MIRABEL: models for integrated review and assessment of biodiversity in European landscapes

In this paper, we present the methodology and some results from the application of an integrating conceptual framework, MIRABEL, to analyze the consequences of environmental change for biodiversity. For 28 European countries, MIRABEL tabulates changes in the status of threatened habitats predicted to result from 10 environmental pressures. Regional variations in the severity of the pressures and impacts are taken into account by compiling separate impact tables for each of 13 Ecological Regions. Results suggest that agricultural intensification is one of the main threats, however, differences recorded by MIRABEL in the intensity of the pressures, their rate of change and their past and expected impacts on biodiversity in the various Ecological Regions is telling evidence of Europe's biogeographical variety, and of the need to take this into consideration when assessing environmental change.     

Integrated assessment for aerobic biodegradability of organic substances

In this paper, the amount of oxygen consumption, end products and activities of microorganisms are considered as the three factors which affect the biodegradability of organic substances in water. Two integrated assessment methods for biodegradability of organic substances, fuzzy clustering integrated assessment and weighted integrated assessment, have been developed. Simultaneously, the detail steps for assessing a new organic substance biodegradability with these two integrated assessment methods are proposed.     

Fate and exposure models in relation to risk assessment

The recognition of potential long-term effects of substances, has led to the development of regulations and legislation which emphasis the need for assessing the risks posed by both new and existing substances for man and the environment. The evaluation of fate and exposure models is put into perspective in relation to the developments over the last five years in the framework of the EU regulations and national legislation within the European Community. The validation of environmental exposure models (multi-media models) is described in the context of quality assurance of models available to a user group, which is different from the quality assurance aspects for a developers group.     

Assessment models and dynamic variables for dynamic life cycle assessment of buildings: a review

Environmental Science and Pollution Research - Life cycle assessment (LCA) is widely used to quantify the environmental performance of buildings. Recently, the potential temporal variations in the...     

Wastewater disinfection by peracetic acid: assessment of models for tracking residual measurements and inactivation.

With its potential for low (if any) disinfection byproduct formation and easy retrofit for chlorine contactors, peracetic acid (PAA) or use of PAA in combination with other disinfectant technologies may be an attractive alternative to chlorine-based disinfection. Examples of systems that might benefit from use of PAA are water reuse schemes or plants discharging to sensitive receiving water bodies. Though PAA is in use in numerous wastewater treatment plants in Europe, its chemical kinetics, microbial inactivation rates, and mode of action against microorganisms are not thoroughly understood. This paper presents results from experimental studies of PAA demand, PAA decay, and microbial inactivation, with a complementary modeling analysis. Model results are used to evaluate techniques for measurement of PAA concentration and to develop hypotheses regarding the mode of action of PAA in bacterial inactivation. Kinetic and microbial inactivation rate data were collected for typical wastewaters and may be useful for engineers in evaluating whether to convert from chlorine to PAA disinfection.     

Kinetic assessment of persistent halogenated xenobiotics in cell culture models: comparison of mono- and poly-halogenated compounds

We evaluated the suitability of single and multiple cell type cultures as model systems to characterise cellular kinetics of highly lipophilic compounds with potential ecotoxicological impact. Confluent mono-layers of human skin fibroblasts, rat astrocytoma C6 cells, non-differentiated and differentiated mouse 3T3 cells were kept in culture medium supplemented with 10% foetal calf serum. For competitive uptake experiments up to four different cell types, grown on glass sectors, were exposed for 3 h to ¹⁴C-labelled model compounds, dissolved either in organic solvents or incorporated into unilamellar lecithin liposomes. Bromo-, or chloro-benzenes, decabromodiphenylether (DBP), and dichlorodiphenyl ethylene (DDE) were tested in rather high concentration of 20 μM. Cellular toxicity was low. Compound levels were related to protein, DNA, and triglyceride contents. Cellular uptake was fast and dependent on physico-chemical properties of the compounds (lipophilicity, molecular size), formulation, and cell type. Mono-halogenated benzenes showed low and similar uptake levels (= low accumulation compounds). DBP and DDE showed much higher cellular accumulations (= high accumulation compounds) except for DBP in 3T3 cells. Uptake from liposomal formulations was mostly higher than if compounds were dissolved in organic solvents. The extent of uptake correlated with the cellular content of triglycerides, except for DBP. Uptake competition between different cell types was studied in a sectorial multi-cell culture model. For low accumulation compounds negligible differences were found among C6 cells and fibroblasts. Uptake of DDE was slightly and that of DBP highly increased in fibroblasts. Well-defined cell culture systems, especially the sectorial model, are appropriate to screen for bioaccumulation and cytotoxicity of (unknown) chemical entities in vitro.     

