An uncertainty estimate of global mercury emissions using the Monte Carlo technique

Abstract

In recent years, a substantial amount of work has been done to evaluate uncertainty associated with major industrial source emissions. Yet, little has been done to assess uncertainty associated with natural source emissions. Importantly, uncertainty estimates continue to be particularly relevant in the assessment of potential regulatory options, as confidence in emissions can lead to different cost-benefit assessments. To address this problem, we employed the Monte Carlo technique to improve uncertainty estimates associated with mercury emissions from both natural and anthropogenic sources. Results demonstrate that uncertainties, as they are understood in the existing literature, are overestimated. While we are aware that a probabilistic approach like the Monte Carlo technique has certain limitations (it does not consider the accuracy of available input data, for example) it still is useful in crafting a better assessment of mercury emission uncertainty.

Keywords

• Uncertainty
• stochastic simulation
• error natural sources
• anthropogenic sources