Parameter uncertainty and variability in evaluative fate and exposure models

Environmental and economic cost-benefit comparison of sponge city construction in different urban functional regions

This study conducts a life cycle environmental and economic quantification comparison of urban runoff source control facilities (URSCFs) through construction and operation stages in two urban functional regions (i.e., residential area and campus). From the environmental perspective, URSCFs construction in residential area has both higher environmental impacts and benefits than that in campus. The operation stage of URSCFs can observe significant benefit for both residential area and campus. We then develop a set of monetized method to make a comprehensive benefit evaluation (i.e., environmental, economic, and social benefit) of URSCFs. Overall, the two areas have payback time less than thirteen years for their investment which is acceptable when compared with the assumed total service period (30 years). Specifically, the payback time of campus is 5.62 years and residential area is 12.44 years. This implies that the campus has great potential to achieve high cost-benefit ratio and thus the Sponge City construction in campus can implement URSCFs with less engineering and material consumption due to its more spacious site than residential area with high building density. For both residential area and campus, permeable pavement has the highest environmental impact and economic cost because of the concrete consumption. Thus, we recommend that it should be cautious of the construction of concrete permeable pavement and find environmentally and economically alternatives in future URSCFs projects.

An automated framework for compiling and integrating chemical hazard data

Comparative chemical hazard assessment, which compares hazards for several endpoints across several chemicals, can be used for a variety of purposes including alternatives assessment and the prioritization of chemicals for further assessment. A new framework was developed to compile and integrate chemical hazard data for several human health and ecotoxicity endpoints from public online sources including hazardous chemical lists, Globally Harmonized System hazard codes (H-codes) or hazard categories from government health agencies, experimental quantitative toxicity values, and predicted values using Quantitative Structure-Activity Relationship (QSAR) models. QSAR model predictions were obtained using EPA's Toxicity Estimation Software Tool. Java programming was used to download hazard data, convert data from each source into a consistent score record format, and store the data in a database. Scoring criteria based on the EPA's Design for the Environment Program Alternatives Assessment Criteria for Hazard Evaluation were used to determine ordinal hazard scores (i.e., low, medium, high, or very high) for each score record. Different methodologies were assessed for integrating data from multiple sources into one score for each hazard endpoint for each chemical. The chemical hazard assessment (CHA) Database developed in this study currently contains more than 990,000 score records for more than 85,000 chemicals. The CHA Database and the methods used in its development may contribute to several cheminformatics, public health, and environmental activities.

Mineral processing simulation based-environmental life cycle assessment for rare earth project development: A case study on the Songwe Hill project

Rare earth elements (REE), including neodymium, praseodymium, and dysprosium are used in a range of low-carbon technologies, such as electric vehicles and wind turbines, and demand for these REE is forecast to grow. This study demonstrates that a process simulation-based life cycle assessment (LCA) carried out at the early stages of a REE project, such as at the pre-feasibility stage, can inform subsequent decision making during the development of the project and help reduce its environmental impacts. As new REE supply chains are established and new mines are opened. It is important that the environmental consequences of different production options are examined in a life cycle context in order that the environment footprint of these raw materials is kept as low as possible. Here, we present a cradle-to-gate and process simulation-based life cycle assessment (LCA) for a potential new supply of REE at Songwe Hill in Malawi. We examine different project options including energy selection and a comparison of on-site acid regeneration versus virgin acid consumption which were being considered for the project. The LCA results show that the global warming potential of producing 1 kg of rare earth oxide (REO) from Songwe Hill is between 17 and 87 kg CO₂-eq. A scenario that combines on-site acid regeneration with off-peak hydroelectric and photovoltaic energy gives the lowest global warming potential and performs well in other impact categories. This approach can equally well be applied to all other types of ore deposits and should be considered as a routine addition to all pre-feasibility studies.

Health risk assessment of arsenic from blended water in distribution systems

In a water distribution system with different sources, water blending occurs, causing specific variations of the arsenic level. This study was undertaken to investigate the concentration and cancer risk of arsenic in blended water in Xi'an city. A total of 672 tap water samples were collected from eight sampling points in the blending zones for arsenic determination. The risk was evaluated through oral ingestion and dermal absorption, separately for males and females, as well as with respect to seasons and blending zones. Although the arsenic concentrations always fulfilled the requirements of the World Health Organization (WHO) (≤10 μg L^-1), the total cancer risk value was higher than the general guidance risk value of 1.00 × 10^-6. In the blending zone of the Qujiang and No.3 WTPs (Z2), the total cancer risk value was over 1.00 × 10^-5, indicating that public health would be affected to some extent. More than 99% of the total cancer risk was from oral ingestion, and dermal absorption had a little contribution. With higher exposure duration and lower body weight, women had a higher cancer risk. In addition, due to several influential factors, the total cancer risk in the four blending zones reached the maximum in different seasons. The sensitivity analysis by the tornado chart proved that body weight, arsenic concentration and ingestion rate significantly contributed to cancer risk. This study suggests the regular monitoring of water blending zones for improving risk management.

