Estimation of the Thermal Sensitivity of a Dwelling to Variations in Architectural and Behavioural Parameters

The provision of energy for households is a major contributor to greenhouse gas emissions in the domestic sector. There is significant scope for energy savings and thus emission reduction in this sector. This paper constructs a bridge between thermal analysis and environmental assessment in the occupancy stage of the dwelling life cycle, approaching both methods as being on a common system Environment–Dwelling–Inhabitant. The importance of the local level in the thermal analysis and assessment of either a dwelling or an inhabitant's behaviour is demonstrated. It is shown that the researcher can choose between natural experiment, computer experiment and mathematical modelling to analyze the system. Such a choice is discussed for two particular methods of thermal analysis. Thermal Nomograms are the result of mathematical modelling, and the Energy Score Sheet is the result of a computer experiment in energy rating. Despite being developed for the purpose of thermal analysis, these methods can also be utilized for environmental assessment at the local level. The discussion centres on Australian conditions where the majority of the population resides in a relatively benign climate wherein behavioural alterations have significant potential for energy savings and environmental impact. The purpose of the paper is to emphasise benefits apart from energy minimisation to promote the use of energy efficient housing strategies.     

Air quality impact assessment

Air quality impact assessment (AQIA) is an important technique for determining the relative contribution to ground level pollutant concentrations of specific current or future source emissions at receptor sites. The principal activities in AQIA are air quality modelling and monitoring techniques. The choice of techniques which are applicable to a particular situation is intimately related to the problem to be assessed. A review of relevant modelling techniques has been presented, with emphasis placed on Gaussian plume models because of their ease of use and broad applicability. Alternative modelling techniques have been suggested when departures from the Gaussian form in the atmosphere occurs or when more detailed information on atmospheric chemistry, deposition or long range transport is required. The objectives and techniques of ambient air quality monitoring have been examined and the siting of instruments, duration and frequency of sampling, choice of monitoring rationale (fixed or mobile), minimization of sampling errors, data storage and analysis are discussed. Modelling and monitoring are essential to successful AQIA. An orderly approach to the principles and procedures involved in performing AQIA studies, using these two techniques in conjunction, has been presented.     

A Comparison Between Regression Models and Genetic Programming for Predictions of Chlorophyll-a Concentrations in Northern Lakes

Chlorophyll-a (chl-a) concentrations are often used as a proxy for water quality problems as well as phytoplankton blooms. Available chl-a models range from simple phosphorus loading models to complex regression and dynamic models. A comparison of multiple regression models was made with genetic programming (GP) techniques to predict chl-a concentrations over a large range of 104 Swedish lakes. Independent variables used were lake area, mean depth, iron, latitude, ammonium, nitrogen + nitrate, pH, phosphate, secchi depth, silicon, temperature, total phosphorus, total nitrogen and total organic carbon. GP is a method based on the Darwinian evolution theory. This implies that a program will be able to test different mathematical equations, iterating and improving each equation using fundamental ideas from evolution theory to increase the predictive power. A good correspondence was found between the multiple regression and the GP modelling approach. No significant improvement of the predictive power was found using GP, and it is therefore recommended that multiple regression methods should be preferred when predicting chl-a concentrations as these models tend to be less complex and the modelling approach is easier to use. Results from GP were in some cases more accurate compared to multiple regressions; however, the best model was created by multiple regressions which used concentrations of total phosphorus, total nitrogen and latitude as independent variables. These findings will be an important note for limnologists and modelling managers when developing future models of chl-a concentrations in lakes.     

Quantitative health impact assessment methodology for societal initiatives: A scoping review

Health initiatives are increasingly situated outside the institutionalised public health sector. The intersectoral character of societal initiatives, along with indirect relationships between initiatives and health, makes making projections of reach, impact and goal achievement complex. This scoping review of the peer-reviewed literature searches for appropriate methods to conduct quantitative health impact assessment for such initiatives. Database searches were done in PubMed and Web of Science, as well as a reference list search. Studies were then selected in a systematic manner. The review includes 64 studies. Most studies made estimates using simulation methods, notably with Monte Carlo, Markov and system dynamics modelling. Inputs for the models such as transition probabilities and price elasticities were taken from census, register and survey data, evidence from previous (scientific) studies and sometimes outcomes from stakeholder participation. Of different health outcome measures, the number of deaths was most frequently used, followed by QALYs and DALYs and life years. Health effect distribution is frequently mentioned, but not often estimated. Scientific methodological publications on HIAs focusing on civil society initiatives are relatively sparse, indicating possibilities for further methodological advancement. Estimating health effect distributions and incorporating stakeholder participation could make meaningful additions to standard practice.     

