海洋水质在线监测系统中硝酸盐测量方法比较

硝酸盐是海洋水质监测的重要指标,目前在海洋水质在线监测系统中搭载的硝酸盐在线分析仪的种类较多,采用的测量原理也不尽相同.选取了 3种采用不同测量方法的代表性硝酸盐分析仪[氯化钒还原比色法硝酸盐分析仪、二乙烯三胺五乙酸还原比色法(DTPA)硝酸盐分析仪、紫外分光光度法硝酸盐分析仪],结合各自的测量原理、化学试剂特性等,就...     

Bacteriological Purification of the Finnish River Kymi

With its total drainage basin of 37 107 km2 and mean annual discharge of 307 m3 s-1, the River Kymi is one of the largest in Finland. Presently it receives treated domestic wastewaters of about 160 000 inhabitants through eight treatment plants and treated industrial effluents from four paper mills, two cardboard mills and one pulp mill. In the 1960s all the wastewaters were discharged untreated to the river. However, the construction of domestic wastewater treatment plants began in the 1970s and mechanical wastewater treatment became common in industry. By the end of the 1980s practically all the wastewaters discharged to the river were treated in activated sludge processes. The aim of this paper was to investigate the influence of wastewater purification on the bacteriological quality of the river during these three decades. The bacteriological quality of the river was evaluated on the basis of annual medians of fecal streptococci (FS) calculated for 15 sites on the basis of 4804 FS enumerations from the years 1964-1992. The results show that the bacteriological quality improved steadily as the number of treatment plants increased and wastewater treatment became more effective. In the beginning of the 1960s the annual FS medians in the central part of the river were typically 1000-1500 CFU/100 ml, whereas in the 1990s they had decreased to 30-40 CFU/100 ml (CFU = colony forming units). The results indicate that FS input to the river was mainly of domestic origin.     

Water quality index applied to rivers in the Vistula river basin in Poland

Summary A new method of a water quality index has been proposed. The unit indices were determined from the values of individual parameters using continuous functions. The base for such functions were the four water quality classes used in Poland. The summarized WQI is the square root of the harmonic mean of squares of unit indices. Using this mean we have eliminated the use of weights of parameters. Parameters are divided into basic parameters (7) and other additional parameters (19). The additional parameter is considered only if its unit index is lower than WQI from basic parameters. For many measurements at one point the guaranteed WQI has been calculated. The points of WQI were connected and the curves of WQI along the river were obtained.A method of WQI calculating and preparation of WQI curves has been shown using as an example the Pilica river in Poland. The WQI was then calculated for 31 rivers in the Vistula river basin by measuring points.     

Developing an environmental water quality monitoring program for Haraz River in Northern Iran

Water quality management plans are an indispensable strategy for conservation and utilization of water resources in a sustainable manner. One common industrial use of water is aquaculture. The present study is an attempt to use statistical analyses in order to prepare an environmental water quality monitoring program for Haraz River, in Northern Iran. For this purpose, the analysis of a total number of 18 physicochemical parameters was performed at 15 stations during a 1-year sampling period. According to the results of the multivariate statistical methods, the optimal monitoring would be possible by only 3 stations and 12 parameters, including NH₃, EC, BOD, TSS, DO, PO₄, NO₃, TDS, temperature, turbidity, coliform, and discharge. In other words, newly designed network, with a total number of 36 measurements (3 stations × 12 parameters = 36 parameters), could achieve exactly the same performance as the former network, designed based on 234 measurements (13 stations × 18 parameters = 234 parameters). Based on the results of cluster, principal component, and factor analyses, the stations were divided into three groups of high pollution (HP), medium pollution (MP), and low pollution (LP). By clustering the stations, it would be possible to track the water quality of Haraz River, only by one station at each cluster, which facilitates rapid assessment of the water quality in the river basin. Emphasizing on three main axes of monitoring program, including measurement parameters, sampling frequency, and spatial pattern of sampling points, the water quality monitoring program was optimized for the river basin based on natural conditions of the study area, monitoring objectives, and required financial resources (a total annual cost of about US $2625, excluding the overhead costs).     

