scholarly journals COVID-19 higher induced mortality in Chinese regions with lower air quality

2020 ◽  
Author(s):  
Riccardo Pansini ◽  
Davide Fornacca
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Viral Infections ◽  
The United States ◽  
Global Level ◽  
Population Densities ◽  
Geographical Expansion ◽  
New Form ◽  
Detrimental Impact ◽  
Varying Population

AbstractCOVID-19 has spread in all continents in a span of just over three months, escalating into a pandemic that poses several humanitarian as well as scientific challenges. We here investigated the geographical expansion of the infection and correlate it with the annual indexes of air quality observed from the Sentinel-5 satellite orbiting around China, Italy and the U.S.A. Controlling for population size, we find more viral infections in those areas afflicted by Carbon Monoxide (CO) and Nitrogen Dioxide (NO2). Higher mortality was also correlated with poor air quality, namely with high PM2.5, CO and NO2 values. In Italy, the correspondence between poor air quality and SARS-CoV-2 appearance and induced mortality was the starkest. Similar to smoking, people living in polluted areas are more vulnerable to SARS-CoV-2 infections and induced mortality. This further suggests the detrimental impact climate change will have on the trajectory of future epidemics.SignificanceWe found a significant correlation between levels of air quality and COVID-19 spread and mortality in China, Italy and the United States. Despite the infection being still ongoing at a global level, these correlations are relatively robust not being influenced by varying population densities. Living in an area with low air quality seems to be a risk factor for becoming infected and dying from this new form of coronavirus.

scholarly journals Early evidence of a higher incidence of COVID-19 in the air-polluted regions of eight severely affected countries

2020 ◽  
Author(s):  
Riccardo Pansini ◽  
Davide Fornacca
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Viral Infections ◽  
The United States ◽  
Pm 2.5 ◽  
Po Valley ◽  
European Area ◽  
The United Kingdom ◽  
Early Evidence ◽  
Detrimental Impact

AbstractCOVID-19 has spread in all continents in a span of just over three months, escalating into a pandemic that poses several humanitarian as well as scientific challenges. We here investigated the geographical character of the infection and correlate it with several annual satellite and ground indexes of air quality in: China, the United States, Italy, Iran, France, Spain, Germany, and the United Kingdom. Controlling for population size, we found more viral infections in those areas afflicted by high PM 2.5 and Nitrogen Dioxide values. Higher mortality was also correlated with relatively poor air quality. In Italy, the correspondence between the Po valley pollution and SARS-CoV-2 infections and induced mortality was the starkest, originating right in the most polluted European area. Air pollution appears to be for this disease a risk factor similar to smoking. This suggests the detrimental impact climate change will have on the trajectory of future respiratory epidemics.

scholarly journals COVID-19 higher morbidity and mortality in Chinese regions with lower air quality

2020 ◽  
Author(s):  
Riccardo Pansini ◽  
Davide Fornacca
Keyword(s):  
Air Pollution ◽  
Risk Factor ◽  
Air Quality ◽  
Viral Infections ◽  
List Type ◽  
High Carbon ◽  
Pm 2.5 ◽  
Short Summary ◽  
New Form ◽  
Detrimental Impact

AbstractWe investigated the geographical character of the COVID-19 infection in China and correlated it with satellite- and ground-based measurements of air quality. Controlling for population size, we found more viral infections in those areas afflicted by high Carbon Monoxide, formaldehyde, PM 2.5, and Nitrogen Dioxide values. Higher mortality was also correlated with relatively poor air quality. Air pollution appears to be a risk factor for the incidence of this disease, similar to smoking. This suggests the detrimental impact of air pollution in these types of respiratory epidemics.Short summaryThere is a significant correlation between air pollution and COVID-19 spread and mortality in China.The correlation stands at a second-order administration level, after controlling for varying population densities and removing Wuhan and Hubei from the dataset.Living in an area with low air quality is a risk factor for becoming infected and dying from this new form of coronavirus.

