The EXPURT model for calculating external gamma doses from deposited material in inhabited areas

EXPURT, NRPB's model for calculating external gamma doses in inhabited areas, was originally developed in the mid-1980s. Deposition on surfaces in the area, the subsequent transfer of material between different surfaces or its removal from the system, and dose rates in various locations from material on the different surfaces are modelled. The model has been updated to take account of more recent experimental data on the transfer rates between surfaces and to make it more flexible for use in assessing dose rates following an accidental release. EXPURT is a compartmental model and models the transfer of material between the surfaces using a set of first order differential equations. It enables the impact of the decontamination of surfaces on doses and dose rates to be explored. The paper describes the EXPURT model and presents some preliminary results obtained using it.     

Review of dynamical models for external dose calculations based on Monte Carlo simulations in urbanised areas

After an accidental release of radionuclides to the inhabited environment the external gamma irradiation from deposited radioactivity contributes significantly to the radiation exposure of the population for extended periods. For evaluating this exposure pathway, three main model requirements are needed: (i) to calculate the air kerma value per photon emitted per unit source area, based on Monte Carlo (MC) simulations; (ii) to describe the distribution and dynamics of radionuclides on the diverse urban surfaces; and (iii) to combine all these elements in a relevant urban model to calculate the resulting doses according to the actual scenario. This paper provides an overview about the different approaches to calculate photon transport in urban areas and about several dose calculation codes published. Two types of Monte Carlo simulations are presented using the global and the local approaches of photon transport. Moreover, two different philosophies of the dose calculation, the "location factor method" and a combination of relative contamination of surfaces with air kerma values are described. The main features of six codes (ECOSYS, EDEM2M, EXPURT, PARATI, TEMAS, URGENT) are highlighted together with a short model-model features intercomparison.     

Potential release scenarios for carbon nanotubes used in composites

The expected widespread use of carbon nanotube (CNT)-composites in consumer products calls for an assessment of the possible release and exposure to workers, consumers and the environment. Release of CNTs may occur at all steps in the life cycle of products, but to date only limited information is available about release of CNTs from actual products and articles. As a starting point for exposure assessment, exploring sources and pathways of release helps to identify relevant applications and situations where the environment and especially humans may encounter releases of CNTs. It is the aim of this review to identify various potential release scenarios for CNTs used in polymers and identify the greatest likelihood of release at the various stages throughout the life-cycle of the product. The available information on release of CNTs from products and articles is reviewed in a first part. In a second part nine relevant release scenarios are described in detail: injection molding, manufacturing, sports equipment, electronics, windmill blades, fuel system components, tires, textiles, incineration, and landfills. Release from products can potentially occur by two pathways; (a) where free CNTs are released directly, or more frequently (b) where the initial release is a particle with CNTs embedded in the matrix, potentially followed by the subsequent release of CNTs from the matrix.The potential for release during manufacturing exists for all scenarios, however, this is also the situation when exposure can be best controlled. For most of the other life cycle stages and their corresponding release scenarios, potential release of CNTs can be considered to be low, but it cannot be excluded totally. Direct release to the environment is also considered to be very low for most scenarios except for the use of CNTs in tires where significant abrasion during use and release into the environment would occur. Also the possible future use of CNTs in textiles could result in consumer exposure. A possibility for significant release also exists during recycling operations when the polymers containing CNTs are handled together with other polymers and mainly occupational users would be exposed.It can be concluded that in general, significant release of CNTs from products and articles is unlikely except in manufacturing and subsequent processing, tires, recycling, and potentially in textiles. However except for high energy machining processes, most likely the resulting exposure for these scenarios will be low and to a non-pristine form of CNTs. Actual exposure studies, which quantify the amount of material released should be conducted to provide further evidence for this conclusion.     

