WARM: a European model for energy and environmental analysis

This paper describes the structure of a newly developed econometric, imperfectly competitive, general equilibrium model for the medium term study of energy and environmental problems. The geographical coverage of the model regards twelve European countries as well as the European Union as a whole. Compared to existing quantitative E3 (economy-energy-environment) models, the WARM model is characterized by a few novel and relevant features Firstly, in contrast to multicountry interlinked models, it copes with the international dimension by integrating differences from a common European denominator within a unified and homogeneously designed framework. A panel data estimation approach is used to achieve this objective. Secondly, in contrast to the traditional market-based philosophy of many econometric models, it adopts a perspective focused upon economic agents' decisions. Thirdly, in contrast with the practice of modelling technical progress as an exogenous and deterministic phenomenon, it incorporates an explicit attempt of modelling the sources and effects of endogenous technical change. A Kalman filter latent variable approach is the methodology from which statistical information on the dynamics of technical progress can be obtained. Finally, all markets in the model are imperfectly competitive, including the labour market where the wage bargaining process is explicitly modelled and estimated. This last feature is especially important in view of the European unemployment problem.     

Use of log-linear modelling to assess environmental changes

The impact of dredging on a biological community is assessed through the use of log-linear modelling. The experiment is designed as a nested design and the data is collected at several stations within each of natural and dredged areas. The log-linear modelling analysis indicates the dredging has an impact on the abundance of dominant species.     

Numerical modelling of the environmental impact of landfill leachate leakage on groundwater quality – a field application

Waste disposal facilities are mainly responsible for the gradual quality degradation of subsurface freshwater reservoirs. The main objective of this work is to identify the groundwater contamination risk due to potential leachate leakage and seepage beneath the municipal landfill of the City of Patras in Greece. A groundwater and leachate mass transport model of the underlying aquifer was developed for this purpose. The derived simulation results indicate that, depending on the permeability of the soil at the location of leakage, the contamination risk for the groundwater can be high. In order to quantify the magnitude and the extent of the leakage, a risk assessment model for the leachate contaminant plume was developed. The risk assessment analysis shows that the municipal drinking wells are under high risk of contamination.     

Towards the establishment of an environmental quality standard for aluminium in surface waters

Steps taken to establish an environmental quality standard (EQS) for aluminium are described. The range of water types in England and Wales and the concentrations of low molecular weight (active) forms of aluminium have been assessed in order to evaluate the risk posed by aluminium in surface waters. Levels of low molecular weight forms of aluminium are mainly in the range 0-25 microg l(-1). Data suggest that dissolved aluminium might form the basis of a reasonably useful prediction of active aluminium leading to a simplified approach to compliance monitoring of an EQS set in terms of active aluminium.     

Developing an environmental water quality monitoring program for Haraz River in Northern Iran

Water quality management plans are an indispensable strategy for conservation and utilization of water resources in a sustainable manner. One common industrial use of water is aquaculture. The present study is an attempt to use statistical analyses in order to prepare an environmental water quality monitoring program for Haraz River, in Northern Iran. For this purpose, the analysis of a total number of 18 physicochemical parameters was performed at 15 stations during a 1-year sampling period. According to the results of the multivariate statistical methods, the optimal monitoring would be possible by only 3 stations and 12 parameters, including NH₃, EC, BOD, TSS, DO, PO₄, NO₃, TDS, temperature, turbidity, coliform, and discharge. In other words, newly designed network, with a total number of 36 measurements (3 stations × 12 parameters = 36 parameters), could achieve exactly the same performance as the former network, designed based on 234 measurements (13 stations × 18 parameters = 234 parameters). Based on the results of cluster, principal component, and factor analyses, the stations were divided into three groups of high pollution (HP), medium pollution (MP), and low pollution (LP). By clustering the stations, it would be possible to track the water quality of Haraz River, only by one station at each cluster, which facilitates rapid assessment of the water quality in the river basin. Emphasizing on three main axes of monitoring program, including measurement parameters, sampling frequency, and spatial pattern of sampling points, the water quality monitoring program was optimized for the river basin based on natural conditions of the study area, monitoring objectives, and required financial resources (a total annual cost of about US $2625, excluding the overhead costs).     

Syndromes of Global Change: a qualitative modelling approach to assist global environmental management

A novel transdisciplinary approach to investigate Global Change (GC) is presented. The approach rests on the decomposition of the intrigue dynamics of GC into patterns of civilization–nature interactions (syndromes) by an iterative scientific process of observations, data and system theoretical analyses, and modelling attempts. We illustrate the approach by a detailed analysis of the Sahel Syndrome, which describes the rural poverty driven overuse of natural resources. The investigation is performed by (i) identifying relevant symptoms and interlinkages which are characteristics for this pattern, and (ii) a qualitative model representing the internal dynamics of the essential flywheel. The geographical patchwork of the regions affected by the syndrome which is obtained by global data analysis, proves the high global relevance of this pattern. The qualitative model is employed for an evaluation of basic policy strategies debated in the context of rural poverty driven environmental degradation. It turns out that a mixed policy of combating poverty and introducing soil preserving agricultural techniques and practices is most promising to tackle the syndrome dynamics.     

