Economics of place-based monitoring under the safe drinking water act, part III: performance evaluation of place-based monitoring strategies

The goals of environmental legislation and associated regulations are to protect public health, natural resources, and ecosystems. In this context, monitoring programs should provide timely and relevant information so that the regulatory community can implement legislation in a cost-effective and efficient manner. The Safe Drinking Water Act (SDWA) of 1974 attempts to ensure that public water systems (PWSs) supply safe water to its consumers. As is the case with many other federal environmental statutes, SDWA monitoring has been implemented in relatively uniform fashion across the USA. In this three part series, we present over 30 years of evidence to demonstrate unique patterns in water quality contaminants over space and time, develop alternative place-based monitoring approaches that exploit such patterns, and evaluate the economic performance of such approaches to current monitoring practice. Part III: Place-based (PBA) and current SDWA monitoring approaches were implemented on test datasets (1995-2001) from 19 water systems and evaluated based on the following criteria: percent of total detections, percent detections above threshold values (e.g. 20, 50, 90% of MCL), and cost. The PBA outperformed the current SDWA monitoring requirements in terms of total detections, missed only a small proportion of detections below the MCL, and captured all detections above 50% of the MCL. Essentially the same information obtained from current compliance monitoring requirements can be gained at approximately one-eighth the cost by implementing the PBA. Temporal sampling strategies were implemented on test datasets (1995-2001) from four water systems and evaluated by the following criteria: parameter estimation, percent deviation from "true" 90th, 95th, and 99th percentiles, and number of samples versus accuracy of the estimate. Non event-based (NEB) strategies were superior in estimating percentiles 1-50, but underestimated the higher percentiles. Event-based strategies were superior in estimating 95th and 99th percentiles, and required significantly fewer samples (than NEB strategies) to estimate the "true" 95th and 99th percentiles. Incorporation of place-based information significantly improves the performance of monitoring and temporal sampling strategies in the context of surface-influenced water systems in the state of Iowa. Application of similar methods to other areas and types of water systems would likely produce similar results. Compared to current SDWA monitoring, the place based approach allows for cost-effective, enhanced characterization of local contaminants of concern.     

Economics of place-based monitoring under the safe drinking water act, part I: spatial and temporal patterns of contaminants, and design of screening strategies

The goals of environmental legislation and associated regulations are to protect public health, natural resources, and ecosystems. In this context, monitoring programs should provide timely and relevant information so that the regulatory community can implement legislation in a cost-effective and efficient manner. The Safe Drinking Water Act (SDWA) of 1974 attempts to ensure that public water systems (PWSs) supply safe water to its consumers. As is the case with many other federal environmental statutes, SDWA monitoring has been implemented in relatively uniform fashion across the USA. In this three part series, spatial and temporal patterns in water quality data are utilized to develop, compare, and evaluate the economic performance of alternative place-based monitoring approaches to current monitoring practice. Under the Safe Drinking Water Act (SDWA), a common list of over 90 contaminants is analyzed nationwide using EPA-authorized laboratory procedures. National and state-level summaries of SDWA data have shown that not all contaminants occur in all places at all times. This hypothesis is confirmed and extended by showing that only a few (less than seven) contaminants are of concern in any one of 19 Iowa surface water systems studied. These systems collectively serve about 350,000 people and their sizes vary between 1,200 and 120,000. The distributions of contaminants found in these systems are positively skewed, with many non-detect measurements. A screening strategy to identify such contaminants in individual systems is presented. These findings have significant implications not only for the design of alternative monitoring programs, but also in multi-billion-dollar decisions that influence the course of future drinking water infrastructure, repair, and maintenance investments.     

