Metropolitan Air Quality and Weather Forecasting Services
Project Director: Dr. Gufran Beig
Deputy Project Director: Dr. D. M. Chate
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-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 firstname.lastname@example.org
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):
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 NOX 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
For the first time, different anthropogenic NOX 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 NOX 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 NOX 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.
Project Director: Dr. Gufran Beig, Scientist-G
Deputy Project Director: Dr. D.M. Chate, Scientist-E