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Looking for long-term particle number concentrations and size distribution data to better understand air pollution dynamics in Delhi?
Of course you are!
New paper w/ @joshapte @SahilBh_India @pkanan03 & others at @UTAustin @iitdelhi.
Resources in
https://www.atmos-chem-phys.net/20/8533/2020/
Of course you are!
New paper w/ @joshapte @SahilBh_India @pkanan03 & others at @UTAustin @iitdelhi.
Resources in
https://www.atmos-chem-phys.net/20/8533/2020/
The hourly size distribution data for the entire period discussed in this paper in online and free to use. Make sure to cite the @EGU_ACP paper as well if you are using these data. https://dataverse.tdl.org/dataset.xhtml?persistentId=doi:10.18738/T8/PCO1BP
Meteorological parameters (temp, RH, wind speed/dir, boundary layer height, etc.) are extremely important to understanding air pollution dynamics. There are some extremely useful open datasets. We used @NASA's MERRA2 (reanalysis dataset) for this paper.
https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/
https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/
For ground-based meteorological data, obtaining airport met data (anywhere in the world!) is extremely easy using the IEM tool. https://mesonet.agron.iastate.edu/request/download.phtml
Supplementary air pollution data such as PM2.5, NO, SO2, etc can be obtained through local regulatory agencies. @OpenAQ is an excellent resource for obtaining such datasets. Make sure to cite them (e.g., Fig 3 caption of our paper).
https://github.com/openaq/openaq-info/blob/master/FAQ.md#citing
https://github.com/openaq/openaq-info/blob/master/FAQ.md#citing
Some additional references/resources for those trying to understand aerosol dynamics in polluted environments.
In Gani et al. 2019 we provided an overview of sources and processes that drive submicron aerosol mass in Delhi.
(Data link in next tweet) https://www.atmos-chem-phys.net/19/6843/2019/
In Gani et al. 2019 we provided an overview of sources and processes that drive submicron aerosol mass in Delhi.
(Data link in next tweet) https://www.atmos-chem-phys.net/19/6843/2019/
The hourly aerosol composition data for Delhi has been available for use since the study was published last year. https://dataverse.tdl.org/dataset.xhtml?persistentId=doi:10.18738/T8/9L33CI
The details of source apportionment for submicron aerosol mass in Delhi can be found in Bhandari et al. (2020). @SahilBh_India https://www.atmos-chem-phys.net/20/735/2020/
Understanding aerosol physical and chemical properties can be useful for understanding aerosol hygroscopicity and cloud condensation nuclei formation as shown in Arub et al. (2020). https://www.atmos-chem-phys.net/20/6953/2020/
Aerosol properties also have an impact on low-cost sensor performance.
Crilley et al. (2020) looked at the effect of aerosol composition on the performance of low-cost optical particle counter. https://amt.copernicus.org/articles/13/1181/2020/
Crilley et al. (2020) looked at the effect of aerosol composition on the performance of low-cost optical particle counter. https://amt.copernicus.org/articles/13/1181/2020/
By comparing data collected using low-cost sensors and research-grade instruments, Hagan et al. (2019) provided insights into using low-cost sensors for inferring sources of air pollution. @DHagan7 https://pubs.acs.org/doi/full/10.1021/acs.estlett.9b00393
Bonus resource for meteorological data:
@ECMWF @CopernicusECMWF's ERA5 is amazing!
So easy to access reanalysis met data for any location on the planet (free!).
I can email my data acquisition documentation for all met data resources mentioned in. https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5
@ECMWF @CopernicusECMWF's ERA5 is amazing!
So easy to access reanalysis met data for any location on the planet (free!).
I can email my data acquisition documentation for all met data resources mentioned in
. https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5
