Bayesian Analysis of Air Emission Violations from Waste Incineration and Coincineration Plants.

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ID: 14208
2018
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Abstract
Waste incineration and coincineration plants in most European countries have frequently updated their flue gas cleaning systems, surpassing in most cases E.U. air emission standards. At the same time, in most developing countries, cement and other coincineration facilities follow less stringent emission regulations and have a mixed record of protecting air quality. The European Union, the United States, and Canada have established penalties for air emission violations that account for the harm done to the environment and to human health and aiming to remove the economic benefit reaped as a result of noncompliance. Despite their legal completeness, these regulations do not adequately address the probabilistic nature of air pollution. This article recasts the issue of air pollution penalties in a Bayesian decision-making framework with the aspiration that the assessment of penalties on a rigorous mathematical framework can assist in alleviating the mistrust by sections of the public on the effectiveness of air pollution regulations. Integration of economic analyses into risk assessments of emission violations can help clarify to policymakers the effect of environmental policies. Our analysis indicates that the penalty structure of the United States appears to favor the update of emission systems more often than the corresponding European Commission's penalties. Our study advances the use of the loss function as a risk analysis tool that can be used as a public policy instrument to promote environmentally friendlier air emission choices. A parabolic, compared to a linear, loss function was seen to justify higher expenses in gas cleaning systems.
Reference Key
paleologos2018bayesianrisk Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Paleologos, Evan K;Elhakeem, Mohamed;Amrousi, Mohamed El;
Journal Risk analysis : an official publication of the Society for Risk Analysis
Year 2018
DOI
10.1111/risa.13130
URL
Keywords Keywords not found

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