Our data is spatiotemporally rich and is one of the only publicly available datasets for calibrated PM values based in a developing country. The difference between the PM value distributions of a developing and a developed country is staggering. To corroborate our point and the need for a dataset like ours, we provide a detailed analysis comparing a mobile air monitoring dataset[2] which belongs to the city Hamilton in Ontario, Canada collected during 114 days of air pollution monitoring between November 2005 to November 2016 with our dataset based on a number of parameters. For the purpose of comparison, we divide Delhi and Hamilton into regions by rounding off the latitude and longitude of each record to 3 decimal places and the grouping all the record belonging to each region.
The following tables show comparison of Kolkata dataset with Delhi dataset and Canada dataset over different parameters. It also presents statistical comparison of PM values recorded by both datasets.
Metric | Kolkata Dataset | Delhi Dataset | Canada Dataset | Zurich dataset |
---|---|---|---|---|
Total number of samples | 104447 | 12542183 | 46080 | Varying for different pollutants (19.9 - 49.7 Million) |
Sample with atleast one PM (1.0, 2.5, 10.0) value | 104447 | 12542183 | 13048 | - |
Pollutants covered | PM2.5 | PM1, PM2.5, PM10 | CO, NO, NO2, SO2, O3, PM1, PM2.5, PM10 | O3, CO, NO2 and UFP |
Vehicles used | Static@Colleges / Mobile@Public bus | Public bus | Commercial van | Trams |
Monitoring Period | 142 days | 91 days | 114 days | Varying for different pollutants (2.5 - 4.5 years) |
Calibration | Yes | No | No | - |
Pollutants | vendor1 (honeywell) | vendor2 (alphasense) | vendor3 (winsen) |
---|---|---|---|
SO2 | 17,337 INR | 8,500 INR | 10,600 INR |
NO | 14,600 INR | 8,500 INR | - |
NO2 | 10,618 INR | 8,500 INR | 10,530 INR |
CO | - | 8,500 INR | 4,450 INR |
CO2 | - | - | 2,910 INR |
O3 | - | - | 4,288.28 INR |
Metric | Kolkata | Delhi | Canada |
---|---|---|---|
Mean | 75.82 | 207.92 | 15.08 |
Std | 35.49 | 114.36 | 12.87 |
Missing % | 0 | 0 | 73.62 |
Jason Jingshi Li, Boi Faltings, Olga Saukh, David Hasenfratz, and Jan Beutel. Sensing the airwe breathe: The opensense zurich dataset. In proceedings of the Twenty-Sixth AAAI Conferenceon Artificial Intelligence , AAAI’12, page 323–325. AAAI Press, 2012.
Matthew D. Adams and Denis Corr. A mobile air pollution monitoring data set.Data, 4(1),2019