Abstract 36: Mapping and Multilevel Modeling of Climate Change and Air Pollution With Risk of Stroke in the United States and China: Findings From the Drexel-SARI Low Carbon and Healthy City Study

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Longjian Liu ◽  
Hui Liu ◽  
Xuan Yang ◽  
Feng Jia ◽  
Mingquan Wang
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Air Quality ◽  
Pollution Index ◽  
The United States ◽  
Potential Interaction ◽  
Low Carbon ◽  
Multilevel Regression ◽  
Healthy City ◽  
Nationally Representative

Introduction and Hypothesis: Stroke is a leading cause of death and the major cause of disability in the world. However, few studies applied multilevel regression techniques to explore the association of stroke risk with climate change and air pollution. In the study, we aimed to test the hypothesis that the disproportionately distributed stroke rates across the counties and cities within a country are significantly associated with air pollution and temperature. Methods: We used data from U.S. 1118 counties in 49 states, which had estimated measures of particulate matter (PM)2.5 for the years 2010-2013, and data from China 120 cities in 32 provinces (including 4 municipalities), which had measures of Air Pollution Index (API) for the years 2012-2013. We assessed the association between air quality and prevalence of stroke using spatial mapping, autocorrelation and multilevel regression models. Results: Findings from the U.S. show that the highest average PM2.5 level was in July (10.2 μg/m3) and the lowest in October (7.63 μg/m3) for the years 2010-2013. Annual average PM2.5 levels were significantly different across the 1118 counties, and were significantly associated with stroke rates. Multilevel regression analysis indicated that the prevalence of stroke significantly increased by 1.19% for every 10 μg/m3 increase of PM2.5 (p<0.001). Significant variability in PM2.5 by states was observed (p=0.019). More than 70% of the variation in stroke rates existed across the counties (p=0.017) and 18.7% existed across the states (p=0.047). In China, the highest API was observed in the month of December, with a result of 75.76 in 2012 and 97.51 in 2013. The lowest API was observed in July, with a result of 51.21 in 2012, and 54.23 in 2013. Prevalence of stroke was significantly higher in cities with higher API concentrations. The associations between air quality and risk of stroke were significantly mediated by temperatures. Conclusions: The study, using nationally representative data, is one of the first studies to address a positive and complex association between air quality and prevalence of stroke, and a potential interaction effect of temperatures on the air - stroke association.

scholarly journals Strong influence of 2000–2050 climate change on particulate matter in the United States: Results from a new statistical model

2016 ◽  
Author(s):  
Lu Shen ◽  
Loretta J. Mickley ◽  
Lee T. Murray
Keyword(s):  
Climate Change ◽  
United States ◽  
Particulate Matter ◽  
Air Quality ◽  
Statistical Model ◽  
The United States ◽  
Anthropogenic Sources ◽  
Meteorological Variables ◽  
Eastern United States ◽  
Low Cloud

Abstract. We use a statistical model to investigate the effect of 2000–2050 climate change on fine particulate matter (PM2.5) air quality across the contiguous United States. By applying observed relationships of PM2.5 and meteorology to the IPCC Coupled Model Intercomparision Project Phase 5 (CMIP5) archives, we bypass many of the uncertainties inherent in chemistry-climate models. Our approach uses both the relationships between PM2.5 and local meteorology as well as the synoptic circulation patterns, defined as the Singular Value Decomposition (SVD) pattern of the spatial correlations between PM2.5 and meteorological variables in the surrounding region. Using an ensemble of 17 GCMs under the RCP4.5 scenario, we project an increase of ~ 1 μg m−3 in annual mean PM2.5 in the eastern US and a decrease of 0.3–1.2 μg m−3 in the Intermountain West by the 2050s, assuming present-day anthropogenic sources of PM2.5. Mean summertime PM2.5 increases as much as 2–3 μg m−3 in the eastern United States due to faster oxidation rates and greater mass of organic carbon from biogenic emissions. Mean wintertime PM2.5 decreases by 0.3–3 μg m−3 over most regions in United States, likely due to the volatilization of ammonium nitrate. Our approach provides an efficient method to calculate the climate penalty or benefit on air quality across a range of models and scenarios. We find that current atmospheric chemistry models may underestimate or even fail to capture the strongly positive sensitivity of monthly mean PM2.5 to temperature in the eastern United States in summer, and may underestimate future changes in PM2.5 in a warmer climate. In GEOS-Chem, the underestimate in monthly mean PM2.5-temperature relationship in the East in summer is likely caused by overly strong negative sensitivity of monthly mean low cloud fraction to temperature in the assimilated meteorology (~ −0.04 K−1), compared to the weak sensitivity implied by satellite observations (±0.01 K−1). The strong negative dependence of low cloud cover on temperature, in turn, causes the modeled rates of sulfate aqueous oxidation to diminish too rapidly as temperatures rise, leading to the underestimate of sulfate-temperature slopes, especially in the South. Our work underscores the importance of evaluating the sensitivity of PM2.5 to its key controlling meteorological variables in climate-chemistry models on multiple timescales before they are applied to project future air quality.

