Metropolitan Air Quality and Weather Forecasting Services

Project Director: Dr. Gufran Beig

Deputy Project Director: Dr. D. M. Chate

• Development of Early warning system to predict Air Quality and Weather for Indian metropolitan cities namely- “SAFAR” (System of Air quality and Weather Forecasting And Research). To investigate the role of air pollution and its impact on Human Health and Crop Yield. 
• Development of Chemical-transport modelling capability to understand the linkages of atmospheric Chemistry with weather and climate.
• Development of improved high-resolution gridded national emission inventories.
• Establishment of MAPAN (Modeling Air Pollution And Networking) –A national monitoring Network for atmospheric chemical parameters. 
• Investigating the role of carbonaceous species (black carbon, organic carbon, brown carbon, etc.).

Under the MoES Programmes “Atmospheric, Climate Science and Services”, a core programme “System of Air quality Forecasting and Research (SAFAR)” (http://safar.tropmet.res.in/) has been indigenously conceived, developed and commissioned by IITM, Pune. SAFAR is operational in Delhi, Pune, Mumbai and soon will be made operational soon in Ahmedabad  and provides site-specific detailed customized meteorological and air quality products and spreads awareness through large public display digital boards, News frames, toll-free telephones, SMS services, web portal and IVRS. 

For Indian domain, a national network of “Modeling Air Pollution And Networking (MAPAN)” consisting of about 15 air quality and weather monitoring stations are setup all over India. MAPAN provides baseline data for broad input fields to regional air quality model for Indian domain, nested domain coarser resolution for SAFAR and investigate the role of anthropogenic versus long-range transport. The operational technology for air quality and automatic weather stations of SAFAR and MAPAN are sustainable against natural hazards as recently experienced during Hudhud cyclonic storms over Eastern coast (Vishakhapatnam).

This group continues to quantify the impact of chemical emissions on the distribution of trace gases regionally and also on other regions of the globe along with timing and location of long-range pollution transport events using 3-D global coupled modeling systems. Also, focuses on quantifying the impact of air quality on persistent winter fog formation, duration and dissipation in the Indo-Gangetic Plains including Delhi and variability of carboneous aerosols (black carbon and organic carbon) in glaciers.

In addition to achieving the aforementioned extensive developmental, operational and capacity buildings goals via SAFAR and MAPAN in accordance with mandate of sanctioned project objectives, data of air quality and weather parameters generated through these networks served the strategic hypotheses driven science plan which added significant dimension to the vision and mission of IITM and evidently reflected in terms of scientific publications in the refereed SCI Journals.

SYSTEM OF AIR QUALITY FORECASTING AND RESEARCH

SAFAR is a dedicated air quality information service for Indian Metropolitan Cities, developed to make India self sufficient in providing frontier research based scientific accredited robust air quality information in real time and its forecast.  

Air is a mixture of various gases, important for survival of human race and life on the Earth, in a fixed proportion it’s a life supporting system, but if the composition of air alters then elevated concentration of certain trace gases can lead to detrimental effects on human health, environment and other form of life. In view of current scenario of air pollution problem, the Ministry of Earth sciences commissioned an ambitious project namely SAFAR, which has been conceived, developed and implemented by its constituent. Currently SAFAR is operational in three major metro cities of India viz. Delhi (Since 2010), Pune (Since 2013) and Mumbai (Since 2015). It is planned to expand it for Ahmedabad, Chennai and Kolkata in the current 5-yr plan period.

SAFAR system has integrated four scientific components: (1) Air Quality and weather monitoring; (2) Development of high resolution emission inventories (3) Developing Air Quality Forecasting Model (4) Translating data to information in public friendly format.

• SAFAR Observational Network: 10 air quality parameters and 6 weather parameters have been monitored round the clock at strategically selected 10 locations spread across city area which represents different microenvironments including industrial, residential, background/ cleaner, urban complex, agricultural zones, urban down town area etc.

• AIR QUALITY & WEATHER PARAMETERS OBSERVED & FORECASTED:

• PM2.5, PM10, O₃, CO, NOx (NO+NO₂), CO₂, Black Carbon, Benzene, Toulene, and Xylene.
• UV-dose, Rainfall, Temperature, Humidity, Wind speed & direction.

