One question that is repeatedly asked and the most confusing one to answer is, what/who is causing this pollution in the city?
Using the WRF-CAMx modeling system, a series of simulations are conducted every day, to apportionment source contributions, based on a detailed spatially and temporally resolved emissions inventory. The hourly average source contributions (presented below) is a modeled average for all the 1 km x 1 km grids overlapping in each of the districts. A map showing the geographical extent of each of the districts is presented here (along with a kml file for reference and use). The modeling domain considered for this exercise includes 14 districts – 9 in Delhi, 2 in Haryana, and 3 in Uttar Pradesh.
What is included in the 7 clubbed source categories is described below and more information on the emission sources is available here. If you click on any of the source categories in the legend, it will allow you to minus that contribution and see what could be the PM2.5 concentrations without its contribution. If you click on it again, the source will be added back to the chart.
The data fields are updated everyday at ~7:00 PM IST.
- TRA.PASS = pollution due to the vehicle exhaust emissions from passenger vehicles (2Ws, 3Ws, 4Ws, Taxis, and Buses)
- TRA.FRGT = pollution due to the vehicle exhaust emissions from freight vehicles (heavy and light trucks, and non-road vehicles)
- URB.DUST = pollution due to the re-suspended dust due to vehicle movement on the roads and dust due to the construction activities (dust is also linked to the meteorological fields – for example, no re-suspension under rainy conditions)
- RESI = pollution due to the emissions from domestic cooking, space heating, water heating, and lighting
- IND.BK = pollution due to the emissions from industrial activities and brick kilns
- PP.GS = pollution due to emissions from power plants and in-situ diesel generator sets
- WST.BURN = pollution due to the emissions from open waste burning
- OUTSIDE = pollution linked to boundary conditions, in other words, pollution from outside the 80 km x 80 km modeling domain; which is calculated from a simulation over the Indian subcontinent, including the anthropogenic emissions, seasonal fires and dust events (calculated based on the most recent satellite data), and other natural sources
Back to the Delhi air quality forecasting page. Additional data fields from the forecasting system
- animations of hourly wind, temperature, precipitation, and mixing heights
- daily (24 hour) average concentrations
- animations of hourly average concentrations
- hourly time series at the district level
- hourly time series for select locations
- modeled source contributions to hourly PM2.5 concentrations
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