Health impact assessment – A survey on quantifying tools

Integrating human health into prospective impact assessments is known to be challenging. This is true for both approaches: dedicated health impact assessments (HIA) as well as inclusion of health into more general impact assessments. Acknowledging the full range of participatory, qualitative, and quantitative approaches, this study focuses on the latter, especially on computational tools for quantitative health modelling. We conducted a survey among tool developers concerning the status quo of development and availability of such tools; experiences made with model usage in real-life situations; and priorities for further development. Responding toolmaker groups described 17 such tools, most of them being maintained and reported as ready for use and covering a wide range of topics, including risk & protective factors, exposures, policies, and health outcomes. In recent years, existing models have been improved and were applied in new ways, and completely new models emerged. There was high agreement among respondents on the need to further develop methods for assessment of inequalities and uncertainty. The contribution of quantitative modeling to health foresight would benefit from building joint strategies of further tool development, improving the visibility of quantitative tools and methods, and engaging continuously with actual and potential users.     

Cultural Theory and integrated assessment

Most scientific work, integrated assessment included, tries to avoid bias. Cultural Theory, however, suggests that bias is unavoidable, and it predicts the various biases that are possible, the social conditions under which each will occur and the essentially complex nature of their interaction. If Cultural Theory is right (and examples from energy modelling and human land use in mountain ecosystems suggest that it is) then it is important that it and integrated assessment come together. The paper begins by explaining how this has, in fact, been happening, and then explores the implications of this for integrated assessment. Cultural Theory, in completing the fourfold typology of forms of social solidarity that is implicit in the classic markets‐and‐hierarchies distinction, gives us human systems that are complex: non‐linear, indeterministic, far from equilibrium, highly sensitive to initial conditions, and with future states that are unpredictable. Since the same has now been done to the classic ecological distinction between pioneer and climax communities, we find ourselves trying to manage a system, of which we ourselves are part, that is not manageable in the way that simple systems are manageable. Coming to terms with that new understanding, and putting together the tool‐kit appropriate to policy in a complex world, is the task we face. “Always learning, never getting it right” captures the new understanding: a sentiment that many integrated assessors will find congenial. The new tool‐kit, however, with its emphasis on reflexivity, on scenario planning and on micro and macro each as the cause of the other, presents more of a challenge.     

EIA training courses organized by the centre for environmental management and planning,University of Aberdeen: An analysis of experience

In 1980, the World Health Organization (Regional Office for Europe) invited The Centre for Environmental Management and Planning (CEMP) to organize a two-week training course on Environmental Impact Assessment (EIA) to provide a comprehensive introduction to EIA with emphasis on methods and techniques for impact identification, prediction and assessment. Not suprisingly the topic of environmental health impact assessment was to be a major focus. Since 1980, the course has been held each year at the University of Aberdeen. An analysis of participation in the course during its first five years yields several impressions about the success of this training effort and the ways in which it might be improved.     

A critical review of principal traffic noise models: Strategies and implications

The paper presents an exhaustive comparison of principal traffic noise models adopted in recent years in developed nations. The comparison is drawn on the basis of technical attributes including source modelling and sound propagation algorithms. Although the characterization of source in terms of rolling and propulsion noise in conjunction with advanced numerical methods for sound propagation has significantly reduced the uncertainty in traffic noise predictions, the approach followed is quite complex and requires specialized mathematical skills for predictions which is sometimes quite cumbersome for town planners. Also, it is sometimes difficult to follow the best approach when a variety of solutions have been proposed. This paper critically reviews all these aspects pertaining to the recent models developed and adapted in some countries and also discusses the strategies followed and implications of these models.     

