Multimedia Fate Model Research Articles

Using gridded multimedia model to simulate spatial fate of Benzo[α]pyrene on regional scale

Predicting the environmental multimedia fate is an essential step in the process of assessing the human exposure and health impacts of chemicals released into the environment. Multimedia fate models have been widely applied to calculate the fate and distribution of chemicals in the environment, which can serve as input to a human exposure model. In this study, a grid based multimedia fugacity model at regional scale was developed together with a case study modeling the fate and transfer of Benzo[α]pyrene (BaP) in Bohai coastal region, China. Based on the estimated emission and in-site survey in 2008, the BaP concentrations in air, vegetation, soil, fresh water, fresh water sediment and coastal water as well as the transfer fluxes were derived under the steady-state assumption. The model results were validated through comparison between the measured and modeled concentrations of BaP. The model results indicated that the predicted concentrations of BaP in air, fresh water, soil and sediment generally agreed with field observations. Model predictions suggest that soil was the dominant sink of BaP in terrestrial systems. Flow from air to soil, vegetation and costal water were three major pathways of BaP inter-media transport processes. Most of the BaP entering the sea was transferred by air flow, which was also the crucial driving force in the spatial distribution processes of BaP. The Yellow River, Liaohe River and Daliao River played an important role in the spatial transformation processes of BaP. Compared with advection outflow, degradation was more important in removal processes of BaP. Sensitivities of the model estimates to input parameters were tested. The result showed that emission rates, compartment dimensions, transport velocity and degradation rates of BaP were the most influential parameters for the model output. Monte Carlo simulation was carried out to determine parameter uncertainty, from which the coefficients of variation for the estimated BaP concentrations in air and soil were computed, which were 0.46 and 1.53, respectively. The model output–concentrations of BaP in multimedia environment can be used in human exposure and risk assessment in the Bohai coastal region. The results also provide significant indicators on the likely dominant fate, influence range of emission and transport processes determining behavior of BaP in the Bohai coastal region, which is instrumental in human exposure and risk assessment in the region.

Investigating the need for complex vs. simple scenarios to improve predictions of aquatic ecosystem exposure with the SoilPlus model

A spatially-explicit version of the recent multimedia fate model SoilPlus was developed and applied to predict the runoff of three pesticides in a small agricultural watershed in north-eastern Italy. In order to evaluate model response to increasing spatial resolution, a tiered simulation approach was adopted, also using a dynamic model for surface water (DynA model), to predict the fate of pesticides in runoff water and sediment, and concentrations in river water. Simulation outputs were compared to water concentrations measured in the basin. Results showed that a high spatial resolution and scenario complexity improved model predictions of metolachlor and terbuthylazine in runoff to an acceptable performance (R2 = 0.64–0.70). The importance was also shown of a field-based database of properties (i.e. soil texture and organic carbon, rainfall and water flow, pesticides half-life in soil) in reducing the distance between predicted and measured surface water concentrations and its relevance for risk assessment.

Model-based evaluation of the use of polycyclic aromatic hydrocarbons molecular diagnostic ratios as a source identification tool

Polycyclic Aromatic Hydrocarbons (PAHs) molecular diagnostic ratios (MDRs) are unitless concentration ratios of pair-PAHs with the same molecular weight (MW); MDRs have long been used as a tool for PAHs source identification purposes. In the present paper, the efficiency of the MDR methodology is evaluated through the use of a multimedia fate model, the calculation of characteristic travel distances (CTD) and the estimation of air concentrations for individual PAHs as a function of distance from an initial point source. The results show that PAHs with the same MW are sometimes characterized by substantially different CTDs and therefore their air concentrations and hence MDRs are predicted to change as the distance from the original source increases. From the assessed pair-PAHs, the biggest CTD difference is seen for Fluoranthene (107 km) vs. Pyrene (26 km). This study provides a strong indication that MDRs are of limited use as a source identification tool.