Study of the Climate Change Impacts on Water Quality in the Upstream Portion of the Cau River Basin,Vietnam

This paper presents simulations of climate change impacts on water quality in the upstream portion of the Cau River Basin in the North of Vietnam. The integrated modeling system GIBSI was used to simulate hydrological processes, pollutant and sediment wash-off in the river basin, and pollutant transport and transformation in the river network. Three projections for climate change based on emission scenarios B1, B2, and A2 of IPCC Special Report on Emission Scenarios (SRES) were considered. By assuming that the input pollution sources and watershed configuration were constant, based on 2008 data, water quality in the river network was simulated up to the terminal year 2050. For each climate change scenario, patterns of precipitation in wet and dry year were considered. The change in annual and monthly trends for dissolved oxygen (DO), biochemical oxygen demand (BOD), and ammonium ions (NH4+) load and concentration for different portions of the watershed have been analyzed. The results of these simulations show that climate change has more impact on changing the seasonal water quality parameters than on altering the average annual load of the pollutants. The percent change and change pattern in water quality parameters are different for wet and dry year, and the changes in wet year are smaller than those in dry year.     

Brown trout as a sentinel organism for organic pollution in the field using catalytic and immunochemical assays of cytochrome P-450 1A

The measurement in some living organisms of adequate biomarkers (e.g. cytochrome P-450) to assess the organic pollution in freshwater ecosystems is well established. However, the sensitivity of this approach depends on the analytical measurement method employed and on the chosen living organism for the biomonitoring. Three analytical methods were compared for measuring cytochrome P-450 1A levels in wild brown trout (Salmo trutta): a catalytic one, based on measurement of the ethoxyresorufin-O-deethylase (EROD) activity, and two immunochemical methods, namely, enzyme-linked immunosorbent assay (ELISA) and western blotting. The P-450 1A levels in those animals from a river located in an industrialized area (Trubia River, Northern Spain) and also from individuals living in a low-contamination reference area have been studied. Significant differences (Mann-Whitney U-test, P < 0.01) between rivers were found (ELISA and EROD assays), with the values for Trubia river being similar to those observed in laboratory experiments with well known P-450 1A inducers. However, no significant differences were observed in terms of sex and age. Western blot analysis confirmed the presence of a single band of 56 kDa (corresponding with P-450 1 A protein) in microsomes of fish caught in the Trubia river. On the other hand, and associated with the chemical analysis of PAHs in the waters of both rivers by SPME-GC-MS, high levels of naphthalene (P-450 1A inducer) in the contaminated river were found. In brief, a wide difference between basal levels and P-450 1A induction levels could be detected in trout living in natural field conditions using both EROD activity assay and immunochemical methods. Therefore, brown trout could constitute a good sentinel organism to biomonitor the exposure to PAHs in rivers using P-450 1A measurements.     

Estimation of suspended sediment concentration from turbidity measurements using artificial neural networks

Suspended sediment concentration (SSC) is generally determined from the direct measurement of sediment concentration of river or from sediment transport equations. Direct measurement is very costly and cannot be conducted for all river gauge stations. Therefore, correct estimation of suspended sediment amount carried by a river is very important in terms of water pollution, channel navigability, reservoir filling, fish habitat, river aesthetics and scientific interests. This study investigates the feasibility of using turbidity as a surrogate for SSC as in situ turbidity meters are being increasingly used to generate continuous records of SSC in rivers. For this reason, regression analysis (RA) and artificial neural networks (ANNs) were employed to estimate SSC based on in situ turbidity measurements. The SSC was firstly experimentally determined for the surface water samples collected from the six monitoring stations along the main branch of the stream Harsit, Eastern Black Sea Basin, Turkey. There were 144 data for each variable obtained on a fortnightly basis during March 2009 and February 2010. In the ANN method, the used data for training, testing and validation sets are 108, 24 and 12 of total 144 data, respectively. As the results of analyses, the smallest mean absolute error (MAE) and root mean square error (RMSE) values for validation set were obtained from the ANN method with 11.40 and 17.87, respectively. However these were 19.12 and 25.09 for RA. It was concluded that turbidity could be a surrogate for SSC in the streams, and the ANNs method used for the estimation of SSC provided acceptable results.     

