Mass balance modelling of contaminants in river basins: a flexible matrix approach

A novel and flexible approach is described for simulating the behaviour of chemicals in river basins. A number (n) of river reaches are defined and their connectivity is described by entries in an n x n matrix. Changes in segmentation can be readily accommodated by altering the matrix entries, without the need for model revision. Two models are described. The simpler QMX-R model only considers advection and an overall loss due to the combined processes of volatilization, net transfer to sediment and degradation. The rate constant for the overall loss is derived from fugacity calculations for a single segment system. The more rigorous QMX-F model performs fugacity calculations for each segment and explicitly includes the processes of advection, evaporation, water-sediment exchange and degradation in both water and sediment. In this way chemical exposure in all compartments (including equilibrium concentrations in biota) can be estimated. Both models are designed to serve as intermediate-complexity exposure assessment tools for river basins with relatively low data requirements. By considering the spatially explicit nature of emission sources and the changes in concentration which occur with transport in the channel system, the approach offers significant advantages over simple one-segment simulations while being more readily applicable than more sophisticated, highly segmented, GIS-based models.     

Spatial variability in compartmental fate modelling

A new approach is presented which is designed to address the spatial heterogeneity of the environment in compartmental mass balance models of chemical fate in the environment. It rests on the assumption of chemical equilibration within one phase despite prevailing environmental heterogeneity. Composite D- and Z-values are derived from sub-unit specific environmental parameters and are used to solve mass balance equations which can be adopted essentially unchanged from existing compartmental fugacity models. With the resulting common fugacity value for each compartment, sub-unit specific concentrations and process rates can be calculated. The approach is illustrated using the QWASI lake model to calculate the fate of hexachlorobenzene in a hypothetical lake sub-divided in four distinct sub-units. The approach allows the subdivision of each compartment in a large number of sub-units with distinct environmental characteristics without substantially increasing model complexity. This is a necessary condition for linking fugacity models to geographical information systems.     

Data requirements of GREAT-ER: Modelling and validation using LAS in four UK catchments

Higher-tier environmental risk assessments on “down-the-drain” chemicals in river networks can be conducted using models such as GREAT-ER (Geography-referenced Regional Exposure Assessment Tool for European Rivers). It is important these models are evaluated and their sensitivities to input variables understood. This study had two primary objectives: evaluate GREAT-ER model performance, comparing simulated modelled predictions for LAS (linear alkylbenzene sulphonate) with measured concentrations, for four rivers in the UK, and investigate model sensitivity to input variables. We demonstrate that the GREAT-ER model is very sensitive to variability in river discharges. However it is insensitive to the form of distributions used to describe chemical usage and removal rate in sewage treatment plants (STPs). It is concluded that more effort should be directed towards improving empirical estimates of effluent load and reducing uncertainty associated with usage and removal rates in STPs. Simulations could be improved by incorporating the effect of river depth on dissipation rates.     

Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data

Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified.     

New PEC definitions for river basins applicable to GIS-based environmental exposure assessment

By means of GREAT-ER (Geo-Referenced Regional Exposure Assessment Tool for European Rivers) aquatic chemical fate simulations can be performed for river basins. To apply the resulting digital maps with local (river stretch specific) predicted concentrations in regional aquatic exposure and risk assessment, the output has to be aggregated to a (single) value representative of exposure in the catchment. Two spatially aggregated PEC definitions are proposed for this purpose: PECinitial (unweighted aggregation of concentrations just downstream of wastewater emissions) and PECcatchment (weighted aggregation of all average stretch concentrations). These PECs were tested using simulations for two pilot study catchments (Calder and Went, UK). This confirmed the theoretical considerations which led to the definitions, and it illustrated the need for weighting to resolve scale-dependencies.     