Human Health Risk Assessment Applied to Rural Populations Dependent on Unregulated Drinking Water Sources: A Scoping Review

Safe drinking water is a global challenge for rural populations dependent on unregulated water. A scoping review of research on human health risk assessments (HHRA) applied to this vulnerable population may be used to improve assessments applied by government and researchers. This review aims to summarize and describe the characteristics of HHRA methods, publications, and current literature gaps of HHRA studies on rural populations dependent on unregulated or unspecified drinking water. Peer-reviewed literature was systematically searched (January 2000 to May 2014) and identified at least one drinking water source as unregulated (21%) or unspecified (79%) in 100 studies. Only 7% of reviewed studies identified a rural community dependent on unregulated drinking water. Source water and hazards most frequently cited included groundwater (67%) and chemical water hazards (82%). Most HHRAs (86%) applied deterministic methods with 14% reporting probabilistic and stochastic methods. Publications increased over time with 57% set in Asia, and 47% of studies identified at least one literature gap in the areas of research, risk management, and community exposure. HHRAs applied to rural populations dependent on unregulated water are poorly represented in the literature even though almost half of the global population is rural.

Conceptual Framework To Extend Life Cycle Assessment Using Near-Field Human Exposure Modeling and High-Throughput Tools for Chemicals

Life Cycle Assessment (LCA) is a decision-making tool that accounts for multiple impacts across the life cycle of a product or service. This paper presents a conceptual framework to integrate human health impact assessment with risk screening approaches to extend LCA to include near-field chemical sources (e.g., those originating from consumer products and building materials) that have traditionally been excluded from LCA. A new generation of rapid human exposure modeling and high-throughput toxicity testing is transforming chemical risk prioritization and provides an opportunity for integration of screening-level risk assessment (RA) with LCA. The combined LCA and RA approach considers environmental impacts of products alongside risks to human health, which is consistent with regulatory frameworks addressing RA within a sustainability mindset. A case study is presented to juxtapose LCA and risk screening approaches for a chemical used in a consumer product. The case study demonstrates how these new risk screening tools can be used to inform toxicity impact estimates in LCA and highlights needs for future research. The framework provides a basis for developing tools and methods to support decision making on the use of chemicals in products.

The influence of uncertainty and location-specific conditions on the environmental prioritisation of human pharmaceuticals in Europe

The selection of priority APIs (Active Pharmaceutical Ingredients) can benefit from a spatially explicit approach, since an API might exceed the threshold of environmental concern in one location, while staying below that same threshold in another. However, such a spatially explicit approach is relatively data intensive and subject to parameter uncertainty due to limited data. This raises the question to what extent a spatially explicit approach for the environmental prioritisation of APIs remains worthwhile when accounting for uncertainty in parameter settings. We show here that the inclusion of spatially explicit information enables a more efficient environmental prioritisation of APIs in Europe, compared with a non-spatial EU-wide approach, also under uncertain conditions. In a case study with nine antibiotics, uncertainty distributions of the PAF (Potentially Affected Fraction) of aquatic species were calculated in 100∗100km(2) environmental grid cells throughout Europe, and used for the selection of priority APIs. Two APIs have median PAF values that exceed a threshold PAF of 1% in at least one environmental grid cell in Europe, i.e., oxytetracycline and erythromycin. At a tenfold lower threshold PAF (i.e., 0.1%), two additional APIs would be selected, i.e., cefuroxime and ciprofloxacin. However, in 94% of the environmental grid cells in Europe, no APIs exceed either of the thresholds. This illustrates the advantage of following a location-specific approach in the prioritisation of APIs. This added value remains when accounting for uncertainty in parameter settings, i.e., if the 95th percentile of the PAF instead of its median value is compared with the threshold. In 96% of the environmental grid cells, the location-specific approach still enables a reduction of the selection of priority APIs of at least 50%, compared with a EU-wide prioritisation.

Spatial variability versus parameter uncertainty in freshwater fate and exposure factors of chemicals

We compared the influence of spatial variability in environmental characteristics and the uncertainty in measured substance properties of seven chemicals on freshwater fate factors (FFs), representing the residence time in the freshwater environment, and on exposure factors (XFs), representing the dissolved fraction of a chemical. The influence of spatial variability was quantified using the SimpleBox model in which Europe was divided in 100 × 100 km regions, nested in a regional (300 × 300 km) and supra-regional (500 × 500 km) scale. Uncertainty in substance properties was quantified by means of probabilistic modelling. Spatial variability and parameter uncertainty were expressed by the ratio k of the 95%ile and 5%ile of the FF and XF. Our analysis shows that spatial variability ranges in FFs of persistent chemicals that partition predominantly into one environmental compartment was up to 2 orders of magnitude larger compared to uncertainty. For the other (less persistent) chemicals, uncertainty in the FF was up to 1 order of magnitude larger than spatial variability. Variability and uncertainty in freshwater XFs of the seven chemicals was negligible (k < 1.5). We found that, depending on the chemical and emission scenario, accounting for region-specific environmental characteristics in multimedia fate modelling, as well as accounting for parameter uncertainty, can have a significant influence on freshwater fate factor predictions. Therefore, we conclude that it is important that fate factors should not only account for parameter uncertainty, but for spatial variability as well, as this further increases the reliability of ecotoxicological impacts in LCA.

