Air Quality Analysis for Raipur-Durg-Bhillai, India


India APnA City ProgramParticulate matter source contributions for Raipur-Durg-Bhilai region of Chhattisgarh, India
Journal article in Aerosol and Air Quality Research (2019) Download

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Raipur serves as its capital of the state Chhattisgarh, a relatively young state formed in the year 2000, with an estimated urban population of 2.5 million (along with its twin city Durg-Bhillai). Geographically it is located on the banks of the Mahanadi River and is between the Chota Nagpur and Deccan Plateau on the north and south of the city. Naya Raipur (New Raipur) is a satellite city located 17 km away from Raipur and is spread over an area of about 8000 hectares to house a population of 450,000 over time. Agricultural processing, wood, coal, steel and cement manufacturing are the main industries in Raipur. Given its proximity to the main mining regions, it is one of the largest steel manufacturing cities in India – with about 200 steel rolling mills, 195 sponge iron plants, and a large chemical plant that manufactures formalin.

in 2015, the WHO has for the 2nd consecutive year ranked Raipur as one of the top ten polluted cities in the world. A number of sources including vehicular traffic, industry, and domestic burning are highlighted as the cause of air pollution in the city.

To assess Raipur’s air quality, we selected 60km x 30km domain. This domain is further segregated into 1km grids, to study the spatial variations in the emission and the pollution loads.

Monitoring Emissions Meteorology Dispersion References

Monitoring

We present below a summary of the ambient monitoring data available under the National Ambient Monitoring Program (NAMP), operated and maintained by the Central Pollution Control Board (CPCB, New Delhi, India). In Raipur, there are 2 manual stations reporting data on PM10, SO2, and NO2 and no continuous air monitoring stations (CAMS).

 

 


Satellite Data Derived Surface PM2.5 Concentrations:

The results of satellite data derived concentrations are useful for evaluating annual trends in pollution levels and are not a proxy for on-ground monitoring networks. This data is estimated using satellite feeds and global chemical transport models. Satellites are not measuring one location all the time, instead, a combination of satellites provide a cache of measurements that are interpreted using global chemical transport models (GEOS-Chem) to represent the vertical mix of pollution and estimate ground-based concentrations with the help of previous ground-based measurements. The global transport models rely on gridded emission estimates for multiple sectors to establish a relationship with satellite observations over multiple years. These databases were also used to study the global burden of disease, which estimated air pollution as the top 10 causes of premature mortality and morbidity in India. Below, we present a summary of PM2.5 concentrations from this exercise, for the city of Raipur. The global PM2.5 files are available for download and further analysis @ Dalhousie University.

Emissions

We compiled an emissions inventory for the Raipur region for the following pollutants – sulfur dioxide (SO2), nitrogen oxides (NOx), carbon monoxide (CO), non-methane volatile organic compounds (NMVOCs), carbon dioxide (CO2); and particulate matter (PM) in four bins (a) coarse PM with size fraction between 2.5 and 10 μm (b) fine PM with size fraction less than 2.5 μm (c) black carbon (BC) and (d) organic carbon (OC), for year 2015 and projected to 2030.

We customized the SIM-air family of tools to fit the base information collated from the central pollution control board, state pollution control board, census bureau, national sample survey office, ministry of road transport and highways, annual survey of industries, central electrical authority, ministry of heavy industries, municipal waste management, geographical information systems, meteorological department, and publications from academic and non-governmental institutions.

This emissions inventory is based on the available local activity and fuel consumption estimates for the selected urban airshed (presented in the grid above) and does not include natural emission sources (like dust storms, lightning) and seasonal open (agricultural and forest) fires; which can only be included in a regional scale simulation. These emission sources are accounted in the concentration calculation as an external (also known as boundary or long-range) contribution to the city’s air quality.

The emissions inventory was then spatially segregated at a 0.01° grid resolution in longitude and latitude (equivalent of 1 km) to create a spatial map of emissions for each pollutant (PM2.5, PM10, SO2, NOx, CO and VOCs). Below is the gridded PM2.5 emissions and the total (shares by sector) emissions.