The current practice of health risk assessment: potential impact on standards for toxic air contaminants

Since the Bhopal incident, the public has placed pressure on regulatory agencies to set community exposure limits for the dozens of chemicals that may be released by manufacturing facilities. More or less objective limits can be established for the vast majority of these chemicals through the use of risk assessment. However, each step of the risk assessment process (i.e., hazard identification, dose-response assessment, exposure assessment, and risk characterization) contains a number of pitfalls that scientists need to avoid to ensure that valid limits are established. For example, in the hazard identification step there has been little discrimination among animal carcinogens with respect to mechanism of action or the epidemiology experience. In the dose-response portion, rarely is the range of "plausible" estimated risks presented. Physiologically based pharmacokinetic (PB-PK) models should be used to understand the difference between the tissue doses and the administered dose, as well as the difference in target tissue concentrations of the toxicant between rodents and humans. Biologically-based models like the Moolgavkar-Knudson-Venzon (MKV) should be developed and used, when appropriate. The exposure assessment step can be significantly improved by using more sensitive and specific sampling and analytical methods, more accurate exposure parameters, and computer models that can account for complex environmental factors. Whenever possible, model predictions of exposure and uptake should be validated by biological monitoring of exposed persons (urine, blood, adipose) or by field measurements of plants, soil, fish, air, or water. In each portion of an assessment, the weight of evidence approach should be used to identify the most defensible value. In the risk characterization, the best estimate of the potential risk as well as the highest plausible risk should be presented. Future assessments would be much improved if quantitative uncertainty analyses were conducted. Procedures are currently available for making future assessments. By correcting some of these shortcomings in how health risk assessments have been conducted, scientists and risk managers should be better able to identify scientifically appropriate ambient air standards and emission limits.     

Potential Impact on Standards for Toxic Air Contaminants

Since the Bhopal incident, the public has placed pressure on regulatory agencies to set community exposure limits for the dozens of chemicals that may be released by manufacturing facilities. More or less objective limits can be established for the vast majority of these chemicals through the use of risk assessment. However, each step of the risk assessment process (i.e., hazard identification, dose-response assessment, exposure assessment, and risk characterization) contains a number of pitfalls that scientists need to avoid to ensure that valid limits are established. For example, in the hazard identification step there has been little discrimination among animal carcinogens with respect to mechanism of action or the epidemiology experience. In the dose-response portion, rarely is the range of “plausible” estimated risks presented. Physiologically based pharmacokinetic (PB-PK) models should be used to understand the difference between the tissue doses and the administered dose, as well as the difference in target tissue concentrations of the toxicant between rodents and humans. Biologically-based models like the Moolgavkar-Knudson-Venzon (MKV) should be developed and used, when appropriate. The exposure assessment step can be significantly improved by using more sensitive and specific sampling and analytical methods, more accurate exposure parameters, and computer models that can account for complex environmental factors. Whenever possible, model predictions of exposure and uptake should be validated by biological monitoring of exposed persons (urine, blood, adipose) or by field measurements of plants, soil, fish, air, or water. In each portion of an assessment, the weight of evidence approach should be used to identify the most defensible value. In the risk characterization, the best estimate of the potential risk as well as the highest plausible risk should be presented. Future assessments would be much improved if quantitative uncertainty analyses were conducted. Procedures are currently available for making future assessments. By correcting some of these shortcomings in how health risk assessments have been conducted, scientists and risk managers should be better able to identify scientifically appropriate ambient air standards and emission limits.     

Can we take the pulse of environmental governance the way we take the pulse of nature? Applying the Freshwater Health Index in Latin America

Quantitative assessments have long been used to evaluate the condition of the natural environment, providing information for standard setting, adaptive management, and monitoring. Similar approaches have been developed to measure environmental governance, however, the end result (e.g., numeric indicators) belies the subjective and normative judgments that are involved in evaluating governance. We demonstrate a framework that makes this information transparent, through an application of the Freshwater Health Index in three different river basins in Latin America. Water Governance is measured on a 0–100 scale, using data derived from perception-based surveys administered to stakeholders. Results suggest that water governance is a primary area of concern in all three places, with low overall scores (Guandu-26, Alto Mayo-38, Bogotá-43). We conclude that this approach to measuring governance at the river basin scale provides valuable information to support monitoring and decision making, and we offer suggestions on how it can be improved.Electronic supplementary materialThe online version of this article (10.1007/s13280-020-01407-8) contains supplementary material, which is available to authorized users.     