Application of an environmental impact assessment methodology to a site discharging low levels of radioactivity to a freshwater environment in Norway

Significant shifts in opinion regarding environmental protection from ionising radiation have resulted in the development and availability of bespoke approaches for the assessment of impacts on wildlife from radioactive contaminants. The application of such assessment methodologies to actual situations, however, remains relatively limited. This paper describes the implementation of the ERICA Integrated Approach and associated tools within the context of routine discharges of radioactive materials to a freshwater environment. The article follows the implementation through its relevant stages and discusses strengths and weaknesses of the approach in relation to the case study. For current discharge levels, ¹³⁷Cs and ⁶⁰Co constitute the main dose contributors to the majority of reference organisms studied, although ²⁴¹Am and ³H are the main contributors for the phyto- and zooplankton categories. Patterns are observed depending on whether the reference organism is sediment-associated or not. At current discharge levels, none of the reference organisms exceeded or approached the selected screening level, and impacts on biota could be regarded as negligible.     

Input strategy analysis for an air quality data modelling procedure at a local scale based on neural network

In recent years, a significant part of the studies on air pollutants has been devoted to improve statistical techniques for forecasting the values of their concentrations in the atmosphere. Reliable predictions of pollutant trends are essential not only for setting up preventive measures able to avoid risks for human health but also for helping stakeholders to take decision about traffic limitations. In this paper, we present an operating procedure, including both pollutant concentration measurements (CO, SO₂, NO₂, O₃, PM10) and meteorological parameters (hourly data of atmospheric pressure, relative humidity, wind speed), which improves the simple use of neural network for the prediction of pollutant concentration trends by means of the integration of multivariate statistical analysis. In particular, we used principal component analysis in order to define an unconstrained mix of variables able to improve the performance of the model. The developed procedure is particularly suitable for characterizing the investigated phenomena at a local scale.     

Estimating home energy decision parameters for a hybrid energy—economy policy model

Hybrid energy–economy models combine the advantages of a technologically explicit bottom–up model with the behavioral realism sought after by top–down models in order to help policymakers assess the likely technology-specific response and economy-wide impact of policies to induce technological change. We use a discrete choice survey to estimate key technology choice parameters for a hybrid model. Two choice experiments are conducted for household energy-related decisions about retrofitting home building structures and choosing a space heating and conditioning system. Based on a discrete choice survey of 625 householders, we estimate a discrete choice model and then demonstrate how its parameters translate into the behavioral parameters of a hybrid model. We then simulate household energy policies, including, individual subsidies and increased regulations.     

Development of a model to assess environmental performance, concerning HSE-MS principles

The main objective of the present study was to develop a valid and appropriate model to evaluate companies’ efficiency and environmental performance, concerning health, safety, and environmental management system principles. The proposed model overcomes the shortcomings of the previous models developed in this area. This model has been designed on the basis of a mathematical method known as Data Envelopment Analysis (DEA). In order to differentiate high-performing companies from weak ones, one of DEA nonradial models named as enhanced Russell graph efficiency measure has been applied. Since some of the environmental performance indicators cannot be controlled by companies’ managers, it was necessary to develop the model in a way that it could be applied when discretionary and/or nondiscretionary factors were involved. The model, then, has been modified on a real case that comprised 12 oil and gas general contractors. The results showed the relative efficiency, inefficiency sources, and the rank of contractors.     

Fuzzy clustering analysis in environmental impact assessment — A complement tool to environmental quality index

In spite of rapid progress achieved in the methodological research underlying environmental impact assessment (EIA), the problem of weighting various parameters has not yet been solved. This paper presents a new approach, fuzzy clustering analysis, which is illustrated with an EIA case study on Baoshan-Wusong District in Shanghai, China. Fuzzy clustering analysis may be used whenever a composite classification of environmental quality/impact incorporates multiple parameters. In such cases the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering analysis, the classification is determined by a fuzzy relation. After a fuzzy similarity matrix has been established and the fuzzy relation stabilized, a dynamic clustering chart can be developed. Given a suitable threshold, the appropriate classification can be accomplished. The methodology is relatively simple and the results can be interpreted to provide valuable information to support decision making and improve management of the environment.     