Multimedia fate modeling and comparative impact on freshwater ecosystems of pharmaceuticals from biosolids-amended soils

This study modeled the impact on freshwater ecosystems of pharmaceuticals detected in biosolids following application on agricultural soils. The detected sulfonamides and hydrochlorothiazide displayed comparatively moderate retention in solid matrices and, therefore, higher transfer fractions from biosolids to the freshwater compartment. However, the residence times of these pharmaceuticals in freshwater were estimated to be short due to abiotic degradation processes. The non-steroidal anti-inflammatory mefenamic acid had the highest environmental impact on aquatic ecosystems and warrants further investigation. The estimation of the solid-water partitioning coefficient was generally the most influential parameter of the probabilistic comparative impact assessment. These results and the modeling approach used in this study serve to prioritize pharmaceuticals in the research effort to assess the risks and the environmental impacts on aquatic biota of these emerging pollutants.

General Model for Estimating Partition Coefficients to Organisms and Their Tissues Using the Biological Compositions and Polyparameter Linear Free Energy Relationships

Equilibrium partition coefficients of organic chemicals from water to an organism or its tissues are typically estimated by using the total lipid content in combination with the octanol-water partition coefficient (K(ow)). This estimation method can cause systematic errors if (1) different lipid types have different sorptive capacities, (2) nonlipid components such as proteins have a significant contribution, and/or (3) K(ow) is not a suitable descriptor. As an alternative, this study proposes a more general model that uses detailed organism and tissue compositions (i.e., contents of storage lipid, membrane lipid, albumin, other proteins, and water) and polyparameter linear free energy relationships (PP-LFERs). The values calculated by the established PP-LFER-composition-based model agree well with experimental in vitro partition coefficients and in vivo steady-state concentration ratios from the literature with a root mean squared error of 0.32-0.53 log units, without any additional fitting. This model estimates a high contribution of the protein fraction to the overall tissue sorptive capacity in lean tissues (e.g., muscle), in particular for H-bond donor polar compounds. Direct model comparison revealed that the simple lipid-octanol model still calculates many tissue-water partition coefficients within 1 log unit of those calculated by the PP-LFER-composition-based model. Thus, the lipid-octanol model can be used as an order-of-magnitude approximation, for example, for multimedia fate modeling, but may not be suitable for more accurate predictions. Storage lipid-rich phases (e.g., adipose, milk) are prone to particularly large systematic errors. The new model provides useful implications for validity of lipid-normalization of concentrations in organisms, interpretation of biomonitoring results, and assessment of toxicity.

UNDERSTANDING QUANTITATIVE STRUCTURE–PROPERTY RELATIONSHIPS UNCERTAINTY IN ENVIRONMENTAL FATE MODELING

In cases in which experimental data on chemical-specific input parameters are lacking, chemical regulations allow the use of alternatives to testing, such as in silico predictions based on quantitative structure-property relationships (QSPRs). Such predictions are often given as point estimates; however, little is known about the extent to which uncertainties associated with QSPR predictions contribute to uncertainty in fate assessments. In the present study, QSPR-induced uncertainty in overall persistence (POV ) and long-range transport potential (LRTP) was studied by integrating QSPRs into probabilistic assessments of five polybrominated diphenyl ethers (PBDEs), using the multimedia fate model Simplebox. The uncertainty analysis considered QSPR predictions of the fate input parameters' melting point, water solubility, vapor pressure, organic carbon-water partition coefficient, hydroxyl radical degradation, biodegradation, and photolytic degradation. Uncertainty in POV and LRTP was dominated by the uncertainty in direct photolysis and the biodegradation half-life in water. However, the QSPRs developed specifically for PBDEs had a relatively low contribution to uncertainty. These findings suggest that the reliability of the ranking of PBDEs on the basis of POV and LRTP can be substantially improved by developing better QSPRs to estimate degradation properties. The present study demonstrates the use of uncertainty and sensitivity analyses in nontesting strategies and highlights the need for guidance when compounds fall outside the applicability domain of a QSPR.

