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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 9
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.
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

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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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.
Andrade, M., de Miranda, R. M., Fornaro, A., Kerr, A., Oyama, B., de Andre, P., and Saldiva, P.: Vehicle emissions and PM2. 5 mass concentrations in six Brazilian cities, Air. Qual. Atmos. Health., 5, 79–88, https://doi.org/10.1007/s11869-010-0104-5, 2012.
Bakker, R., Elbersen, W., Poppens, R., and Lesschen, J. P.: Rice straw and wheat straw: potential feedstocks for the biobased economy, Wageningen UR, Food & Biobased Research, NL Agency, 2013.
Bocchi, C., Bazzini, C., Fontana, F., Pinto, G., Martino, A., and Cassoni, F.: Characterization of urban aerosol: seasonal variation of mutagenicity and genotoxicity of PM2. 5, PM1 and semi-volatile organic compounds, Mutat. Res., 809, 16–23, https://doi.org/10.1016/j.mrgentox.2016.07.007, 2016.
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.
This paper presents a low-technical method of estimating particulate air pollution in small...
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