Gridded PM2.5 Emissions (2015)

Emissions Inventory

Total PM2.5 Emissions by Sector 2015-2030

Emissions Inventory Emissions Inventory Emissions Inventory

Total Estimated Emissions by Sector for 2015 (units – mil.tons/year for CO2 and tons/year for the rest)

PM2.5PM10BCOCNOxCOVOCSO2CO2
TRAN 5,900 6,200 2,700 1,850 7,650 58,200 19,250 3501.86
RESI 2,750 2,800 500 1,500 650 41,700 5,050 4000.24
INDU 26,350 30,200 5,000 4,100 43,550 35,900 90,500 5,800 0.48
DUST 2,650 16,450 -------
WAST 1,600 1,700 10095050 7,700 1,550 500.01
DGST850900500150 7,800 2,050 2001000.35
BRIC 1,400 1,400 350500 1,000 17,750 1,600 9000.18
41,500 59,650 9,150 9,050 60,700 163,300 118,150 7,600 3.13

TRAN = transport emissions from road, rail, aviation, and shipping (for coastal cities); RESI = residential emissions from cooking, heating, and lighting activities; INDU = industrial emissions from small, medium, and heavy industries (including power generation); DUST = dust emissions from road re-suspension and construction activities; WAST = open waste burning emissions; DGST = diesel generator set emissions; BRIC = brick kiln emissions (not included in the industrial emissions)

Meteorology

We processed the NCEP Reanalysis global meteorological fields from 2010 to 2016 through the 3D-WRF meteorological model. A summary of the data for year 2015, averaged for Raipur is presented below. Download the processed data which includes information on year, month, day, hour, precipitation (mm/hour), mixing height (m), temperature (C), wind speed (m/sec), and wind direction (degrees) – key parameters which determine the intensity of dispersion of emissions.

 

Dispersion Modeling

We calculated the ambient PM2.5 concentrations and the source contributions, using gridded emissions inventory, 3D meteorological data (from WRF), and the CAMx regional chemical transport model. The model simulates concentrations at 0.01° grid resolution and sector contributions, which include contributions from primary emissions, secondary sources via chemical reactions, and long range transport via boundary conditions (represented as “outside” in the pie graph below).

PM2.5 Source Contributions Ambient PM2.5 Concentrations PM2.5 Source Contributions

Findings and Recommendations

  • Modeled urban average ambient PM2.5 concentration is 82.3 ± 21.8 μg/m3 – is more than 2 times the national standard (40) and more than 8 times the WHO guideline (10)
  • The city requires at least 19 continuous air monitoring stations to statistically, spatially, and temporally, represent the mix of sources and range of pollution in the city (current status – 2 manual and 0 continuous)
  • The modeled source contributions highlight the heavy industries (mostly steel), followed by transport (including on road dust), domestic cooking and heating, industries, open waste burning, and influence of outside sources, as the key air pollution sources in the urban area
  • The city has an estimated 26% of the ambient annual PM2.5 pollution (in 2015) originating outside the urban airshed, which suggests that some regional interventions could reduce the pollution loads. This contribution is mostly stemming from coal-fired power plants, large (metal and non-metal processing) industries, and brick kilns located outside the urban airshed
  • The city needs to aggressively promote public and non-motorized transport as part of the city’s urban development plan, along with the improvement of the road infrastructure to reduce on-road dust re-suspension
  • By 2030, the vehicle exhaust emissions are expected to remain constant, if and only if, Bharat 6 fuel standards are introduced nationally in 2020, as recommended by the Auto Fuel Policy
  • By 2030, the share of emissions from residential cooking and lighting is expected to decrease with a greater share of LPG, residential electrification, and increasing urbanization. However, since the availability of biomass and coal in the region is high, a fair share of its use is expected to continue, unless an aggressive program is in place a 100% technology shift to cleaner options like LPG and electricity
  • The 115 brick kilns in the urban airshed are are fueled mostly by coal and agri-waste. These kilns can benefit from a technology upgrade to (for example) zig-zag and fixed chimney kilns, in order to improve their overall energy efficiency Similarly, the coal-fired power plants need to practice and enforce stricter environmental standards for all the criteria pollutants
  • Open waste burning is dispersed across the city and requires stricter regulations for addressing the issue, as the city generates ever more garbage, with limited capacity to sort and dispose of it.

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