On deriving influences of upwind agricultural and anthropogenic emissions on greenhouse gas concentrations and air quali
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Ó Indian Academy of Sciences (0123456789().,-volV)(0123456789( ).,-volV)
On deriving inCuences of upwind agricultural and anthropogenic emissions on greenhouse gas concentrations and air quality over Delhi in India: A stochastic Lagrangian footprint approach THEERTHA KARIYATHAN1,2, DHANYALEKSHMI PILLAI1,* , ELDHO ELIAS1 and THARA ANNA MATHEW1 1
Indian Institute of Science Education and Research Bhopal (IISERB), Bhopal Bypass Road, Bhauri, Bhopal 462 066, Madhya Pradesh, India. 2 Present address: Max Planck Institute for Biogeochemistry, 07745 Jena, Germany. *Corresponding author. e-mail: [email protected] MS received 15 January 2020; revised 22 May 2020; accepted 27 May 2020
Delhi, the capital city of India witnesses severe degradation of air quality and rapid enhancement of trace gases during winter. Still it is unclear about the relative role of the meteorological conditions and the post-monsoon agricultural stubble burning on the occurrence of these events. To overcome this, we examine the use of applying high-resolution transport model to establish the link between atmospheric concentrations and upstream surface Cuxes. This study reports the implementation of a Lagrangian approach and demonstrates its capability in deriving the upwind inCuences over Delhi. We simulate stochastic back trajectories over Delhi by implementing stochastic time-inverted Lagrangian transport (STILT) model, driven by the meteorological Belds from the European Centre for Medium Range Weather Forecasts (ECMWF) model. During the postmonsoon, when mixing layer height is shallow, we Bnd high near-Beld inCuence. The variations in footprint simulations with receptor heights show the eAect of mixing layer dynamics on the air-parcels. By using atemporal emission Belds, we Bnd a considerable impact of meteorological conditions during November that contributes to the enhancements of trace gases. Together with strong emissions (anthropogenic and biomass burning), these enhancements can be several orders higher compared to other seasons. Through the receptororiented STILT implementation over India, we envision a wide range of applications spanning from air quality to climate change. An advantage of this implementation is that it allows the use of pre-calculated footprints in simulating any trace gas species and particulate matter, making it computationally less demanding than running an ensemble of full atmospheric transport model. Keywords. Lagrangian modelling; atmospheric transport; backward trajectory; urban scale air-quality; greenhouse gas mixing ratio; Delhi winter pollution.
1. Introduction Over the past few years, the onset of winter in north India gains media prominence due to its association with exorbitant level of pollutants and
trace gases in the lower atmosphere. While local urban sources (e.g., road trafBc, residential airconditioning systems, industries and power plants) are primarily responsible for the increased emissions (Olivier et al. 2005; Ghude et al. 2008, 2013;
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