广佛珠江河网区石油类污染数值模拟研究

基于EFDC模型,构建了广佛珠江感潮河网区三维水动力模型;同时,通过耦合石油类污染物水力输运与悬沙吸附一沉降过程,构建石油类水质数学模型,从而更全面客观地模拟水体石油类污染物的迁移转化过程。通过2001年1月实例模拟及验证,表明模型能较好地模拟再现珠江水体石油类浓度变化过程,为日后珠江水环境质量监控与水质改善、城市河涌整治成果评价及预测等提供技术支持。     

Implementing In-Stream Nutrient Processes in Large-Scale Landscape Modeling for the Impact Assessment on Water Quality

For a long time, watershed models focused on the transport of chemicals from the terrestrial part of the watershed to the surface water bodies by leaching and erosion. After the substances had reached the surface water, they were routed through the channel network often without any further transformation. Today, there is a need to extend watershed models with in-stream processes to bring them closer to natural conditions and to enhance their usability as support tools for water management and water quality policies. This paper presents experience with implementing in-stream processes in a ecohydrological dynamic watershed model and its application on the large scale in the Saale River basin in Germany. Results demonstrate that new implemented water quality parameters like chlorophyll a concentrations or oxygen amount in the reach can be reproduced quite well, although the model results, compared with results achieved without taking into account algal and transformation processes in the river, show obvious improvement only for some of the examined nutrients. Finally, some climate and water management scenarios expected to impact in-stream processes in the Saale basin were run. Their results illustrate the relative importance of physical boundary conditions on the amount and concentration of the phytoplankton, which leads to the conclusion that measures to improve water quality should not only take nutrient inputs into account but also climate influences and river morphology.     

Water quality of arctic rivers in Finnish Lapland

The water quality monitoring data of eight rivers situated in the Finnish Lapland above the Arctic Circle were investigated. These rivers are icebound annually for about 200 days. They belong to the International River Basin District founded according to the European Union Water Framework Directive and shared with Norway. They are part of the European river monitoring network that includes some 3,400 river sites. The water quality monitoring datasets available varied between the rivers, the longest comprising the period 1975–2003 and the shortest 1989–2003. For each river, annual medians of eight water quality variables were calculated. In addition, medians and fifth and 95th percentiles were calculated for the whole observation periods. The medians indicated good river water quality in comparison to other national or foreign rivers. However, the river water quality oscillated widely. Some rivers were in practice in pristine state, whereas some showed slight human impacts, e.g., occasional high values of hygienic indicator bacteria.     

Probability of misclassifying biological elements in surface waters

Measurement uncertainties are inherent to assessment of biological indices of water bodies. The effect of these uncertainties on the probability of misclassification of ecological status is the subject of this paper. Four Monte-Carlo (M-C) models were applied to simulate the occurrence of random errors in the measurements of metrics corresponding to four biological elements of surface waters: macrophytes, phytoplankton, phytobenthos, and benthic macroinvertebrates. Long series of error-prone measurement values of these metrics, generated by M-C models, were used to identify cases in which values of any of the four biological indices lay outside of the “true” water body class, i.e., outside the class assigned from the actual physical measurements. Fraction of such cases in the M-C generated series was used to estimate the probability of misclassification. The method is particularly useful for estimating the probability of misclassification of the ecological status of surface water bodies in the case of short sequences of measurements of biological indices. The results of the Monte-Carlo simulations show a relatively high sensitivity of this probability to measurement errors of the river macrophyte index (MIR) and high robustness to measurement errors of the benthic macroinvertebrate index (MMI). The proposed method of using Monte-Carlo models to estimate the probability of misclassification has significant potential for assessing the uncertainty of water body status reported to the EC by the EU member countries according to WFD. The method can be readily applied also in risk assessment of water management decisions before adopting the status dependent corrective actions.     