Evaluating the fate and behaviour of cyclic volatile methyl siloxanes in two contrasting North American lakes using a multi-media model

The behaviour of cyclic volatile methyl siloxanes (cVMS) in lakes was explored using a fugacity-based steady-state non-equilibrium multimedia fate and transport model (a modified version of QWASI). Three substances were investigated: Octamethylcyclotetrasiloxane (D4), Decamethylcyclopentasiloxane (D5) and Dodecamethylcyclohexasiloxane (D6) in two contrasting North American lakes: Lake Ontario and Lake Pepin (a natural shallow lake on the Mississippi river between Minnesota and Wisconsin). Values for the principal partition coefficients and the hydrolysis rate constant were adjusted for the mean annual temperatures of each lake. Hydrolysis rate constants were also adjusted for the fraction of chemical calculated to be in the freely dissolved phase. Half-lives in sediment were calculated from partitioning theory, assuming hydrolysis can occur only in the dissolved phase. Best estimates of substance-specific emissions were obtained by combining current per capita approximations of usage and fraction lost to domestic waste water, the population of the lake catchment and cVMS removal in waste water treatment. Concentrations were generally lower and chemical residence times longer in Lake Ontario than in Lake Pepin, owing to greater depth, a higher hydraulic retention time and a higher degree of dilution. Overall persistence in Lake Pepin is significantly influenced by the high rate of sediment burial assumed in the model, as well as by a relatively high rate of water discharge. Despite the many similarities of the compounds considered, the dominant loss mechanisms vary significantly and are not the same in each lake system. This highlights the pitfalls of subjective evaluation of chemical fate and illustrates the important role which models have to play in providing a quantitative framework for assessing chemical behaviour objectively under the influence of a complex and interacting set of factors.

Making fate and exposure models for freshwater ecotoxicity in life cycle assessment suitable for organic acids and bases

Freshwater fate and exposure factors were determined for organic acids and bases, making use of the knowledge on electrical interaction of ionizing chemicals and their sorption to particles. The fate factor represents the residence time in the environment whereas exposure factors equal the dissolved fraction of a chemical. Multimedia fate, exposure, and effect model USES–LCA was updated to take into account the influence of ionization, based upon the acid dissociation constant (pKa) of a chemical, and the environmental pH. Freshwater fate (FF) and exposure (XF) factors were determined for 415 acids and 496 bases emitted to freshwater, air, and soil. The relevance of taking account of the degree of ionization of chemicals was tested by determining the ratio (R) of the new vs. fate and exposure factors determined with USES–LCA suitable for neutral chemicals only. Our results show that the majority of freshwater fate and exposure factors of chemicals that are largely ionized in the environment are larger with the ionics model compared to the factors determined with the neutrals model version. RFF ranged from 2.4×10−1 to 1.6×101 for freshwater emissions, from 1.2×10−2 to 2.0×104 for soil emissions and from 5.8×10−2 to 6.0×103 for air emissions, and RXF from 5.3×10−1 to 2.2×101. Prediction of changed solid–water partitioning, implying a change in runoff and in removal via sedimentation, and prediction of negligible air–water partition coefficient, leading to negligible volatilization were the main contributors to the changes in freshwater fate factors.

Simulation and prediction of phenolic compounds fate in Songhua River, China

The demand for numerical models to simulate and predict the transport and fate of organic pollutants in the environment is a reflection of certain restrictions of experimental research. Various phenolic pollutants have been detected at different concentration levels in the Songhua River, China. A multimedia fate model is coupled with the kinematic wave transport equations to accurately and simply characterize dynamic water flow, velocity and depth. The resulting model is applied to describe the temporal and spatial behavior of eight phenol compounds in the Songhua River. The predictive power of this model is evaluated by statistical tests using field observations during different hydrological seasons of the year 2007. The goodness-of-fit of model prediction for phenolic contaminants is, in general, agreeable. For one focal compound, the pathways and mass fluxes from the river system to the surrounding environment are also evaluated. Uncertainty analysis is performed by Monte Carlo stimulation to judge the influence of variability of input parameters on modeled results. The results indicate that the model has the ability to provide decision makers with valuable reference data for consideration of water pollution controls. Model simulation indicates that phenolic pollution in the river during the low-flow period of 2009 is remarkably reduced when compared to the same period of 2007.

