Article ID Journal Published Year Pages File Type
6316038 Environmental Pollution 2016 12 Pages PDF
Abstract

•A modification of the coefficients in statistical regression method is proposed.•Results have been evaluated by using Large Scale Urban Consumption energy model.•Findings fill the gap with respect to anthropogenic heat emissions in urban Taiwan.

High energy consumption in the urban environment impacts the urban surface energy budget and causes the emission of anthropogenic heat fluxes (AHFs) into the atmosphere. AHFs vary over time and space. Thus, a reliable estimation of AHF is needed for mesoscale meteorological modeling. This study used a statistical regression method to estimate the annual mean gridded AHF with high spatial (1-km) resolution. Compared with current methods for AHF estimation, the statistical regression method is straightforward and can be easily incorporated with meteorological modeling. AHF of the highly populated urban areas in Taiwan were estimated using data from the anthropogenic pollutant emission inventory of CO and NOx for year 2010. Over 40% of the total AHF values in Taiwan main island fell within the range of 10-40 Wm−2. When the study domain was confined to urban land, the percentage contributions from AHF values were increased, with over 68% of the total AHF values within the range of 10-40 Wm−2. AHF values > 40 Wm−2 were more abundant in the Southern region, followed by the Central and Northern regions. An assessment of the heat emissions by the large scale urban consumption of energy (LUCY) model revealed that the mean AHFs are reasonably close to those produced while the maximum AHFs are underestimated. The results obtained evidence the impact of spatial distribution of land use types, particularly population densities, main highways and industries on AHF generation in Taiwan.

Related Topics
Life Sciences Environmental Science Environmental Chemistry
Authors
, , , ,