Urban Climate

those are the original data used in this paper.

lst.stefan-boltzman.sh - GRASS GIS shellscript

• The datasets presented here can be useful to identify gaps of research and opportunities for further development on indoor thermal comfort in tropical regions. • The data allows statistical analysis of volume, origin, emphasis, and impact of representative documentation in this subject. • The tables provided facilitate the comparison of research from different countries and cities concerning their climate and demographics. • The reader can easily visualise the content, impact and number of citations of different studies on ITC and the presence of tendencies and data patterns. • This data can be combined with similar data from other regions for further insights into state-of-the-art research worldwide.

In this paper, we are presenting databases and results for 20 Indian cities. Due to space constraints and to avoid repetition, several figures and tables are not included in the main text. The Supplementary contains the following (a) for 20 cities - selected urban airsheds as google KML files showing 0.01º grids (b) for 20 cities - urban-rural built area maps, emission projections for PM2.5 between 2015 and 2030, gridded PM2.5 emission maps, modeled PM2.5 concentration maps, and modeled monthly variation of PM2.5 concentrations for the selected airshed (c) for 20 cities – the WRF modeled wind speed, wind direction, temperature, precipitation and mixing height for the airshed as annual summary figures, summary table showing monthly variation, and database of hourly values (d) for all India – list of number of operational ambient monitoring stations and recommendation number of monitoring stations by state (37) and by district (640) (e) for all India – daily average ambient monitoring data for the period of 2011-2015 from all the stations operational under the national ambient monitoring programme (f) for all India – summary of satellite data + global model based surface PM2.5 estimates for the period of 1998 and 2016 by state (37) and by district (640) and (g) for 20 cities – summary of WRF-CAMx modeled PM2.5 source apportionment.