Multimedia fate modeling of polycyclic aromatic hydrocarbons (PAHs) in Lake Small Baiyangdian, Northern China

A QWASI (Quantitative Water Air Sediment Interaction) fugacity model was developed to characterize the fate and transfer of fifteen priority PAHs in Lake Small Baiyangdian. The PAH concentrations in the air (air, particulates), water (water, suspended solids, plants and fishes) and sediment (water and solids) as well as the transfer fluxes between adjacent compartments were derived under the steady-state assumption. Sensitivities of the model estimates to input parameters were tested. Monte Carlo simulation was conducted for the uncertainty analysis. The results indicate that there was generally good agreement between the modeled and measured concentrations with the differences within an order of magnitude for the majority of PAH components. The fluxes into and out of the lake as well as each compartment were well-balanced. The average bioaccumulation flux of PAHs by plants was four times higher than that by fishes. The transfer directions of PAHs were from air to water and to sediment. Temperature was the most influential parameter, and was more sensitive to the modeled concentrations of middle- and high-molecular-weight PAHs that were considered as the source of the model uncertainty. The model developed in this study could well characterize the fate and transfer of PAHs in the lake.

Development and Evaluation of the KOrea Insecticide Exposure Model (KOIEM) for Managing Insecticides

The KOrea Insecticide Exposure Model (KOIEM) was developed to facilitate ecological risk-based management of Korean insecticides. KOIEM, applied as a multimedia fate model, evaluates water, soil, air, and vegetation compartments based on three water-body types (streams, ditches, and ponds). Deltamethrin, a pyrethroid insecticide, was used to evaluate and create the model parameters. After exposure of both the stream and the ditch to deltamethrin, the KOIEM-predicted concentrations and the observed levels were in agreement. The model was also evaluated using the accuracy factor (AF), which was 4.32 and 0.35 for the stream and ditch, respectively. Ecological risk assessment was also performed to evaluate the application of KOIEM for four popular South Korean insecticides (cypermethrin, deltamethrin, diazinon, and permethrin). Despite the insecticides having low PECs in water, their risk quotients were typically above 1.0. Thus, KOIEM modification would be required in further studies to account for spatial variation.

New Perspectives on Nanomaterial Aquatic Ecotoxicity: Production Impacts Exceed Direct Exposure Impacts for Carbon Nanotoubes

Environmental impacts due to engineered nanomaterials arise both from releases of the nanomaterials themselves as well as from their synthesis. In this work, we employ the USEtox model to quantify and compare aquatic ecotoxicity impacts over the life cycle of carbon nanotubes (CNTs). USEtox is an integrated multimedia fate, transport, and toxicity model covering large classes of organic and inorganic substances. This work evaluates the impacts of non-CNT emissions from three methods of synthesis (arc ablation, CVD, and HiPco), and compares these to the modeled ecotoxicity of CNTs released to the environment. Parameters for evaluating CNT ecotoxicity are bounded by a highly conservative "worst case" scenario and a "realistic" scenario that draws from existing literature on CNT fate, transport, and ecotoxicity. The results indicate that the ecotoxicity impacts of nanomaterial production processes are roughly equivalent to the ecotoxicity of CNT releases under the unrealistic worst case scenario, while exceeding the results of the realistic scenario by 3 orders of magnitude. Ecotoxicity from production processes is dominated by emissions of metals from electricity generation. Uncertainty exists for both production and release stages, and is modeled using a combination of Monte Carlo simulation and scenario analysis. The results of this analysis underscore the contributions of existing work on CNT fate and transport, as well as the importance of life cycle considerations in allocating time and resources toward research on mitigating the impacts of novel materials.