Factors influencing recovery and restoration following a chemical incident

Chemicals are an important part of our society. A wide range of chemicals are discharged into the environment every day from residential, commercial and industrial sources. Many of these discharges do not pose a threat to public health or the environment. However, global events have shown that chemical incidents or accidents can have severe consequences on human health, the environment and society. It is important that appropriate tools and technical guidance are available to ensure that a robust and efficient approach to developing a remediation strategy is adopted. The purpose of remediation is to protect human health from future exposure and to return the affected area back to normal as soon as possible. There are a range of recovery options (techniques or methods for remediation) that are applicable to a broad range of chemicals and incidents. Recovery options should be evaluated according to their appropriateness and efficacy for removing contaminants from the environment; however economic drivers and social and political considerations often influence decision makers on which remedial actions are implemented during the recovery phase of a chemical incident. To date, there is limited information in the literature on remediation strategies and recovery options that have been implemented following a chemical incident, or how successful they have been. Additional factors that can affect the approach taken for recovery are not well assessed or understood by decision makers involved in the remediation and restoration of the environment following a chemical incident. The identification of this gap has led to the development of the UK Recovery Handbook for Chemical Incidents to provide a framework for choosing an effective recovery strategy. A compendium of practical evidence-based recovery options (techniques or methods for remediation) for inhabited areas, food production systems and water environments has also been developed and is included in the chemical handbook. This paper presents the key factors that should be considered when developing a recovery strategy with respect to how these may impact on its effectiveness. The paper also highlights the importance of these factors through an evaluation of recovery strategies implemented following real chemical incidents that have been reported in the literature.     

A new general dynamic model predicting radionuclide concentrations and fluxes in coastal areas from readily accessible driving variables

This paper presents a general, process-based dynamic model for coastal areas for radionuclides (metals, organics and nutrients) from both single pulse fallout and continuous deposition. The model gives radionuclide concentrations in water (total, dissolved and particulate phases and concentrations in sediments and fish) for entire defined coastal areas. The model gives monthly variations. It accounts for inflow from tributaries, direct fallout to the coastal area, internal fluxes (sedimentation, resuspension, diffusion, burial, mixing and biouptake and retention in fish) and fluxes to and from the sea outside the defined coastal area and/or adjacent coastal areas. The fluxes of water and substances between the sea and the coastal area are differentiated into three categories of coast types: (i) areas where the water exchange is regulated by tidal effects; (ii) open coastal areas where the water exchange is regulated by coastal currents; and (iii) semi-enclosed archipelago coasts. The coastal model gives the fluxes to and from the following four abiotic compartments: surface water, deep water, ET areas (i.e., areas where fine sediment erosion and transport processes dominate the bottom dynamic conditions and resuspension appears) and A-areas (i.e., areas of continuous fine sediment accumulation). Criteria to define the boundaries for the given coastal area towards the sea, and to define whether a coastal area is open or closed are given in operational terms. The model is simple to apply since all driving variables may be readily accessed from maps and standard monitoring programs. The driving variables are: latitude, catchment area, mean annual precipitation, fallout and month of fallout and parameters expressing coastal size and form as determined from, e.g., digitized bathymetric maps using a GIS program. Selected results: the predictions of radionuclide concentrations in water and fish largely depend on two factors, the concentration in the sea outside the given coastal area and/or adjacent coastal areas and the ecological half-life of the radionuclide in the sea. Uncertainties in these factors generally dominate all other uncertainties, e.g., concerning the surface water retention time, the settling velocity of the particulate fraction, the distribution coefficient regulating the fluxes in dissolved and particulate phases, the catchment area influences and the factors regulating biouptake and excretion of the radionuclide in fish. This means that the conditions in the sea are of paramount importance for the conditions in the coastal area, even for relatively enclosed coastal areas. This coastal model may be regarded as a tool for testing working hypotheses on the relative roles of different processes in different coastal areas. Such information is essential for getting realistic expectations of various remedial measures, such as coastal dredging discussed in this work.     