Neural network and multiple regression models for PM10 prediction in Athens: a comparative assessment

Particulate atmospheric pollution in urban areas is considered to have significant impact on human health. Therefore, the ability to make accurate predictions of particulate ambient concentrations is important to improve public awareness and air quality management. This study examines the possibility of using neural network methods as tools for daily average particulate matter with aerodynamic diameter <10 microm (PM10) concentration forecasting, providing an alternative to statistical models widely used up to this day. Based on a data inventory, in a fixed central site in Athens, Greece, ranging over a two-year period, and using mainly meteorological variables as inputs, neural network models and multiple linear regression models were developed and evaluated. Comparison statistics used indicate that the neural network approach has an edge over regression models, expressed both in terms of prediction error (root mean square error values lower by 8.2-9.4%) and of episodic prediction ability (false alarm rate values lower by 7-13%). The results demonstrate that artificial neural networks (ANNs), if properly trained and formed, can provide adequate solutions to particulate pollution prognostic demands.     

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains. Part I: hourly and seasonal ozone

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI's assessment.     

Comparison of the industrial source complex and AERMOD dispersion models: case study for human health risk assessment

Air quality models are typically used to predict the fate and transport of air emissions from industrial sources to comply with federal and state regulatory requirements and environmental standards, as well as to determine pollution control requirements. For many years, the U.S. Environmental Protection Agency (EPA) widely used the Industrial Source Complex (ISC) model because of its broad applicability to multiple source types. Recently, EPA adopted a new rule that replaces ISC with AERMOD, a state-of-the-practice air dispersion model, in many air quality impact assessments. This study compared the two models as well as their enhanced versions that incorporate the Plume Rise Model Enhancements (PRIME) algorithm. PRIME takes into account the effects of building downwash on plume dispersion. The comparison used actual point, area, and volume sources located on two separate facilities in conjunction with site-specific terrain and meteorological data. The modeled maximum total period average ground-level air concentrations were used to calculate potential health effects for human receptors. The results show that the switch from ISC to AERMOD and the incorporation of the PRIME algorithm tend to generate lower concentration estimates at the point of maximum ground-level concentration. However, the magnitude of difference varies from insignificant to significant depending on the types of the sources and the site-specific conditions. The differences in human health effects, predicted using results from the two models, mirror the concentrations predicted by the models.     

基于熵权-集对分析的多级生态塘功效综合评价

借助熵权-集对分析法,以龙泓涧流域主流多级生态塘中具有代表性的8个断面为研究对象,针对其水质特点,选取溶解氧(DO)、COD、TN、NH3-N和TP等5项指标,对多级生态塘系统的净化功效进行了综合评价,并对多级生态塘系统内不同形态氮的去除效率进行了分析。结果表明,氮污染物是引起本流域内水质较差的主要污染物,通过多级生态塘系统的净化,本流域内水质由Ⅴ类提升至Ⅲ类,并对氮污染负荷的削减具有比较明显的功效。最后,对本系统的进一步优化提出建议,为龙泓涧流域的水资源管理提供了理论指导。     

Integrated approach of environmental impact and risk assessment of Rosia Montana Mining Area, Romania

The environmental impact assessment of mining sites represents nowadays a large interest topic in Romania. Historical pollution in the Rosia Montana mining area of Romania caused extensive damage to environmental media. This paper has two goals: to investigate the environmental pollution induced by mining activities in the Rosia Montana area and to quantify the environmental impacts and associated risks by means of an integrated approach. Thus, a new method was developed and applied for quantifying the impact of mining activities, taking account of the quality of environmental media in the mining area, and used as case study in the present paper. The associated risks are a function of the environmental impacts and the probability of their occurrence. The results show that the environmental impacts and quantified risks, based on quality indicators to characterize the environmental quality, are of a higher order, and thus measures for pollution remediation and control need to be considered in the investigated area. The conclusion drawn is that an integrated approach for the assessment of environmental impact and associated risks is a valuable and more objective method, and is an important tool that can be applied in the decision-making process for national authorities in the prioritization of emergency action.     

Integrated assessment of the control of wastewater pollution in Zarqa Governate, Jordan

Zarqa, the second largest city in Jordan and home of 52% of the industries in the country, suffers the worst water shortage and pollution. The purpose of this paper is to illustrate the potential problems associated with the pollution by industrial and municipal wastewater in Zarqa region and the possibilities for its control. The paper examines the major causes of pollution, the qualities and the quantities of pollutants, and the major obstacles facing the existing practices in the Kherbit As-Samra Wastewater Treatment Plant. The physical, chemical, biological and hydraulic overloading of As-Samra cause the station to be inefficient. Development of alternative solutions, taking into consideration all technical, financial, social, geographical and political constraints, is a challenge for the decision-makers in the water industry. The analysis and findings of this paper will lay the ground and assist decision-makers in setting up programmes to control wastewater pollution in the region.     