Integration of an atmospheric dispersion model with a dynamic multimedia fate model: Development and illustration

Growing attention is devoted to understand the influence of the short-term variations in air concentrations on the environmental fate of semivolatile organic compounds (SVOCs) such as polycyclic aromatic hydrocarbons (PAHs). These variations are ascribable to factors such as temperature-mediated air-surface exchange and variability of planetary boundary layer (PBL) height and structure. But when investigating the fate of SVOCs at a local scale, further variability can derive from specific point source contributions. In this context, a new modeling approach (AirPlus) which integrates a previously developed model (AirFug) with an air dispersion model (AERMOD) is presented. The integrated model is illustrated for two PAHs in a Northern Italy scenario. Results show how chemical contributions deriving from background advective inflows, local emissions and a point source interact in an hourly-varying meteorological scenario to determine air concentration rapid changes and the consequent response of the soil compartment.

Indirect human exposure assessment of airborne lead deposited on soil via a simplified fate and speciation modelling approach

In order to estimate the total exposure to the lead emissions from a municipal waste combustion plant in Denmark, the indirect pathway via ingestion of lead deposited on soil has to be quantified. Multi-media fate models developed for both Risk Assessment (RA) and Life Cycle Assessment (LCA) can be used for this purpose, but present high uncertainties in the assessment of metal's fate. More sophisticated and metal-specific geochemical models exist, that could lower the uncertainties by e.g. accounting for metal speciation, but they require a large amount of data and are unpractical to combine broadly with other fate and dispersion models. In this study, a Simplified Fate & Speciation Model (SFSM) is presented, that is based on the parsimony principle: “as simple as possible, as complex as needed”, and that can be used for indirect human exposure assessment in different context like RA and regionalized LCA. SFSM couples traditional multi-media mass balances with empirical speciation models in a tool that has a simple theoretical framework and that is not data-intensive. The model calculates total concentration, dissolved concentration, and free ion activity of Cd, Cu, Ni, Pb and Zn in different soil layers, after accounting for metal deposition and dispersion. The model is tested for these five metals by using data from peer reviewed literature. Results show good accordance between measured and calculated values (factor of 3). The model is used to predict the human exposure via soil to lead initially emitted into air by the waste combustion plant and both the lead cumulative exposure and intake fraction are calculated.

A multimedia fate model to evaluate the fate of PAHs in Songhua River, China

A multimedia fate model coupling dynamic water flow with a level IV fugacity model has been developed and applied to simulate the temporal and spatial fate of Polycyclic Aromatic Hydrocarbons (PAHs) in the Songhua River, China. The model has two components: in the first, the one-dimensional network kinematic wave equation is used to calculate varying water flow and depth. In the second, Fugacity IV equations are implemented to predict contaminant distributions in four environmental media. The estimated concentrations of eight PAHs in Songhua River are obtained, and all simulated results are in acceptable agreement with monitoring data, as verified with the Theil’s inequality coefficient test. The sensitivity of PAH concentration in each environmental phase to input parameters are also evaluated. Our results show the model predicts reasonably accurate contaminant concentrations in natural rivers, and that it can be used to supply necessary information for control and management of water pollution.

Guidance on the Selection of Efficient Computational Methods for Multimedia Fate Models

Dynamic multimedia fate models (MFMs) have to deal with the temporal and spatial variation of physical-chemical properties, environmental scenarios, and chemical emissions. In such complex simulation tools, an analytical solution is not practically feasible, and even a numerical approach requires a suitable choice of the method in order to obtain satisfying speed and reliability, particularly when certain combinations of modeling scenarios and chemical properties occur. In this paper, considering some examples of a wide range of realistic chemical and scenario properties, some sources of stiffness in MFM equations are pinpointed. Next, a comparison of the performances of several numerical schemes (chosen as representatives of three wide classes) is performed. The accuracy and the computational effort required by each method is evaluated, illustrating the general effectiveness of automatically adapted timesteps in numerical algorithms and the pros and cons of implicit timestepping. The results show that automatic error control methods can significantly improve the quality of the computed solutions and most often lead to relevant savings in computing time. Additionally, explicit and implicit methods are compared, indicating that an implicit method of medium order (around 5) is the best choice as a general purpose MFM computing engine.