scholarly journals The potential effects of climate change on air quality across the conterminous U.S. at 2030 under three Representative Concentration Pathways (RCPs)

2018 ◽  
Author(s):  
Christopher G. Nolte ◽  
Tanya L. Spero ◽  
Jared H. Bowden ◽  
Megan S. Mallard ◽  
Patrick D. Dolwick
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Global Climate ◽  
Regional Climate ◽  
The United States ◽  
Historical Period ◽  
Daily Maximum ◽  
Good Representation ◽  
Representative Concentration Pathways ◽  
Concentration Changes

Abstract. The potential impacts of climate change on regional ozone (O3) and fine particulate (PM2.5) air quality in the United States are investigated by downscaling Community Earth System Model (CESM) global climate simulations with the Weather Research and Forecasting (WRF) model, then using the downscaled meteorological fields with the Community Multiscale Air Quality (CMAQ) model. Regional climate and air quality change between 2000 and 2030 under three Representative Concentration Pathways (RCPs) is simulated using 11-year time slices from CESM. The regional climate fields represent historical daily maximum and daily minimum temperatures well, with mean biases less than 2 K for most regions of the U.S. and most seasons of the year and good representation of the variability. Precipitation in the central and eastern U.S. is well simulated for the historical period, with seasonal and annual biases generally less than 25 %, and positive biases in the western U.S. throughout the year and in part of the eastern U.S. during summer. Maximum daily 8-h ozone (MDA8 O3) is projected to increase during summer and autumn in the central and eastern U.S. The increase in summer mean MDA8 O3 is largest under RCP8.5, exceeding 4 ppb in some locations, with smaller seasonal mean increases of up to 2 ppb simulated during autumn and changes during spring generally less than 1 ppb. Increases are magnified at the upper end of the O3 distribution, particularly where projected increases in temperature are greater. Annual average PM2.5 concentration changes range from −1.0 to 1.0 μg m−3. Organic PM2.5 concentrations increase during summer and autumn due to increased biogenic emissions. Decreases in aerosol nitrate occur during winter, accompanied by lesser decreases in ammonium and sulfate, due to warmer temperatures causing increased partitioning to the gas phase. Among meteorological factors examined to account for modeled changes in pollution, temperature and isoprene emissions are found to have the largest changes and the greatest impact on O3 concentrations.

scholarly journals Early Spread of COVID-19 in the Air-Polluted Regions of Eight Severely Affected Countries

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 795
Author(s):  
Riccardo Pansini ◽  
Davide Fornacca
Keyword(s):  
Air Pollution ◽  
Risk Factor ◽  
Air Quality ◽  
Viral Infections ◽  
The United States ◽  
Po Valley ◽  
Pollution Levels ◽  
European Area ◽  
The United Kingdom ◽  
High Risk Factor

