Significance of PM2.5 Air Quality at the Indian Capital

Sahu, Shovan Kumar; Kota, Sri Harsha

doi:10.4209/aaqr.2016.06.0262

Cited by 82 publications

(39 citation statements)

References 41 publications

(44 reference statements)

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“…To understand the overall improvement in air quality, air quality index (AQI) was computed. The details of AQI are available elsewhere (CPCB, 2014;Sahu and Kota, 2017), and only briefly summarized here. AQI uses PM 10 , PM 2.5 , NO 2 , O 3 , CO, SO 2 , NH 3 and Pb, of which minimum concentrations three pollutants should be available, with at least one being either PM 2.5 or PM 10 .…”

Section: Aqi and Health Risk Calculationsmentioning

confidence: 99%

Effect of restricted emissions during COVID-19 on air quality in India

Sharma

Zhang

Anshika

et al. 2020

Science of The Total Environment

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977

119

997

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The effectiveness and cost are always top factors for policy-makers to decide control measures and most measures had no pre-test before implementation. Due to the COVID-19 pandemic, human activities are largely restricted in many regions in India since mid-March of 2020, and it is a progressing experiment to testify effectiveness of restricted emissions. In this study, concentrations of six criteria pollutants, PM 10 , PM 2.5 , CO, NO 2 , ozone and SO 2 during March 16th to April 14th from 2017 to 2020 in 22 cities covering different regions of India were analysed. Overall, around 43, 31, 10, and 18% decreases in PM 2.5 , PM 10 , CO, and NO 2 in India were observed during lockdown period compared to previous years. While, there were 17% increase in O 3 and negligible changes in SO 2 . The air quality index (AQI) reduced by 44, 33, 29, 15 and 32% in north, south, east, central and western India, respectively. Correlation between cities especially in northern and eastern regions improved in 2020 compared to previous years, indicating more significant regional transport than previous years. The mean excessive risks of PM reduced by~52% nationwide due to restricted activities in lockdown period. To eliminate the effects of possible favourable meteorology, the WRF-AERMOD model system was also applied in Delhi-NCR with actual meteorology during the lockdown period and an un-favourable event in early November of 2019 and results show that predicted PM 2.5 could increase by only 33% in unfavourable meteorology. This study gives confidence to the regulatory bodies that even during unfavourable meteorology, a significant improvement in air quality could be expected if strict execution of air quality control plans is implemented.

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Section: Aqi and Health Risk Calculationsmentioning

confidence: 99%

Effect of restricted emissions during COVID-19 on air quality in India

Sharma

Zhang

Anshika

et al. 2020

Science of The Total Environment

Self Cite

977

119

997

View full text Add to dashboard Cite

show abstract

“…Literatures on PM 2.5 and PM 10 were often conducted independently, and mainly in health effects, spatial distributions, temporal trends, source apportionment, chemical composition, and influential factors analysis [23][24][25][26][27][28][29][30][31]. In terms of the relationship between PM 2.5 and PM 10 , it is proved that the mass concentration of PM 2.5 was highly correlated with PM 10 [32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

PM_2.5/PM₁₀ Ratios in Eight Economic Regions and Their Relationship with Meteorology in China

Zhao

Chen

et al. 2019

Advances in Meteorology

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China is suffering severe ambient air pollution in recent decades and particulate matter (PM) has become the major pollutant, especially for PM2.5 and PM10, which have highly raised scholars and policy-makers’ attention in last few years. The existing research has focused on the characteristics of PM2.5 and PM10, respectively, or analyzed the correlation between the two pollutants, while the ratio of PM2.5 to PM10 has been taken less consideration. In this study, daily mean PM2.5 and PM10 mass concentrations in 31 provincial capitals from 2014 to 2016 were used to present the temporal variations and spatial distribution of PM2.5/PM10 ratios among eight economic regions. And then, statistical method and correlation analysis were adopted to investigate the relationship between the ratios and AQI, the rate of change on the ratios, and the impact of meteorological parameters on the ratios. The results indicated that PM2.5/PM10 ratios showed an increasing trend from northwest to southeast due to different economic development and industrial types. The highest values were observed in winter among all regions, and the ratios on weekends were higher than that of on weekdays in most of the regions. Besides, domestic heating in northern China had a significant contribution to the ratios. Moreover, ratios had less changes, and the rate of change was stable in summer. As for air quality, the higher the ratio, the larger the possibility of high AQI so that the air pollution will be more severe. In terms of meteorological factors, the results demonstrated that relative humidity, precipitation, and pressure were the most important factors and had significantly positive impacts, while sunshine duration, temperature, and wind speed had negative effects on the ratios. The findings could identify the pollution sources among PM10 and be helpful for making regulation locally to reduce emission which considers anthropogenic sources and meteorological diffusion simultaneously.

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“…Guo et al: Source contributions and potential reductions to health effects Efforts have been made to estimate the premature deaths associated with PM 2.5 in India. For example, Sahu and Kota (2017) estimated that 41 out of 100 000 lives in Delhi could be saved by meeting the WHO suggested annual PM 2.5 guideline based on time series analysis. Such studies require extensive data, which are not available in all Indian cities.…”

mentioning

confidence: 99%

Source contributions and potential reductions to health effects of particulate matter in India

et al. 2018

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Abstract. Health effects of exposure to fine particulate matter (PM2.5) in India were estimated in this study based on a source-oriented version of the Community Multi-scale Air Quality (CMAQ) model. Contributions of different sources to premature mortality and years of life lost (YLL) were quantified in 2015. Premature mortality due to cerebrovascular disease (CEVD) was the highest in India (0.44 million), followed by ischaemic heart disease (IHD, 0.40 million), chronic obstructive pulmonary disease (COPD, 0.18 million), and lung cancer (LC, 0.01 million), with a total of 1.04 million deaths. The states with highest premature mortality were Uttar Pradesh (0.23 million), Bihar (0.12 million), and West Bengal (0.10 million). The highest total YLL was 2 years in Delhi, and the Indo-Gangetic plains and eastern India had higher YLL (∼1 years) than other regions. The residential sector was the largest contributor to PM2.5 concentrations (∼40 µg m−3), total premature mortality (0.58 million), and YLL (∼0.2 years). Other important sources included industry (∼20 µg m−3), agriculture (∼10 µg m−3), and energy (∼5 µg m−3) with their national averaged contributions of 0.21, 0.12, and 0.07 million to premature mortality, and 0.12, 0.1, and 0.05 years to YLL. Reducing PM2.5 concentrations would lead to a significant reduction of premature mortality and YLL. For example, premature mortality in Uttar Pradesh (including Delhi) due to PM2.5 exposures would be reduced by 79 % and YLL would be reduced by 83 % when reducing PM2.5 concentrations to 10 µg m−3.

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Significance of PM2.5 Air Quality at the Indian Capital

Cited by 82 publications

References 41 publications

Effect of restricted emissions during COVID-19 on air quality in India

Effect of restricted emissions during COVID-19 on air quality in India

PM_2.5/PM₁₀ Ratios in Eight Economic Regions and Their Relationship with Meteorology in China

Source contributions and potential reductions to health effects of particulate matter in India

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Significance of PM2.5 Air Quality at the Indian Capital

Cited by 82 publications

References 41 publications

Effect of restricted emissions during COVID-19 on air quality in India

Effect of restricted emissions during COVID-19 on air quality in India

PM2.5/PM10 Ratios in Eight Economic Regions and Their Relationship with Meteorology in China

Source contributions and potential reductions to health effects of particulate matter in India

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PM_2.5/PM₁₀ Ratios in Eight Economic Regions and Their Relationship with Meteorology in China