Sources and distribution of hexabromocyclododecanes (HBCDs) in Japanese river sediment

The distribution of hexabromocyclododecane (HBCD) in the sediment of three Japanese rivers with different characteristics (i.e., population and potential source in the catchment) was investigated and compared with the results estimated using a multimedia fate model (ChemCAN). High concentrations of HBCD in sediments in the range of 134-2060 ng g(-1) were found in a river receiving textile wastewater. This contrasted with the much lower concentrations (0.8-4.8 ng g(-1)) observed for an urban river (with a surrounding population of 1.8 million). The medians of observed HBCD concentrations in each river were close to those estimated based on the assumed input source (e.g., 1810 ng g(-1) for the observed median concentration, and 1436 ng g(-1) for the estimation, in the Kuzuryu River). These results demonstrated the importance of considering source contributions of HBCD, including both industrial and consumer sources, to aquatic environments, for reliable risk management.

Implications of considering metal bioavailability in estimates of freshwater ecotoxicity: examination of two case studies

Previous methods of estimating characterization factors (CFs) of metals in life cycle impact assessment (LCIA) models were based on multimedia fate, exposure, and effect models originally developed to address the potential impacts of organic chemicals. When applied to metals, the models neglect the influence of ambient chemistry on metal speciation, bioavailability and toxicity. Gandhi et al. (2010) presented a new method of calculating CFs for freshwater ecotoxicity that addresses these metal-specific issues. In this paper, we compared and assessed the consequences of using the new method versus currently available LCIA models for calculating freshwater ecotoxicity, as applied to two case studies previously examined by Gloria et al. (2006): (1) the production of copper (Cu) pipe and (2) a zinc (Zn) gutter system. Using the same inventory data as presented by Gloria et al. (2006), we calculated and compared the LCIA outcomes for freshwater ecotoxicity of each case study using four models: USES-LCA 1.0, USES-LCA 2.0, USEtox™ using the previous approach, and USEtox™ using the new method. Since the new method requires specification of water chemistry for the freshwater compartment, we explored the effect of using seven freshwater archetypes. We analyzed the freshwater ecotoxicity outcomes of the two case studies with respect to the different models, infinite versus 100 years time scales for calculating impacts after metal emissions, and water chemistries representing environmental variability. Significant differences in CFs, overall freshwater ecotoxicity score (Σ CF × emissions) and the contributions of individual metals to the overall score were traced back to differences in modeling methods (e.g., variations in compartments included in the fate model), the choice of metal partition coefficients versus those explicitly calculated based on water chemistry (USEtox™ (new)), and the calculation of effect factors. Metal CFs calculated using USES-LCA 1.0 ranked Co > Ni > Cd ≈ Cu > Zn > Pb, but changed using USEtox™ (new) to Cd > Co > Ni > Zn > Cu > Pb for the archetype of hard alkaline water and Cd > Ni > Co > Cu ≈ Zn > Pb for the archetype of soft, acidic water. For the Cu pipe, total freshwater ecotoxicity scores for metal emissions into air and water ranged from 0.01 to 0.02 for USES-LCA1.0, ~1 for USEtox™ (previous) to 0.0002–0.01 1, 4-dichlorobenzene (DCB) eq. for USEtox™ (new) depending on the archetype. Whereas Cu followed by Ni emissions contributed most to total freshwater ecotoxicity estimated by USES-LCA1.0, Cu, Cd, Ni, and Zn, emissions were all important contributors towards freshwater ecotoxicity with USEtox™ (new), with differences in contributions dependent on the freshwater archetype. For the Zn gutter case study, the total scores varied from 10 for USEtox™ (previous) to 0.008 for USES-LCA 2.0 and 0.02–0.11 equal to 1, 4-DCB for USEtox™ (new). Zn contributed ~98% towards the freshwater ecotoxicity scores of metals in all models. For both case studies, differences in ecotoxicity scores were not significant for the infinite vs. 100 years time scale. Accounting for metal bioavailability and speciation by using USEtox™ (new) when calculating CFs decreased by 1–4 orders of magnitude the total metal freshwater ecotoxicity scores (Σ CF × emissions) attributable to metal emissions tallied for Cu pipe and Zn gutter system case studies (Gloria et al. 2006). This broad range came from the model used in comparison to USEtox™ (new) and the choice of freshwater archetype. Additionally, contributions of each metal to the total score of the Cu pipe case study changed significantly from the use of previous CFs (Huijbregts et al. 2000) versus the revised CFs (Gandhi et al. 2010). Metal CFs calculated using the method proposed by Gandhi et al. (2010) significantly lowers the total freshwater ecotoxicity impact of metal emissions. It is suggested that this lower estimate of potential impact from metal emissions is consistent with our understanding of metal chemistry. The magnitude of the potential freshwater ecotoxicity of metals depends on the chemistry of the modeled freshwater compartment, similarly to the dependence of acidification potential on regionally variant freshwater chemistry.