A concurrent neuro-fuzzy inference system for screening the ecological risk in rivers

Purpose  

A conceptual model to assess water quality in river basins was developed here. The model was based on ecological risk assessment principles, and incorporated a novel ranking and scoring system, based on self-organizing maps, to account for the likely ecological hazards posed by the presence of chemical substances in freshwater. This approach was used to study the chemical pollution in the Ebro River basin (Spain), whose currently applied environmental indices must be revised in terms of scientific accuracy.     

Simulating the response of metal contaminated lakes to reductions in atmospheric loading using a modified QWASI model

The changes in metal concentration following significant reductions in atmospheric metal loading of two nickel and copper contaminated lakes in Coniston Valley of the Sudbury Basin of Ontario, Canada were simulated by using steady-state and dynamic versions of a modified Quantitative Water Air Sediment Interaction (QWASI) Model. Metal partitioning and precipitation processes were quantified with the aid of US EPA's MINTEQA2 Model. The dynamic model successfully described the recovery of the two lakes and identified key input, loss and partitioning processes. A useful modelling strategy is to develop one or more steady-state models that give an approximate representation of conditions at defined times, then extend this to a dynamic version which can take into account the differing rates of response of components of the system. This modelling strategy can be used for designing and assessing remediation programs for metal contaminated lakes and watersheds.     

MODELKEY. Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity (5 pp)

BACKGROUND: Triggered by the requirement of Water Framework Directive for a good ecological status for European river systems till 2015 and by still existing lacks in tools for cause identification of insufficient ecological status MODELKEY (http:// www.modelkey.org), an Integrated Project with 26 partners from 14 European countries, was started in 2005. MODELKEY is the acronym for 'Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity'. The project is funded by the European Commission within the Sixth Framework Programme. OBJECTIVES: MODELKEY comprises a multidisciplinary approach aiming at developing interlinked tools for an enhanced understanding of cause-effect-relationships between insufficient ecological status and environmental pollution as causative factor and for the assessment and forecasting of the risks of key pollutants on fresh water and marine ecosystems at a river basin and adjacent marine environment scale. New modelling tools for risk assessment including generic exposure assessment models, mechanistic models of toxic effects in simplified food chains, integrated diagnostic effect models based on community patterns, predictive component effect models applying artificial neural networks and GIS-based analysis of integrated risk indexes will be developed and linked to a user-friendly decision support system for the prioritisation of risks, contamination sources and contaminated sites. APPROACH: Modelling will be closely interlinked with extensive laboratory and field investigations. Early warning strategies on the basis of sub-lethal effects in vitro and in vivo are provided and combined with fractionation and analytical tools for effect-directed analysis of key toxicants. Integrated assessment of exposure and effects on biofilms, invertebrate and fish communities linking chemical analysis in water, sediment and biota with in vitro, in vivo and community level effect analysis is designed to provide data and conceptual understanding for risk arising from key toxicants in aquatic ecosystems and will be used for verification of various modelling approaches. CONCLUSION AND PERSPECTIVE: The developed tools will be verified in case studies representing European key areas including Mediterranean, Western and Central European river basins. An end-user-directed decision support system will be provided for cost-effective tool selection and appropriate risk and site prioritisation.     