流域环境风险评价研究进展

在分析流域环境风险内涵的基础上,从研究内容和研究方法两个方面,综述了国内外流域环境风险评价研究现状。指出目前研究内容主要集中在流域水质健康风险评价、流域生态风险评价、地下水环境风险评价、突发事件和农业非点源污染的流域环境风险评价等方面,主要采用基于层次分析、突变理论或经验公式(数学模型)的研究方法。在此基础上讨论了目前研究存在的不足,并从复杂动态系统分析的角度提出了未来的发展趋势。     

Environmental Impact Assessment of the Mining and Concentration Activities in the Kola Peninsula, Russia by Multidate Remote Sensing

On the Kola Peninsula, the mining and concentration industry exerts anthropogenic impact on the environment. Tailing dumps cause airborne pollution through dusting, and waterborne pollution due to direct dumping and accidental releases. The objectives were: (1) to analyse multidate satellite imagesfor 1964–1996 to assess the environmental pollution from themining and concentration activity in the Kola in temporal perspective; (2) to evaluate remote sensing methods for integrated environmental impact assessment. The area of mining and industrial sites steadily expands and amounted to 94 km² in 1996. The polluted water surface amounted to at least 150 km² through dumping in 1978 and to 106 km² in1986 due to dusting. Thus, the impact from the mining and concentration activity should be reconsidered as more significant than it was officially anticipated. In the past the main mechanism of pollution wasdirect dumping into the lakes. Currently and in future, airborne pollution after dusting storms will dominate. The effective recultivation of the tailing dumps will be a long-term process. For effective assessment of impacts from the mining and concentration industry, remote sensing methods should be complemented by in-situ measurements, fieldwork, and mathematical modelling.     

Rethinking human health impact assessment

Most EIA programs around the world require the consideration of human health impacts. Yet relatively few EIA documents adequately address those impacts. This article examines how, why, and to what extent health impacts are analyzed in environmental impact assessments in the U.S. An empirical study of 42 environmental impact statements found that more than half contained no mention of health impacts. In the others, health impacts were analyzed narrowly, if at all, using risk assessment to quantify the carcinogenic potential of a single substance over a single generation. This analytic focus overlooks other significant morbidity and mortality risks, cumulative and intergenerational effects, and broader determinants of health. This article investigates these problems and provides recommendations to improve human health impact assessment, using strategic environmental assessment, qualitative health data, health outcomes in addition to cancer, and a precautionary approach to risk.     

Assessing corporate project impacts in changeable contexts: A human rights perspective

Project-level impact assessment was originally conceived as a snapshot taken in advance of project implementation, contrasting current conditions with a likely future scenario involving a variety of predicted impacts. Current best practice guidance has encouraged a shift towards longitudinal assessments from the pre-project stage through the implementation and operating phases. Experience and study show, however, that assessment of infrastructure-intensive projects rarely endures past the project's construction phase. Negative consequences for environmental, social and health outcomes have been documented. Such consequences clarify the pressing need for longitudinal assessment in each of these domains, with human rights impact assessment (HRIA) as an umbrella over, and critical augmentation of, environmental, social and health assessments. Project impacts on human rights are more closely linked to political, economic and other factors beyond immediate effects of a company's policy and action throughout the project lifecycle. Delineating these processes requires an adequate framework, with strategies for collecting longitudinal data, protocols that provide core information for impact assessment and guidance for adaptive mitigation strategies as project-related effects change over time. This article presents general principles for the design and implementation of sustained, longitudinal HRIA, based on experience assessing and responding to human rights impact in a uranium mining project in Malawi. The case study demonstrates the value of longitudinal assessment both for limiting corporate risk and improving human welfare.     

Impact of model parameterization on predictive uncertainty of regional groundwater models in the context of environmental impact assessment

Parameterization strategy impacts models' outputs and the associated uncertainty. This is particularly true for transient regional groundwater models where parameters can only be weakly constrained by insufficient observations. However, this is rarely investigated under any particular model structure. This study bridges this gap using a regional groundwater model developed to understand the impact of coal seam gas extraction on groundwater systems in a probabilistic framework. Two different parameterization schemes were implemented for hydraulic conductivity and specific storage. The first method solely relies on the relationship between hydraulic properties and burial depths. The second more complex strategy allows more spatial variations of hydraulic parameters using pilot points. The study provides new insights and practical guidance on the application of groundwater modelling for environmental impact assessment. The results suggest that the choice of model parameterization has a significant influence on predictive uncertainty. The model using the simple parameterization provides predictions with a much wider range than the model with a more sophisticated parameterization. This is because that the lowly parameterized model tends to generate more extreme effective hydraulic parameter fields unless the parameterization simplification converts the inverse problem to a (close to) well-posed problem that rarely exists for applied regional groundwater modelling. The potential impact of model parameterization should be discussed explicitly in groundwater modelling applications to support decision making to avoid misinterpretation of the modelling results.     