A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment

The life cycle assessment (LCA) framework has established itself as the leading tool for the assessment of the environmental impact of products. Several works have established the need of integrating the LCA and risk analysis methodologies, due to the several common aspects. One of the ways to reach such integration is through guaranteeing that uncertainties in LCA modeling are carefully treated. It has been claimed that more attention should be paid to quantifying the uncertainties present in the various phases of LCA. Though the topic has been attracting increasing attention of practitioners and experts in LCA, there is still a lack of understanding and a limited use of the available statistical tools. In this work, we introduce a protocol to conduct global sensitivity analysis in LCA. The article focuses on the life cycle impact assessment (LCIA), and particularly on the relevance of global techniques for the development of trustable impact assessment models. We use a novel characterization model developed for the quantification of the impacts of noise on humans as a test case. We show that global SA is fundamental to guarantee that the modeler has a complete understanding of: (i) the structure of the model and (ii) the importance of uncertain model inputs and the interaction among them.

Integration of life cycle assessment and regional emission information in agricultural systems

BACKGROUND

Life cycle assessment (LCA) is a compilation and evaluation of the input energy and materials, output emissions and the potential environmental impacts of a product, service or system throughout its life cycle. While methodological issues of LCA are still being developed, much research is being conducted worldwide in order to improve them. One of the important advances in LCA is a regionalised LCA, i.e. the development of regionalised databases, inventories, and impact assessment methods and models.

RESULTS

Regional emission information (REI) was developed and integrated with the characterisation results in LCA of an agricultural product in the study area. Comparison of outcomes obtained with LCA characterisation results that did not include REI shows that the characterisation results taking REI into account are much higher as regards human toxicity, from 0.02% to 0.18%, freshwater ecotoxicity from 89% to 99% and terrestrial ecotoxicity from 8.006% to 26.177%.

CONCLUSION

Results of current LCA studies on agricultural products and systems that do not include REI are under-estimating the life cycle environmental impact. For the LCA of agricultural products and systems, the REI as well as regionalised life cycle inventory data should be developed and integrated into the current LCA approach.

Effects of input uncertainty and variability on the modelled environmental fate of organic pollutants under global climate change scenarios

Global climate change (GCC) is expected to influence the fate, exposure and risks of organic pollutants to wildlife and humans. Multimedia chemical fate models have been previously applied to estimate how GCC affects pollutant concentrations in the environment and biota, but previous studies have not addressed how uncertainty and variability of model inputs affect model predictions. Here, we assess the influence of climate variability and chemical property uncertainty on future projections of environmental fate of six polychlorinated biphenyl congeners under different GCC scenarios using a spreadsheet version of the ChemCAN model and the Crystal Ball® software. Regardless of emission mode, results demonstrate: (i) uncertainty in degradation half-lives dominates the variance of modelled absolute levels of PCB congeners under GCC scenarios; (ii) when the ratios of predictions under GCC to predictions under present day climate are modelled, climate variability dominates the variance of modelled ratios; and (iii) the ratios also indicate a maximum of about a factor of 2 change in the long-term average environmental concentrations due to GCC that is forecasted between present conditions and the period between 2080 and 2099. We conclude that chemical property uncertainty does not preclude assessing relative changes in a GCC scenario compared to a present-day scenario if variance in model outputs due to chemical properties and degradation half-lives can be assumed to cancel out in the two scenarios.

Influence of global climate change on chemical fate and bioaccumulation: the role of multimedia models

Multimedia environmental fate models are valuable tools for investigating potential changes associated with global climate change, particularly because thermodynamic forcing on partitioning behavior as well as diffusive and nondiffusive exchange processes are implicitly considered. Similarly, food-web bioaccumulation models are capable of integrating the net effect of changes associated with factors such as temperature, growth rates, feeding preferences, and partitioning behavior on bioaccumulation potential. For the climate change scenarios considered in the present study, such tools indicate that alterations to exposure concentrations are typically within a factor of 2 of the baseline output. Based on an appreciation for the uncertainty in model parameters and baseline output, the authors recommend caution when interpreting or speculating on the relative importance of global climate change with respect to how changes caused by it will influence chemical fate and bioavailability.

Prioritizing chemicals and data requirements for screening-level exposure and risk assessment

BACKGROUND

Scientists and regulatory agencies strive to identify chemicals that may cause harmful effects to humans and the environment; however, prioritization is challenging because of the large number of chemicals requiring evaluation and limited data and resources.

