A new tool to process forecast meteorological data for atmospheric pollution dispersion simulations of accident scenarios: A Sicily-based case study

Francesca Martorana,Mariarosa Giardina,Calogero Zammuto,Pietro Buffa,Marco Beccali

doi:10.13044/j.sdewes.d8.0377

Francesca Martorana, Mariarosa Giardina + Show 3 more

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https://doi.org/10.13044/j.sdewes.d8.0377

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Abstract

A new tool to process forecast meteorological data for atmospheric pollution dispersion simulations of accident scenarios: A Sicily-based case study

Highlights

Risk management, assessment, and mitigation for high-risk plants exposed to operational risks or natural hazards are built on: actions that attempt to identify potential risks [1]; data obtained from an accurate knowledge of territorial vulnerability [2]; monitoring network for assessing population exposure to pollution [3]; strategies aimed at supporting decisions on how to manage critical security issues [4] and how to select the appropriate response options for effective risk mitigation [5].Even though many possible risks are foreseeable, one should always be prepared for unlikely scenarios that can lead to catastrophic failures
Comparisons were performed between CALifornia Meteorological Model (CALMET)/CALifornia PUFF Model (CALPUFF) analyses using FORCALM
The results indicate that assessments based on forecast data elaborated with FORCALM are robust and accurate in providing information on the potential impacts

Summary

Introduction

Assessment, and mitigation for high-risk plants exposed to operational risks or natural hazards are built on: actions that attempt to identify potential risks [1]; data obtained from an accurate knowledge of territorial vulnerability [2]; monitoring network for assessing population exposure to pollution [3]; strategies aimed at supporting decisions on how to manage critical security issues [4] and how to select the appropriate response options for effective risk mitigation [5].Even though many possible risks are foreseeable, one should always be prepared for unlikely scenarios that can lead to catastrophic failures. The results are used in the CALifornia Meteorological Model (CALMET) [18] and in the CALifornia PUFF Model (CALPUFF) [19] to simulate predictive air pollution dispersion on a three-dimensional high spatial resolution grid domain.

Results

Conclusion