Articles | Volume 18, issue 4
Atmos. Chem. Phys., 18, 2725–2747, 2018
Atmos. Chem. Phys., 18, 2725–2747, 2018

Research article 26 Feb 2018

Research article | 26 Feb 2018

Integrated emission inventory and modeling to assess distribution of particulate matter mass and black carbon composition in Southeast Asia

Didin Agustian Permadi1, Nguyen Thi Kim Oanh1, and Robert Vautard2 Didin Agustian Permadi et al.
  • 1Environmental Engineering and Management, School of Environment, Resources and Development, Asian Institute of Technology, Klong Luang, Pathumthani 12120, Thailand
  • 2Laboratoire des Sciences du Climate de l'Environment (LSCE), Institut Pierre Simon Laplace (IPSL), Gif-sur-Yvette, France

Abstract. This is part of a research study addressing the potential co-benefits associated with selected black carbon (BC) emission reduction measures on mitigation of air pollution and climate forcing in Southeast Asia (SEA). This paper presents details of emission inventory (EI) results and WRF–CHIMERE model performance evaluation. The SEA regional emissions for 2007 were updated with our EI results for Indonesia, Thailand, and Cambodia and used for the model input. WRF–CHIMERE-simulated 2007 PM10, PM2.5, and BC over the SEA domain (0.25° × 0.25°) and the results were evaluated against the available meteorology and air quality monitoring data in the domain. WRF hourly simulation results were evaluated using the observed data at eight international airport stations in five SEA countries and showed a satisfactory performance. WRF–CHIMERE results for PM10 and PM2.5 showed strong seasonal influence of biomass open burning while the BC distribution showed the influence of urban activities in big SEA cities. Daily average PM10 constructed from the hourly concentrations were obtained from the automatic monitoring stations in three large SEA cities, i.e., Bangkok, Kuala Lumpur, and Surabaya, for model evaluation. The daily observed PM2.5 and BC concentrations obtained from the Improving Air Quality in Asian Developing Countries (AIRPET) project for four cities (i.e., Bangkok, Hanoi, Bandung, and Manila) were also used for model evaluation. In addition, hourly BC concentrations were taken from the measurement results of the Asian Pacific Network (APN) project at a suburban site in Bangkok. The modeled PM10 and BC satisfactorily met all suggested statistical criteria for PM evaluation. The modeled PM2.5∕PM10 ratios estimated for four AIRPET sites ranged between 0.47 and 0.59, lower than observed values of 0.6–0.83. Better agreement was found for BC∕PM2.5 ratios with the modeled values of 0.05–0.33 as compared to the observation values of 0.05–0.28. AODEM (extended aerosol optical depth module) was used to calculate the total columnar aerosol optical depth (AOD) and BC AOD up to the top of the domain at 500 hPa (∼ 5500 m), which did not include the free-tropospheric long-range transport of the pollution. The model AOD results calculated using the internal mixing assumption were evaluated against the observed AOD by both AERONET and MODIS satellite in 10 countries in the domain. Our model results showed that the BC AOD contributed 7.5–12 % of the total AOD, which was in the same range reported by other studies for places with intensive emissions. The results of this paper are used to calculate the regional aerosol direct radiative forcing under different emission reduction scenarios to explore potential co-benefits for air quality improvement, reduction in the number of premature deaths, and climate forcing mitigation in SEA in 2030 (Permadi et al., 2017a).

Short summary
This research quantified the emissions of toxic air pollutants and climate forcing agents from Southeast Asia in 2007. The emission results were used for model simulation of particulate matter air quality. The model outputs were reasonably comparable to available ground level measurement data for both meteorology and air quality. The aerosol optical depth (AOD) for total aerosol and for black carbon alone was calculated and compared to satellite AOD.
Final-revised paper