OBJECTIVES

We aimed to prioritize chemicals for exposure and exposure potential and obtain a quantitative perspective on research needs to better address uncertainty in screening assessments.

METHODS

We used a multimedia mass balance model to prioritize > 12,000 organic chemicals using four far-field human exposure metrics. The propagation of variance (uncertainty) in key chemical information used as model input for calculating exposure metrics was quantified.

RESULTS

Modeled human concentrations and intake rates span approximately 17 and 15 orders of magnitude, respectively. Estimates of exposure potential using human concentrations and a unit emission rate span approximately 13 orders of magnitude, and intake fractions span 7 orders of magnitude. The actual chemical emission rate contributes the greatest variance (uncertainty) in exposure estimates. The human biotransformation half-life is the second greatest source of uncertainty in estimated concentrations. In general, biotransformation and biodegradation half-lives are greater sources of uncertainty in modeled exposure and exposure potential than chemical partition coefficients.

CONCLUSIONS

Mechanistic exposure modeling is suitable for screening and prioritizing large numbers of chemicals. By including uncertainty analysis and uncertainty in chemical information in the exposure estimates, these methods can help identify and address the important sources of uncertainty in human exposure and risk assessment in a systematic manner.

Uncertainty propagation in life cycle assessment of biodiesel versus diesel: global warming and non-renewable energy

Uncertainty information is essential for the proper use of life cycle assessment and environmental assessments in decision making. To investigate the uncertainties of biodiesel and determine the level of confidence in the assertion that biodiesel is more environmentally friendly than diesel, an explicit analytical approach based on the Taylor series expansion for lognormal distribution was applied in the present study. A biodiesel case study demonstrates the probability that biodiesel has a lower global warming and non-renewable energy score than diesel, that is 92.3% and 93.1%, respectively. The results indicate the level of confidence in the assertion that biodiesel is more environmentally friendly than diesel based on the global warming and non-renewable energy scores.

Spatial variations of human health risk associated with exposure to chlorination by-products occurring in drinking water

During disinfection, chlorine reacts with organic matter present in drinking water and forms various undesirable chlorinated by-products (CBPs). This paper describes a study of the spatial variability of human health risk (i.e., cancer effects) from CBP exposure through drinking water in a specific region. The region under study involves nine drinking water distribution systems divided into several zones based on their characteristics. The spatial distribution of cancer risk (CR) was estimated using two years of data (2006-2008) on various CBP species. In this analysis, trihalomethanes (THMs) and haloacetic acids (HAAs) served as surrogates for CBPs. Three possible routes of exposure (i.e., via ingestion, inhalation and dermal contact) were considered for each selected compound. The cancer risk assessment involved estimating a unit risk (R(T)) in each zone of the selected distribution systems. A probabilistic analysis based on Monte Carlo simulations was employed. Risk assessment results showed that cancer risk varied between systems, but also within individual systems. As a result, the population of the same region was not exposed to the same risk associated with CBPs in drinking water. Unacceptable levels (i.e., R(T) > 10(-4)) for the estimated CR were determined for several zones in the studied region. This study demonstrates that a spatial-based analysis performed to represent the spatial distribution of risk estimates can be helpful in identifying suitable risk management strategies. Suggestions for improving the risk analysis procedure are also presented.

Multimedia transport and risk assessment of organophosphate pesticides and a case study in the northern San Joaquin Valley of California

This paper presents a framework for cumulative risk characterization of human exposure to pesticides through multiple exposure pathways. This framework is illustrated through a case study of selected organophosphate (OP) pesticides in the northern San Joaquin Valley of California. Chemical concentrations in environmental media were simulated using a multimedia environmental fate model, and converted to contamination levels in exposure media. The risk characterization in this study was based on a residential-scale exposure to residues of multiple pesticides through everyday activities. Doses from a mixture of OP pesticides that share a common mechanism of toxicity were estimated following US Environmental Protection Agency guidelines for cumulative risk analysis. Uncertainty in the human exposure parameters was included in the Monte Carlo simulation in order to perform stochastic calculations for intakes and corresponding risks of OP pesticides. Risk of brain acetylcholinesterase inhibition was reported as margins of exposure (MOEs) of the 99.9th population percentile for two age groups living in the northern San Joaquin Valley during 1992-2005. Diet was identified as the dominant exposure pathway in cumulative exposure and risk, while the temporal trend and spatial variation in total MOE levels were associated with exposures to contaminated drinking water and ambient air. Uniformly higher risks were observed for children because of their greater inhalation and ingestion rates per body weight, relative to adults. The results indicated that exposures for children were about twice of those estimated for adults. Concerns over children's exposure to OP pesticide through food and water ingestion were suggested based on the spatiotemporal variations predicted for the subchronic MOEs at the 99.9th percentile of exposure in the study area.