COVID-19 escalated into a pandemic posing several humanitarian as well as scientific challenges. We here investigated the geographical character of the early spread of the infection and correlated it with several annual satellite and ground indexes of air quality in China, the United States, Italy, Iran, France, Spain, Germany, and the United Kingdom. The time of the analysis corresponded with the end of the first wave infection in China, namely June 2020. We found more viral infections in those areas afflicted by high PM 2.5 and nitrogen dioxide values. Higher mortality was also correlated with relatively poor air quality. In Italy, the correspondence between the Po Valley pollution and SARS-CoV-2 infections and induced mortality was the starkest, originating right in the most polluted European area. Spain and Germany did not present a noticeable gradient of pollution levels causing non-significant correlations. Densely populated areas were often hotspots of lower air quality levels but were not always correlated with a higher viral incidence. Air pollution has long been recognised as a high risk factor for several respiratory-related diseases and conditions, and it now appears to be a risk factor for COVID-19 as well. As such, air pollution should always be included as a factor for the study of airborne epidemics and further included in public health policies.

scholarly journals The potential effects of climate change on air quality across the conterminous US at 2030 under three Representative Concentration Pathways

2018 ◽  
Vol 18 (20) ◽  
pp. 15471-15489 ◽  
Author(s):  
Christopher G. Nolte ◽  
Tanya L. Spero ◽  
Jared H. Bowden ◽  
Megan S. Mallard ◽  
Patrick D. Dolwick
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Regional Climate ◽  
Regional Scale ◽  
The United States ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Good Representation ◽  
Representative Concentration Pathways ◽  
Concentration Changes

Abstract. The potential impacts of climate change on regional ozone (O3) and fine particulate (PM2.5) air quality in the United States (US) are investigated by linking global climate simulations with regional-scale meteorological and chemical transport models. Regional climate at 2000 and at 2030 under three Representative Concentration Pathways (RCPs) is simulated by using the Weather Research and Forecasting (WRF) model to downscale 11-year time slices from the Community Earth System Model (CESM). The downscaled meteorology is then used with the Community Multiscale Air Quality (CMAQ) model to simulate air quality during each of these 11-year periods. The analysis isolates the future air quality differences arising from climate-driven changes in meteorological parameters and specific natural emissions sources that are strongly influenced by meteorology. Other factors that will affect future air quality, such as anthropogenic air pollutant emissions and chemical boundary conditions, are unchanged across the simulations. The regional climate fields represent historical daily maximum and daily minimum temperatures well, with mean biases of less than 2 K for most regions of the US and most seasons of the year and good representation of variability. Precipitation in the central and eastern US is well simulated for the historical period, with seasonal and annual biases generally less than 25 %, with positive biases exceeding 25 % in the western US throughout the year and in part of the eastern US during summer. Maximum daily 8 h ozone (MDA8 O3) is projected to increase during summer and autumn in the central and eastern US. The increase in summer mean MDA8 O3 is largest under RCP8.5, exceeding 4 ppb in some locations, with smaller seasonal mean increases of up to 2 ppb simulated during autumn and changes during spring generally less than 1 ppb. Increases are magnified at the upper end of the O3 distribution, particularly where projected increases in temperature are greater. Annual average PM2.5 concentration changes range from −1.0 to 1.0 µg m−3. Organic PM2.5 concentrations increase during summer and autumn due to increased biogenic emissions. Aerosol nitrate decreases during winter, accompanied by lesser decreases in ammonium and sulfate, due to warmer temperatures causing increased partitioning to the gas phase. Among meteorological factors examined to account for modeled changes in pollution, temperature and isoprene emissions are found to have the largest changes and the greatest impact on O3 concentrations.

scholarly journals Impacts of future climate change and effects of biogenic emissions on surface ozone and particulate matter concentrations in the United States

2011 ◽  
Vol 11 (10) ◽  
pp. 4789-4806 ◽  
Author(s):  
Y. F. Lam ◽  
J. S. Fu ◽  
S. Wu ◽  
L. J. Mickley
Keyword(s):  
Climate Change ◽  
United States ◽  
Air Quality ◽  
Global Climate Change ◽  
Global Climate ◽  
The United States ◽  
Biogenic Emissions ◽  
Emissions Reduction ◽  
Annual Average ◽  
Future Emissions