A method for monitoring ground water quality near waste storage facilities

A practical optimization approach developed in this paper derives effective monitoring configurations for detecting contaminants in ground water. The approach integrates numerical simulation of contaminant transport and mathematical programming. Well sites identified by the methodology can be monitored to establish the occurrence of a contaminant release before a plume migrates to a regulatory compliance boundary. Monitoring sites are established along several horizons located between the downgradient margin of a contaminant source and a compliance boundary. A horizon can form an effective line of defense against contaminant migration to the compliance boundary if it is spanned (covered) by a sufficient number of sites to yield a well spacing that is equal to or less than a maximum value established by numerical modeling. The objective function of the integer programming model formulation expresses the goals of: (1) covering a maximum number of siting horizons, and (2) allocating wells to the single most effective horizon. The latter is determined from well spacing requirements and the width of the zone of potential contaminant migration traversed by the horizon. The methodology employs a highly tractable linear programming model formulation, and the user is not required to predefine a set of potential well sites. These attributes can facilitate its implementation in practice.     

Using a relative health indicator (RHI) metric to estimate health risk reductions in drinking water

When a new drinking water regulation is being developed, the USEPA conducts a health risk reduction and cost analysis to, in part, estimate quantifiable and non-quantifiable cost and benefits of the various regulatory alternatives. Numerous methodologies are available for cumulative risk assessment ranging from primarily qualitative to primarily quantitative. This research developed a summary metric of relative cumulative health impacts resulting from drinking water, the relative health indicator (RHI). An intermediate level of quantification and modeling was chosen, one which retains the concept of an aggregated metric of public health impact and hence allows for comparisons to be made across “cups of water,” but avoids the need for development and use of complex models that are beyond the existing state of the science. Using the USEPA Six-Year Review data and available national occurrence surveys of drinking water contaminants, the metric is used to test risk reduction as it pertains to the implementation of the arsenic and uranium maximum contaminant levels and quantify “meaningful” risk reduction. Uranium represented the threshold risk reduction against which national non-compliance risk reduction was compared for arsenic, nitrate, and radium. Arsenic non-compliance is most significant and efforts focused on bringing those non-compliant utilities into compliance with the 10 μg/L maximum contaminant level would meet the threshold for meaningful risk reduction.     

Comparison of PoraPak Rxn RP and XAD-2 adsorbents for monitoring dissolved hydrophobic organic contaminants

Accurate determination of the levels of dissolved hydrophobic organic contaminants (HOCs) is an important step in estimating the dynamics of their inputs and losses in aqueous systems. This study explores an alternative method for efficiently sampling dissolved HOCs while mitigating a number of sampling artifacts associated with traditional methods. The adsorption characteristics of a new polymeric resin, PoraPak Rxn RP (PPR), were assessed using sorption isotherm experiments and fixed bed adsorption studies. The adsorption capacities and breakthrough times for four model contaminants (phenol, p-nitrophenol, naphthalene, and 2,4,6-tribromophenol) were proportional to the contaminant’s hydrophobicity. The ability of PPR to isolate dissolved polychlorinated biphenyls (PCBs) in real samples was compared with that of XAD-2, a well-known macroporous polymer that suffers from high background contamination. The results indicated that the PPR resin can be effectively used for monitoring HOCs, with low ∑PCB levels in blanks, decreasing solvent use, and reducing extraction times.     

A Critical Analysis of Illinois’ Fish Mercury Monitoring Program, 1974–1998

Mercury contamination in fish is a serious public health concern that contrasts with other health benefits of eating fish. Like most US states, Illinois has monitored fish mercury contamination for decades to warn the public of mercury exposure risks by consuming fish. Has this monitoring program been effective in detecting public mercury exposure risks? I analyzed fish mercury contamination data from Illinois inland lakes (1974–1998; >?2,300 samples, 18 fish species, 149 lakes) and found that: (a) sampling and analyses have been severely limited since 1985; (b) sampling effort varied widely among lakes and species, and (c) trends and spatial patterns were confused by this variability. As a result of a severely limited and nonstrategic monitoring program, public mercury exposure risks via Illinois fish consumption remain unclear, despite much effort over many years. Illinois monitors fewer fish per angler than many US states, but is not alone in this regard. Illinois should resurrect and redesign its fish contaminant monitoring program to one that strategically and systematically assesses human mercury exposure risk. Other US states and nations may also benefit from similar retrospective examinations of monitoring programs intended to protect public health.     

