Impact of the Benefit Function Slope on the Advantage of Spatially Discriminating the Pollution Abatement Effort

Abstract

Many articles have dealt with the advantages of spatially discriminating the abatement effort when the pollution is non-uniformly mixed. However, few authors have attempted to identify the impact of certain model parameters on the advantage of this discrimination. These parameters are the transfer coefficients, the parameters of the abatement cost function or the level of the quality standard. In this article, we studied the role of the slope of the environmental benefit function on the advantages of spatially discriminating pollution abatement efforts. It appears that the relative increase in the net social benefit between a uniform and a perfectly discriminated control is not affected by this slope. However, in the case of partial discrimination, a steeper benefit slope increases the optimal number of zones.

Cost-benefit analysis of nitrate abatement in the Souffel catchment (France): Sensitivity study of the damage and spatialization of the abatement effort

“…These results are consistent with those in the literature (Krysiak and Schweitzer, 2010;Destandau, 2013) that indicate that a higher degree of damage requires a greater spatialization of the input reduction effort or of decontamination, depending on the study. The absolute and relative advantages of spatialization are approximately 2.5 times greater for uniform vulnerability than for heterogeneous vulnerability (Table 4).…”

“…This can be explained by the limited size of the study catchment, and probably reveals relatively homogeneous characteristics of the polluters in terms of their marginal contribution to the damage. We can also observe in Table 3 that, consistent with the theoretical results of Destandau (2013), the benefit of spatialization increases with the damage generated by the pollution.…”

“…As a result, it is crucial to know the factors that influence the magnitude of the advantage of spatializing the abatement effort on uniform regulation. O'Ryan (2006), Destandau and Nafi (2010), Krysiak and Schweitzer (2010) and Destandau (2013) all addressed this issue. It appears that it is the heterogeneity of the transfer coefficients, the marginal contributions to damage, the shape of the abatement cost curves and the shape of the environmental benefit curve in the event of a first-level regulation (maximization of the net benefit), or the intensity of the standard in the case of a second-level regulation (attaining an environmental standard at the lowest possible cost), which either justifies taking spatialization into account or not.…”

“…Indeed, Tietenberg (2006) presents the results of empirical studies on air pollution reduction policies in the United States where it appears that the gains in pollution control costs to reach the same standard are reduced, depending on the study, by 6.6% to 95.7% with a spatialized vs. uniform policy. Several authors have studied the contextual parameters that could influence the benefit of spatialization (O'Ryan, 2006;Destandau and Nafi, 2010;Krysiak and Schweitzer, 2010;Destandau, 2013).…”

“…On the other hand, for marginal linear abatement costs, the standard has no impact on the benefit of spatialization. In another theoretical study, Destandau (2013) once again attempted to identify the impact of the environmental policy issue on the advantage of spatialization, but this time in a first-best regulation where one seeks to maximize the net benefit. This time, it appeared that the magnitude of the damage could increase the advantage of spatialization.…”