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.     

Simulating uncertainty in climate-pest models with fuzzy numbers

Inputs in climate-pest models are commonly expressed as point estimates ('crisp' numbers), which implies perfect knowledge of the system in study. In reality, however, all model inputs harbor some level of uncertainty. This is particularly true for climate change impact assessments where the inputs (i.e., climate projections) are highly uncertain. In this study, uncertainties in climate projections were expressed as 'fuzzy' numbers; these are uncertain numbers for which one knows that there is a range of possible values and that some values are 'more possible' than others. A generic pest risk model incorporating the combined effects of temperature, soil moisture, and cold stress was implemented in a fuzzy spreadsheet environment and run with three climate scenarios: (1) present climate (control run); (2) crisp climate change; and (3) fuzzy climate change. Under the crisp climate change scenario, winter and summer temperatures and precipitation were altered using best estimates (averaged predictions from the 1995 assessment report of the Intergovernmental Panel on Climate Change [IPCC]). Under the fuzzy scenario, climate changes were expressed as triangular fuzzy numbers, utilizing the extremes (lowest and highest predictions from the IPCC report) in addition to the best estimates. Under each scenario, environmental favorability was calculated for six locations in two geographical regions (Central North America and Southern Europe) with two hypothetical pest species having temperate or mediterranean climate requirements. Simulations with the crisp climate change scenario suggested only minor changes in overall environmental favorability compared with the control run. When simulations were conducted with the fuzzy climate change scenario, however, important changes in environmental favorability emerged, particularly in Southern Europe. In that region, the possibility of considerably increased winter precipitation led to increased values of environmental favorability. However, the simulations also showed that this result harbored a very broad range of possible outcomes. The results support the notion that uncertainty in climate change projections must be reduced before reliable impact assessments can be achieved.     

Prediction of overall persistence and long-range transport potential with multimedia fate models: robustness and sensitivity of results

The hazard indicators persistence (P) and long-range transport potential (LRTP) are used in chemicals assessment to characterize chemicals with regard to the temporal and spatial extent of their environmental exposure. They are often calculated based on the results of multimedia fate models. The environmental and substance-specific input parameters of such models are subject to a range of methodological uncertainties and also influenced by natural variability. We employed probabilistic uncertainty analysis to quantify variance in P and LRTP predictions for chemicals with different partitioning and transport behavior. Variance found in the results is so large that it prevents a clear distinction between chemicals. Additionally, only small improvements are observed when evaluating the results relative to a benchmark chemical. This can be explained by the dominance of substance-specific parameters and the only small direct influence of environmental parameters on P and LRTP as model outcomes. The findings underline the importance of learning how environmental conditions cause variability in substance behavior for improved substance ranking and classification.     

Climate change influence on POPs distribution and fate: a case study

Climate change has the potential of affecting the behaviour and distribution of organic pollutants, including POPs. Direct effects of climate change, like temperature increase, modification of wind and precipitation patterns, sea level rise, snow and ice cover, may be very effective in altering the partitioning of POPs among the environmental compartments. Other consequences of future climate scenarios may imply the alteration of degradation rates, soil properties (and hence land use), air-particle partitioning of chemicals and so forth. A case study is here presented to illustrate the major implications of climate change on the long term at the local scale. A dynamic multimedia model was applied to selected PCB and PCDD/F congeners to simulate the effects of climate change on their distribution and fluxes over the next 50 y in the Venice Lagoon (Italy). Different climate change scenarios were tested, finding noticeable variations in POPs concentration even for minor environmental changes. PCBs and PCDFs environmental concentrations may differ by a factor two in a moderate climate change scenario, compared to a situation with stable climate over the next 50 y. However, model results also suggest that if global warming may have the potential of reducing the environmental levels of these chemicals, it would probably enhance their mobility and hence their potential for long range atmospheric transport.     

Modeling the influence of climate change on the mass balance of polychlorinated biphenyls in the Adriatic Sea

Climate forcing is forecasted to influence the Adriatic Sea region in a variety of ways, including increasing temperature, and affecting wind speeds, marine currents, precipitation and water salinity. The Adriatic Sea is intensively developed with agriculture, industry, and port activities that introduce pollutants to the environment. Here, we developed and applied a Level III fugacity model for the Adriatic Sea to estimate the current mass balance of polychlorinated biphenyls in the Sea, and to examine the effects of a climate change scenario on the distribution of these pollutants. The model’s performance was evaluated for three PCB congeners against measured concentrations in the region using environmental parameters estimated from the 20th century climate scenario described in the Special Report on Emission Scenarios (SRES) by the IPCC, and using Monte Carlo uncertainty analysis. We find that modeled fugacities of PCBs in air, water and sediment of the Adriatic are in good agreement with observations. The model indicates that PCBs in the Adriatic Sea are closely coupled with the atmosphere, which acts as a net source to the water column. We used model experiments to assess the influence of changes in temperature, wind speed, precipitation, marine currents, particulate organic carbon and air inflow concentrations forecast in the IPCC A1B climate change scenario on the mass balance of PCBs in the Sea. Assuming an identical PCBs’ emission profile (e.g. use pattern, treatment/disposal of stockpiles, mode of entry), modeled fugacities of PCBs in the Adriatic Sea under the A1B climate scenario are higher because higher temperatures reduce the fugacity capacity of air, water and sediments, and because diffusive sources to the air are stronger.     