Uncertainty based optimal monitoring network design for a chlorinated hydrocarbon contaminated site

An application of a newly developed optimal monitoring network for the delineation of contaminants in groundwater is demonstrated in this study. Designing a monitoring network in an optimal manner helps to delineate the contaminant plume with a minimum number of monitoring wells at optimal locations at a contaminated site. The basic principle used in this study is that the wells are installed where the measurement uncertainties are minimum at the potential monitoring locations. The development of the optimal monitoring network is based on the utilization of contaminant concentration data from an existing initial arbitrary monitoring network. The concentrations at the locations that were not sampled in the study area are estimated using geostatistical tools. The uncertainty in estimating the contaminant concentrations at such locations is used as design criteria for the optimal monitoring network. The uncertainty in the study area was quantified by using the concentration estimation variances at all the potential monitoring locations. The objective function for the monitoring network design minimizes the spatial concentration estimation variances at all potential monitoring well locations where a monitoring well is not to be installed as per the design criteria. In the proposed methodology, the optimal monitoring network is designed for the current management period and the contaminant concentration data estimated at the potential observation locations are then used as the input to the network design model. The optimal monitoring network is designed for the consideration of two different cases by assuming different initial arbitrary existing data. Three different scenarios depending on the limit of the maximum number of monitoring wells that can be allowed at any period are considered for each case. In order to estimate the efficiency of the developed optimal monitoring networks, mass estimation errors are compared for all the three different scenarios of the two different cases. The developed methodology is useful in coming up with an optimal number of monitoring wells within the budgetary limitations. The methodology also addresses the issue of redundancy, as it refines the existing monitoring network without losing much information of the network. The concept of uncertainty-based network design model is useful in various stages of a potentially contaminated site management such as delineation of contaminant plume and long-term monitoring of the remediation process.     

Continuous ‘Passive’ flow-proportional monitoring of drainage using a new modified Sutro weir (MSW) unit

In view of their crucial role in water and solute transport, enhanced monitoring of agricultural subsurface drain tile systems is important for adequate water quality management. However, existing monitoring techniques for flow and contaminant loads from tile drains are expensive and labour intensive. The aim of this study was to develop a cost-effective and simple method for monitoring loads from tile drains. The Flowcap is a modified Sutro weir (MSW) unit that can be attached to the outlet of tile drains. It is capable of registering total flow, contaminant loads and flow-averaged concentrations. The MSW builds on a modern passive sampling technique that responds to hydraulic pressure and measures average concentrations over time (days to months) for various substances. Mounting the samplers in the MSW allowed a flow-proportional part of the drainage to be sampled. Laboratory testing yielded high linear correlation between the accumulated sampler flow, q _total, and accumulated drainage flow, Q _total (r ²?>?0.96). The slope of these correlations was used to calculate the total drainage discharge from the sampled volume, and therefore contaminant load. A calibration of the MSW under controlled laboratory condition was needed before interpretation of the monitoring results was possible. The MSW does not require a shed, electricity, or maintenance. This enables large-scale monitoring of contaminant loads via tile drains, which can improve contaminant transport models and yield valuable information for the selection and evaluation of mitigation options to improve water quality. Results from this type of monitoring can provide data for the evaluation and optimisation of best management practices in agriculture in order to produce the highest yield without water quality and recipient surface waters being compromised.     

Lake Ontario sediments in monitoring pollution

An investigation was carried out to select locations for long-term monitoring of inputs of contaminants into Lake Ontario using fine-grained bottom sediments as an historical record of pollution. The sediment sampling program was designed to determine sediment heterogeneity in the western, central and eastern depositional basins of the lake. Surficial sediments and sediment cores were collected in each basin to obtain information on horizontal distribution and concentration profiles of major and trace elements in the sediments (Si, Al, Ca, Mg, Fe, Na, K, Ti, Mn, P, As, Co, Cu, Cr, Ni, Pb and Zn). The results of the investigation indicated that fine-grained sediments in three Lake Ontario depositional basins are homogeneous to a high degree, and that only a few sediment cores need to be collected within each basin for the long-term monitoring of inputs of contaminants to the lake.     