Models for human exposure to air pollution

Four models for human exposure to air pollution are discussed and compared. The simple microenvironment monitoring model measures pollutant concentrations at fixed locations, regarded as proxies for similar locations or microenvironments. Since this model does not require pollutant measurements on the individual level, it is easy to implement. However, the model can only be used to estimate the average exposure in a population, and it does not provide any estimate of the variability and distribution of individual exposures. The replicated microenvironment monitoring model provides some estimates of the variability and distribution. However, because of the possible discrepancy between the microenvironment concentration distribution and the individual concentration distribution, some adjustment might be necessary. Integrated personal monitoring allows direct estimation of the average exposure as well as the variability and distribution of individual exposures. Coupled with the appropriate time budget data, a regression analysis can be applied to estimate the contribution from each microenvironment type. However, possible collinearity problems might result in low precision in those estimates. Moreover, it might be difficult to adjust for a possible Hawthorne effect. Continuous personal monitoring has the advantage of recording exposure in each microenvironment type separately, allowing direct estimation of the average exposure as well as the variability and distribution of exposures in each microenvironment type. Moreover, it can also be conducted in conjunction with a two-stage sampling scheme, using information from a large data base on activity patterns, thereby making more efficient use of the monitoring data. It is also easier to adjust for a possible Hawthorne effect in this design.     

Bioclimatic modelling of current and projected climatic suitability of coffee (<Emphasis Type="Italic">Coffea arabica</Emphasis>) production in Zimbabwe

Coffee is an important commodity crop in Zimbabwe and many other African countries in terms of its contribution to local and national economies. Coffee production in terms of productivity and quality face severe constraints due to climate change. A study was therefore carried out to understand and quantify the potential impact of climate change on the coffee sector in Zimbabwe using a bioclimatic modelling approach. Current climatically suitable areas were identified and compared with those areas identified to be climatically suitable under projected 2050 climatic conditions. The projected climatic conditions were obtained from climate predictions of two models: CCSM4 model and HadGEM2 model. Coffee production was found to be mostly sensitive to precipitation factors as these were the most important in determining climatic suitability of coffee production in Zimbabwe. The modelling showed that current coffee suitability varies spatially between the four coffee producing districts in Zimbabwe. Chipinge district has the largest area climatically suitable for coffee production followed by Chimanimani district with Mutare district having the smallest. The modelling predicted that there will be a spatial and quantitative change in climatic suitability for coffee production in Zimbabwe by 2050. The greatest changes are projected for Mutare district where over three quarters according to the CCSM4 model and the entire district according to the HadGEM2 model will turn marginal for coffee production. A westward shift in climatic suitability of coffee was observed for Chipinge and Chimanimani district. The models predicted a loss of between 30,000 ha (CCSM4) and 50,000 ha (HadGEM2) in areas climatically suitable for coffee production by 2050 in Zimbabwe. These changes are likely to be driven by changes in the distribution of precipitation received in the coffee areas. The study presents possible adaptation measures that can be adopted by the coffee sector in Zimbabwe and the region to maintain coffee productivity under a changing climate.     

Pesticides exposure in Pakistan: a review

This is the first systematic review of studies done since 1960, and to give an integrated picture of pesticides exposure to humans, animals, plants, waters, soils/sediments, atmosphere etc. in Pakistan. Authors have extracted data from different departments, published literature in research journals and National reports. Although the wide-spread usage of pesticides in Pakistan has controlled the pests, but like other countries, it has started causing environmental problems in the area. In some areas of Punjab and Sindh groundwater has been found contaminated and is constantly being under the process of contamination due to pesticide use. There is considerable evidence that farmers have overused and misused pesticides especially in cotton-growing areas. It is evident from the biological monitoring studies that farmers are at higher risk for acute and chronic health effects associated with pesticides due to occupational exposure. Furthermore, the intensive use of pesticides (higher sprays more than the recommended dose) in cotton areas involves a special risk for the field workers, pickers, and of an unacceptable residue concentration in cottonseed oil and cakes. The authors have also discussed the merits and demerits of different studies. The review will set the future course of action of different studies on pesticide exposure in Pakistan. Data limitations are still the major obstacle towards establishing clear environmental trends in Pakistan. The authors suggest that a reliable monitoring, assessment and reporting procedures shall be implemented in accordance with appropriate environmental policies, laws and regulations in order to minimize the pesticides exposure.     

