EGU2020-223
https://doi.org/10.5194/egusphere-egu2020-223
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Air Pollution and its potential climate effect in Delhi, India

Ying Chen1,2, Luke Conibear3, Yu Wang4, Liang Ran5, Jianjun He6, Lina Wang7, and Oliver Wild1,2
Ying Chen et al.
  • 1Lancaster Environment Centre, Lancaster University, Lancaster, UK (y.chen65@lancaster.ac.uk)
  • 2Data Science Institute, Lancaster University, Lancaster, UK (y.chen65@lancaster.ac.uk)
  • 3Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK (pmlac@leeds.ac.uk)
  • 4Department of Earth, Atmospheric and Environmental Sciences, University of Manchester, Manchester, UK (yu.wang@manchester.ac.uk)
  • 5Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China (shirleyrl@mail.iap.ac.cn)
  • 6Chinese Academy of Meteorological Sciences, Beijing, China (hejianjun@cma.gov.cn)
  • 7Department of Environmental Science and Engineering, Fudan University, Shanghai, China (wanglina@fudan.edu.cn)

Delhi, the capital city of India with more than 10 million population, is suffering one of the worst particulate matter (or PM2.5) pollution over the world. Based on continuous observations during 2015-2018, we report that the PM2.5 pollution in Delhi is possibly one of the worst within Indian cities, and responsible for ~10,000 premature deaths of cities per year. Especially during the Diwali Fest, the hourly PM2.5 concentrations went above 1600 ug/m3, leading to ~20 extra premature deaths per day (Chen et al., 2019). We find a distinct seasonal variation of PM2.5 mass concentrations and a shift of morning rush hour from winter to summer, but a negligible weekend effect in Delhi. We also report a long-term result of hygroscopicity of PM2.5 in Delhi is about κ= 0.42 ± 0.07 for the first time, indicating much higher potential of cloud droplet activation from fine particles in Delhi compared with other Asian megacities, such as Beijing (κ=0.14–0.23) (Wang and Chen, 2019). It means, in addition to the great health burden, more significant cloud activation and greater influences on climate and hydrologic cycle are expected from fine particles in Delhi.

 

Method & Data

             We analysed the PM2.5 observations from US Embassy in Delhi, and used the Integrated Exposure Response Function to estimate the long-term and short-term health effect of PM2.5 exposure with a particular focus on the Diwali Fest period. Together with the temperature, RH and visibility data from the DEL airport in Delhi, we retrieved the 2016-2018 averaged hygroscopicity (κ) in Delhi according to the κ-kÓ§hler and Mie theories. In summary, we firstly retrieve the optical enhancement from visibility and RH, and then retrieve the optical-κ, and finally estimate the κ from the optical-κ. The detailed retrieving method is given in Wang and Chen (2019), this method has been validated in Beijing within an uncertainty of 30%.

 

Summary

                Our results show a strong seasonal variation of PM2.5 in Delhi, with severest pollution during the winter. The Diwali and New Year Fests also lead to extreme pollution events, i.e. worse than the ‘Severe’ Level, in the beginning of November and January. These lead to adverse health effect and make Delhi the top-1 health burden city in India. The long-term averaged hygroscopicity of PM2.5 in Delhi is much higher than Beijing and Asian average. This indicate much easier for fine particles serving as cloud condensation nuclei and contributing the climate change and hydrology cycle. Moreover, the high optical enhance factor, f(RH), implies strong direct radiative forcing enhancement and influences on the heterogeneous reactions in Delhi.

 

Acknowledgement: We thank NERC Fund supported project (NE/P01531X/1) and the joint scholarship of China Scholarship Council and University of Manchester. We thank the U.S. National Climatic Data Center and AirNow platform maintained by the EPA provide the observations.

 

References:

Chen, Y., Wild, O., Conibear, L., Ran, L., He, J., Wang, L., and Wang, Y.: Atmospheric Environment: X, 100052, 10.1016/j.aeaoa.2019.100052, 2019.

Wang, Y., and Chen, Y.: Geophysical Research Letters, 10.1029/2019GL082339, 2019.

How to cite: Chen, Y., Conibear, L., Wang, Y., Ran, L., He, J., Wang, L., and Wild, O.: Air Pollution and its potential climate effect in Delhi, India, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-223, https://doi.org/10.5194/egusphere-egu2020-223, 2019

How to cite: Chen, Y., Conibear, L., Wang, Y., Ran, L., He, J., Wang, L., and Wild, O.: Air Pollution and its potential climate effect in Delhi, India, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-223, https://doi.org/10.5194/egusphere-egu2020-223, 2019

Displays

Display file