Computer-aided rapid environmental impact assessment

Environmental impact assessment of a project attempts to bring about compatibility between ecology and economics. A computer-aided, quantitative and rapid methodology for environmental impact assessment is presented in this paper. The cost of abatement of deleterious environmental impacts is one of the factors used to identify the best project option from environmental and cost considerations. The methodology is based on the three basic steps of environmental impact assessment vis-à-vis identification, prediction, and evaluation. Several models and predictors for different environmental components are incorporated in the computer program. An evaluation method is presented based on mathematical functions for value function graphs for different aesthetic, environmental, and health risks.     

Multi-scale Atmospheric Dispersion Modelling by Use of Adaptive Gridding Techniques

An accurate prediction of the transport-reaction behaviour of atmospheric chemical species is required to fully understand the impact on the environment of pollution emissions. Elevated levels of secondary pollutants such as ozone in the lower atmosphere can be harmful to the health of both plants and animals, and can cause damage to property present in the urban environment. Detailed models of pollution mechanisms must therefore be developed through comparisons with field measurements to aid the selection of effective abatement policies. Such models must satisfy accuracy requirements both in terms of the number of species represented, and the spatial resolution of species profiles. Computational expense often compels current models to sacrifice detail in one of these areas. This paper attempts to address the latter point by presenting an atmospheric transport-reaction modelling strategy based upon a finite volume discretisation of the atmospheric dispersion equation. The source terms within this equation are provided by an appropriate reduced chemical scheme modelling the major species in the boundary layer. Reaction and transport discretisations are solved efficiently via a splitting technique applied at the level of the non-linear equations. The solution grid is generated using time dependant adaptive techniques, which provide a finer grid around regions of high spatial error in order to adequately resolve species concentration profiles. The techniques discussed are applied in two dimensions employing emissions from both point and area sources. Preliminary results show that the application of adaptive gridding techniques to atmospheric dynamics modelling can provide more accurately resolved species concentration profiles, accompanied by a reduced CPU time invested in solution. Such a model will provide the basis for high resolution studies of the multiple scale interactions between spatially inhomogeneous source patterns in urban and regional environments.     

Intervention analysis in environmental engineering

Intervention analysis techniques are described for identifying and statistically modelling trends which may be present in water quality time series. At the exploratory data analysis stage, simple graphical and modelling methods can be employed for visually detecting and examining trends in a time series caused by one or more external interventions. For instance, a plot of a robust locally weighted regression smooth through a graph of the observations over time may reveal trends and other interesting statistical properties contained in the time series. In addition, statistical tests, such as different versions of the nonparametric Mann-Kendall test, can be used to detect the presence of trends caused by unknown or known external interventions. To characterize rigorously and estimate trends which may be known in advance or else detected using exploratory data analysis studies, different parametric methods can be utilized at the confirmatory data analysis stage. Specifically, the time series modelling approach to intervention analysis can be employed to estimate the magnitudes of the changes in the mean level of the series due to the interventions. Particular types of regression models can also be used for estimating trends, especially when there are many missing observations. To demonstrate how intervention analysis methods can be effectively used in environmental impact assessment, representative applications to water quality time series are presented.Invited Paper for Presentation at The Workshop on Statistical Methods for the Assessment of Point Source Pollution, The Canada Centre for Inland Waters, Burlington, Ontario, Canada, L7R 4A6, September 12–14, 1988.     