Projecting canopy cover change in Tasmanian eucalypt forests using dynamically downscaled regional climate models

Loss of forest cover is a likely consequence of climate change in many parts of the world. To test the vulnerability of eucalypt forests in Australia’s island state of Tasmania, we modelled tree canopy cover in the period 2070–2099 under a high-emission scenario using the current climate–canopy cover relationship in conjunction with output from a dynamically downscaled regional climate model. The current climate–canopy cover relationship was quantified using Random Forest modelling, and the future climate projections were provided by three dynamically downscaled general circulation model (GCM) simulations. Three GCMs were used to show a range of projections for the selected scenario. We also explored the sensitivity of key endemic and non-endemic Tasmanian eucalypts to climate change. All GCMs suggested that canopy cover should remain stable (proportional cover change <10 %) across ~70 % of the Tasmanian eucalypt forests. However, there were geographic areas where all models projected a decline in canopy cover due to increased summer temperatures and lower precipitation, and in addition, all models projected an increase in canopy cover in the coldest part of the state. The model projections differed substantially for other areas. Tasmanian endemic species appear vulnerable to climate change, but species that also occur on the mainland are likely to be less affected. Given these changes, restoration and carbon sequestration plantings must consider the species and provenances most suitable for future, rather than present, climates.     

Effect of the shape of the exposure-response function on estimated hospital costs in a study on non-elective pneumonia hospitalizations related to particulate matter

ObjectiveWe used log-linear and log-log exposure-response (E-R) functions to model the association between PM_2.5 exposure and non-elective hospitalizations for pneumonia, and estimated the attributable hospital costs by using the effect estimates obtained from both functions.MethodsWe used hospital discharge data on 3519 non-elective pneumonia admissions from UZ Brussels between 2007 and 2012 and we combined a case-crossover design with distributed lag models. The annual averted pneumonia hospitalization costs for a reduction in PM_2.5 exposure from the mean (21.4 μg/m³) to the WHO guideline for annual mean PM_2.5 (10 μg/m³) were estimated and extrapolated for Belgium.ResultsNon-elective hospitalizations for pneumonia were significantly associated with PM_2.5 exposure in both models. Using a log-linear E-R function, the estimated risk reduction for pneumonia hospitalization associated with a decrease in mean PM_2.5 exposure to 10 μg/m³ was 4.9%. The corresponding estimate for the log-log model was 10.7%. These estimates translate to an annual pneumonia hospital cost saving in Belgium of €15.5 million and almost €34 million for the log-linear and log-log E-R function, respectively.DiscussionAlthough further research is required to assess the shape of the association between PM_2.5 exposure and pneumonia hospitalizations, we demonstrated that estimates for health effects and associated costs heavily depend on the assumed E-R function. These results are important for policy making, as supra-linear E-R associations imply that significant health benefits may still be obtained from additional pollution control measures in areas where PM levels have already been reduced.     

A quantitative risk assessment method based on population and exposure distributions using Australian air quality data

This paper develops a practical probabilistic method for assessing aggregate population health risks from different types of population exposures. The method consists of calculating the product of two functions: a population-weighted distribution of concentrations and a concentration-response distribution. This operation yields the corresponding aggregated health-risk distribution function. The method can use alternative exposure-response distributions and populations-specific exposure patterns, depending on the context of the assessment. A deterministic sensitivity analysis is included in the methodological aspects of this research. The distributions of concentrations are generated by combining area-specific population densities with atmospheric concentrations for each of the areas where exposure to air pollutants occurs. The exposure-response functions are developed from the literature. The method is exemplified using alternative exposure probabilities to carbon monoxide, nitrogen dioxide, particulate matter (PM₁₀), and exposure-response models developed specifically for these pollutants for assessing health risks, and applied to data from a number of Australian cities. The results, which hold when the functions are monotonic, show single maximum per pollutant, regardless of the choice of exposure and exposure-response distribution. Although those maxima are often below the Australian Air Pollution Standards, there are instances when this is not the case.     

Modelling radioactivity in the Irish Sea: From discharge to dose

In order to support authorised discharges of low level radioactive liquid effluent into coastal regions, mathematical models are required to robustly predict radiological impacts on critical groups of current and proposed changes to liquid discharges. The grid model presented here simulates the long term dispersion and transport of radioactivity discharged from the Sellafield site in Cumbria, UK, and the subsequent exposure of critical groups in Cumbria and across the Irish Sea in Northern Ireland. The fine grid of the model allows a good resolution of the seabed sediment distribution. This benefits the predictions for the last decades of low discharge level, when bed sediment can become a source of contamination by bringing back the legacy of past high discharges. This is highlighted by the dose comparison, where the predicted dose to Cumbria critical group follows well the dose estimated from environmental data during the low discharge level period.     