Impact of future climate changes on high pollution levels

Changes in climate variability as well as changes in extreme weather and climate events in the 20th century, especially those that took place during the last two to three decades of the 20th century, have been discussed in many recent scientific publications. Attempts to project the results of such studies in the future have been made under different assumptions. In this paper, we have chosen one of the well-known scenarios predicting changes of the climate in the world during the last 30 years of the 21st century. This scenario is used, together with several general predictions related to the future climate, to produce three climatic scenarios. The derived climatic scenarios are used to calculate predictions for future pollution levels in Denmark and in Europe by applying the Unified Danish Eulerian Model (UNI-DEM), on a space domain containing the whole of Europe.     

Aquatic fate assessment of the polycyclic musk fragrance HHCB. Scenario and variability analysis in accordance with the EU risk assessment guidelines

By means of the environmental fate and distribution models laid down in the Technical Guidance Documents (TGD) and implemented in the European Union System for the Evaluation of Substances (EUSES) environmental concentrations of the polycyclic musk fragrance HHCB (1,3,4,6,7,8-hexahydro-4,6,6,7,8,8-hexamethyl-cyclopenta-[g]-2- benzopyrane; trade name: e.g. Galaxolide) were calculated for the aquatic environment under consideration of various scenarios. The results were then compared to monitoring data from the region of North Rhine-Westphalia (River Ruhr). An uncertainty analysis was carried out to determine sensitive parameters, to integrate environmental variability and to confirm the model's calculations. The standard scenario of EUSES overestimates the measured concentrations, which confirms the conservative nature of the calculations. The regional-specific scenarios lead to lower deviations from the measured values than the standard scenario. Deviations range from one to two orders of magnitude in the effluent of sewage treatment plants; they amount to one order of magnitude for surface water concentrations on a local scale and conform to monitoring data on a regional scale. The use of measured bioconcentration factors for fish instead of estimated ones reduces deviations remarkably. The investigation reveals that unrealistic worst-case calculations of HHCB can at best be ameliorated by the application of more realistic emission rates and measured bioconcentration factors. The use of regional-specific parameters also diminishes the deviations of the calculations from the measured concentrations.     

Modelling the impact of nitrogen deposition, climate change and nutrient limitations on tree carbon sequestration in Europe for the period 1900-2050

We modelled the combined effects of past and expected future changes in climate and nitrogen deposition on tree carbon sequestration by European forests for the period 1900-2050. Two scenarios for deposition (current legislation and maximum technically feasible reductions) and two climate scenarios (no change and SRES A1 scenario) were used. Furthermore, the possible limitation of forest growth by calcium, magnesium, potassium and phosphorus is investigated. The area and age structure of the forests was assumed to stay constant to observations during the period 1970-1990. Under these assumptions, the simulations show that the change in forest growth and carbon sequestration in the past is dominated by changes in nitrogen deposition, while climate change is the major driver for future carbon sequestration. However, its impact is reduced by nitrogen availability. Furthermore, limitations in base cations, especially magnesium, and in phosphorus may significantly affect predicted growth in the future.     

Projecting Climate Change Effects on Forest Net Primary Productivity in Subtropical Louisiana,USA

This study projected responses of forest net primary productivity (NPP) to three climate change scenarios at a resolution of 5 km × 5 km across the state of Louisiana, USA. In addition, we assessed uncertainties associated with the NPP projection at the grid and state levels. Climate data of the scenarios were derived from Community Climate System Model outputs. Changes in annual NPP between 2000 and 2050 were projected with the forest ecosystem model PnET-II. Results showed that forest productivity would increase under climate change scenarios A1B and A2, but with scenario B1, it would peak during 2011–2020 and then decline. The projected average NPP under B1 over the years from 2000 to 2050 was significantly different from those under A1B and A2. Forest NPP appeared to be primarily a function of temperature, not precipitation. Uncertainties of the NPP projection were due to large spatial resolution of the climate variables. Overall, this study suggested that in order to project effects of climate change on forest ecosystem at regional level, modeling uncertainties could be reduced by increasing the spatial resolution of the climate projections.     

