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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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Atmos. Meas. Tech., 10, 3313-3323, 2017
https://doi.org/10.5194/amt-10-3313-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
11 Sep 2017
Spatial estimation of air PM2.5 emissions using activity data, local emission factors and land cover derived from satellite imagery
Hezron P. Gibe1 and Mylene G. Cayetano1,2 1Institute of Environmental Science and Meteorology, University of the Philippines, Diliman, 1101 Quezon City, Philippines
2International Environmental Research Institute, Gwangju Institute of Science and Technology, Cheomdan-gwagiro, Buk-gu, 500-712 Gwangju, South Korea
Abstract. Exposure to particulate matter (PM) is a serious environmental problem in many urban areas on Earth. In the Philippines, most existing studies and emission inventories have mainly focused on point and mobile sources, while research involving human exposures to particulate pollutants is rare. This paper presents a method for estimating the amount of fine particulate (PM2.5) emissions in a test study site in the city of Cabanatuan, Nueva Ecija, in the Philippines, by utilizing local emission factors, regionally procured data, and land cover/land use (activity data) interpreted from satellite imagery. Geographic information system (GIS) software was used to map the estimated emissions in the study area. The present results suggest that vehicular emissions from motorcycles and tricycles, as well as fuels used by households (charcoal) and burning of agricultural waste, largely contribute to PM2.5 emissions in Cabanatuan. Overall, the method used in this study can be applied in other small urbanizing cities, as long as on-site specific activity, emission factor, and satellite-imaged land cover data are available.

Citation: Gibe, H. P. and Cayetano, M. G.: Spatial estimation of air PM2.5 emissions using activity data, local emission factors and land cover derived from satellite imagery, Atmos. Meas. Tech., 10, 3313-3323, https://doi.org/10.5194/amt-10-3313-2017, 2017.
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Short summary
This paper presents a low-technical method of estimating particulate air pollution in small cities, using Cabanatuan City, Philippines, as the study site, intended for use by stakeholders requiring minimal training in geospatial methods and GIS, for expediting air pollution emission inventories. This method utilizes local emission data and land cover derived from Google Earth satellite images. Results in the study site suggest high emissions from vehicular sources and rice straw burning.
This paper presents a low-technical method of estimating particulate air pollution in small...
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