Health effects of ambient air pollution: Do different methods for estimating exposure lead to different results?

BackgroundSpatially resolved exposure models are increasingly used in epidemiology. We previously reported that, although exhibiting a moderate correlation, pregnancy nitrogen dioxide (NO₂) levels estimated by the nearest air quality monitoring station (AQMS) model and a geostatistical model, showed similar associations with infant birth weight.ObjectivesWe extended this study by comparing a total of four exposure models, including two highly spatially resolved models: a land-use regression (LUR) model and a dispersion model. Comparisons were made in terms of predicted NO₂ and particle (aerodynamic diameter < 10 μm, PM₁₀) exposure and adjusted association with birth weight.MethodsThe four exposure models were implemented in two French metropolitan areas where 1026 pregnant women were followed as part of the EDEN mother–child cohort.ResultsCorrelations between model predictions were high (≥ 0.70), except for NO₂ between the AQMS and both the LUR (r = 0.54) and dispersion models (r = 0.63). Spatial variations as estimated by the AQMS model were greater for NO₂ (95%) than for PM₁₀ (22%). The direction of effect estimates of NO₂ on birth weight varied according to the exposure model, while PM₁₀ effect estimates were more consistent across exposure models.ConclusionsFor PM₁₀, highly spatially resolved exposure model agreed with the poor spatial resolution AQMS model in terms of estimated pollutant levels and health effects. For more spatially heterogeneous pollutants like NO₂, although predicted levels from spatially resolved models (all but AQMS) agreed with each other, our results suggest that some may disagree with each other as well as with the AQMS regarding the direction of the estimated health effects.     

Modelling and experimental studies on the transfer of radionuclides to fruit

Although fruit is an important component of the diet, the extent to which it contributes to radiological exposure remains unclear, partially as a consequence of uncertainties in models and data used to assess transfer of radionuclides in the food chain. A Fruits Working Group operated as part of the IAEA BIOMASS (BIOsphere Modelling and ASSessment) programme from 1997 to 2000, with the aim of improving the robustness of the models that are used for radiological assessment. The Group completed a number of modelling and experimental activities including: (i) a review of experimental, field and modelling information on the transfer of radionuclides to fruit; (ii) discussion of recently completed or ongoing experimental studies; (iii) development of a database on the transfer of radionuclides to fruit; (iv) development of a conceptual model for fruit and (v) two model intercomparison studies and a model validation study. The Group achieved significant advances in understanding the processes involved in transfer of radionuclides to fruit. The work demonstrated that further experimental and modelling studies are required to ensure that the current generation of models can be applied to a wide range of scenarios.     

Environmental mercury contamination in China: sources and impacts

This review article focused on the current status of mercury (Hg) contamination in different ecological compartments in China, and their possible environmental and health impacts, focusing on some major cities. Mercury emission from non-ferrous metals smelting (especially zinc smelting), coal combustion and miscellaneous activities (of which battery and fluorescent lamp production and cement production are the largest), contributed about 45%, 38% and 17%, respectively, to the total Hg emission based on the data of 1999. Mercury contamination is widespread in different ecological compartments such as atmosphere, soil and water. There is evidence showing bioaccumulation and biomagnification of Hg in aquatic food chains, with higher concentrations detected in carnivorous fish. In terms of human exposure to Hg, fish consumption is the major exposure pathway for residents living in coastal cities such as Hong Kong, but inhalation may be another major source, affecting human health in areas with severe atmospheric Hg, such as Guiyang City (Guizhou Province). The first case study indicated that after closure of the acetic acid plant 20 years at Songyuan City (Jilin Province), 16.7% of residents' hair still contained Hg concentration in excess of 1 mg/kg (the reference dosage value, RfD set by USEPA). The second case study indicated that the male residents of Hong Kong who consumed more than four or more meals of fish per week tended to contain higher Hg in their hair, which was linked to their subfertility. There is also increasing evidence showing that skin disorders and autism in Hong Kong children are related to their high Hg body loadings (hair, blood and urine), through prenatal methyl Hg exposure. There seems to be an urgent need to identify the sources of Hg, speciation and concentrations in different ecological compartments, which may lead to high body loadings in human beings. Adverse health effects of residents living in places with a higher background level of Hg, due to long-term exposure to chronic levels of Hg through oral intake should not be overlooked.     