Associations between distance lags,groundwater velocities,and detection efficiencies in groundwater monitoring networks

Effects of distance lags between landfills and monitoring wells on contaminant detection capability were quantified in several groundwater velocity settings. Detection efficiency calculations were made with and without imposing a time limit on contaminant travel. In general, longer distance lags yieldedhigher detection efficiencies. However, detection efficienciesdecreased as monitoring wells approached a buffer zone boundaryimposing a maximum permissible contaminant transport distance.Imposing a time limit on contaminant travel substantially reduced detection efficiency in low velocity settings, especiallyat longer distance lags. Time limits were less significant in high velocity settings where contaminants more quickly reachedmonitoring wells. Detection efficiencies also decreased as velocity increased, but decreases were minor once the velocityreached a threshold value.     

A Water Quality Monitoring Network Design Methodology for the Selection of Critical Sampling Points: Part I

The principal instrument to temporally and spatially manage water resources is a water quality monitoring network. However, to date in most cases, there is a clear absence of a concise strategy or methodology for designing monitoring networks, especially when deciding upon the placement of sampling stations. Since water quality monitoring networks can be quite costly, it is very important to properly design the monitoring network so that maximum information extraction can be accomplished, which in turn is vital when informing decision-makers. This paper presents the development of a methodology for identifying the critical sampling locations within a watershed. Hence, it embodies the spatial component in the design of a water quality monitoring network by designating the critical stream locations that should ideally be sampled. For illustration purposes, the methodology focuses on a single contaminant, namely total phosphorus, and is applicable to small, upland, predominantly agricultural-forested watersheds. It takes a number of hydrologic, topographic, soils, vegetative, and land use factors into account. In addition, it includes an economic as well as logistical component in order to approximate the number of sampling points required for a given budget and to only consider the logistically accessible stream reaches in the analysis, respectively. The methodology utilizes a geographic information system (GIS), hydrologic simulation model, and fuzzy logic.     

Atmospheric deposition and storm induced runoff of heavy metals from different impermeable urban surfaces

Contaminants deposited on impermeable surfaces migrate to stormwater following rainfall events, but accurately quantifying their spatial and temporal yields useful for mitigation purposes is challenging. To overcome limitations in current sampling methods, a system was developed for rapid quantification of contaminant build-up and wash-off dynamics from different impervious surfaces. Thin boards constructed of concrete and two types of asphalt were deployed at different locations of a large carpark to capture spatially distributed contaminants from dry atmospheric deposition over specified periods of time. Following experimental exposure time, the boards were then placed under a rainfall simulator in the laboratory to generate contaminant runoff under controlled conditions. Single parameter effects including surface roughness and material composition, number of antecedent dry days, rain intensity, and water quality on contaminant build-up and wash-off yields could be investigated. The method was applied to quantify spatial differences in deposition rates of contaminants (TSS, zinc, copper and lead) at two locations varying in their distance to vehicle traffic. Results showed that boards exposed at an unused part of the carpark >50 m from vehicular traffic captured similar amounts of contaminants compared with boards that were exposed directly adjacent to the access route, indicating substantial atmospheric contaminant transport. Furthermore, differences in contaminant accumulation as a function of surface composition were observed. Runoff from asphalt boards yielded higher zinc loads compared with concrete surfaces, whereas runoff from concrete surfaces resulted in higher TSS concentrations attributed to its smoother surfaces. The application of this method enables relationships between individual contaminant behaviour and specific catchment characteristics to be investigated and provides a technique to derive site-specific build-up and wash-off functions required for modelling contaminant loads from impermeable surfaces.     

