MAPPING METHODOLOGY OF AIR POLLUTION & GHG (CO, HC, NO<SUB>X</SUB> AND CO<SUB>2</SUB>, CH<SUB>4</SUB>) EMISSIONS IN A MESO-SCALE MAP WITH 30

• Main Author: AGUS ARDHANA, FAISAL
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/27092
• Institution: Institut Teknologi Bandung

<p align="justify">Abstract: The importance of using a grid mapping system in order to analyze in more detail, showing that a simple grid mapping method is needed without sacrificing accuracy of the map. The purpose of this study is to develop method by Suhadi and Emerentiana (2009) which resulted in the emission loads inventory on scale administrative boundaries, into the form of gridded map so that we will get a simple methodology to map emission in a meso-scale which can be <br /> <br /> integrated into a gridded map in a national scale. This research used Jakarta as a case study using a grid resolution of 30" (900m x 900m) with air pollution <br /> <br /> parameters mapped of CO, CO₂, CH₄, HC and NO_X from domestic (household), vehicle, industrial and power plants sectors taken from Suhadi and Emerentiana, 2009. The emission map used the Top–Down method, based on a set of assumptions to obtain emission load in each grid. Results of mapping show for all parameters of air pollutants, the largest emission load from a source-based motor vehicle located was found in the District Kramat Jati, East Jakarta. Emission loads inventory in the gridded mapping of 30" is able to show spatial distribution in much more detailed location.Validation into the grid system was only carried out on domestic source because it is the only source that has detailed data such as population density on each 5” (150m x 150m) grid to be agregated into 30” grid so it can be compared with 30” grid using Top Down Method. The difference of emission loads resulted from Top Down the methods to the Bottom Up method is influenced by the use of population distribution map of Jakarta, where the emission load calculation based on population of each grid is not in accordance with the class of land, the use of emission factors that are not suitable with the conditions in Indonesia and the lack of fuel consumption data at the local level.<p align="justify">