Identifying opportunities for long-lasting habitat conservation and restoration in Hawaii’s shifting climate

Conservation efforts in isolated archipelagos such as Hawaii often focus on habitat-based conservation and restoration efforts that benefit multiple species. Unfortunately, identifying locations where such efforts are safer from climatic shifts is still challenging. We aimed to provide a method to approximate these potential habitat shifts for similar data- and research-limited contexts. We modeled the relationship between climate and the potential distribution of native biomes across the Hawaiian archipelago to provide a first approximation of potential native biome shifts under end-of-century projected climate. Our correlative model circumvents the lack of data necessary for the parameterization of mechanistic vegetation models in isolated and data-poor islands. We identified locations consistently expected to remain the same in terms of the native biome compatibility by the end of the century with a robust evaluation of sources of uncertainty in our projections. Our results show that, despite large differences in climate projections considered, 35% of the areas considered are consistently projected to maintain their current compatibility to native biomes. By integrating our native biome compatibility projections with maps of current actual cover, we identified areas ideal for long-term habitat conservation and restoration. Our modeling approach can be used with relatively simple data; offers multiple forms of projection confidence estimates, model calibration, and variable selection routines; and is compatible with ensemble projections. This method is not only applicable to potential native cover, as done in this study, but to any set of vegetation classes that are related to environmental predictors available for modeling.     

Determining when contamination is pollution - weight of evidence determinations for sediments and effluents

Contamination is simply the presence of a substance where it should not be or at concentrations above background. Pollution is contamination that results in or can result in adverse biological effects to resident communities. All pollutants are contaminants, but not all contaminants are pollutants. Differentiating pollution from contamination cannot be done solely on the basis of chemical analyses because such analyses provide no information on bioavailability or on toxicity. Effects-based measures such as laboratory or field toxicity tests and measures of the status of resident, exposed communities provide key information, but cannot be used independently to determine pollution status. Laboratory studies can be predictive, but are rarely realistic. Measures of resident communities include innate natural variability and cannot easily distinguish between adaptation to contamination (a genetic process) and acclimation (a physiological process that may decrease energy reserves, possibly reducing such critical population-level parameters as reproduction). Finally, contaminant effects may not only be direct but also indirect; predicting such effects requires knowledge of the system under study as well as appropriate use of lines of evidence (LOE) such as toxicity tests directed to key species. Consequently, in sediments, effluents or other inputs/environmental compartments, determining when contamination is or may in future become pollution, requires a weight of evidence (WOE) assessment using different LOE appropriate to the situation under investigation. WOE investigations provide two different types of information: definitive conclusions regarding pollution; or, information as to what additional, investigative studies are necessary for definitive conclusions. Effectively, a WOE assessment comprises an initial screening-level ecological risk assessment (ERA), which may be followed by a detailed-level ERA if key uncertainties need to be resolved.     

The cost-effectiveness of residential radon remediation programmes: assumptions about benefits stream profiles over time

A recent cost-effectiveness analysis of a residential radon remediation programme considered and highlighted many areas of uncertainty in the parameters chosen for the analysis. One assumption not challenged in the study was the benefits stream profile adopted. There are several different ways of loading the benefits in terms of life years into the cost-effectiveness model and several of these are explored and the results are reported in this study. The benefits profile depends upon the lead-time to cancer manifestation post environmental carcinogen (radon) exposure. The literature reviewed suggests that there are many options for loading benefits to radon-induced lung cancer prevention programmes. In this study, the alternative benefits stream profiles are explored and their implications for the cost-effectiveness ratio are examined. Adopting different benefits stream profiles to the model results in a range of cost-effectiveness ratios from 14912.90 pounds per life year gained to 52416.27 pounds per life year gained. The preferred model is reported where the life years gained are assumed to be equally distributed over the last 15 years of the 40-year time horizon of the analysis (Y25-40) and the corresponding cost-effectiveness ratio is 37,943 pounds per life year gained.