Informatics Publishing Limited

Sachin D. Ghude ¹, G. S. Bhat ², Thara Prabhakaran ¹, R. K. Jenamani ³, D. M. Chate ¹, P. D. Safai ¹, A. K. Karipot ⁴, M. Konwar ¹, Prakash Pithani ¹, V. Sinha ⁵, P. S. P. Rao ¹, S. A. Dixit ¹, S. Tiwari ¹, K. Todekar ¹, S. Varpe ¹, A. K. Srivastava ¹, D. S. Bisht ¹, P. Murugavel ¹, Kaushar Ali ¹, Usha Mina ⁶, M. Dharua ¹, J. Rao ¹, B. Padmakumari ¹, A. Hazra ¹, N. Nigam ³, U. Shende ³, D. M. Lal ¹, B. P. Chandra ⁵, A. K. Mishra ⁵, A. Kumar ⁵, H. Hakkim ⁵, H. Pawar ⁵, P. Acharja ¹, Rachana Kulkarni ¹, C. Subharthi ¹, B. Balaji ¹, M. Varghese ¹, S. Bera ¹, M. Rajeevan ⁷

Affiliations
1 Indian Institute of Tropical Meteorology, Pashan, Pune 411 008, IN
2 Indian Institute of Science, Bengaluru 560 012, IN
3 India Meteorological Department, New Delhi 110 003, IN
4 Savitribai Phule Pune University, Pune 411 007, IN
5 Indian Institute of Science Education and Research Mohali, Mohali 140 306, IN
6 Indian Agricultural Research Institute, Pusa, New Delhi 110 012, IN
7 Ministry of Earth Sciences, Government of India, New Delhi 110 003, IN

Abstract

The objectives of the Winter Fog Experiment (WIFEX) over the Indo-Gangetic Plains of India are to develop better now-casting and forecasting of winter fog on various time- and spatial scales. Maximum fog occurrence over northwest India is about 48 days (visibility <1000 m) per year, and it occurs mostly during the December-February time-period. The physical and chemical characteristics of fog, meteorological factors responsible for its genesis, sustenance, intensity and dissipation are poorly understood. Improved understanding on the above aspects is required to develop reliable forecasting models and observational techniques for accurate prediction of the fog events. Extensive sets of comprehensive ground-based instrumentation were deployed at the Indira Gandhi International Airport, New Delhi. Major in situ sensors were deployed to measure surface micro-meteorological conditions, radiation balance, turbulence, thermodynamical structure of the surface layer, fog droplet and aerosol microphysics, aerosol optical properties, and aerosol and fog water chemistry to describe the complete environmental conditions under which fog develops. In addition, Weather Forecasting Model coupled with chemistry is planned for fog prediction at a spatial resolution of 2 km. The present study provides an introductory overview of the winter fog field campaign with its unique instrumentation.

Keywords

Aerosols, Atmospheric Profiles, Forecasting, Winter Fog.

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B. P. Chandra ¹, V. Sinha ¹, H. Hakkim ¹, A. Kumar ¹, H. Pawar ¹, A. K. Mishra ¹, G. Sharma ¹, Pallavi ¹, S. Garg ¹, Sachin D. Ghude ², D. M. Chate ², Prakash Pithani ², Rachana Kulkarni ², R. K. Jenamani ³, M. Rajeevan ⁴

Affiliations
1 Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Mohali, Sector 81, S.A.S. Nagar, Manauli PO 140 306, IN
2 Indian Institute of Tropical Meteorology, Pashan, Pune 411 008, IN
3 India Meteorological Department, New Delhi 110 003, IN
4 Ministry of Earth Sciences, Government of India, New Delhi 110 003, IN

Abstract

We studied the impact of the odd–even traffic rule (implemented in Delhi during 1–15 January 2016) on primary traffic emissions using measurements of 13 volatile organic compounds, carbon monoxide, carbon dioxide and methane at a strategic arterial road in Delhi (28.57°N, 77.11°E, 220 m amsl). Whole air samples (n = 27) were collected during the odd–even rule active (OA) and inactive (OI) days, and analysed at the IISER Mohali Atmospheric Chemistry Facility. The average mass concentration ranking and toluene/benzene ratio were characteristic of primary traffic emissions in both OA and OI samples, with the largest fraction comprising aromatic compounds (55– 70% of total). Statistical tests showed likely increase (p ≤ 0.16; OA > OI) in median concentration of 13 out of 16 measured gases during morning and afternoon periods (sampling hours: 07 : 00–08 : 00 and 13 : 30–14 : 30 IST), whereas no significant difference was observed for evening samples (sampling hour: 19 : 00–20 : 00 IST). This suggests that many four-wheeler users chose to commute earlier, to beat the 8 : 00 AM–8 : 00 PM restrictions, and/or there was an increase in the number of exempted public transport vehicles. Thus, the odd–even rule did not result in anticipated traffic emission reductions in January 2016, likely due to the changed temporal and fleet emission behaviour triggered in response to the regulation.

Keywords

Odd–Even Rule, Pollution, PTR-MS, Traffic, VOCs.

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