Effect of air pollution on the total bacteria and pathogenic bacteria in different sizes of particulate matter

Liu, Huan; Xu, Zhao‐Dong; Zhang, Hao; Yao, Xiangwu; Zhou, Meng; Wang, Jiaqi; He, Zhao; Zhang, Huihui; Lou, Liping; Mao, Weihua; Zheng, Ping; Hu, Baolan

doi:10.1016/j.envpol.2017.10.070

Cited by 194 publications

(116 citation statements)

References 55 publications

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“…Xie et al (2018) indicate that total bacteria concentration is higher in moderately polluted air than in clean or heavily polluted air. Liu et al (2018) show that bacterial concentration is low in moderately or heavily pollution in PM 2.5 and PM 10 , whereas the pathogenic bacteria concentration is very high in heavy and moderate pollution. Sun et al (2018) study bacterial community during low and high particulate matter (PM) pollution and find out that predominant species varied with PM concentration.…”

Section: Infected Individuals Inmentioning

confidence: 92%

“…The exposure to pollutants, such as airborne particulate matter and ozone, generates respiratory and cardiovascular diseases with increases in mortality and hospital admissions (cf., Langrish and Mills, 2014). Wei et al (2020) analyze the effect of heavy aerosol pollution in northern Chinacharacterized by high PM 2.5 concentrations and wide geographical coverage that impacts on environmental ecology, climate change and public health (cf., Liu et al, 2017Liu et al, , 2018Jin et al, 2017). The biological components of air pollutants and bio aerosols also include bacteria, viruses, pollens, fungi, and animal/plant fragments (Després et al, 2012;Fröhlich-Nowoisky et al, 2016;Smets et al, 2016).…”

Section: Infected Individuals Inmentioning

confidence: 99%

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Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID

Coccia

2020

Science of The Total Environment

576

568

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This study has two goals. The first is to explain the geo-environmental determinants of the accelerated diffusion of COVID-19 in Italy that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats having accelerated viral infectivity in society. Using data on N=55 Italian province capitals, and data of infected individuals at as of April 7 th , 2020, results reveal that the accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution of cities measured with days exceeding the limits set for PM10 (particulate matter 10 micrometers or less in diameter) or ozone in previous years. In particular, hinterland cities with average higher number of days exceeding the limits set for PM10 (and a low intensity of wind speed) have a very high number of infected people on 7 th April, 2020 (arithmetic mean about 2,200 infected, with average polluted days greater than 80), than coastal cities also having days of exceeding the limits set for PM10 or ozone but with high intensity of wind speed (arithmetic mean about 944.70 infected individuals, with about 60 average polluted days); moreover, cities having more than 100 days of air pollution (exceeding the limits set for PM10), they have a very high average number of infected people (about 3,350 infected individuals, 7 th April 2020), whereas cities having less than 100 days of air pollution, they have a lower average number of infected individuals (about 1014). The findings here also suggest that to minimize the impact of future epidemics similar to COVID-19, the max number of days per year in which Italian provincial capitals can exceed the limits set for PM10 or for ozone, considering their meteorological conditions, is about 48 days. Moreover, results here reveal that the explanatory variable of air pollution in cities under study seems to be a more important predictor in the initial phase of diffusion (on 17 th March 2020, b1 = 1.27, p<0.001) than interpersonal contacts (b2 = 0.31, p<0.05). In the second phase of maturity of the transmission dynamics of COVID-19, air pollution reduces intensity (on 7 th April, 2020 with b'1 = .81, p<0.001) also because of indirect effect of lockdown, whereas coefficient of transmission by interpersonal contacts has stability (b'2 = 0.31, p<0.01). This result reveals that accelerated transmissions dynamics of COVID-19 is due to mainly to the mechanism of "air pollution-to-human transmission" rather than "human-to-human transmission". Overall, then, transmission dynamics of viral infectivity, such as COVID-19, is due to systemic causes: general factors that are the same for all regions (e.g., biological characteristics of virus, incubation period, etc.) and specific factors which are different for each region (e.g., complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity) and health level of individuals (habits, immune system, age, sex, etc.). Lessons learned for COVID-19 in the case study o...

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Section: Infected Individuals Inmentioning

confidence: 92%

Section: Infected Individuals Inmentioning

confidence: 99%

Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID

Coccia

2020

Science of The Total Environment

576

568

View full text Add to dashboard Cite

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“…Xie et al (2018) indicate that total bacteria concentration is higher in moderately polluted air than in clean or heavily polluted air. Liu et al (2018) show that bacterial concentration is low in moderately or heavily pollution in PM2.5 and PM10, whereas the pathogenic bacteria concentration is very high in heavy and moderate pollution. Sun et al (2018) study bacterial community during low and high particulate matter (PM) pollution and find out that predominant species varied with PM concentration.…”

Section: Why Did This Virus Spread So Rapidly In Italy?mentioning

confidence: 93%

“…The exposure to pollutants, such as airborne particulate matter and ozone, generates respiratory and cardiovascular diseases with increases in mortality and hospital admissions (cf., Langrish and Mills, 2014). Wei et al (2020) analyze the effect of heavy aerosol pollution in northern Chinacharacterized by long-duration, high PM2.5 concentrations and wide geographical coverage that impacts on environmental ecology, climate change and public health (cf., Liu et al, 2017Liu et al, , 2018Jin et al, 2017). The biological components of air pollutants and bio aerosols also include bacteria, viruses, pollens, fungi, and animal/plant fragments (Després et al, 2012;Fröhlich-Nowoisky et al, 2016;Smets et al, 2016).…”

