate physical, chemical, and biological numeric criteria offer the potential to better understand, manage, protect, and restore Minnesota’s waterbodies.     

Assessment of water quality of Rawal Lake by long-time monitoring

Water quality of rivers, natural lakes, and reservoirs in developing countries is being degraded because of the contaminated inflows. There is a serious need for appropriate water quality monitoring for future planning and management of clean water resources. Quality of water in Rawal Lake Pakistan has been investigated in this paper. Flows from the upstream of Rawal Lake and its surrounding villages are highly polluted. Lake water quality parameters like pH, turbidity, alkalinity, calcium, nitrite, sulfate, biological oxygen dissolved, dissolved oxygen, chloride, total dissolved solids (TDS), and coliforms were investigated. Samples of water from different locations of Korang River were collected and tested. Most of the data was collected by field sampling and field visits. However, long-term information was taken from different departments. Statistical parameters (standard deviation, maximum, minimum, mean, mode, kurtosis, skew, and Euclidean distance) of variables were determined. A distinct parameter based on the difference of the maximum value the variable and maximum allowable value of that variable defined by World Health Organization was used for analysis. Grouping and clustering of elements was made on the basis of this parameter. Trend of increasing or decreasing of values of variables over a long time was also taken into account for grouping the variables. It was concluded that the concentration of seven contaminants was higher as compared to the permissible limits under environmental standards. These variables need immediate attention. The environmentally bad conditions of Rawal Lake can only be rectified by appropriate lake environmental supervision, watershed management, and implementation of environmental legislation.     

欧盟优先水污染物与环境质量标准制定及其对我国的借鉴作用

综述了欧盟水框架指令和水政策环境质量标准指令框架下,水环境优先污染物和优先危害物质的确定方法、程序和清单,以及地表水质量标准与生物体质量标准的制定方法及监测要求。提出,我国可借鉴欧盟水框架指令和水政策环境质量标准指令,明确水环境管理和污染物控制目标,制定优先污染物筛选评估技术规范及质量标准,持续评估确定地表水优先污染物,同时,建立潜在高风险物质监测监控制度,进一步完善地表水环境质量标准的指标体系,使得水环境的保护更加科学合理。     

典型行业废水特征有机污染物排放控制标准探讨

通过对典型行业废水有机污染物排放现状的调查研究,探讨我国现有污水排放标准存在的问题,即现有的标准不能有效控制废水特征有机污染物排放。依据美国环保局多介质环境模型,用不同方法计算水介质排放环境目标值,用该值作为标准限值,评价典型行业废水有机污染物监测结果。针对典型行业废水有机污染物排放特征,提出制订排放控制标准的建议。     

Assessing coastal waters of American Samoa: territory-wide water quality data provide a critical “big-picture” view for this tropical archipelago

The coastal waters of American Samoa’s five high islands (Tutuila, Aunu’u, Ofu, Olosega, and Ta’u) were surveyed in 2004 using a probabilistic design. Water quality data were collected from the near-shore coastal habitat, defined as all near-shore coastal waters including embayments, extending out to 1/4 mile off-shore. Hydrography and water column samples were collected, and water quality data were compared to the Territorial water quality standards for pH, dissolved oxygen (DO), Enterococcus, chlorophyll a, water clarity, total nitrogen, and total phosphorus. All station measurements for pH, DO, and Enterococcus satisfied the local water quality standards, although some fraction of the Territory could not be assessed for either DO or Enterococcus. With respect to chlorophyll a, 66 ± 18% of Territory coastal waters complied with the standard, while 34 ± 18% failed to comply with the standard. For water clarity, 54 ± 18% of the Territorial waters complied with the standard while 42 ± 7% failed to comply. Territorial waters satisfied the standards for total nitrogen and phosphorus 72 ± 17% and 92 ± 10%, respectively. These data provide the first “big-picture” view of water quality in the near shore region around the high islands of American Samoa. While the picture is encouraging, these data suggest emerging water quality concerns.     

中国农村饮用水水源地水质状况研究

为了系统评估中国农村饮用水水源地水质变化情况,根据2009—2018年农村饮用水水源地水质监测数据,综合评价和分析了中国农村地表和地下饮用水达标情况、空间分布和主要超标因子等。监测结果表明：10年来,农村饮用水水源地达标率不断提高,这主要得益于地表饮用水水质整体改善;地下饮用水水质达标率持续偏低,且略有变差趋势,与城市地区的差距逐年加大。农村饮用水水源地超标断面和点位在空间上分布较广,主要超标因子相对集中,且表现出与农村和农业面源污染较强的相关性。建议进一步重视农村饮用水水源地（特别是地下饮用水）的保护,加强农村饮用水水源地水质监测,加快农业面源污染防治。     

Small drinking water systems under spatiotemporal water quality variability: a risk-based performance benchmarking framework

Traditional approaches for benchmarking drinking water systems are binary, based solely on the compliance and/or non-compliance of one or more water quality performance indicators against defined regulatory guidelines/standards. The consequence of water quality failure is dependent on location within a water supply system as well as time of the year (i.e., season) with varying levels of water consumption. Conventional approaches used for water quality comparison purposes fail to incorporate spatiotemporal variability and degrees of compliance and/or non-compliance. This can lead to misleading or inaccurate performance assessment data used in the performance benchmarking process. In this research, a hierarchical risk-based water quality performance benchmarking framework is proposed to evaluate small drinking water systems (SDWSs) through cross-comparison amongst similar systems. The proposed framework (R _WQI framework) is designed to quantify consequence associated with seasonal and location-specific water quality issues in a given drinking water supply system to facilitate more efficient decision-making for SDWSs striving for continuous performance improvement. Fuzzy rule-based modelling is used to address imprecision associated with measuring performance based on singular water quality guidelines/standards and the uncertainties present in SDWS operations and monitoring. This proposed R _WQI framework has been demonstrated using data collected from 16 SDWSs in Newfoundland and Labrador and Quebec, Canada, and compared to the Canadian Council of Ministers of the Environment WQI, a traditional, guidelines/standard-based approach. The study found that the R _WQI framework provides an in-depth state of water quality and benchmarks SDWSs more rationally based on the frequency of occurrence and consequence of failure events.     

Natural and anthropogenic contamination of the Fratta-Gorzone river (Veneto, Italy)

Stream-bed sediment samples were collected in 2001 and 2004 along the Fratta-Gorzone River (Italy) to assess the level of heavy metal contamination. The river stretch most affected by discharges of tannery effluent showed total and pseudo-total Cr levels (up to 2,860 mg/kg) that greatly exceed national and international chemical sediment quality standards. The most contaminated section of the river bed is located downstream of the main industrial discharge. However, a large fraction of the Cr present in the sediment appears to be of lithogenic origin. At most sites, more than 50% of Cr is not soluble in aqua-regia and thus unlikely to be very mobile or easily bio-available. A negligible risk to the benthic community can be inferred for Pb, Zn, Cd, Cu and Ni. This work highlights the limitation of using existing chemical sediment quality standards alone for risk assessment. The collection and analysis of suspended solids, the determination of river discharge and of dissolved Cr at 10 field stations allowed to estimate the particulate and dissolved Cr load and to locate the river stretch that was the likely source of contaminated sediment. The pumping of dilution water from the Adige River into the Fratta-Gorzone River did not produce the expected contaminant dilution effect due to re-suspension of contaminated solid particles and the release of Cr in solution.     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.