• Emission Inventory Development: High resolution (1km *1km) emission inventories have been developed using GIS (Geographical Information System) based statistical model which keeps accounting of various air pollution sources within the city area including Biofuel & Fossil fuel burning in thermal power plants, industries, transport, residential, slum sector, windblown dust from paved and unpaved roads, emissions from crematories etc. This process is input for 3-D atmospheric chemistry transport models.

• Air Quality and Weather Forecasting Model:  Setting up state of the art Atmospheric Chemistry Transport Model (ACTM) to forecast the air quality of various pollutants along with weather parameters with inner domain of 1.67 km x 1.67 km resolution. High Performance Computer consist of multiprocessor with high storage capacity is used for running the ACTM which simulates forecast. 

• SAFAR Products- Translate Data to Information:

• AIR QUALITY: Current & 1-3 days’ advance forecast with associated health advisories in terms of Air Quality Index (*AQI)
• HARMFUL RADIATION : Severity of UV radiation with associated skin advisories in terms of UV Index (*UVI)
• WEATHER: Current & 1-3 days’ advance forecast
• EXTREME EVENTS: Alert for  extreme pollution event & weather event
• EMISSION SCENARIO: Identify air pollution hot spots at city level, useful for mitigation planning.

• Public interface & dissemination tools:

SAFAR-Master: One stop shop to know air quality information for all SAFAR Metropolis in the country on digital media at one place located in IITM, Pune .

All the raw data monitored at various locations is transferred to SAFAR –Master, a Digital Control Centre of SAFAR from where after rigorous quality assurance and quality checks data is converted to useful information products and disseminated to maximum stakeholders through following dissemination tools

SAFAR Query Response Service is available at E-mail safar@tropmet.res.in

SAFAR- Decision Support System: Major Beneficiaries are Health Sector, Local Executive Agencies like corporations, Disaster Management Unit, Environment Department, Educational Institutes, Research Community, and Common Citizens.

Modelling Air Pollution and Networking(MAPAN):

Major Achievements:

• System of Air Quality Weather Forecasting and Research (SAFAR)-Delhi  was dedicated to Nation during Common Wealth Games- 2010.
• System of Air Quality Weather Forecasting and Research (SAFAR)-Pune  was dedicated to Nation on 31st  March 2015 for Pune Metropolitan Region (PMR) which includes Pune and Pimpri Chinchwad cities.
• System of Air Quality Weather Forecasting and Research (SAFAR)-Mumbai was dedicated to Nation on 23rd June 2015  for  the MUMBAI METROPILOTAN REGION (SAFAR-Mumbai).  Under the project SAFAR-Mumbai network of 10 Air Quality Monitoring Station (AQMS) has been  established across Greater Mumbai and Navi Mumbai.
• Development of SAFAR-Ahmadabad is in progress: The initial planning and discussion related with implementation of SFAR project for Ahmedabad and Ganghinagar Twin cities has been initiated. Preliminary survey has been conducted in Ahmedabad for identification of suitable location for installation of Air Quality Monitoring Station (AQMS) and Automatic Weather Station (AWS).  MOU has been signed with the Space Application Centre (SAC), Indian Space Research Organization, Dept of Space (Govt. of India), Ahmadabad for scientific cooperation in the project SAFAR-Ahmadabad.
• System of Air Quality and Weather Forecasting Research (SAFAR) provided scientifically & technically assistance to Rajasthan Government  in developing Air Quality MobileApp "RajVayu".  Hon’ble  Chief Minister of Rajasthan,  Smt. Vasundhara Raje dedicated it to nation for sharing information about current  air quality index and weather information  of  Jaipur, Jodhpur and Udaipur on the eve of  World Environmental Day, 4th June 2016.    Details about the air quality, such as  levels of pollutants likes Particulate Matter, SOx, NOx, CO, Ozone, temperature, humidity, wind speed, weather forecast and advisories will be shared with the city residents and tourists.
• ISO 9001:2008 certification to SAFAR: SAFAR (System of Air Quality & Weather Forecasting and Research) India’s first Air Quality Forecasting System, project of ESSO-IITM awarded an ISO 9001:2008 certification from Standard Certification Council of India.