Section: Why Did This Virus Spread So Rapidly In Italy?mentioning

confidence: 99%

Two mechanisms for accelerated diffusion of COVID-19 outbreaks in regions with high intensity of population and polluting industrialization: the air pollution-to-human and human-to-human transmission dynamics

Coccia

2020

Preprint

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What is COVID-19? Coronavirus disease 2019 (COVID-19) is viral infection that generates a severe acute respiratory syndrome with serious pneumonia that may result in progressive respiratory failure and death. What are the goals of this investigation? This study explains the geo-environmental determinants of the accelerated diffusion of COVID-19 in Italy that is generating a high level of deaths and suggests general lessons learned for a strategy to cope with future epidemics similar to COVID-19 to reduce viral infectivity and negative impacts in economic systems and society. What are the results of this study? The main results are: o The accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution. o Hinterland cities have average days of exceeding the limits set for PM10 (particulate matter 10 micrometers or less in diameter) equal to 80 days, and an average number of infected more than 2,000 individuals as of April 1st, 2020, coastal cities have days of exceeding the limits set for PM10 equal to 60 days and have about 700 infected in average. o Cities that average number of 125 days exceeding the limits set for PM10, last year, they have an average number of infected individual higher than 3,200 units, whereas cities having less than 100 days (average number of 48 days) exceeding the limits set for PM10, they have an average number of about 900 infected individuals. o The results reveal that accelerated transmission dynamics of COVID-19 in specific environments is due to two mechanisms given by: air pollution-to-human transmission and human-to-human transmission; in particular, the mechanisms of air pollution-to-human transmission play a critical role rather than human-to-human transmission. o The finding here suggests that to minimize future epidemic similar to COVID-19, the max number of days per year in which cities can exceed the limits set for PM10 or for ozone, considering their meteorological condition, is less than 50 days. After this critical threshold, the analytical output here suggests that environmental inconsistencies because of the combination between air pollution and meteorological conditions (with high moisture%, low wind speed and fog) trigger a take-off of viral infectivity (accelerated epidemic diffusion) with damages for health of population, economy and society. What is a socioeconomic strategy to prevent future epidemics similar to COVID-19? Considering the complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity, lessons learned for COVID-19 have to be applied for a proactive socioeconomic strategy to cope with future epidemics, especially an environmental policy based on reduction of air pollution mainly in hinterland zones of countries, having low wind speed, high percentage of moisture and fog that create an environment that can damage immune system of people and foster a fast transmission of viral infectivity similar to the COVID-19. This study must conclude that a strategy to prevent future epidemics similar to COVID 19 has also to be designed in environmental and sustainability science and not only in terms of biology.

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“…And it has been well documented that the air within hospitals or stock farms is highly contaminated with bacteria (Clark et al, 1983;Park et al, 2013;Solomon et al, 2017). Microorganisms are believed to have varying concentration in the ambient air depending on the pollution state (Liu et al, 2018;Zhai et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Comparison of culturable antibiotic-resistant bacteria in polluted and non-polluted air in Beijing, China

Mao

Ding

Wang

et al. 2019

Environment International

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Background: Air pollution has been a serious health issue in Beijing for years. Airborne antibiotic-resistant bacteria could be a potential health crisis as reserve of antibiotic resistance transmission in environment. The composition and antibiotic resistance pattern of culturable bacterial community and how these are affected by air pollution remain unclear.Objectives: This study aimed to compare the compositions and antibiotic resistance patterns of culturable bacteria in polluted and non-polluted weather conditions in Beijing. Methods: Air samples were collected indoors and outdoors during polluted and non-polluted weather using sixstage Andersen Samplers. For each isolated bacterium, the 16S ribosomal RNA gene was amplified, sequenced, and blasted against the National Center for Biotechnology Information database Antibiotic resistance was conducted by antimicrobial susceptibility testing. Results: Bacterial concentration in polluted weather was significantly higher than in non-polluted weather, both indoors and outdoors (P < 0.05). Gram-positive bacteria (GPB) were dominant in both weathers but gramnegative bacteria (GNB) were more abundant in polluted weather than non-polluted weather both indoors and outdoors. Multidrug-resistant (MDR) bacteria occupied 23.7% of all bacterial isolates, 22.4% of isolates from polluted weather and 27.8% of isolates from non-polluted weather. Penicillins were resisted by 72.4% and 83.3% of isolates from polluted and non-polluted weather, respectively. Conclusions: The bacterial concentration was significantly higher in polluted weather, compared to non-polluted weather. Polluted weather is correlated with changes in the bacterial composition in the air, with a greater abundance of GNB. Penicillins was resisted by over 70% of bacterial isolates. The abundance of MDR bacteria suggested potential risks for human health.

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Effect of air pollution on the total bacteria and pathogenic bacteria in different sizes of particulate matter

Cited by 194 publications

References 55 publications

Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID

Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID

Two mechanisms for accelerated diffusion of COVID-19 outbreaks in regions with high intensity of population and polluting industrialization: the air pollution-to-human and human-to-human transmission dynamics

Comparison of culturable antibiotic-resistant bacteria in polluted and non-polluted air in Beijing, China

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