Modelling the fate of organic micropollutants in stormwater ponds

Urban water managers need to estimate the potential removal of organic micropollutants (MP) in stormwater treatment systems to support MP pollution control strategies. This study documents how the potential removal of organic MP in stormwater treatment systems can be quantified by using multimedia models. The fate of four different MP in a stormwater retention pond was simulated by applying two steady-state multimedia fate models (EPI Suite and SimpleBox) commonly applied in chemical risk assessment and a dynamic multimedia fate model (Stormwater Treatment Unit Model for Micro Pollutants — STUMP). The four simulated organic stormwater MP (iodopropynyl butylcarbamate — IPBC, benzene, glyphosate and pyrene) were selected according to their different urban sources and environmental fate. This ensures that the results can be extended to other relevant stormwater pollutants. All three models use substance inherent properties to calculate MP fate but differ in their ability to represent the small physical scale and high temporal variability of stormwater treatment systems. Therefore the three models generate different results. A Global Sensitivity Analysis (GSA) highlighted that settling/resuspension of particulate matter was the most sensitive process for the dynamic model. The uncertainty of the estimated MP fluxes can be reduced by calibrating the dynamic model against total suspended solids data. This reduction in uncertainty was more significant for the substances with strong tendency to sorb, i.e. glyphosate and pyrene and less significant for substances with a smaller tendency to sorb, i.e. IPBC and benzene. The results provide support to the elaboration of MP pollution control strategies by limiting the need for extensive and complex monitoring campaigns targeting the wide range of specific organic MP found in stormwater runoff.

Development of a Local-Scale Spatially Refined Multimedia Fate Model (LSRMFM) for Urban-Scale Risk Assessment: Model Formulation, GIS-Based Preprocessing, and Case Study

A local-scale spatially refined multimedia fate model (LSRMFM) was developed to evaluate in detail the multimedia transport of organic compounds at a spatial level. The model was derived using a combination of an advection–dispersion–reaction partial differential equation, a steady-state multimedia fugacity model, and a geographical information system. The model was applied to predicting four major volatile organic compounds that are produced as emissions (benzene, toluene, xylene, and styrene) in an urban and industrial area (the 50 × 50-km area was divided into 0.5 × 0.5-km segments) in Korea. To test the accuracy of the model, the LSRMFM was used to predict the extent of dispersion and the data compared with actual measured concentrations and the results of a generic multimedia fate model (GMFM). The results indicated that the method developed herein is appropriate for predicting long-term multimedia pollution. However, the comparison study also illustrated that the developed model has some limitations (e.g., steady-state assumption) in terms of explaining all the observed concentrations, and additional verification and study (e.g., validation using a large observed data set, integration with a more accurate runoff model) would be desirable. In comparing LSRMFM and GMFM, discrepancies between the LSRMFM and GMFM outputs were found, as the result of geographical effects, even though the environmental parameters were identical. The geographical variation for LSRMFM output indicated the existence of considerable local human and ecological risks, whereas the GMFM output indicated less average risk. These results demonstrate that the model has the potential for improving the management of pollutant levels under these refined spatial conditions.