Interactions between operational research and environmental management

Existing methods of establishing ambient air quality monitoring networks typically evaluate only parameters related to ambient concentrations of the contaminant(s) of interest such as emission source characteristics, atmospheric transport and dispersion, secondary reactions, deposition characteristics, and local topography However, adverse health risks from exposures to airborne contaminants are a function of the contaminant and the anatomic and physiologic characteristics of the exposed population Thus, ambient air quality monitoring networks designed for the protection of public health or for epidemiological studies evaluating adverse health impacts from exposures to ambient air contaminants should account for both contaminant characteristics and human health parameters A methodology has been established which optimizes ambient air quality monitoring networks for assessments of adverse human health impacts from exposures to airborne contaminants by incorporating human health risk assessment techniques The use of risk assessment techniques as the basis for designing ambient air quality monitoring networks will help to target limited financial and human resources to evaluate human health risks from exposures to airborne contaminants

Ambient air quality monitoring network design for assessing human health impacts from exposures to airborne contaminants.

A holistic approach for optimal design of air quality monitoring network expansion in an urban area

Assessing relocation strategies of urban air quality monitoring stations by GA-based compromise programming

A new method for multi-objective optimization of air quality monitoring systems based on satellite remote sensing of the troposphere is described in this work The technique uses atmospheric turbidity as surrogate for air pollution loading Through inverse chemical modeling and ancillary information the respective patterns of primary gaseous and particle pollutants are inferred The optimization algorithm uses the resulting maps of ambient air pollution as input It focuses on the gain of information with regard to human exposure to high pollution, potential impact on cultural heritage, compliance to ambient air quality standards, monitoring key point and area source emissions, as well as on the associated cost Application of the method in Brescia, Italy showed its significant potential for improving the cost-effectiveness of air quality monitoring networks at the urban and regional scales

Multi-objective optimization of air quality monitoring.

Minimum Spanning Tree (MST) algorithm developed by Modak and Lohani (1984a) has been extended to consider multiple objectives for the optimum siting of ambient air monitors. Two approaches have been proposed, namely one based on the utility function and another based on the principles of sequential interactive compromise. The sequential interactive approach is heuristic but perhaps best suited to consider several objectives at a time, and particularly when professional judgements are also involved. The utility function approach may be normally restricted to two objectives at a time, but could be extended to consider a number of pollutants in the optimum design. For the purpose of illustration, the case of Taipei City, Taiwan has been considered.

B. N. Lohani

Papers

Optimization of ambient Air Quality Monitoring Networks : (Part III).