Validation of predicted exponential concentration profiles of chemicals in soils

Multimedia mass balance models assume well-mixed homogeneous compartments. Particularly for soils, this does not correspond to reality, which results in potentially large uncertainties in estimates of transport fluxes from soils. A theoretically expected exponential decrease model of chemical concentrations with depth has been proposed, but hardly tested against empirical data. In this paper, we explored the correspondence between theoretically predicted soil concentration profiles and 84 field measured profiles. In most cases, chemical concentrations in soils appear to decline exponentially with depth, and values for the chemical specific soil penetration depth (d(p)) are predicted within one order of magnitude. Over all, the reliability of multimedia models will improve when they account for depth-dependent soil concentrations, so we recommend to take into account the described theoretical exponential decrease model of chemical concentrations with depth in chemical fate studies. In this model the d(p)-values should estimated be either based on local conditions or on a fixed d(p)-value, which we recommend to be 10cm for chemicals with a log K(ow)>3.

Comparison and analysis of different approaches for estimating the human exposure to phthalate esters

The human exposure estimates for dibutyl (DBP) and bis(2-ethylhexyl) phthalate (DEHP) made by two models EUSES and ACC-Human, and by an estimation approach which utilized measured concentrations in exposure media, were compared. The approach which utilized the latest monitoring data for important exposure media, yielded median daily intakes for adult humans for DBP and DEHP of 2.7 and 5.6 microg/kg body weight per day, respectively, which were in the same range as previous estimates based on back-calculation from urinary metabolites. EUSES estimated average daily intakes of DBP and DEHP for humans that were between 8 and 13 times lower. ACC-Human does not estimate average daily intakes, but ACC-Human-estimated human milk concentrations/fugacities were more than a thousand times lower than measured concentrations/fugacities in human milk. It was concluded that the two models underestimate human exposure to phthalate esters because they consider only a few key pathways that are known to be important for other, more persistent, hydrophobic organic compounds. Further, it was shown that there are differences between the two models on the methodology for estimating concentrations in exposure media such as vegetation, milk, beef and fish. ACC-Human uses a mechanistic approach for estimating transfer through aquatic and terrestrial food chains that are known to be important for human exposure to persistent, hydrophobic organics and can, unlike EUSES, account for food chain metabolism. It proved difficult, however, to obtain organism metabolism rates needed as model inputs to ACC-Human. If exposure estimates of phthalate esters are needed, it is recommended to use an estimation approach based on high quality monitoring data as presented here and/or back-calculate daily intake from concentrations of metabolites in human urine samples from the general population.

A multimedia environmental model of chemical distribution: fate, transport, and uncertainty analysis

This paper presented a framework for analysis of chemical concentration in the environment and evaluation of variance propagation within the model. This framework was illustrated through a case study of selected organic compounds of benzo[alpha]pyrene (BAP) and hexachlorobenzene (HCB) in the Great Lakes region. A multimedia environmental fate model was applied to perform stochastic simulations of chemical concentrations in various media. Both uncertainty in chemical properties and variability in hydrometeorological parameters were included in the Monte Carlo simulation, resulting in a distribution of concentrations in each medium. Parameters of compartmental dimensions, densities, emissions, and background concentrations were assumed to be constant in this study. The predicted concentrations in air, surface water and sediment were compared to reported data for validation purpose. Based on rank correlations, a sensitivity analysis was conducted to determine the influence of individual input parameters on the output variance for concentration in each environmental medium and for the basin-wide total mass inventory. Results of model validation indicated that the model predictions were in reasonable agreement with spatial distribution patterns, among the five lake basins, of reported data in the literature. For the chemical and environmental parameters given in this study, parameters associated to air-ground partitioning (such as moisture in surface soil, vapor pressure, and deposition velocity) and chemical distribution in soil solid (such as organic carbon partition coefficient and organic carbon content in root-zone soil) were targeted to reduce the uncertainty in basin-wide mass inventory. This results of sensitivity analysis in this study also indicated that the model sensitivity to an input parameter might be affected by the magnitudes of input parameters defined by the parameter settings in the simulation scenario. Therefore, uncertainty and sensitivity analyses for environmental fate models was suggested to be conducted after the model output was validated based on an appropriate input parameter settings.

Using a probabilistic approach in an ecological risk assessment simulation tool: test case for depleted uranium (DU)

A probabilistic approach was applied in an ecological risk assessment (ERA) to characterize risk and address uncertainty employing Monte Carlo simulations for assessing parameter and risk probabilistic distributions. This simulation tool (ERA) includes a Window's based interface, an interactive and modifiable database management system (DBMS) that addresses a food web at trophic levels, and a comprehensive evaluation of exposure pathways. To illustrate this model, ecological risks from depleted uranium (DU) exposure at the US Army Yuma Proving Ground (YPG) and Aberdeen Proving Ground (APG) were assessed and characterized. Probabilistic distributions showed that at YPG, a reduction in plant root weight is considered likely to occur (98% likelihood) from exposure to DU; for most terrestrial animals, likelihood for adverse reproduction effects ranges from 0.1% to 44%. However, for the lesser long-nosed bat, the effects are expected to occur (>99% likelihood) through the reduction in size and weight of offspring. Based on available DU data for the firing range at APG, DU uptake will not likely affect survival of aquatic plants and animals (<0.1% likelihood). Based on field and laboratory studies conducted at APG and YPG on pocket mice, kangaroo rat, white-throated woodrat, deer, and milfoil, body burden concentrations observed fall into the distributions simulated at both sites.

