Supporting multi-stakeholder environmental decisions

This paper examines how multiple criteria analysis (MCA) can be used to support multi-stakeholder environmental management decisions. It presents a study through which 48 stakeholders from environmental, primary production and community interest groups used MCA to prioritise 30 environmental management problems in the Mackay-Whitsunday region of Queensland, Australia. The MCA model, with procedures for aggregating multi-stakeholder output, was used to inform a final decision on the priority of the region's environmental management problems. The result was used in the region's environmental management plan as required under Australia's Natural Heritage Trust programme. The study shows how relatively simple MCA methods can help stakeholders make group decisions, even when they hold strongly conflicting preferences.     

探析资源环境承载力约束下的“多规合一”思路

在我国进一步加强城市治理、大力开展环境与资源保护工作中,提出相关部门需要通力合作,实现"多规合一"的要求。而在"多规合一"中,资源环境承载力及其约束发挥了重要的作用。本文立足于此背景,在阐明资源环境承载力与"多规合一"基本内涵的基础上,结合相关研究资料,重点围绕资源环境承载力约束下的"多规合一"思路进行简要分析研究。     

Agricultural causes of desertification risk in Minqin, China

This study uses statistical modeling techniques to develop a desertification risk index (RI) for Minqin County, Gansu Province, China. Twenty socio-economic factors were selected and compared with the RI results to explore the spatial and temporal variability of desertification risk in the study area and to identify possible local driving forces behind desertification risk. The explanatory factors were different in 1988, 1992 and 1997, possibly reflecting the role of temporal variation as a contributor to desertification. The average number of sheep per-household was found to be an important indicator of change in desertification risk, while changes in ridge crop planting area explained the distribution of the rate of change in desertification risk in 1988-1992. The results suggests that the RI was useful in expanding the understanding of spatial temporal desertification issues in Minqin County, as well as identifying a current set of agricultural activities related to desertification risk. Further, given the limited nature of consistent data and observations for the area, development of the RI also served to establish a baseline for future investigations into desertification change and the risks such change might pose for the region.     

Effects of sludge characteristics on electrical resistance and energy consumption during electro-dewatering process

The increase of electrical resistance (ER) and energy consumption (EC) during the later stage of dewatering is a major problem hindering the development of electro-dewatering (EDW) technology. As the variations of sludge characteristics are significant during the EDW process, the relationships between sludge characteristics and ER and EC during EDW remain unclear. In this study, the effects of moisture content (MC), thickness, pH, conductivity, zeta potential, temperature, and gas volume on the ER and EC during the EDW process were statistically investigated using correlation and multiple linear regression analyses. Herein, the results showed that the ER of the sludge near the anode was primarily affected by pH, whereas the sludge near the cathode was primarily affected by the MC and conductivity. Further, sludge temperature and conductivity were the most reliable indicators to predict the EC near the anode and cathode, respectively. The results of this study provide theoretical guidance useful for solving the increase of ER and EC during the later stage of the EDW process.     

GIS and multiple-criteria evaluation for the optimisation of tsetse fly eradication programmes

Tsetse flies are the vectors of trypanosomes, the causal agent of trypanosomiasis, a widespread disease of livestock and people in Africa. Control of tsetse may open vast areas of land to livestock-keeping, with the associated benefits of developing mixed crop-livestock production systems. However, as well as possible positive impacts there are also risks: bush clearing would accelerate and cattle numbers would rise, leading to a reduction of vegetation cover, and an increase in runoff and erosion; there may also be increased pressure on conserved areas and reductions in biodiversity. The objective of this study is to show how remotely sensed and other environmental data can be combined in a decision support system to help inform tsetse control programmes in a manner that could be used to limit possible detrimental effects of tsetse control. For Zambia, a methodology is developed that combines a tree-based decision-support approach with the use of Multiple-Criteria Evaluation (MCE), within a Geographical Information System (GIS), in order to target areas for tsetse control. The results show clear differentiation of priority areas under a series of hypothetical scenarios, and some areas (e.g. northwest of Petauke in the Eastern Province of Zambia) are consistently flagged as high priority for control. It is also demonstrated that priority areas do not comprise isolated tsetse populations, meaning that disease control using an integrated approach is likely to be more economically viable than local eradication.     

Model-based hazard identification in multiphase chemical reactors

Chemical productions operated in extreme conditions (high pressure, high temperature) require a detailed analysis of all potentially dangerous situations that can lead to a major industrial accident and thus cause a loss of life and property. Many accidents in the near or distant history underline the need of a detailed safety analysis in process industries, not only in the phase of plant design but also during the operation of the plant. It would be shown that simulation of a chemical unit using an appropriate mathematical model and the nonlinear analysis theory can be a suitable tool for safety analysis. This approach is based on mathematical modeling of a process unit where both the steady-state analysis, including the analysis of the steady states multiplicity and stability, and the dynamic simulation are used. Principal objective of this paper is to summarize problems regarding the model-based hazard identification in processes. A case study, focused on phenomena of multiple steady states in ammonia synthesis reactor will be presented. The influence of the model complexity and model parameters uncertainly on the quality of safety analysis would be underline.     

Multiple pool fires: Occurrence,simulation, modeling and management

When two or more pool fires burn in such close proximity of one another that they can influence each other, they are termed ‘multiple pool fires’ (MPF). The characteristics and the structure of MPFs are significantly different from that of stand-alone pool fires. Even though MPFs have known to occur fairly often in chemical process industries, much lesser work has been done towards simulation, modeling and control of MPFs as compared to stand-alone pool fires.This paper is perhaps the first-ever attempt at surveying the MPF state-of-the-art. It recounts MPF accidents and catalogs the controlled experiments that have been done to understand the mechanism and impact of MPFs. Attempts to model MPFs have been assessed and possible ways to manage MPFs have been touched upon.     

A two-stage inexact joint-probabilistic programming method for air quality management under uncertainty

A two-stage inexact joint-probabilistic programming (TIJP) method is developed for planning a regional air quality management system with multiple pollutants and multiple sources. The TIJP method incorporates the techniques of two-stage stochastic programming, joint-probabilistic constraint programming and interval mathematical programming, where uncertainties expressed as probability distributions and interval values can be addressed. Moreover, it can not only examine the risk of violating joint-probability constraints, but also account for economic penalties as corrective measures against any infeasibility. The developed TIJP method is applied to a case study of a regional air pollution control problem, where the air quality index (AQI) is introduced for evaluation of the integrated air quality management system associated with multiple pollutants. The joint-probability exists in the environmental constraints for AQI, such that individual probabilistic constraints for each pollutant can be efficiently incorporated within the TIJP model. The results indicate that useful solutions for air quality management practices have been generated; they can help decision makers to identify desired pollution abatement strategies with minimized system cost and maximized environmental efficiency.     

More is not always better: coping with ambiguity in natural resources management

Coping with ambiguities in natural resources management has become unavoidable. Ambiguity is a distinct type of uncertainty that results from the simultaneous presence of multiple valid, and sometimes conflicting, ways of framing a problem. As such, it reflects discrepancies in meanings and interpretations. Under the presence of ambiguity it is not clear what problem is to be solved, who should be involved in the decision processes or what is an appropriate course of action. Despite the extensive literature about methodologies and tools to deal with uncertainty, not much has been said about how to handle ambiguities. In this paper, we discuss the notions of framing and ambiguity, and we identify five broad strategies to handle it: rational problem solving, persuasion, dialogical learning, negotiation and opposition. We compare these approaches in terms of their assumptions, mechanisms and outcomes and illustrate each approach with a number of concrete methods.