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CATERINA MOGNO 1 , Paul P almer 1 , Tim Wallington 2

European WRF-Chem User Workshop 2019, Munich 7-8 May. Quantifying the role of the transport sector on observed variations of PM2.5 over the National Capital Region of Delhi. CATERINA MOGNO 1 , Paul P almer 1 , Tim Wallington 2. 1 The University of Edinburgh, School of Geosciences.

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CATERINA MOGNO 1 , Paul P almer 1 , Tim Wallington 2

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  1. European WRF-Chem User Workshop 2019, Munich 7-8 May Quantifying the role of the transport sector on observed variations of PM2.5 over the National Capital Region of Delhi CATERINA MOGNO1, Paul Palmer1, Tim Wallington2 1 The University of Edinburgh, School of Geosciences 2 Research and Advanced Engineering, Ford Motor Company, MI -USA

  2. Outline 01 Context 02 Research Questions 03 Preliminary work 04 Future work 0

  3. Context: PM2.5 and health 01 PM2.5 = particulate matter of 2.5 microns or less in diameter PM2.5 affect human health more than any other pollutant (WHO*) 4.2 million premature deaths worldwide in 2016. 91% occurring in low- and middle-income countries Stroke, heart diseases , lung cancer, respiratory diseases (e.g. asthma) * World Health Organisation, “Ambient (outdoor) air quality and health, factsheet,” 2018. 0

  4. Context: Organic Aerosols (OA) 01 Organic Aerosol evolution in the atmosphere: 0

  5. Context: pollution in Delhi 01 2018 annual mean: 106 μg/m3 WHO guideline value annual mean: 10 μg/m3 Data source: US Embassy in India, Delhi Air Quality Data Information.

  6. Context: pollution in Delhi 01 Reality of Delhi’s pollution is very complex: 0

  7. Context: pollution in Delhi 01 * Reality of Delhi’s pollution is very complex: Multiple local sources Transboundary pollution Influence of meteorology 0 * Sharma, S. K., and T. K. Mandal. "Chemical composition of fine mode particulate matter (PM2. 5) in an urban area of Delhi, India and its source apportionment." Urban Climate 21 (2017): 106-122.

  8. Context: transport in Delhi 01

  9. Context: transport in Delhi 01 * One of major sources: up to 25% of direct emissions of PM2.5 Vehicle emissions are continuous Increase in the number of vehicles air quality policy measures * Data source: Government of india, Ministry of Statistics and Programme Implementation, Statistical Year Book India 2018

  10. DIAGNOSTIC: How much does transport contribute to PM2.5 over Delhi? - primary PM2.5 emitted vs secondary PM2.5 formation from gas precursors (e.g. NOx and VOCs). - chemical factors/ meteorological conditions/ environmental conditions that control this contribution during different seasons. Research questions 02 0

  11. Research questions 02 2)PROGNOSTIC: How transport contribution to PM2.5 over Delhi can be reduced? - sensitivity study on different emissions from transport: seasonal analysis and during extreme events (e.g. Diwali, heatwaves) 0

  12. Preliminary work: experimental design 03 Observation data availability • AOD: AERONET (ground-based) + MODIS (satellite) • Ground PM2.5 observation: CPCB data (38 stations) + US Embassy (1 station) 0

  13. Preliminary work: experimental design 03 WRFchem 4.0 setup: first attempt • Chemistry: MOZART - MOSAIC-VBS (chem_opt =202) (SOA treated with the Volatility Basis Set - POA inert) • Anthropogenic emissions: inventory EDGAR/HTAP • Biogenic emissions: MEGAN • Fires emissions: FINN • BC and IC: MOZART-4 • Meteorology: GFS • Simulation: 1 year (all seasons) 0

  14. Preliminary work: experimental design 03 WRFchem 4.0 setup: first attempt • Outer Domain: 0 • Simulation: 1 year (all seasons)

  15. Preliminary work: experimental design 03 WRFchem 4.0 setup: challenges, other ideas ? Alternative Chemistry: SAPRC99 - MOSAIC-VBS (chem_opt =203) SOA VBS POA considered semivolatile + some emissions to consider gas-to-particle of IVOCs Is it feasible ( preparation of emissions, speciation of inventory etc) ? Alternative inventories ? Nesting domain choice and simulation run(s) ? BC and IC from GEOSchem ? Data assimilation WRF-DA ? WRFchem running on a Web Cloud 0

  16. Future work: next steps 04 • Complete observational data availability and inventory availability • Complete set-up and test runs WRFchem • Baseline simulation and model evaluation 0

  17. THANK YOU! • Presentation template by SlidesCarnival

  18. Preliminary work: experimental design 03 Inventory data availability (anthropogenic emissions) 0

  19. Context: Organic Aerosols (OA) 01 modeling OA Volatility Basis Set (VBS) Key features of OA evolution: VOLATILITY O:C RATIO Donahue, Neil M., et al. "A two-dimensional volatility basis set–Part 2: Diagnostics of organic-aerosol evolution." Atmospheric Chemistry and Physics 12.2 (2012): 615-634. 0

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