Important Results:

• Air quality simulation over South Asia using Hemispheric Transport of Air Pollution version-2 (HTAP-v2) emission inventory and Model for Ozone and Related chemical Tracers 3 (MOZART-4)

  Distribution of tropospheric ozone (O₃) and its precursors are presented for the South Asia using the Model for Ozone and Related chemical Tracers (MOZART-4) and Hemispheric Transport of Air Pollution version-2 (HTAP-v2) emission inventory. The model simulated O₃, carbon monoxide (CO) and nitrogen dioxide (NO₂) are evaluated against surface-based, balloon-borne and satellite-based (MOPITT and OMI) observations. The model systematically overestimates surface O₃ mixing ratios (range of mean bias about: 1-30 ppbv) at different ground-based measurement sites in India. Comparison between simulated and observed vertical profiles of ozone shows a positive bias from the surface up to 600 hPa and a negative bias above 600 hPa. The simulated seasonal variation in surface CO mixing ratio is consistent with the surface observations, but has a negative bias of about 50-200 ppb which can be attributed to a large part to the coarse model resolution. In contrast to the surface evaluation, the model shows a high bias of about 15-20×10¹⁷ molecules/cm² over South Asia when compared to satellite derived CO columns from the MOPITT instrument. The model also overestimates OMI retrieved tropospheric column NO₂ abundance by about 100-250×10¹³ molecules/cm². A response to 20% reduction in all anthropogenic emissions over South Asia shows a decrease in the annual mean O₃ mixing ratios by about 3-12 ppb, CO by about 10-80 ppb and NO_X by about 3-6 ppb at the surface level. During summer monsoon, O₃ mixing ratios at 200 hPa show a decrease of about 6-12 ppb over South Asia and about 1-4 ppb over the remote northern hemispheric western Pacific region. [Surendran D.E., Ghude S.D., Beig G., Emmons L.K., Jena C., Rajesh Kumar, Pfister G.G., Chate D.M., Air quality simulation over South Asia using Hemispheric Transport of Air Pollution version-2 (HTAP-v2) emission inventory and Model for Ozone and Related chemical Tracers (MOZART-4), Atmospheric Environment, 122, December 2015, DOI:10.1016/j.atmosenv.2015.08.023, 357-372]

Fig. 1. Comparison between modeled(MOZART) and observed surface ozone and CO

• Inter-comparison of different NO_X emission inventories and associated variation in simulated surface ozone in Indian region

For the first time, different anthropogenic NO_X emission inventories are compared and examined for variations in simulated surface ozone (O₃) in India. Six anthropogenic NOx emission inventories namely Emission Database for Global Atmospheric Research (EDGAR), Intercontinental Chemical Transport Experiment-Phase B (INTEX-B), Regional Emission Inventory in Asia (REAS), MACCity, Indian National Emission Inventory (India-NOx), and Top-Down NO_X emission inventory for India (Top-Down) are included in the comparison. These emission inventories are included in regional chemical transport model WRF-Chem to simulate tropospheric column NO₂ and surface O₃ mixing ratios for the month of summer (15 March to 15 April) and winter (December) in 2005. Predicted tropospheric NO₂ using different NOx emission inventories is evaluated with the OMI satellite observations. All emission inventories show similar spatial features, however, uncertainty in NOx emissions distribution is about 20-50% over rural regions and about 60-160% over the major point sources. Compared to OMI, the largest bias in simulated tropospheric NO₂ columns is seen in the REAS (-243.0 ± 338.8×10¹³ molecules cm^-2) emission inventory, followed by EDGAR (-199.1 ± 272.2×10¹³ molecules cm^-2), MACCity (-150.5 ± 236.3×10¹³ molecules cm^-2), INTEX-B (-96.8 ± 199.5×10¹³ molecules cm^-2), India-NOx (-87.7 ± 159.9×10¹³ molecules cm^-2) and Top-Down (-30.8 ± 69.6×10¹³ molecules cm^-2) inventories during winter. Simulations using different NO_X emission inventories produces maximum deviation in daytime 8-h averaged O₃ of the order of 9-17 ppb (15-40%) in summer and 3-12 ppb (5-25%) in winter over most of the land area. choice of NOx emission inventories has significant effect on surface O₃ concentration for air quality studies over India. [Jena C., Ghude S.D., Beig G., Chate D.M., Kumar R., Pfister G.G., Lal D.M., Surendran D.E., Fadnavis S., Van der A R.J., Inter-comparison of different NOX emission inventories and associated variation in simulated surface ozone in Indian region, Atmospheric Environment, 117, September 2015, DOI:10.1016/j.atmosenv.2015.06.057, 61-73]

Fig. 2. Spatial distribution NOX emissions from optimized Top-Down inventory (emission unit is 1011 NO molecules/cm2/s) for winter, pre-monsoon, monsoon and post-monsoon
seasons. Seasons are mentioned on top of the each panel.