Life cycle assessment part 2: current impact assessment practice

Providing our society with goods and services contributes to a wide range of environmental impacts. Waste generation, emissions and the consumption of resources occur at many stages in a product's life cycle-from raw material extraction, energy acquisition, production and manufacturing, use, reuse, recycling, through to ultimate disposal. These all contribute to impacts such as climate change, stratospheric ozone depletion, photooxidant formation (smog), eutrophication, acidification, toxicological stress on human health and ecosystems, the depletion of resources and noise-among others. The need exists to address these product-related contributions more holistically and in an integrated manner, providing complimentary insights to those of regulatory/process-oriented methodologies. A previous article (Part 1, Rebitzer et al., 2004) outlined how to define and model a product's life cycle in current practice, as well as the methods and tools that are available for compiling the associated waste, emissions and resource consumption data into a life cycle inventory. This article highlights how practitioners and researchers from many domains have come together to provide indicators for the different impacts attributable to products in the life cycle impact assessment (LCIA) phase of life cycle assessment (LCA).

Regional differences in chemical fate model outcome

The fate of anthropogenic substances in the environment is increasingly determined using multimedia mass balance models. It is, therefore, critical to fully understand how such models work and what their limitations are. The effects of uncertainty and variation in the chemical properties, discharges, and landscape parameters on model outcome have been examined by other researchers. Here, the role of landscape properties in controlling region-to-region differences in chemical fate is examined. Specifically, regions of Canada and the ChemCAN model are used to explore the region-to-region difference in fate for benzo[a]pyrene, hexachlorobenzene, tetrachloroethylene, alpha-hexachlorocyclohexane, 2,2',5,5'-tetrachlorobiphenyl (PCB 52), and atrazine emitted individually to air, water, and soil. To facilitate the same analysis in other places a description of the model and the methods for obtaining the landscape parameters used here are given. Differences in fate are the unique result of combining the input parameters of chemical properties, emission data, and landscape parameters. While region-to-region differences are small compared to the chemical-to-chemical differences that may span many orders of magnitude for physical-chemical or degradation properties, chemical fate is not the same for regions of differing landscape parameters. It is therefore concluded that the quality of results obtained from regional environmental fate models can be improved by the use of region-specific landscape parameters.

Effects of time-averaging climate parameters on predicted multicompartmental fate of pesticides and POPs

With the aim to investigate the justification of time-averaging of climate parameters in multicompartment modelling the effects of various climate parameters and different modes of entry on the predicted substances' total environmental burdens and the compartmental fractions were studied. A simple, non-steady state zero-dimensional (box) mass-balance model of intercompartmental mass exchange which comprises four compartments was used for this purpose. Each two runs were performed, one temporally unresolved (time-averaged conditions) and a time-resolved (hourly or higher) control run. In many cases significant discrepancies are predicted, depending on the substance and on the parameter. We find discrepancies exceeding 10% relative to the control run and up to an order of magnitude for prediction of the total environmental burden from neglecting seasonalities of the soil and ocean temperatures and the hydroxyl radical concentration in the atmosphere and diurnalities of atmospheric mixing depth and the hydroxyl radical concentration in the atmosphere. Under some conditions it was indicated that substance sensitivity could be explained by the magnitude of the sink terms in the compartment(s) with parameters varying. In general, however, any key for understanding substance sensitivity seems not be linked in an easy manner to the properties of the substance, to the fractions of its burden or to the sink terms in either of the compartments with parameters varying. Averaging of diurnal variability was found to cause errors of total environmental residence time of different sign for different substances. The effects of time-averaging of several parameters are in general not additive but synergistic as well as compensatory effects occur. An implication of these findings is that the ranking of substances according to persistence is sensitive to time resolution on the scale of hours to months. As a conclusion it is recommended to use high temporal resolution in multi-media modelling.

Measures of importance for economic analysis based on decision modeling

In probabilistic economic analysis, the uncertainty concerning input parameters is quantified, and determines the level of uncertainty over the optimal decision. Researchers from a wide range of disciplines employ mathematical models to simulate complex processes. Common through many such disciplines is the conduct of importance analysis to determine those input parameters that contribute most to the uncertainty over the optimal decision based on the results of the analysis. In this study, we compare a range of potential importance measures to see how they compare with methods used in economic analysis. Techniques were classified as variance/correlation, information, probability, entropy, or elasticity-based measures. A selection of the most commonly used measures were applied to an economic model of treatment for patients with Parkinson's disease. Techniques were evaluated in terms of their ranking of variables, complexity, and interpretation.

