NO₂ and SO₂dispersion modeling and relative roles of emission sources over Map Ta Phut industrial area, Thailand

Abstract

Map Ta Phut industrial area (MA) is the largest industrial complex in Thailand. There has been concern about many air pollutants over this area. Air quality management for the area is known to be difficult, due to lack of understanding of how emissions from different sources or sectors (e.g., industrial, power plant, transportation, and residential) contribute to air quality degradation in the area. In this study, a dispersion study of NO 2 and SO 2 was conducted using the AERMOD model. The areaspecific emission inventories of NO x and SO 2 were prepared, including both stack and nonstack sources, and divided into 11 emission groups. Annual simulations were performed for the year 2006. Modeled concentrations were evaluated with observations. Underestimation of both pollutants was found, and stack emission estimates were scaled to improve the modeled results before quantifying relative roles of individual emission groups to ambient concentration over four selected impacted areas (two are residential and the others are highly industrialized). Two concentration measures (i.e., annual average area-wide concentration or AC, and area-wide robust highest concentration or AR) were used to aggregately represent mean and high-end concentrations for each individual area, respectively. For AC-NO 2 , on-road mobile emissions were found to be the largest contributor in the two residential areas (36-38% of total AC-NO 2 ), while petrochemical-industry emissions play the most important role in the two industrialized areas (34-51%). For AR-NO 2 , biomass burning has the most influence in all impacted areas (>90%) except for one residential area where on-road mobile is the largest (75%). For AC-SO 2 , the petrochemical industry contributes most in all impacted areas (38-56%). For AR-SO 2 , the results vary. Since the petrochemical industry was often identified as the major contributor despite not being the largest emitter, air quality workers should pay special attention to this emission group when managing air quality for the MA.Implications: Effective air quality management in Map Ta Phut Industrial Area, Thailand requires better understanding of how emissions from various sources contribute to the degradation of ambient air quality. Based on the dispersion study here, petrochemical industry was generally identified as the major contributor to ambient NO 2 and SO 2 . By accounting for all stack and non-stack sources, on-road mobile emissions were found to be important in some particular areas.

Ozone and its potential control strategy for Chon Buri city, Thailand

“…AERMET requires both surface meteorological data to drive its surface energy balance module and morning upper-air data for its daytime mixing height calculation in which mixing height increases due to sensible heat transferred from the surface to the atmospheric boundary layer. The configuration and implementation of AERSURFACE and AERMET here follow those in Chusai et al (2012) mostly, with some adjustment to suit our Chon Buri application.…”

“…Based on a three-day back-trajectory examination using the HYSPLIT model (Draxler and Hess, 1998; http://www.arl. noaa.gov/HYSPLIT.php) (details not shown), the trajectory paths of air mass arriving at the city center in the afternoon of both episodes do not pass through any nearby highly polluted or large cities, that is, Bangkok metropolitan (PCD, 2001) to the northwest of the city, and Rayong (Chusai et al, 2012;Phan and Manomaiphiboon, 2012) to the south-southeast. Also, they do not pass through any other large cities in Thailand and neighboring countries.…”

Evaluation of Dispersion Model Performance in Predicting So2 Concentrations From Petroleum Refinery Complex

“…The RHC is preferred to the actual peak value and represents a rounded estimate of the highest concentrations, based on a tail exponential fit to the upper end of the distribution. With this procedure, the effect of extreme values on model comparison is reduced [11]. Results from robust highest concentration indicated that AERMOD provided slightly better result in predicting extreme end of SO2 concentration than CALPUFF (percentage of overall difference in RHC from AERMOD was about 33 % while this value from CALPUFF prediction was about 35%).…”

Use of GIS Tools for Environmental Conflict Resolution at Map Ta Phut Industrial Zone in Thailand

“…Therefore, their analysis of change was limited to a short time span. A research study conducted in the Map Ta Phut industrial zone has examined the spatial dispersion of NO 2 and SO 2 in relation to point sources [36]. This research used a high resolution land cover data set, documenting the status of Map Ta Phut in 2007 and a spatial model called AERMOD (American Meteorological Society-Environmental Protection Agency Regulatory Model).…”