太湖流域河流入河污染负荷通量与入湖水质响应关系分析——以殷村港为例

以2020年1—12月太湖主要入湖河流殷村港水质自动监测站的监测数据及2020年太湖水位资料为依据,构建了一维水量水质耦合数学模型,建立了入河污染负荷通量与入湖控制断面水质响应关系,以入太湖控制断面殷村港站达Ⅲ类水质水为目标,模拟计算了殷村港站主要污染物入湖水质变化过程。结果表明,殷村港站高锰酸盐指数、氨氮、总磷等水质指标浓度最大值均明显的降低,其中氨氮浓度降低幅度相对较大,主要集中于3—6月;高锰酸盐指数和总磷日均入河污染负荷通量变化相对较小,氨氮日均入河污染负荷通量降低幅度相对较大;殷村港站高锰酸盐指数、氨氮、总磷等水质指标年入河污染负荷削减量分别为24.17,41.43,3.87 t。提出,基于核算出的削减量需进一步结合污染负荷通量过程和污染源溯源分析,确定不同水质指标下入河污染负荷控制方向,为科学合理规划殷村港主要污染物的入河污染负荷总量控制提供科学依据。     

An appraisal of changes in seasonal water quality during passage through a shallow reservoir in Western Poland

Following restoration changes in Antoninek Reservoir physico-chemical and biological processes in the water column and bottom sediments were measured to outline mechanisms of changes in nitrogen, phosphorus and organic matter concentrations during water flow through this reservoir. Intensive mineralisation of organic matter in the shallow sediments stimulated primary production and influenced increasing ammonia and nitrite nitrogen concentrations. Two main factors affected concentrations of phosphorus: (1) its presence in the external loads of river waters entering the reservoir, more important in the colder seasons as the water discharge was higher and (2) from the internal loads coming from bottom sediments. The quality of the river water during its flow through this reservoir improved for most parameters and seasons. However, concentrations of nutrients were still high in waters flowing out from the reservoir and in some months they were higher in the outflow than in waters entering the reservoir.     

Assessing Impact of Urbanization on River Water Quality In The Pearl River Delta Economic Zone, China

The Pearl River Delta Economic Zone is one of the most developed regions in China. It has been undergoing a rapid urbanization since the reformation and opening of China in 1978. This process plays a significant impact on the urban environment, particularly river water quality. The main goal of this present study is to assess the impact of urban activities especially urbanization on river water quality for the study area. Some Landsat TM images from 2000 were used to map the areas for different pollution levels of urban river sections for the study area. In addition, an improved equalized synthetic pollution index method was utilized to assess the field analytical results. The results indicate that there is a positive correlation between the rapidity of urbanization and the pollution levels of urban river water. Compared to the rural river water, urban river water was polluted more seriously. During the urban development process, urbanization and urban activities had a significant negative impact on the river water quality.     

Optimizing water quality monitoring networks using continuous longitudinal monitoring data: a case study of Wen-Rui Tang River, Wenzhou, China

Identification of representative sampling sites is a critical issue in establishing an effective water quality monitoring program. This is especially important at the urban-agriculture interface where water quality conditions can change rapidly over short distances. The objective of this research was to optimize the spatial allocation of discrete monitoring sites for synoptic water quality monitoring through analysis of continuous longitudinal monitoring data collected by attaching a water quality sonde and GPS to a boat. Sampling was conducted six times from March to October 2009 along a 6.5 km segment of the Wen-Rui Tang River in eastern China that represented an urban-agricultural interface. When travelling at a velocity of ～2.4 km h(-1), this resulted in water quality measurements at ～20 m interval. Ammonia nitrogen (NH(4)(+)-N), electrical conductivity (EC), dissolved oxygen (DO), and turbidity data were collected and analyzed using Cluster Analysis (CA) to identify optimal locations for establishment of long-term monitoring sites. The analysis identified two distinct water quality segments for NH(4)(+)-N and EC and three distinct segments for DO and turbidity. According to our research results, the current fixed-location sampling sites should be adjusted to more effectively capture the distinct differences in the spatial distribution of water quality conditions. In addition, this methodology identified river reaches that require more comprehensive study of the factors leading to the changes in water quality within the identified river segment. The study demonstrates that continuous longitudinal monitoring can be a highly effective method for optimizing monitoring site locations for water quality studies.     