Human health and environmental risk assessment: the need for a more harmonised and integrated approach

Historically the procedures for human risk assessment and for risk assessment have developed separately with different terminologies and separate data bases. The identification that there are many common features and that sharing of certain types of data for risk assessment purposes would be beneficial is a driver towards a better integration of their procedures. Risk assessors are facing increasing challenges from governments, stimulated by public pressure for (i) human and environmental risk assessments of an ever growing number of products and processes, (ii) further restrictions of the use of animal tests and human studies on ethical grounds, (iii) the requirement to demonstrate that the assessments are independent, transparent and of high quality, (iv) reducing resources in particular a diminishing number of individuals with the scientific depth, breadth and independence act as risk assessors, (v) the need to incorporate new sciences continually and new discoveries into the risk assessment process. It is important for society that these challenges are met successfully. This requires changes in both risk assessment procedures and in the infrastructure needed to support them. Risk assessment is a science based process for establishing the likelihood of adverse effects to human health and to the environment from specific chemical, biological and physical agents. In the last few years there has been a renewed effort, by international bodies such as WHO, OECD and the EU, to achieve a more integrated and harmonised approach to risk assessment. Before examining the potential for a more integrated approach to risk assessment it is timely to consider the key factors which have led to the current position.

Geographical scenario uncertainty in generic fate and exposure factors of toxic pollutants for life-cycle impact assessment

In environmental life-cycle assessments (LCA), fate and exposure factors account for the general fate and exposure properties of chemicals under generic environmental conditions by means of 'evaluative' multi-media fate and exposure box models. To assess the effect of using different generic environmental conditions, fate and exposure factors of chemicals emitted under typical conditions of (1). Western Europe, (2). Australia and (3). the United States of America were compared with the multi-media fate and exposure box model USES-LCA. Comparing the results of the three evaluative environments, it was found that the uncertainty in fate and exposure factors for ecosystems and humans due to choice of an evaluative environment, as represented by the ratio of the 97.5th and 50th percentile, is between a factor 2 and 10. Particularly, fate and exposure factors of emissions causing effects in fresh water ecosystems and effects on human health have relatively high uncertainty. This uncertainty is mainly caused by the continental difference in the average soil erosion rate, the dimensions of the fresh water and agricultural soil compartment, and the fraction of drinking water coming from ground water.

Joint persistence of transformation products in chemicals assessment: case studies and uncertainty analysis

The joint persistence (JP) quantifies the environmental persistence of a parent compound and a selection of relevant transformation products. Here, the importance as well as the uncertainty of the JP in comparison to the persistence of the parent compound alone (primary persistence, PP) are investigated. To demonstrate the effect of transformation products on the environmental persistence of organic chemicals, three case studies of parent compounds (nonylphenol ethoxylates, perchloroethylene, atrazine) and transformation products are investigated in detail with a multimedia fate model. Comparison of the PP and JP values shows that transformation products can significantly increase the persistence. In addition to the point estimates of PP and JP, the associated uncertainties are investigated. For each of the case studies, the chemical-specific input parameters of all compounds are varied and the corresponding variance of the PP and JP is determined by Monte Carlo simulations. Interestingly, the higher number of input parameters required for the JP does not necessarily increase the uncertainty of the JP as compared to that of the PP alone. An exact mathematical expression specifying the contribution of each transformation product to the JP is given. When transformation products are grouped in different generations, it becomes discernible that the first generation increases the JP most; the later generations are of decreasing importance. Finally, the effect of incomplete knowledge of the transformation products and their properties on the JP results is discussed. For reliable JP estimates, knowledge of the first generation transformation products and their degradation rate constants is required.

Model description of an alternately operated wastewater treatment plant--evaluation of the applicability of SimpleTreat

Alternately operated wastewater treatment plants (WWTPs) are fundamentally different compared to conventional activated sludge WWTPs with respect to flow patterns and aeration in the biological reactors. Several model applications exist for conventional WWTPs, e.g. SimpleTreat, and in this study the effect of substituting a complex discontinuous operation, involving alternating degradation and flow conditions between two reactors, with one single bioreactor with continuos flow (SimpleTreat) has been investigated by setting up two models representing the respective operation schemes. The discontinuous operation induces fluctuations in the outlet concentrations that are not modelled with the single bioreactor model, however, the fluctuations and the associated uncertainties were found to be insignificant compared to the influence of the input parameter uncertainties on the model results. An empirical relationship between an aggregate pseudo-1st order degradation rate for the single bioreactor model and realistic aerobic and anoxic 1st order degradation rates, respectively, has been established. When using this aggregate degradation rate in the single bioreactor model an outlet concentration can be calculated that deviates no more than 2% from the mean outlet concentration from the alternating operation model. For substances with aerobic half-lives longer than approximately 2 h, which is valid for many chemical substances, the aggregate 1st order degradation rate can be set equal to the aerobic 1st order degradation rate.

