scholarly journals Particulate matter air pollution and national and county life expectancy loss in the USA: A spatiotemporal analysis

PLoS Medicine ◽  
2019 ◽  
Vol 16 (7) ◽  
pp. e1002856 ◽  
Author(s):  
James E. Bennett ◽  
Helen Tamura-Wicks ◽  
Robbie M. Parks ◽  
Richard T. Burnett ◽  
C. Arden Pope ◽  
...  
2019 ◽  
Author(s):  
Terrence D. Hill ◽  
Andrew Jorgenson ◽  
Peter Ore ◽  
Kelly S. Balistreri ◽  
Brett Clark

Although studies have shown that air pollution can be devastating to population health, little is known about the health implications of the intersection of air pollution and income inequality. We investigate if air pollution is especially detrimental to the health of US state populations characterized by more inequitable distributions of income. In other words, are the populations of states with higher levels of income inequality especially vulnerable to similar levels of air pollution? We use two-way fixed-effects panel regression techniques to analyze longitudinal data for 49 US states and the District of Columbia (2000–2010) to model state-level life expectancy as a function of fine particulate matter, income inequality, and other state-level factors. We estimate models with interaction terms to formally assess whether the association between fine particulate matter and life expectancy varies by level of state income inequality. Across multiple life expectancy outcomes and additive models, states with higher PM2.5 levels tend to exhibit lower average life expectancy. This general pattern is observed with our specifications for raw and weighted PM2.5 and with adjustments for income share of the top 10%, total population, GDP per capita, median household income, median age, percent college degree or higher, percent black, and percent Hispanic/Latino. We also find that the association between state PM2.5 levels and average life expectancy intensifies in states with higher levels of income inequality. More specifically, PM2.5 levels are more detrimental to population life expectancy in states where a higher percentage of income is concentrated in the top 10% of the state income distribution. We discuss the implications of our results for future research in social epidemiology and environmental justice.


2020 ◽  
Vol 32 (3) ◽  
pp. 1131-1162
Author(s):  
Howook (Sean) Chang ◽  
Chang Huh ◽  
Tiffany S. Legendre ◽  
John J. Simpson

Purpose A growing number of travelers seek well-being when traveling. As concerning about outdoor air pollution in tourism destinations escalates, little is known about indoor air pollution in hotel guestrooms. The purpose of the present study is to assess particulate matter (PM) pollution in US hotel guestrooms and to provide baseline indoor PM readings in occupied and unoccupied rooms. Design/methodology/approach A series of field tests and experiments monitoring PM levels were conducted in the guestrooms overnight – with and without occupants – using the sophisticated, industrial-grade PM-monitoring equipment. Findings The results revealed that PM levels were very low when rooms were unoccupied or when guests were asleep. However, unhealthy PM mass concentrations were observed in occupied rooms when guests engaged in physical activity such as showering and walking around or while room attendants cleaned rooms. Among the physical activities, room cleaning caused hazardous indoor PM pollution, reaching 1,665.9 µg/m3 of PM10 and 140.4 µg/m3 of PM2.5 although they tended to be brief. Research limitations/implications Leveraging increasing guest demand in well-being is essential for sustainable business and further growth. Indoor air quality must be recognized as an important factor to be controlled for well-being and health of guests and employees. Major hotel brands should take it into consideration as they infuse well-being DNA into their products and culture. Originality/value To the best of the authors’ knowledge, this study is the first empirical investigation of PM pollution both in occupied and unoccupied hotel guestrooms in the USA, which reveals unhealthy PM pollution associated with the routine human activities in occupied guestrooms.


2017 ◽  
Vol 2017 (67) ◽  
pp. 31-37
Author(s):  
O. Turos ◽  
◽  
T. Maremukha ◽  
I. Kobzarenko ◽  
A. Petrosian ◽  
...  

2020 ◽  
Author(s):  
Rıdvan Karacan

<p>Today, production is carried out depending on fossil fuels. Fossil fuels pollute the air as they contain high levels of carbon. Many studies have been carried out on the economic costs of air pollution. However, in the present study, unlike the former ones, economic growth's relationship with the COVID-19 virus in addition to air pollution was examined. The COVID-19 virus, which was initially reported in Wuhan, China in December 2019 and affected the whole world, has caused many cases and deaths. Researchers have been going on studying how the virus is transmitted. Some of these studies suggest that the number of virus-related cases increases in regions with a high level of air pollution. Based on this fact, it is thought that air pollution will increase the number of COVID-19 cases in G7 Countries where industrial production is widespread. Therefore, the negative aspects of economic growth, which currently depends on fossil fuels, is tried to be revealed. The research was carried out for the period between 2000-2019. Panel cointegration test and panel causality analysis were used for the empirical analysis. Particulate matter known as PM2.5[1] was used as an indicator of air pollution. Consequently, a positive long-term relationship has been identified between PM2.5 and economic growth. This relationship also affects the number of COVID-19 cases.</p><p><br></p><p><br></p><p>[1] "Fine particulate matter (PM2.5) is an air pollutant that poses the greatest risk to health globally, affecting more people than any other pollutant (WHO, 2018). Chronic exposure to PM2.5 considerably increases the risk of respiratory and cardiovascular diseases in particular (WHO, 2018). For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator" (OECD.Stat).</p>


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