Abstract. Simulations of present and future average regional ozone and PM2.5 concentrations over the United States were performed to investigate the potential impacts of global climate change and emissions on regional air quality using CMAQ. Various emissions and climate conditions with different biogenic emissions and domain resolutions were implemented to study the sensitivity of future air quality trends from the impacts of changing biogenic emissions. A comparison of GEOS-Chem and CMAQ was performed to investigate the effect of downscaling on the prediction of future air quality trends. For ozone, the impacts of global climate change are relatively smaller when compared to the impacts of anticipated future emissions reduction, except for the Northeast area, where increasing biogenic emissions due to climate change have stronger positive effects (increases) to the regional ozone air quality. The combination effect from both climate change and emission reductions leads to approximately a 10 % or 5 ppbv decrease of the maximum daily average eight-hour ozone (MDA8) over the Eastern United States. For PM2.5, the impacts of global climate change have shown insignificant effect, where as the impacts of anticipated future emissions reduction account for the majority of overall PM2.5 reductions. The annual average 24-h PM2.5 of the future-year condition was found to be about 40 % lower than the one from the present-year condition, of which 60 % of its overall reductions are contributed to by the decrease of SO4 and NO3 particulate matters. Changing the biogenic emissions model increases the MDA8 ozone by about 5–10 % or 3–5 ppbv in the Northeast area. Conversely, it reduces the annual average PM2.5 by 5 % or 1.0 μg m−3 in the Southeast region.

scholarly journals Influence of 2000–2050 climate change on particulate matter in the United States: results from a new statistical model

2017 ◽  
Vol 17 (6) ◽  
pp. 4355-4367 ◽  
Author(s):  
Lu Shen ◽  
Loretta J. Mickley ◽  
Lee T. Murray
Keyword(s):  
Climate Change ◽  
United States ◽  
Particulate Matter ◽  
Air Quality ◽  
Statistical Model ◽  
Climate Models ◽  
The United States ◽  
Meteorological Variables ◽  
Eastern United States ◽  
Low Cloud

Abstract. We use a statistical model to investigate the effect of 2000–2050 climate change on fine particulate matter (PM2. 5) air quality across the contiguous United States. By applying observed relationships of PM2. 5 and meteorology to the IPCC Coupled Model Intercomparision Project Phase 5 (CMIP5) archives, we bypass some of the uncertainties inherent in chemistry-climate models. Our approach uses both the relationships between PM2. 5 and local meteorology as well as the synoptic circulation patterns, defined as the singular value decomposition (SVD) pattern of the spatial correlations between PM2. 5 and meteorological variables in the surrounding region. Using an ensemble of 19 global climate models (GCMs) under the RCP4.5 scenario, we project an increase of 0.4–1.4 µg m−3 in annual mean PM2. 5 in the eastern US and a decrease of 0.3–1.2 µg m−3 in the Intermountain West by the 2050s, assuming present-day anthropogenic sources of PM2. 5. Mean summertime PM2. 5 increases as much as 2–3 µg m−3 in the eastern United States due to faster oxidation rates and greater mass of organic aerosols from biogenic emissions. Mean wintertime PM2. 5 decreases by 0.3–3 µg m−3 over most regions in the United States, likely due to the volatilization of ammonium nitrate. Our approach provides an efficient method to calculate the potential climate penalty on air quality across a range of models and scenarios. We find that current atmospheric chemistry models may underestimate or even fail to capture the strongly positive sensitivity of monthly mean PM2. 5 to temperature in the eastern United States in summer, and they may underestimate future changes in PM2. 5 in a warmer climate. In GEOS-Chem, the underestimate in monthly mean PM2. 5–temperature relationship in the east in summer is likely caused by overly strong negative sensitivity of monthly mean low cloud fraction to temperature in the assimilated meteorology ( ∼  −0.04 K−1) compared to the weak sensitivity implied by satellite observations (±0.01 K−1). The strong negative dependence of low cloud cover on temperature in turn causes the modeled rates of sulfate aqueous oxidation to diminish too rapidly as temperatures rise, leading to the underestimate of sulfate–temperature slopes, especially in the south. Our work underscores the importance of evaluating the sensitivity of PM2. 5 to its key controlling meteorological variables in climate-chemistry models on multiple timescales before they are applied to project future air quality.

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