Systematic review of Chinese studies of short-term exposure to air pollution and daily mortality

Shang, Yu; Sun, Zhiwei; Cao, Junji; Wang, Xinming; Zhong, Lexuan; Bi, Xinhui; Li, Hong; Liu, Wenxin; Zhu, Tong; Huang, Wei

doi:10.1016/j.envint.2013.01.010

Cited by 441 publications

(214 citation statements)

References 50 publications

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“…This value lies in the range of global estimate by Atkinson et al (2014), and closer to several studies in China (Dai et al, 2004;Chen et al, 2011) and the US (Ostro et al, 2006). Furthermore, to better cogitate its associated health benefits, the possible number of non-accidental deaths averted by reducing PM 2.5 concentrations, to suggested levels by WHO and INAAQS was estimated following Shang et al (2013). The expected number of premature deaths (PD i ) Fig.…”

Section: Estimation Of Health Risk Associated With Pollutantsmentioning

confidence: 91%

Significance of PM2.5 Air Quality at the Indian Capital

Sahu

Kota

2017

Aerosol Air Qual. Res.

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In New Delhi, the capital city of India, concentrations of regulated air pollutants often exceed the Indian national ambient air quality standards (INAAQS). As the sources of these pollutants differ, it is of utmost priority to understand the most dangerous air pollutant to formulate better control strategies in the city. In this study, regulated air pollutant concentrations in New Delhi during 2011 to 2014 were collected. Compared to other pollutants, PM 2.5 concentrations exceeded the INAAQS quite often. While PM 2.5 exceeded INAAQS during 85% of the days, NO 2 , O 3 , CO and SO 2 exceeded only on 37, 14, 11 and 0% of the days, respectively. Using air quality index approach, the most dominant pollutant was identified as PM 2.5 , for 75 to 90% of the days. However, a seasonal variation in the percentage dominance of PM 2.5 was observed. For example, PM 2.5 was dominant during 95% of the winter and 68% of monsoon days. In addition to absolute concentrations, pollutants can also be ranked by studying their associated short term mortality impacts. However, such studies are rare in India. For the first time, the short term impact of PM 2.5 concentrations on non-disease specific mortality in New Delhi was assessed using Poisson regression models. Results indicated that the excessive risk associated with PM 2.5 estimated was 0.57, which was higher than the other regulated pollutants. This indicates a projected 6.2 and 6.5% decrease in mortality by meeting the PM 2.5 Indian standards and WHO set limits, respectively.

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Section: Estimation Of Health Risk Associated With Pollutantsmentioning

confidence: 91%

Significance of PM2.5 Air Quality at the Indian Capital

Sahu

Kota

2017

Aerosol Air Qual. Res.

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“…During these episodes, ambient 24-h average PM 2.5 levels up to 175 μg m −3 have been recorded, well over the World Health Organization (WHO) daily Air Quality Guidelines of 25 μg m −3 . High PM 2.5 levels are closely associated with long-and short-term health problems (Tie et al, 2009;van Donkelaar et al, 2010;Chen R.J. et al, 2012;Shang et al, 2013). In an attempt to reduce particulate pollution, the Chinese government has recently implemented new national ambient air quality standards, which for the first time include PM 2.5 .…”

Section: Introductionmentioning

confidence: 99%

Trends of ambient fine particles and major chemical components in the Pearl River Delta region: Observation at a regional background site in fall and winter

Wang

Guo

et al. 2014

Science of The Total Environment

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“…Atmospheric pollution is also associated with a variety of adverse health effects, including respiratory and cardiovascular mortalities, impaired lung function, and heart disease (Anderson, 2009;Dadvand et al, 2011;Puza et al, 2011;Yu et al, 2012;Shang et al, 2013). Other studies (Huang et al, 2009;Thach et al, 2010) have attempted to link atmospheric visibility to adverse health effects.…”

Section: Introductionmentioning

confidence: 99%

Long-Term Trends in Visibility and Its Relationship with Mortality, Air-Quality Index, and Meteorological Factors in Selected Areas of Korea

Lee

2015

Aerosol Air Qual. Res.

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We investigated temporal trends in atmospheric visibility as well as their relationship to non-accident-related daily mortality, the Comprehensive Air-quality Index (CAI) in Korea, and selected meteorological factors in four cities (Seoul, Busan, Daegu, and Ulsan) and one remote island (Ullungdo) for the period 2001-2009. According to the mean values, Seoul exhibited the lowest visibility (12.2 km), followed by Ullungdo (12.6 km), Ulsan (14.2 km), Daegu (14.7 km), and Busan (17.3 km). Conversely, Ullungdo had the lowest CAI value (82.4) and no respiratory mortality (RM) occurrences at all, and Seoul had both the highest mean CAI value (122) and the highest occurrence of daily RM (5.3). There were negative correlations between visibility and two meteorological parameters (relative humidity and ambient temperature) in all five areas, whereas there were generally positive correlations between visibility and the other two meteorological parameters (precipitation and wind speed). For some lag periods, the mortality in the cities was significantly correlated with visibility and the CAI, whereas mortality in Ullungdo was not. Busan had the highest excess risk for non-accidentrelated daily mortality, followed by Daegu, Seoul, and Ulsan.

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Systematic review of Chinese studies of short-term exposure to air pollution and daily mortality

Cited by 441 publications

References 50 publications

Significance of PM2.5 Air Quality at the Indian Capital

Significance of PM2.5 Air Quality at the Indian Capital

Trends of ambient fine particles and major chemical components in the Pearl River Delta region: Observation at a regional background site in fall and winter

Long-Term Trends in Visibility and Its Relationship with Mortality, Air-Quality Index, and Meteorological Factors in Selected Areas of Korea

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