Policy Interventions and Their Impact on Air Quality in Delhi City — an Analysis of 17 Years of Data

Gulia, Sunil; Goyal, Prachi; Prakash, Mamta; Goyal, Sanjeev; Kumar, Rakesh

doi:10.1007/s11270-021-05402-x

Cited by 8 publications

(3 citation statements)

References 6 publications

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“…Sporadically, efforts have been introduced to improve air quality by adopting measures to control emissions in Delhi. However, the impact of these interventions has been negated by the rapid development of different sectors, which has further deteriorated the air quality [2]. Air pollutants emitted from diverse sources have detrimental impacts, which are of serious concern in urban cities in India.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Air Pollution Mitigation Measures on Secondary Pollutants PM10 and Ozone Using Chemical Transport Modelling over Megacity Delhi, India

2022

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Sporadic efforts have been introduced to control emissions in Delhi, but the air quality has declined further due to the rapid development of different sectors. In this study, the impact of various mitigation scenarios on air quality for PM10, ozone, and its precursors are studied using a chemical transport model, namely WRF-Chem. The Emission Database for Global Atmospheric Research emission inventory was modified and introduced into the WRF-Chem model to assess the impact of selected emission control scenarios on different sectors. The simulations were conducted with reduced emissions for these sectors over the study domain: (a) implementation of Bharat Stage—VI norms in the transport sector, (b) conversion of fuel from coal to natural gas in the energy sector, and (c) fuel shift to LPG in the residential sector. The transport sector noted a decrease of 4.9% in PM10, 44.1% in ozone, and 18.9% in NOx concentrations with emission reduction measures. In the energy sector, a marginal reduction of 3.9% in NOx concentrations was noted, and no change was observed in PM10 and ozone concentrations. In the residential sector, a decrease of 8% in PM-10, 47.7% in ozone, and 49.8% in NOx concentrations were noted. The VOC-to-NOx ratios were also studied, revealing the ozone production over the study domain was mostly VOC-limited. As the inclusion of control measures resulted in varying levels of reduction in pollutant concentrations, it was also studied in the context of improving the air quality index. The WRF-Chem model can be successfully implemented to study the effectiveness of any regulated control measures.

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Section: Introductionmentioning

confidence: 99%

Assessment of Air Pollution Mitigation Measures on Secondary Pollutants PM10 and Ozone Using Chemical Transport Modelling over Megacity Delhi, India

2022

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“…[ 1 ] The regulatory bodies of India continuously iterated that if in spite of these measures, pollution levels are not reduced up to the acceptable levels a complete lockdown may be imposed to control the rising levels of air pollution in urban areas. [ 8 ] However, no scientific evidence was available for considering lockdown as a pollution abatement strategy.…”

Section: Introductionmentioning

confidence: 99%

Lockdown as an Empirical Strategy to Curb Air Pollution: Evidence from a Quasi‐Natural Experiment

Yadav¹,

Singh

Soni

et al. 2022

CLEAN Soil Air Water

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In this study, three approaches namely parallel, sequential, and multiple linear regression are applied to analyze the local air quality improvements during the COVID-19 lockdowns. In the present work, the authors have analyzed the monitoring data of the following primary air pollutants: particulate matter (PM 10 and PM 2.5 ), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), and carbon monoxide (CO). During the lockdown period, the first phase has most noticeable impact on airquality evidenced by the parallel approach, and it has reflected a significant reduction in concentration levels of PM 10 (27%), PM 2.5 (19%), NO 2 (74%), SO 2 (36%), and CO (47%), respectively. In the sequential approach, a reduction in pollution levels is also observed for different pollutants, however, these results are biased due to rainfall in that period. In the multiple linear regression approach, the concentrations of primary air pollutants are selected, and set as target variables to predict their expected values during the city's lockdown period.The obtained results suggest that if a 21-days lockdown is implemented, then a reduction of 42 µg m −3 in PM 10 , 23 µg m −3 in PM 2.5 , 14 µg m −3 in NO 2 , 2 µg m −3 in SO 2 , and 0.7 mg m −3 in CO can be achieved.

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“…We witness the first traces of it, especially in relation to air pollution, in the National Air Quality Index (NAQI), launched by the Indian government in 2014, which provides real-time data on air quality in major cities across the country. Delhi, the capital city of India, is an important case in this change since data-driven governance using air-quality monitoring stations to calculate the AQI has led to several decision-making and policyguiding interventions in the city (Gulia et al 2021).…”

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confidence: 99%

In Search of a “Social-AQI”

Dwivedi,

Yaqoob,

Khan

et al. 2023

samaj

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Policy Interventions and Their Impact on Air Quality in Delhi City — an Analysis of 17 Years of Data

Cited by 8 publications

References 6 publications

Assessment of Air Pollution Mitigation Measures on Secondary Pollutants PM10 and Ozone Using Chemical Transport Modelling over Megacity Delhi, India

Assessment of Air Pollution Mitigation Measures on Secondary Pollutants PM10 and Ozone Using Chemical Transport Modelling over Megacity Delhi, India

Lockdown as an Empirical Strategy to Curb Air Pollution: Evidence from a Quasi‐Natural Experiment

In Search of a “Social-AQI”

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