Ensuring quality in long term environmental monitoring for chemical speciation

The awareness regarding quality assurance (QA) and quality control (QC) for environmental monitoring has considerably increased in the past few years, especially with respect to the determination of chemical species, since errors occurring at various levels may considerably affect the interpretation of results (e.g. studies of toxic impact, geochemical pathways, etc.). QA for environmental analysis covers a broad range of activities from sample collection to laboratory work and the approach for ensuring quality data should be considered in a global context. However, whereas great emphasis has been placed on QA within the laboratory, there have been few systematic attempts to evaluate risks of discrepancies related, for example, to field manipulations. The situation is even worse when monitoring is applied to relatively new fields such as chemical speciation. This paper outlines some of the main aspects of quality control of environmental analysis, including the validation of methods, sampling and sample handling, storage, etc., with special emphasis on the monitoring of chemical forms of elements (e.g. species of tin, mercury, lead and selenium).     

Representation of the environmental quality profile of a metropolitan area

The spatially and temporally varying environmental quality of a metropolitan area is described by means of empirically derived environmental indices. The approach is based on the principles of benefit analysis and consists of a number of logical steps including the selection, the measurement and determination of the spatial distribution, and the normalization (scaling) of the selected environmental indicators. To derive composite indices, the normalized indicators are weighted, based on the Delphi technique and subsequently aggregated. The results are given by means of isopleths, including single and composite index isopleths plotted by computer on common maps.World Health Organization     

Scaling methods in assessing environmental quality: A methodological approach to eutrophication

The identification of pollution levels by numerical classification-ordination and the statistical confirmation of the detected trends-were attempted in a eutrophication assessment study. Special emphasis was placed on the importance of data scaling and the selection of a distance coefficient that would accentuate discrete states within the system. Among metric, binary and ordinal variable scaling, ordinal numbers showed the maximum sensitivity in discriminating pollution levels; the observed trends were further enhanced by using the absolute distance coefficient as a resemblance measure. The eutrophic patterns identified were statistically confirmed by a non-parametric permutation test. Finally a step-by-step multivariate procedure is proposed for assessing environmental quality in aquatic ecosystems.     

Hydrologic modelling for Lake Basaka: development and application of a conceptual water budget model

Quantification of fluxes of water into and out of terminal lakes like Basaka has fundamental challenges. This is due to the fact that accurate measurement and quantification of most of the parameters of a lake’s hydrologic cycle are difficult. Furthermore, quantitative understanding of the hydrologic systems and hence, the data-intensive modelling is difficult in developing countries like Ethiopia due to limitation of sufficient recorded data. Therefore, formulation of a conceptual water balance model is extremely important as it presents a convenient analytical tool with simplified assumptions to simulate the magnitude of unknown fluxes. In the current study, a conceptual lake water balance model was systematically formulated, solved, calibrated, and validated successfully. Then, the surface water and groundwater interaction was quantified, and a mathematical relationship developed. The overall agreement between the observed and simulated lake stage at monthly time step was confirmed based on the standard performance parameters (R ², MAE, RMSE, E _f). The result showed that hydrological water balance of the lake is dominated by the groundwater (GW) component. The net GW flux in recent period (post-2000s) accounts about 56 % of the total water inflow. Hence, GW plays a leading role in the hydrodynamics and existence of Lake Basaka and is mostly responsible for the expansion of the lake. Thus, identification of the potential sources/causes for the GW flux plays a leading role in order to limit the further expansion of the lake. Measurement of GW movement and exchange in the area is a high priority for future research.     

Laser-induced breakdown spectroscopy application in environmental monitoring of water quality: a review

Water quality monitoring is a critical part of environmental management and protection, and to be able to qualitatively and quantitatively determine contamination and impurity levels in water is especially important. Compared to the currently available water quality monitoring methods and techniques, laser-induced breakdown spectroscopy (LIBS) has several advantages, including no need for sample pre-preparation, fast and easy operation, and chemical free during the process. Therefore, it is of great importance to understand the fundamentals of aqueous LIBS analysis and effectively apply this technique to environmental monitoring. This article reviews the research conducted on LIBS analysis for liquid samples, and the article content includes LIBS theory, history and applications, quantitative analysis of metallic species in liquids, LIBS signal enhancement methods and data processing, characteristics of plasma generated by laser in water, and the factors affecting accuracy of analysis results. Although there have been many research works focusing on aqueous LIBS analysis, detection limit and stability of this technique still need to be improved to satisfy the requirements of environmental monitoring standard. In addition, determination of nonmetallic species in liquid by LIBS is equally important and needs immediate attention from the community. This comprehensive review will assist the readers to better understand the aqueous LIBS technique and help to identify current research needs for environmental monitoring of water quality.     