Sensitivity of online coupled model to extreme pollution event over a mega city Delhi

Sensitivity of interactive Weather-Chemistry model has been examined to predict the air quality (1 and 3 days in advance) of Indian mega city Delhi during two identical extreme events of Diwali in 2012 and 2013. Analysis is conducted 3 days prior to 3 days later of Diwali day for both events to verify the rapid changes in fine particulate matter (PM2.5) due to widespread display of Diwali fireworks. The model successfully predicted the variability in PM2.5 during 2012 for the entire period of analysis with reasonable accuracy. Although model performed reasonably well until Diwali day in 2013 but it was unable to simulate rapid built up of PM2.5 (1500 mg3 hourly average) during post Diwali day as it failed to capture unusual mid-night steep temperature gradient followed by a record lowering of boundary layer height. The predictability of the model and its limitation to micrometeorological processes are discussed in detail. [Srinivas R. et. al., Atmospheric Pollution Research, January 2016]

Fig. PM2.5 1D and 3D (one day and three day) forecast validation over Delhi (a) Diwali-2012 (b) Diwali-2013.

• Reka Srinivas a, Gufran Beig annd Sunil K. Peshin, Role of transport in elevated CO levels over Delhi during onset phase of monsoon, Atmospheric Environment (USA), 123, doi:10.1016/j.atmosenv.2016.06.003 , 2016.
• Neha Parkhi, D.M. Chate, S.D. Ghude, Sunil Peshin, A. Mahajan, Reka Srinivas, D. Surendran, K. Ali, S. Singh, H.K. Trimbake , Gufran Beig, Large inter annual variation in air quality during the annual festival ‘Diwali’ in an Indian megacity , Journal of Environmental Sciences, JES-D-15-00655, 2016.
• Surendaran, D., Gufran Beig, et al., Quantifying the sectorial contribution of pollution transport from South Asia during summer and winter monsoon seasons in support of HTAP-2 experiment, Atmospheric Environment (USA), ATMENV-D-16-00781, 177, 2016.
• J. Sperling, P. Romero-Lankao, and Gufran Beig, Exploring citizen infrastructure and environmental priorities in Mumbai, India, Environmental Science and Policy (USA), doi.org/10.1016/j.envsci.2016.02.006 , 60, 19–27, 2016.
• S.D. Ghude, C. K. Jena, G. Beig, R. Kumar, S. H. Kulkarni and D. M. Chate, Impact of emission mitigation on ozone-induced wheat and rice damage in India, Current Science, 110, 2016.
• K. Ali, A. S. Panicker , Gufran Beig, R. Srinivas , P. Acharya , Carbonaceous aerosols over Pune and Hyderabad (India) and influence of meteorological factors, Journal of Atmospheric Chemistry (Europe), DOI: 10.1007/s10874-015-9314-4, 1-29, 2016.
• S. S. Gunthe, Gufran Beig and L. K. Sahu, Study of relationship between daily maxima in ozone and temperature in an urban site in India, Current Science, 110, doi: 201610.18520/cs/v110/i10/1994-1999, 2016.
• Reka Srinivas, A. S. Panicker, N. S. Parkhi, S. K. Peshin, Gufran Beig, Sensitivity of online coupled model to extreme pollution event over a mega city Delhi , Atmopsheric Pollution Research (USA), doi: 10.1016/j.apr.2015.07.001 , 25-30, 2016.
• Chakraborty , T., Gufran Beig, F. Dentner and O. Wild, Atmospheric transport of ozone between Southern and Eastern Asia, Science of the Total Environment (USA), DOI : 10.1016/j.scitotenv.2015.03.066, 28-39, 2015.
• S. K. Sahu, Gufran Beig and Neha Parkhi, High Resolution emission inventory of NOx and CO for Mega City Delhi, India, Aerosol and Air Quality Research (USA) , 1-8, doi: 10.4209/aaqr.2014.07.0132, 2015.

Project Director: Dr. Gufran Beig, Scientist-G

Deputy Project Director: Dr. D.M. Chate, Scientist-E