Effect-Directed Analysis of Key Toxicants in European River Basins. A Review (9 pp)

Background, Aim and Scope Extensive monitoring programs on chemical contamination are run in many European river basins. With respect to the implementation of the European Union (EU) Water Framework Directive (WFD), these programs are increasingly accompanied by monitoring the ecological status of the river basins. Assuming an impact of chemical contamination on the ecological status, the assignment of effects in aquatic ecosystems to those stressors that cause the effects is a prerequisite for taking political or technical measures to achieve the goals of the WFD. Thus, one focus of present European research is on toxicant identification in European river basins in order to allow for a reduction of toxic pressure on aquatic ecosystems according to the WFD. Main Features: An overview is presented on studies that were performed to link chemical pollution in European river basins to measurable ecotoxic effects. This includes correlation-based approaches as well as investigations that apply effect-directed analysis (EDA) integrating toxicity testing, fractionation and non-target chemical analysis. Effect-based key toxicants that were identified in European surface waters are compiled and compared to EU priority pollutants. Further needs for research are identified. Results: Studies on the identification of effect-based key toxicants focused on mutagenicity, aryl hydrocarbon receptor-mediated effects, endocrine disruption, green algae, and invertebrates. The identified pollutants include priority pollutants and other well-known environmental pollutants such as polycyclic aromatic hydrocarbons, polychlorinated dibenzo-p-dioxins, furans, and biphenyls, nonylphenol, some pesticides and tributyltin, but also other compounds that were neither considered as environmental pollutants before nor regulated such as substituted phenols, natural or synthetic estrogens and androgens, dinaphthofurans, 2-(2-naphthalenyl)benzothiophene, and N-phenyl-2-naphthylamine. Discussion: Individual studies at specific sites in a European river basin demonstrated the power of combined biological and chemical analytical approaches and, particularly, of effect-directed analysis. However, the available information on effect-based key toxicants is very limited with respect to the entirety of rivers possibly at risk due to chemical contamination and with respect to toxicological endpoints considered at a specific site. A relatively broad basis of information exists only for estrogenicity and aryl hydrocarbon, receptor-mediated effects. Conclusions: The development of tools and strategies for an identification of key toxicants on a broader scale are a challenging task for the next years. Since investigations dealing with toxicant identification are too labor and cost-intensive for monitoring purposes, they have to be focused on the key sites in a river basin. These should include hot spots of contamination, particularly if there is evidence that they might pose a risk for downstream areas, but may also involve accumulation zones in the lower reach of a river in order to get an integrated picture on the contamination of the basin. Perspectives: While EDA is almost exclusively based on measurable effects in in vitro and in vivo biotests to date, an increasing focus in the future should be on the integration of EDA into Ecological Risk Assessment and on the development of tools to confirm EDA-determined key toxicants as stressors in populations, communities and ecosystems. Considering these requirements and applied in a focused way, toxicant identification may significantly help to implement the Water Framework Directive by providing evidence on the main stressors and possible mitigation measures in order to improve the ecological status of a river ecosystem.     

Analysis of coupled model uncertainties in source-to-dose modeling of human exposures to ambient air pollution: A PM2.5 case study

Quantitative assessment of human exposures and health effects due to air pollution involve detailed characterization of impacts of air quality on exposure and dose. A key challenge is to integrate these three components on a consistent spatial and temporal basis taking into account linkages and feedbacks. The current state-of-practice for such assessments is to exercise emission, meteorology, air quality, exposure, and dose models separately, and to link them together by using the output of one model as input to the subsequent downstream model. Quantification of variability and uncertainty has been an important topic in the exposure assessment community for a number of years. Variability refers to differences in the value of a quantity (e.g., exposure) over time, space, or among individuals. Uncertainty refers to lack of knowledge regarding the true value of a quantity. An emerging challenge is how to quantify variability and uncertainty in integrated assessments over the source-to-dose continuum by considering contributions from individual as well as linked components. For a case study of fine particulate matter (PM_2.5) in North Carolina during July 2002, we characterize variability and uncertainty associated with each of the individual concentration, exposure and dose models that are linked, and use a conceptual framework to quantify and evaluate the implications of coupled model uncertainties. We find that the resulting overall uncertainties due to combined effects of both variability and uncertainty are smaller (usually by a factor of 3–4) than the crudely multiplied model-specific overall uncertainty ratios. Future research will need to examine the impact of potential dependencies among the model components by conducting a truly coupled modeling analysis.     