Intake fraction for multimedia pollutants: a tool for life cycle analysis and comparative risk assessment

We employ the intake fraction (iF) as an effective tool for expressing the source-to-intake relationship for pollutant emissions in life cycle analysis (LCA) or comparative risk assessment. Intake fraction is the fraction of chemical mass emitted into the environment that eventually passes into a member of the population through inhalation, ingestion, or dermal exposure. To date, this concept has been primarily applied to pollutants whose primary route of exposure is inhalation. Here we extend the use of iF to multimedia pollutants with multiple exposure pathways. We use a level III multimedia model to calculate iF for TCDD and compare the result to one calculated from measured levels of dioxin toxic equivalents in the environment. We calculate iF for emissions to air and surface water for 308 chemicals. We correlate the primary exposure route with the magnitudes of the octanol-water partition coefficient, Kow, and of the air-water partitioning coefficient (dimensionless Henry constant), Kaw. This results in value ranges of Kow and Kaw where the chemical exposure route can be classified with limited input data requirements as primarily inhalation, primarily ingestion, or multipathway. For the inhalation and ingestion dominant pollutants, we also define empirical relationships based on chemical properties for quantifying the intake fraction. The empirical relationships facilitate rapid evaluation of many chemicals in terms of the intake. By defining a theoretical upper limit for iF in a multimedia environment we find that iF calculations provide insight into the multimedia model algorithms and help identify unusual patterns of exposure and questionable exposure model results.

Priority assessment of toxic substances in life cycle assessment. III: Export of potential impact over time and space

Toxicity potentials are scaling factors used in life cycle assessment (LCA) indicating their relative importance in terms of potential toxic impacts. This paper presents the results of an uncertainty assessment of toxicity potentials for 181 substances that were calculated with the global nested multi-media fate, exposure and effects model USES-LCA. The variance in toxicity potentials resulting from choices in the modelling procedure was quantified by means of scenario analysis. A first scenario analysis showed to what extent potential impacts in the relatively short term are obscured by the inclusion of impacts on the very long term. Toxicity potentials representing potential impacts over time horizons of 20, 100 and 500 years were compared with toxicity potentials representing potential impacts over an infinite time horizon. Time horizon dependent differences up to 6.5 orders of magnitude were found for metal toxicity potentials, while for toxicity potentials of organic substances under study, differences remain within 0.5 orders of magnitude. The second scenario analysis addressed to what extent potential impacts on the continental scale are obscured by the inclusion of impacts on the global scale. Exclusion of potential impacts on the global scale changed the toxicity potentials of metals and volatile persistent halogenated organics up to 2.3 orders of magnitude. These scenario analyses also provide the basis for determining exports to future generations and outside the emission area.

Human toxicity potentials for life-cycle assessment and toxics release inventory risk screening

The human toxicity potential (HTP), a calculated index that reflects the potential harm of a unit of chemical released into the environment, is based on both the inherent toxicity of a compound and its potential dose. It is used to weight emissions inventoried as part of a life-cycle assessment (LCA) or in the toxics release inventory (TRI) and to aggregate emissions in terms of a reference compound. Total emissions can be evaluated in terms of benzene equivalence (carcinogens) and toluene equivalents (noncarcinogens). The potential dose is calculated using a generic fate and exposure model, CalTOX, which determines the distribution of a chemical in a model environment and accounts for a number of exposure routes, including inhalation, ingestion of produce, fish, and meat, and dermal contact with water and soil. Toxicity is represented by the cancer potency q1* for carcinogens and the safe dose (RfD, RfC) for noncarcinogens. This article presents cancer and noncancer HTP values for air and surface-water emissions of 330 compounds. This list covers 258 chemicals listed in U.S. Environmental Protection Agency TRI, or 79 weight-% of the TRI releases to air reported in 1997.

Priority assessment of toxic substances in life cycle assessment. Part II: assessing parameter uncertainty and human variability in the calculation of toxicity potentials

Toxicity potentials are standard values used in life cycle assessment (LCA) to enable a comparison of toxic impacts between substances. This paper presents the results of an uncertainty assessment of toxicity potentials that were calculated with the global nested multi-media fate, exposure and effects model USES-LCA. The variance in toxicity potentials resulting from input parameter uncertainties and human variability was quantified by means of Monte Carlo analysis with Latin Hypercube sampling (LHS). For Atrazine, 2,3,7,8-TCDD and Lead, variation, expressed by the ratio of the 97.5%-ile and the 2.5%-ile, ranges from about 1.5 to 6 orders of magnitude. The major part of this variation originates from a limited set of substance-specific input parameters, i.e. parameters that describe transport mechanisms, substance degradation, indirect exposure routes and no-effect concentrations. Considerable correlations were found between the toxicity potentials of one substance, in particular within one impact category. The uncertainties and correlations reported in the present study may have a significant impact on the outcome of LCA case studies.