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains: Part II. Fine particulate matter and visibility

As part of the Southern Appalachian Mountains Initiative, a comprehensive air quality modeling system was developed to evaluate potential emission control strategies to reduce atmospheric pollutant levels at the Class I areas located in the Southern Appalachian Mountains. Six multiday episodes between 1991 and 1995 were simulated, and the skill of the modeling system was evaluated. Two papers comprise various parts of this study. Part I details the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. This paper (part II) addresses issues involved with modeling particulate matter (PM) and its relationship to visibility. For most of the episodes, the fractional error was approximately 50% or less for the major constituents of the fine PM (i.e., sulfate [SO4] and organics) in the region. The mean normalized errors and fractional errors are generally larger for the NO3 and soil components, but these components are relatively small. Variations in modeling bias with pollutant levels were also examined. The model showed a systematic overestimation for low levels and an underestimation for high levels for most PM species. For ammonium, the model showed better performance at lower SO4 concentrations when the measured SO4 was assumed to be completely neutralized (ammonium sulfate) and better performance at higher SO4 concentrations when the partially neutralized (ammonium bisulfate) assumption was made. The contributions of various components of PM to reductions in visibility were also calculated; SO4 was found to be the major contributor.     

The ChimERA project: coupling mechanistic exposure and effect models into an integrated platform for ecological risk assessment

Current techniques for the ecological risk assessment of chemical substances are often criticised for their lack of environmental realism, ecological relevance and methodological accuracy. ChimERA is a 3-year project (2013–2016), funded by Cefic’s Long Range Initiative (LRI) that aims to address some of these concerns by developing and testing mechanistic fate and effect models, and coupling of these models into one integrated platform for risk assessment. This paper discusses the backdrop against which this project was initiated and lists its objectives and planned methodology.     

The application of predictive models in the environmental risk assessment of ECONOR

Environmental risk assessment of products requires information on the physico-chemical properties, persistence and ecotoxicity of the product, its constituents and possible metabolic and degradation products. Experimental investigations are usually required to generate this information and consequently risk assessment can be costly and time consuming. One possible approach to minimising the amount of experimental testing is to supplement experimental data with data predicted using models such as quantitative structure-activity relationships (QSARs). Using these models, information can be generated based primarily on the knowledge of the chemical structure of the substance(s) under investigation. In this study predictive models were used to assess the environmental risk of the veterinary medicine, ECONOR which contains the active ingredient valnemulin. Available experimental data on the properties, degradability and ecotoxicity of valnemulin was supplemented with predicted data. Where possible, experimental data was used to validate the predicted approaches and this indicated that the predictions were accurate. Information on usage, properties and degradability was input to fate models to predict environmental concentrations (PECs) of valnemulin in soil, pore water and groundwater. Comparison of PECs with experimental and predicted ecotoxicity data for valnemulin indicated that that even under 'worst case' scenarios the environmental risk posed by valnemulin was low.     

Integrated toxicity assessment of DEHP and DBP toward aquatic ecosystem based on multiple trophic model assays

Environmental Science and Pollution Research - To comprehensively understand the toxic risks of phthalates to aquatic ecosystems, we examined the acute toxicity of di-(2-ethylhexyl) phthalate...     

Reactive nitrogen and the world: 200 years of change

This paper examines the impact of food and energy production on the global N cycle by contrasting N flows in the late-19th century with those of the late-20th century. We have a good understanding of the amounts of reactive N created by humans, and the primary points of loss to the environment. However, we have a poor understanding of nitrogen's rate of accumulation in environmental reservoirs, which is problematic because of the cascading effects of accumulated N in the environment. The substantial regional variability in reactive nitrogen creation, its degree of distribution, and the likelihood of increased rates of reactive-N formation (especially in Asia) in the future creates a situation that calls for the development of a Total Reactive Nitrogen Approach that will optimize food and energy production and protect environmental systems.     

Integrated assessment of heavy metal (Pb, Zn, Cd) highway pollution: bioaccumulation in soil, Graminaceae and land snails

To assess the contamination induced by traffic at the vicinity of a highway (A31, France), several complementary studies were carried out on two sites, with different profiles and traffic intensity. Concentrations of zinc, lead and cadmium were measured by atomic absorption spectrophotometry in deposits, roadside soil and autochthonous plants (Graminaceae) gathered at the vicinity of the highway (1-320 m), and in the viscera of snails Helix aspersa, transferred as sentinel in the sites. According to the results obtained for different compartments, the highway induces a contamination on the surrounding environment, up to 320 m, but with the maximum contamination observed between 5 and 20 m: the concentrations measured in plants at the vicinity of the highway were 2.1 mg Pb kg(-1) DW, 0.06 mg Cd kg(-1) DW, 62 mg Zn kg(-1) DW and the concentrations measured in snails were 21.3 mg Pb kg(-1) DW, 5.7 mg Cd kg(-1) DW, 510.8 mg Zn kg(-1) DW. The levels measured decreased with increasing distance from the highway. Results of the three metals studied indicated that lead seems to be the best metal to evaluate road transport contamination.