Estimation of PCDD/F distribution and fluxes in the Venice Lagoon,Italy: combining measurement and modelling approaches

The available experimental information on the occurrence of PCDD/Fs in the Venice Lagoon, Italy, was compiled and used to calculate fugacities for the environmental compartments of sediment, suspended particulate matter (SPM), water and air and then used to estimate fugacity ratios and assess the likely net direction of flux between media. The bottom sediment: SPM fugacity ratios for different PCDD/Fs indicate conditions close to equilibrium, suggestive of the close coupling of SPM with re-suspended sediment. Sediment/water and the sediment/air fugacity ratios suggest that net flux directions vary depending on the congener and the location within the lagoon. Net sediment-water-air movement (i.e. re-mobilisation/volatilisation) is suggested for the lighter congeners from the industrial canals, where the highest PCDD/F concentrations in the lagoon occur. The tendency to volatilise increases with decreasing congener molecular weight. In contrast, net deposition (air-water-sediment) appears to be occurring for the heaviest (hepta- and octa-) substituted PCDD/Fs. OCDF represents a marker of the industrial district of the lagoon, decreasing in concentration and as a fraction of total PCDD/Fs with increasing distance. The fugacity-based quantitative water air sediment interaction (QWASI) mass-balance model was applied to the central part of the lagoon. The key parameters for the determination of the model output, identified by a sensitivity analysis, were: the sediment active depth, the sediment re-suspension and deposition rates, and the total input of PCDD/Fs to the system. The QWASI model also indicates the tendency for the lighter PCDD/Fs to be released from surface sediment to the water column.     

Hydrological change--climate change impact simulations for Sweden

Climate change resulting from the enhanced greenhouse effect is expected to give rise to changes in hydrological systems. This hydrological change, as with the change in climate variables, will vary regionally around the globe. Impact studies at local and regional scales are needed to assess how different regions will be affected. This study focuses on assessment of hydrological impacts of climate change over a wide range of Swedish basins. Different methods of transferring the signal of climate change from climate models to hydrological models were used. Several hydrological model simulations using regional climate model scenarios from Swedish Regional Climate Modelling Programme (SWECLIM) are presented. A principal conclusion is that subregional impacts to river flow vary considerably according to whether a basin is in northern or southern Sweden. Furthermore, projected hydrological change is just as dependent on the choice of the global climate model used for regional climate model boundary conditions as the choice of anthropogenic emissions scenario.     

International river basin management under the EU water framework directive: an assessment of cooperation and water quality in the Baltic Sea Drainage Basin

We address issues connected with international river basin management and the EU Water Framework Directive (WFD). By creating a register of River Basin Districts established under the WFD, we show that the number and area of international River Basin Districts are significant. Further, we present an assessment of international cooperation and water quality in 14 international river basins in the Baltic Sea Drainage Basin. Our results indicate that the WFD is a push forward for international river basin management in the region. However the WFD in general, and the principle of river basin management in particular, may be hard to implement in river basins shared between EU Member States and countries outside the EU. According to the study, Vistula, Pregola, and Nemunas appear to be the international basins within the Baltic Sea Drainage Basin in greatest need of intensified cooperation with regard to the state of the water quality.     

