Articles | Volume 10, issue 9
https://doi.org/10.5194/amt-10-3313-2017
https://doi.org/10.5194/amt-10-3313-2017
Research article
 | 
11 Sep 2017
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. Gibe and Mylene G. Cayetano

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Cited articles

Ahanchian, M. and Biona, J.: Energy demand, emissions forecasts and mitigation strategies modeled over a medium-range horizon: the case of the land transportation sector in Metro Manila, Energ. Policy, 66, 615–629, https://doi.org/10.1016/j.enpol.2013.11.026, 2014.
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Cassidy, B., Alabanza-Akers, M., Akers, T., Hall, D., Ryan, P., Bayer, C., and Naeher, L.: Particulate matter and carbon monoxide multiple regression models using environmental characteristics in a high diesel-use area of Baguio City, Philippines, Sci. Total. Environ., 381, 47–58, https://doi.org/10.1016/j.scitotenv.2007.03.010, 2007.
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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.