A water quality monitoring network design methodology for the selection of critical sampling points: Part II

In order to resolve the spatial component of the design of a water quality monitoring network, a methodology has been developed to identify the critical sampling locations within a watershed. This methodology, called Critical Sampling Points (CSP), focuses on the contaminant total phosphorus (TP), and is applicable to small, predominantly agricultural-forested watersheds. The CSP methodology was translated into a model, called Water Quality Monitoring Station Analysis (WQMSA). It incorporates a geographic information system (GIS) for spatial analysis and data manipulation purposes, a hydrologic/water quality simulation model for estimating TP loads, and an artificial intelligence technology for improved input data representation. The model input data include a number of hydrologic, topographic, soils, vegetative, and land use factors. The model also includes an economic and logistics component. The validity of the CSP methodology was tested on a small experimental Pennsylvanian watershed, for which TP data from a number of single storm events were available for various sampling points within the watershed. A comparison of the ratios of observed to predicted TP loads between sampling points revealed that the model's results were promising.     

Urban stormwater harvesting and reuse: a probe into the chemical, toxicology and microbiological contaminants in water quality

Stormwater is one of the last major untapped urban water resources that can be exploited as an alternative water source in Australia. The information in the current Australian Guidelines for Water Recycling relating to stormwater harvesting and reuse only emphasises on a limited number of stormwater quality parameters. In order to supply stormwater as a source for higher value end-uses, a more comprehensive assessment on the potential public health risks has to be undertaken. Owing to the stochastic variations in rainfall, catchment hydrology and also the types of non-point pollution sources that can provide contaminants relating to different anthropogenic activities and catchment land uses, the characterisation of public health risks in stormwater is complex, tedious and not always possible through the conventional detection and analytical methods. In this study, a holistic approach was undertaken to assess the potential public health risks in urban stormwater samples from a medium-density residential catchment. A combined chemical–toxicological assessment was used to characterise the potential health risks arising from chemical contaminants, while a combination of standard culture methods and quantitative polymerase chain reaction (qPCR) methods was used for detection and quantification of faecal indicator bacteria (FIB) and pathogens in urban stormwater. Results showed that the concentration of chemical contaminants and associated toxicity were relatively low when benchmarked against other alternative water sources such as recycled wastewater. However, the concentrations of heavy metals particularly cadmium and lead have exceeded the Australian guideline values, indicating potential public health risks. Also, high numbers of FIB were detected in urban stormwater samples obtained from wet weather events. In addition, qPCR detection of human-related pathogens suggested there are frequent sewage ingressions into the urban stormwater runoff during wet weather events. Further water quality monitoring study will be conducted at different contrasting urban catchments in order to undertake a more comprehensive public health risk assessment for urban stormwater.     

Development of a new risk-based framework to guide investment in water quality monitoring

An innovative framework for optimising investments in water quality monitoring has been developed for use by water and environmental agencies. By utilising historical data, investigating the accuracy of monitoring methods and considering the risk tolerance of the management agency, this new methodology calculates optimum water quality monitoring frequencies for individual water bodies. Such information can be applied to water quality constituents of concern in both engineered and natural water bodies and will guide the investment of monitoring resources. Here we present both the development of the framework itself and a proof of concept by applying it to the occurrence of hazardous cyanobacterial blooms in freshwater lakes. This application to existing data demonstrates the robustness of the approach and the capacity of the framework to optimise the allocation of both monitoring and mitigation resources. When applied to cyanobacterial blooms in the Swan Coastal Plain of Western Australia, we determined that optimising the monitoring regime at individual lakes could greatly alter the overall monitoring schedule for the region, rendering it more risk averse without increasing the amount of monitoring resources required. For water resources with high-density temporal data related to constituents of concern, a similar reduction in risk may be observed by applying the framework.     