Combined source apportionment,using positive matrix factorization–chemical mass balance and principal component analysis/multiple linear regression–chemical mass balance models

The methods of positive matrix factorization–chemical mass balance and principal component analysis/multiple linear regression–chemical mass balance were studied in this paper, for combined source apportionment. Due to the high similarity among the source profiles, several problems would raised when only one receptor model was applied. For example, the collinearity problem would result in the negative contributions when applying CMB model; certain sources would not to be separated out when applying PCA or PMF model. In this study, PCA/MLR–CMB model and PMF–CMB were attempted to resolve the problem, where the combined models were applied to study the synthetic and ambient datasets. In synthetic dataset, there were seven sources (six actual sources from real world, and one unknown source). The results obtained by the combined models show that the combined source apportionment technique is feasible. In addition, an ambient dataset from a northern city in China was analyzed by PCA/MLR–CMB model and PMF–CMB model, and these two models got the similar results. The results show that coal combustion contributed the largest fraction to the total mass.     

Support vector machine―an alternative to artificial neuron network for water quality forecasting in an agricultural nonpoint source polluted river?

Water quality forecasting in agricultural drainage river basins is difficult because of the complicated nonpoint source (NPS) pollution transport processes and river self-purification processes involved in highly nonlinear problems. Artificial neural network (ANN) and support vector model (SVM) were developed to predict total nitrogen (TN) and total phosphorus (TP) concentrations for any location of the river polluted by agricultural NPS pollution in eastern China. River flow, water temperature, flow travel time, rainfall, dissolved oxygen, and upstream TN or TP concentrations were selected as initial inputs of the two models. Monthly, bimonthly, and trimonthly datasets were selected to train the two models, respectively, and the same monthly dataset which had not been used for training was chosen to test the models in order to compare their generalization performance. Trial and error analysis and genetic algorisms (GA) were employed to optimize the parameters of ANN and SVM models, respectively. The results indicated that the proposed SVM models performed better generalization ability due to avoiding the occurrence of overtraining and optimizing fewer parameters based on structural risk minimization (SRM) principle. Furthermore, both TN and TP SVM models trained by trimonthly datasets achieved greater forecasting accuracy than corresponding ANN models. Thus, SVM models will be a powerful alternative method because it is an efficient and economic tool to accurately predict water quality with low risk. The sensitivity analyses of two models indicated that decreasing upstream input concentrations during the dry season and NPS emission along the reach during average or flood season should be an effective way to improve Changle River water quality. If the necessary water quality and hydrology data and even trimonthly data are available, the SVM methodology developed here can easily be applied to other NPS-polluted rivers.     

Model comparison for risk assessment: a case study of contaminated groundwater

Many environmental multimedia risk assessment models have been developed and widely used along with increasing sophistication of the risk assessment method. Despite of the considerable improvement, uncertainty remains a primary threat to the credibility of and users' confidence in the model-based risk assessments. In particular, it has been indicated that scenario and model uncertainty may affect significantly the assessment outcome. Furthermore, the uncertainty resulting from choosing different models has been shown more important than that caused by parameter uncertainty. Based on the relationship between exposure pathways and estimated risk results, this study develops a screening procedure to compare the relative suitability between potential multimedia models, which would facilitate the reduction of uncertainty due to model selection. MEPAS, MMSOILS, and CalTOX models, combined with Monte Carlo simulation, are applied to a realistic groundwater-contaminated site to demonstrate the process. It is also shown that the identification of important parameters and exposure pathways, and implicitly, the subsequent design of uncertainty reduction and risk management measures, would be better-formed.     

Geochemical techniques on contaminated sediments-river basin view

The big flood in the upper Elbe River catchment area has revealed a wide spectrum of problems with contaminated sediments. So far, an effective strategy for managing contaminated sediments on a river basin scale is still missing and it seems that not much has been learned from the lessons received during the last decade. In the following overview, special emphasis is given to the utilization of geochemically-based techniques for sediment remediation, which can be applied in different parts of a river basin. The examples presented here are mostly from the Elbe River catchment area. In general, new technical problem solutions need a set of practical process knowledge that uses a wide range of simulation techniques, as well as models in different spatial and temporal scales. The evaluation of recent flood events clearly demonstrates the importance of chemical expertise in the decision-making process for the sustainable development in river basins.