Development of a Dynamic Aquatic Model (DynA Model): Estimating Temporal Emissions of DDT to Lake Maggiore (N. Italy)

- DOI: http://dx.doi.org/10.1065/espr2006.01.009 Background, Aims and Scope Most existing models used to describe the fate of chemicals in surface water and sediment generally consider a 'static scenario', in which a contaminant is discharged at a constant rate and environmental input parameters do not change during the simulation time. This approach is not suitable in environmental scenarios characterized by daily or periodic changes of several input parameters. The aim of this study is to estimate approximate emissions of DDT lo Lake Maggiore using a new surface water model, (DynA Model) that describes the fate of a chemical in a dynamic scenario. Methods The model is developed on the grounds of an existing and validated model (QWASI). A numerical solution was adopted to build the fully dynamic version of the model. Results and Discussion The model was applied to Lake Maggiore emitting DDT at a constant rate until steady-state was reached. Emissions were stopped and later sporadic 'pulse' emissions were added. This was done to calculate the amount of DDT needed to simulate concentrations close to those measured in water and sediments. This allowed the evaluation of the order of magnitude of emissions. An uncertainty analysis for sediment resuspension was also performed, given the lack of measured resuspension rates. Conclusion The model showed the time response of the Lake Maggiore system to varying emission scenarios and provided what are regarded as reasonable estimates of DDT emissions. The model demonstrated the importance of sediment-water exchange. Recommendation and Outlook In order to better calculate DDT concentrations the model should be run with different discharge scenarios to clarify the time trends of concentrations, possibly with the use of different sets of measured data (such as biota and sediment deposition/resuspension rates).     

Modelling the fate of persistent organic pollutants in Europe: parameterisation of a gridded distribution model

A regionally segmented multimedia fate model for the European continent is described together with an illustrative steady-state case study examining the fate of gamma-HCH (lindane) based on 1998 emission data. The study builds on the regionally segmented BETR North America model structure and describes the regional segmentation and parameterisation for Europe. The European continent is described by a 5 degrees x5 degrees grid, leading to 50 regions together with four perimetric boxes representing regions buffering the European environment. Each zone comprises seven compartments including; upper and lower atmosphere, soil, vegetation, fresh water and sediment and coastal water. Inter-regions flows of air and water are described, exploiting information originating from GIS databases and other georeferenced data. The model is primarily designed to describe the fate of Persistent Organic Pollutants (POPs) within the European environment by examining chemical partitioning and degradation in each region, and inter-region transport either under steady-state conditions or fully dynamically. A test case scenario is presented which examines the fate of estimated spatially resolved atmospheric emissions of lindane throughout Europe within the lower atmosphere and surface soil compartments. In accordance with the predominant wind direction in Europe, the model predicts high concentrations close to the major sources as well as towards Central and Northeast regions. Elevated soil concentrations in Scandinavian soils provide further evidence of the potential of increased scavenging by forests and subsequent accumulation by organic-rich terrestrial surfaces. Initial model predictions have revealed a factor of 5-10 underestimation of lindane concentrations in the atmosphere. This is explained by an underestimation of source strength and/or an underestimation of European background levels. The model presented can further be used to predict deposition fluxes and chemical inventories, and it can also be adapted to provide characteristic travel distances and overall environmental persistence, which can be compared with other long-range transport prediction methods.     

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.     

Evaluating multimedia/multipathway model intake fraction estimates using POP emission and monitoring data

This paper presents a structured evaluation of a novel multimedia chemical fate and multi-pathway human exposure model for Western Europe, IMPACT 2002, using data for PCDD/F congeners. PCDD/F congeners provide an illustration of the potential use of POPs (Persistent Organic Pollutant) data for the evaluation of such models. Based on available emission estimates, model predictions with and without spatial resolution are evaluated at three different stages against monitored data: at environmental contamination levels, food exposure concentration, and in terms of human intake fractions (iF): the fraction of an emission that is taken in by the population. The iF is approximately 3.5.10(-3) for emissions of dioxin in Western Europe. This iF compares well to the traditional non-spatial multi-media/-pathway model predictions of 3.9.10(-3) for the same region and to 2.10(-3) for the USA. Approximately 95% of the intake from Western European emissions occurs within the same region, 5% being transferred out of the region in terms of food contaminants and atmospheric advective transport.     