An approach to the assessment of the quality of environmental monitoring data

This paper reports an approach to the assessment of the validity of environmental monitoring data--a 'data filter'. The strategy has been developed through the UK National Marine Analytical Quality Control (AQC) Scheme for application to data collected for the UK National Marine Monitoring Plan, although the principles described are applicable more widely. The proposed data filter is divided into three components: Part A, 'QA/QC'--an assessment of the laboratory's practices in Quality Assurance/Quality Control; Part B, 'fitness for purpose'--an evaluation of the standard of accuracy that can be demonstrated by activities in (A), in relation to the intended application of the data; and Part C, the overall assessment on which data will be accepted as usable or rejected as being of suspect quality. A pilot application of the proposed approach is reported. The approach described in this paper is intended to formalise the assessment of environmental monitoring data for fitness for a chosen purpose. The issues important to fitness for purpose are discussed and assigned a relative priority order on which to judge the reliability/usefulness of monitoring data.     

Tailoring a non-path-dependent model for environmental risk management and polycentric urban land-use planning

This study attempts to develop a non-path-dependent model for environmental risk management and polycentric urban land-use planning in Gorgan Township area, Iran. Applying three suitability layers of environmental risk (soil erosion, flood risk, fire risk, and land susceptibility), urbanization potential, and integrated surface (environmental risk plus urbanization potential layers), a non-path-dependent Cellular Automata-Markov Chain (CA-MC) model was configured to execute three scenarios of polycentric urban growth allocation. Specifically, the modeling approach improved the traditional functionality of the CA-MC model from a prediction algorithm into an innovative land allocation tool. Besides, due to its flexibility, the non-path-dependent model was able to explicitly include different characteristics of the landscape structure ranging from physical land attributes to landscape functions and processes (natural hazards). Accordingly, three polycentric urban growth allocation efforts were undertaken and compared in terms of connectivity and compactness of the resultant patterns and consumption of other land resources. Based on results, the polycentric allocation procedure based on integrated suitability layer produced a more manageable pattern of urban landscape, while the growth option based on environmental risk layer was more successful for protecting farmlands against excessive urbanization. This study suggests that polycentric urban land-use planning under the strategy of rural land development programs is an available option for designing an urban landscape with lower exposure to natural hazards and more economic benefits to rural residents. Finally, the non-path-dependent modeling is a recommended approach, when highly flexible and interactive decision-support systems as well as trend-breaking scenarios are desired.     

Assessment of multifaceted environmental issues and model development of an Indo-Burma hotspot region

The present article provides a multifaceted critical research review on environmental issues intimately related with the socio-economy of North East India (NE), a part of Indo-Burma hotspot. Further, the article addresses the issue of sustainable development of NE India through diverse ecological practices inextricably linked with traditional ecological knowledge (TEK). The biodiversity of NE India comprises endemic floral diversity, particularly medicinal plants of importance to pharmaceutical industry, and unique faunal diversity. Nevertheless, it is very unfortunate that this great land of biodiversity is least explored taxonomically as well as biotechnologically, probably due to geographical and political constraints. Different anthropogenic and socio-economic factors have perturbed the pristine ecology of this region, leading to environmental degradation. Also, the practice of unregulated shifting cultivation (jhooming), bamboo flowering, biological invasions and anthropogenic perturbations to biodiversity exacerbate the gloomy situation. Instead of a plethora of policies, the TEK of NE people may be integrated with modern scientific knowledge in order to conserve the environment which is the strong pillar for socio-economic sector here. The aforesaid approach can be practiced in NE India through the broad implementation and extension of agroforestry practices. Further, case studies on Apatanis, ethnomedicinal plants use by indigenous tribal groups and sacred forests are particularly relevant in the context of conservation of environmental health in totality while addressing the socioeconomic impact as well. In context with the prevailing scenarios in this region, we developed an eco-sustainable model for natural resource management through agroforestry practices in order to uplift the social as well as environmental framework.     

Site environmental assessment to an old paint factory in China

High ethyl-benzene and total petroleum hydrocarbons (TPHs) were found in the soil samples and groundwater samples during a site environmental assessment for an old paint factory in the city Changchun, Jilin province of China. The target old paint plant had been in operation for near 30 years by manufacturing resin and house paint. Driving force for this study was to identify potential environmental contamination existing in this paint factory which is located next to a new resident area under construction. The assessment result would be used as baseline environmental data input for remediation plan when the factory site will be changed into potential resident area in near future. The analytical data from the soil samples from different area of the factory which had high exposure to operation showed that solid waster storage area was contaminated with high heavy metals (Cd, Pb, and Zn) and waster paint storage areas were contaminated with ethyl-benzene, xylene and C9-C30 aromatic hydrocarbon solvent. The analytical data from the groundwater samples from different area of the factory showed that resin plant area and waster paint storage areas were contaminated with high concentration of naphthalene, ethyl-benzene and xylene which exceed the reference standard. Remediation action is recommended.