An inquiry into the potential of scenario analysis for dealing with uncertainty in strategic environmental assessment in China

Strategic environmental assessment (SEA) inherently needs to address greater levels of uncertainty in the formulation and implementation processes of strategic decisions, compared with project environmental impact assessment. The range of uncertainties includes internal and external factors of the complex system that is concerned in the strategy. Scenario analysis is increasingly being used to cope with uncertainty in SEA. Following a brief introduction of scenarios and scenario analysis, this paper examines the rationale for scenario analysis in SEA in the context of China. The state of the art associated with scenario analysis applied to SEA in China was reviewed through four SEA case analyses. Lessons learned from these cases indicated the word “scenario” appears to be abused and the scenario-based methods appear to be misused due to the lack of understanding of an uncertain future and scenario analysis. However, good experiences were also drawn on, regarding how to integrate scenario analysis into the SEA process in China, how to cope with driving forces including uncertainties, how to combine qualitative scenario storylines with quantitative impact predictions, and how to conduct assessments and propose recommendations based on scenarios. Additionally, the ways to improve the application of this tool in SEA were suggested. We concluded by calling for further methodological research on this issue and more practices.     

An inquiry into the potential of scenario analysis for dealing with uncertainty in strategic environmental assessment in China

Strategic environmental assessment (SEA) inherently needs to address greater levels of uncertainty in the formulation and implementation processes of strategic decisions, compared with project environmental impact assessment. The range of uncertainties includes internal and external factors of the complex system that is concerned in the strategy. Scenario analysis is increasingly being used to cope with uncertainty in SEA. Following a brief introduction of scenarios and scenario analysis, this paper examines the rationale for scenario analysis in SEA in the context of China. The state of the art associated with scenario analysis applied to SEA in China was reviewed through four SEA case analyses. Lessons learned from these cases indicated the word “scenario” appears to be abused and the scenario-based methods appear to be misused due to the lack of understanding of an uncertain future and scenario analysis. However, good experiences were also drawn on, regarding how to integrate scenario analysis into the SEA process in China, how to cope with driving forces including uncertainties, how to combine qualitative scenario storylines with quantitative impact predictions, and how to conduct assessments and propose recommendations based on scenarios. Additionally, the ways to improve the application of this tool in SEA were suggested. We concluded by calling for further methodological research on this issue and more practices.     

Methods for land use impact assessment: A review

Many types of methods to assess land use impact have been developed. Nevertheless a systematic synthesis of all these approaches is necessary to highlight the most commonly used and most effective methods. Given the growing interest in this area of research, a review of the different methods of assessing land use impact (LUI) was performed using bibliometric analysis. One hundred eighty seven articles of agricultural and biological science, and environmental sciences were examined. According to our results, the most frequently used land use assessment methods are Life-Cycle Assessment, Material Flow Analysis/Input–Output Analysis, Environmental Impact Assessment and Ecological Footprint. Comparison of the methods allowed their specific features to be identified and to arrive at the conclusion that a combination of several methods is the best basis for a comprehensive analysis of land use impact assessment.     

Assessment of regional metal levels in ambient air by statistical regression models

The assessment of the particulate matter (PM) levels and its constituents presented in the atmosphere is an important requirement of the air quality management and air pollution abatement. The heavy metal levels in PM10 are commonly evaluated by experimental measurements; nevertheless, the EC Directives also allow the Regional Governments to estimate the regulated metal levels (Pb in Directive 2008/50/EC and As, Ni and Cd in Directive 2004/107/EC) by objective estimation and modelling techniques. These techniques are proper alternatives to the experimental determination because the required analysis and/or the number of required sampling sites are reduced. The present work aims to estimate the annual levels of regulated heavy metals by means of multivariate linear regression (MLR) and principal component regression (PCR) at four sites in the Cantabria region (Northern Spain). Since the objective estimation techniques may only be applied when the regulated metal concentrations are below to the lower assessment threshold, a previous evaluation of the determined annual levels of heavy metals is conducted to test the fulfilment of the EC Directives requirements. At the four studied sites, the results show that the objective estimations are allowed alternatives to the experimental determination. The annual average metal concentrations are well estimated by the MLR technique in all the studied sites; furthermore, the EC quality requirements for the objective estimations are fulfilled by the developed statistical MLR models. Hence these estimations may be used by Regional Governments as a proper alternative to the experimental measurements for the regulated metal levels assessment.