Model and input uncertainty in multi-media fate modeling: benzo[a]pyrene concentrations in Europe

This paper evaluates the contribution of (i) uncertainty in substance properties, (ii) lack of spatial variability, (iii) intermodel differences and (iv) neglecting sorption to black carbon (BC) to the uncertainty of Benzo[a]pyrene (BaP) concentrations in European air, soil and fresh water predicted by the multi-media fate model Simplebox. Uncertainty in substance properties was quantified using probabilistic modeling. The influence of spatial variability was quantified by estimating variation in predicted concentrations with three spatially explicit fate models (Impact 2002, EVn BETR and BETR Global). Intermodel differences were quantified by comparing concentration estimates of Simplebox, Impact 2002, EVn BETR and the European part of BETR Global. Finally, predictions of a BC-inclusive version of Simplebox were compared with predictions of a BC-exclusive version. For air concentrations of BaP, the lack of spatial variability in emissions was most influential. For freshwater concentrations of BaP, intermodel differences and lack of spatial variability in dimensions of fresh water bodies were the dominant sources of uncertainty. For soil, all sources of uncertainty were of comparable magnitude. Our results indicate that uncertainty in Simplebox can be as large as three orders of magnitude for BaP concentrations in the environment and would be substantially underestimated by focusing on one source of uncertainty only.     

Evaluation and comparison of multimedia mass balance models of chemical fate: application of EUSES and ChemCAN to 68 chemicals in Japan

The European Union System for Evaluation of Substances (EUSES) and the ChemCAN chemical fate model are applied to describe the fate of 68 chemicals on two spatial scales in Japan. Emission information on the chemicals has been obtained from Japan's Pollutant Release and Transfer Registry and available monitoring data gathered from government reports. Environmental concentrations calculated by the two models for the four primary environmental media of air, water, soil and sediment agree within a factor of 3 for over 70% of the data, and within a factor of 10 for over 87% of the data. Reasons for certain large discrepancies are discussed. Concentrations calculated by the models are generally consistent with the lower range of concentrations that are observed in the environment. Agreement between modeled and observed concentrations is considerably improved by including an estimate of the advective input of chemicals in air from outside Japan. The agreement between the EUSES and ChemCAN models suggests that results of individual chemical assessments are not likely to be significantly affected by the choice of chemical fate model. Primary sources of discrepancy between modeled and observed concentrations are believed to be uncertainties in emission rates, degradation half-lives, and the lack of data on advective inflow of contaminants in air.     

Long-range transport and global fractionation of POPs: insights from multimedia modeling studies

The long-range transport of persistent organic pollutants (POPs) is investigated with two multimedia box models of the global system. ChemRange is a purely evaluative, one-dimensional steady-state (level III) model; CliMoChem is a two-dimensional model with different temperatures, land/water ratios and vegetation types in different latitudinal zones. Model results are presented for three case studies: (i) the effect of atmospheric aerosol particles on the long-range transport of POPs, (ii) the effect of oceanic deposition on the long-range transport of different PCB congeners, (iii) the global fractionation of different PCB congeners. The model results for these case studies show: (i) the low atmospheric half-lives estimated for several organochlorine pesticides are likely to be inconsistent with the observed long-range transport of these compounds; (ii) export to the deep sea reduces the potential for long-range transport of highly hydrophobic compounds (but does not remove these chemicals from the biosphere); (iii) there are different meanings of the term global fractionation that refer to different aspects of the fractionation process and need to be distinguished. The case-study results further indicate that the influences of varying environmental conditions on the physicochemical properties and the degradation rate constants of POPs need to be determined.     

Impact of climate change and seasonal trends on the fate of Arctic oil spills

We investigated the effects of a warmer climate, and seasonal trends, on the fate of oil spilled in the Arctic. Three well blowout scenarios, two shipping accidents and a pipeline rupture were considered. We used ensembles of numerical simulations, using the OSCAR oil spill model, with environmental data for the periods 2009–2012 and 2050–2053 (representing a warmer future) as inputs to the model. Future atmospheric forcing was based on the IPCC’s A1B scenario, with the ocean data generated by the hydrodynamic model SINMOD. We found differences in “typical” outcome of a spill in a warmer future compared to the present, mainly due to a longer season of open water. We have demonstrated that ice cover is extremely important for predicting the fate of an Arctic oil spill, and find that oil spills in a warming climate will in some cases result in greater areal coverage and shoreline exposure.     

Developing climatic scenarios for pesticide fate modelling in Europe

A climatic classification for Europe suitable for pesticide fate modelling was constructed using a 3-stage process involving the identification of key climatic variables, the extraction of the dominant modes of spatial variability in those variables and the use of k-means clustering to identify regions with similar climates. The procedure identified 16 coherent zones that reflect the variability of climate across Europe whilst maintaining a manageable number of zones for subsequent modelling studies. An analysis of basic climatic parameters for each zone demonstrates the success of the scheme in identifying distinct climatic regions. Objective criteria were used to identify one representative 26-year daily meteorological series from a European dataset for each zone. The representativeness of each series was then verified against the zonal classifications. These new FOOTPRINT climate zones provide a state-of-the-art objective classification of European climate complete with representative daily data that are suitable for use in pesticide fate modelling.