River water quality and pollution sources in the Pearl River Delta, China

Some physicochemical parameters were determined for thirty field water samples collected from different water channels in the Pearl River Delta Economic Zone river system. The analytical results were compared with the environmental quality standards for surface water. Using the SPSS software, statistical analyses were performed to determine the main pollutants of the river water. The main purpose of the present research is to investigate the river water quality and to determine the main pollutants and pollution sources. Furthermore, the research provides some approaches for protecting and improving river water quality. The results indicate that the predominant pollutants are ammonium, phosphorus, and organic compounds. The wastewater discharged from households in urban and rural areas, industrial facilities, and non-point sources from agricultural areas are the main sources of pollution in river water in the Pearl River Delta Economic Zone.     

Adaptive Consensus Principal Component Analysis for On-Line Batch Process Monitoring

As the regulations of effluent quality are increasingly stringent, the on-line monitoring of wastewater treatment processes becomes very important. Multivariate statistical process control such as principal component analysis (PCA) has found wide applications in process fault detection and diagnosis using measurement data. In this work, we propose a consensus PCA algorithm for adaptive wastewater treatment process monitoring. The method overcomes the problem of changing operating conditions by updating the covariance structure recursively. The algorithm does not require any estimation compared to typical multiway PCA models. With this method process disturbances are detected in real time and the responsible measurements are directly identified. The presented methodology is successfully applied to a pilot-scale sequencing batch reactor for wastewater treatment.     

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.     

2016—2021年上海市杨浦区黄浦江流域水质变化与污染特征分析

为全面了解并跟踪上海市杨浦区黄浦江流域的水质情况,于2016年1月—2021年12月对杨浦区黄浦江流域的6个监测断面的地表水质量进行调查。采用单因子污染指数分析法和水质综合污染指数分析法,探究了杨浦区内黄浦江流域水质的污染变化特征。结果表明,自2017年杨浦区开展河道整治以来,流域总体水质明显改善,出口水质从重度污染提升到良好水平;居民区密集的虬江断面水质相对较差,后续需加强对虬江流域的污染排放管理;水质污染特征分析结果发现河道的主要污染物种类从氨氮(NH₃-N)转换为总磷(TP),说明河道整治提升了河道的自净能力,水质改善效果显著;水质在非汛期优于汛期,气温、降雨、泵站放江和污水排放是影响水质的主要原因。     

Performance of biotic indices in comparison to chemical-based Water Quality Index (WQI) in evaluating the water quality of urban river

In order to evaluate the water quality of one of the most polluted urban river in Malaysia, the Penchala River, performance of eight biotic indices, Biomonitoring Working Party (BMWP), BMWP^Thai, BMWP^Viet, Average Score Per Taxon (ASPT), ASPT^Thai, BMWP^Viet, Family Biotic Index (FBI), and Singapore Biotic Index (SingScore), was compared. The water quality categorization based on these biotic indices was then compared with the categorization of Malaysian Water Quality Index (WQI) derived from measurements of six water physicochemical parameters (pH, BOD, COD, NH₃-N, DO, and TSS). The river was divided into four sections: upstream section (recreational area), middle stream 1 (residential area), middle stream 2 (commercial area), and downstream. Abundance and diversity of the macroinvertebrates were the highest in the upstream section (407 individual and H′?=?1.56, respectively), followed by the middle stream 1 (356 individual and H′?=?0.82). The least abundance was recorded in the downstream section (214 individual). Among all biotic indices, BMWP was the most reliable in evaluating the water quality of this urban river as their classifications were comparable to the WQI. BMWPs in this study have strong relationships with dissolved oxygen (DO) content. Our results demonstrated that the biotic indices were more sensitive towards organic pollution than the WQI. BMWP indices especially BMWP^Viet were the most reliable and could be adopted along with the WQI for assessment of water quality in urban rivers.