Abstract

ABSTRACT Environmental impact assessments in Brazil have usually focused solely on project-related issues without considering the regional context. Although required by current environmental legislation, cumulative impact assessments have not been included in the overall environmental assessment of projects. However, in recent Strategic Environmental Assessment (SEA) studies of policies, plans, and programs undertaken on a voluntary basis in support of the decision-making process, this kind of assessment has been performed especially with respect to air quality. This paper presents the application of a methodology for the quantification of cumulative impacts on air quality under high uncertainty caused by various mining activities in a single region that is recommended for SEA studies. In this way, the methodology presented here is suitable for areas lacking detailed modeling information. The developed approach uses a relatively simplified mathematical model, lowering information gathering costs and requiring little processing time. The application of the methodology is illustrated in the case of a SEA of the Corumbá Mining and Industrial Complex Development Program. Despite the lack of data needed for a minimum characterization of conditions of the area surrounding the region modeled, the quantification of impact cumulativeness on air quality has played an important role in the context of the SEA. IMPLICATIONS The importance in the Brazilian context of the analysis of cumulativeness in environmental impact assessments has become increasingly evident to some public and private stakeholders who have begun to discuss the issue thanks to SEA studies. This paper presents an alternative methodology to conduct quantitative analysis of cumulative impacts on air quality, requiring less detailed field data while using a less complex, but usually conservative, mathematical model of atmospheric pollutant dispersion. The developed approach provides support for decision-making, enabling policy-makers to discuss strategic options in the formulation of programs, plans, and policies in these cases with potentially high uncertainty.

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