我国流域水生态完整性评价方法构建

流域水生态完整性评价是指通过对水生态系统中不同水生态指标(生物和非生物)的监测以及由数学方法综合形成的综合评价指数,来反映水生态系统完整性状况。近年来,世界各国水环境管理政策发生了变化,开始强调生态保护,重视水体的生态质量。中国现行的常规理化监测指标(如COD、氨氮、BOD5)很难满足水环境管理的需求,难以全面准确地反映水环境质量变化的趋势。因此,在借鉴欧美发达国家流域水生态完整性评价方法的基础上,结合中国目前监测现状以及流域水环境管理需求,构建了包括物理生境指标、理化指标、水生生物指标在内的流域水生态完整性监测与评价方法,以期为中国流域水质目标管理技术体系的业务化运行提供可资借鉴的技术支撑,实现从单一的化学指标监测转向综合的水生态系统监测,实现流域水生态完整性的监测与评价。     

Using multivariate techniques as a strategy to guide optimization projects for the surface water quality network monitoring in the Velhas river basin,Brazil

Surface water quality monitoring networks are usually deployed and rarely re-evaluated with regard to their effectiveness. In this sense, this work sought to evaluate and to guide optimization projects for the water quality monitoring network of the Velhas river basin, using multivariate statistical methods. The cluster, principal components, and factorial analyses, associated with non-parametric tests and the analysis of violation to the standards set recommended by legislation, identified the most relevant water quality parameters and monitoring sites, and evaluated the sampling frequency. Thermotolerant coliforms, total arsenic, and total phosphorus were considered the most relevant parameters for characterization of water quality in the river basin. The monitoring sites BV156, BV141, BV142, BV150, BV137, and BV153 were considered priorities for maintenance of the network. The multivariate statistical analysis showed the importance of a monthly sampling frequency, specifically the parameters considered most important.     

Design of on-line river water quality monitoring systems using the entropy theory: a case study

The design of a water quality monitoring network is considered as the main component of water quality management including selection of the water quality variables, location of sampling stations and determination of sampling frequencies. In this study, an entropy-based approach is presented for design of an on-line water quality monitoring network for the Karoon River, which is the largest and the most important river in Iran. In the proposed algorithm of design, the number and location of sampling sites and sampling frequencies are determined by minimizing the redundant information, which is quantified using the entropy theory. A water quality simulation model is also used to generate the time series of the concentration of water quality variables at some potential sites along the river. As several water quality variables are usually considered in the design of water quality monitoring networks, the pair-wise comparison is used to combine the spatial and temporal frequencies calculated for each water quality variable. After selecting the sampling frequencies, different components of a comprehensive monitoring system such as data acquisition, transmission and processing are designed for the study area, and technical characteristics of the on-line and off-line monitoring equipment are presented. Finally, the assessment for the human resources needs, as well as training and quality assurance programs are presented considering the existing resources in the study area. The results show that the proposed approach can be effectively used for the optimal design of the river monitoring systems.     

Ambient Air Quality Monitoring Network Design for Assessing Human Health Impacts from Exposures to Airborne Contaminants

Existing methods of establishing ambientair quality monitoring networks typically evaluateonly parameters related to ambient concentrations ofthe contaminant(s) of interest such as emissionsource characteristics, atmospheric transport anddispersion, secondary reactions, depositioncharacteristics, and local topography. However,adverse health risks from exposures to airbornecontaminants are a function of the contaminant andthe anatomic and physiologic characteristics of theexposed population. Thus, ambient air qualitymonitoring networks designed for the protection ofpublic health or for epidemiological studiesevaluating adverse health impacts from exposures toambient air contaminants should account for bothcontaminant characteristics and human healthparameters. A methodology has been establishedwhich optimizes ambient air quality monitoringnetworks for assessments of adverse human healthimpacts from exposures to airborne contaminants byincorporating human health risk assessmenttechniques. The use of risk assessment techniquesas the basis for designing ambient air qualitymonitoring networks will help to target limitedfinancial and human resources to evaluate humanhealth risks from exposures to airbornecontaminants.     

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.