scholarly journals Changes in the concentration of air pollutants before and after the COVID-19 blockade period and their correlation with vegetation coverage

2021 ◽  
Author(s):  
Manguo Zhou ◽  
Yanguo Huang ◽  
Guilan Li
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Vegetation Index ◽  
Pearson Correlation ◽  
Air Pollutant ◽  
Atmospheric Environment ◽  
Vegetation Coverage ◽  
Time Space ◽  
Climatic Environment ◽  
The Impact

AbstractIn order to control the spread of COVID-19, China had implemented strict lockdown measures. The closure of cities had had a huge impact on human production and consumption activities, which had greatly reduced population mobility. This article used air pollutant data from 341 cities in mainland China and divided these cities into seven major regions based on geographic conditions and climatic environment. The impact of urban blockade on air quality during COVID-19 was studied from the perspectives of time, space, and season. In addition, this article used Normalized Difference Vegetation Index (NDVI) to systematically analyze the characteristics of air pollution in the country and used the Pearson correlation coefficient to explore the relationship between NDVI and the air pollutant concentrations during the COVID-19 period. Then, linear regression was used to find the quantitative relationship between NDVI and AQI, and the fitting effect of the model was found to be significant through t test. Finally, some countermeasures were proposed based on the analysis results, and suggestions were provided for improving air quality. This paper has drawn the following conclusions: (1) the concentration of pollutants varied greatly in different regions, and the causes of their pollution sources were also different. The region with the largest decline in AQI was the Northeast China (60.01%), while the AQI in the southwest China had the smallest change range, and its value had increased by 1.72%. In addition, after the implementation of the city blockade, the concentration of NO2 in different regions dropped the most, but the increase in O3 was more obvious. (2) Higher vegetation coverage would have a beneficial impact on the atmospheric environment. Areas with higher NDVI values have relatively low AQI. There is a negative correlation between NDVI and AQI, and an average increase of 0.1 in NDVI will reduce AQI by 3.75 (95% confidence interval). In the case of less human intervention, the higher the vegetation coverage, the lower the local pollutant concentration will be. Therefore, the degree of vegetation coverage would have a direct or indirect impact on air pollution.

scholarly journals Gender Differences in Association between Air Pollution and Daily Mortality in the Capital of the Green Lungs of Poland–Population-Based Study with 2,953,000 Person-Years of Follow-Up

2020 ◽  
Vol 9 (8) ◽  
pp. 2351
Author(s):  
Łukasz Kuźma ◽  
Krzysztof Struniawski ◽  
Szymon Pogorzelski ◽  
Hanna Bachórzewska-Gajewska ◽  
Sławomir Dobrzycki
Keyword(s):  
Public Health ◽  
Gender Differences ◽  
Air Pollution ◽  
Air Quality ◽  
Air Pollutant ◽  
World Health ◽  
The European Union ◽  
Daily Mortality ◽  
Male Population ◽  
The Impact

(1) Introduction: air pollution is considered to be one of the main risk factors for public health. According to the European Environment Agency (EEA), air pollution contributes to the premature deaths of approximately 500,000 citizens of the European Union (EU), including almost 5000 inhabitants of Poland every year. (2) Purpose: to assess the gender differences in the impact of air pollution on the mortality in the population of the city of Bialystok—the capital of the Green Lungs of Poland. (3) Materials and Methods: based on the data from the Central Statistical Office, the number—and causes of death—of Białystok residents in the period 2008–2017 were analyzed. The study utilized the data recorded by the Provincial Inspectorate for Environmental Protection station and the Institute of Meteorology and Water Management during the analysis period. Time series regression with Poisson distribution was used in statistical analysis. (4) Results: A total of 34,005 deaths had been recorded, in which women accounted for 47.5%. The proportion of cardiovascular-related deaths was 48% (n = 16,370). An increase of SO2 concentration by 1-µg/m3 (relative risk (RR) 1.07, 95% confidence interval (CI) 1.02–1.12; p = 0.005) and a 10 °C decrease of temperature (RR 1.03, 95% CI 1.01–1.05; p = 0.005) were related to an increase in the number of daily deaths. No gender differences in the impact of air pollution on mortality were observed. In the analysis of the subgroup of cardiovascular deaths, the main pollutant that was found to have an effect on daily mortality was particulate matter with a diameter of 2.5 μm or less (PM2.5); the RR for 10-µg/m3 increase of PM2.5 was 1.07 (95% CI 1.02–1.12; p = 0.01), and this effect was noted only in the male population. (5) Conclusions: air quality and atmospheric conditions had an impact on the mortality of Bialystok residents. The main air pollutant that influenced the mortality rate was SO2, and there were no gender differences in the impact of this pollutant. In the male population, an increased exposure to PM2.5 concentration was associated with significantly higher cardiovascular mortality. These findings suggest that improving air quality, in particular, even with lower SO2 levels than currently allowed by the World Health Organization (WHO) guidelines, may benefit public health. Further studies on this topic are needed, but our results bring questions whether the recommendations concerning acceptable concentrations of air pollutants should be stricter, or is there a safe concentration of SO2 in the air at all.

scholarly journals Investigating the impacts of air quality and weather indicators on the spread of SARS-COV-2 in Istanbul, Turkey

2021 ◽  
pp. 71-71
Author(s):  
Caner Taniş ◽  
Kadir Karakaya
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Meteorological Parameters ◽  
Positive Impact ◽  
Pearson Correlation ◽  
Quality Data ◽  
Hospital Discharges ◽  
Weather Parameters ◽  
The Impact ◽  
Quality Indexes

Background/aim: Air pollution is having a positive impact on the spread of the SARS-COV-2 virus. The effects of meteorological parameters on the spread of SARS-COV-2 are a matter of curiosity. The main purpose of this paper is to determine the association between air quality indexes (PM2.5, PM10, NO2, SO2, CO, and O3) and weather parameters (temperature, humidity, pressure, dew, wind speed) with the number of SARS-COV-2 cases, hospitalizations, hospital discharges. In this paper, we also focused on determining the impact of air pollution and weather parameters on the number of daily hospitalizations and daily discharges. Materials and methods: It is gleaned daily cases, hospitalizations, hospital discharges, meteorological, and air quality data in Istanbul from Turkey between July 15, 2020, and September 30, 2020. We performed the Pearson correlation analysis to evaluate the effects of meteorological parameters and air quality indexes on the variables related to SARS-COV-2. Results: It is determined a statistically significant positive relationship between air quality indexes such as CO, SO2, PM2.5, PM10, NO2, and the number of daily confirmed SARS-COV-2 cases. We also observed a negative association between weather parameters such as temperature and pressure and the number of daily confirmed SARS-COV-2 cases. Conclusion: Our study proposes that high air quality could reduce the number of SARS-COV-2 cases. The empirical findings of this paper might provide key input to prevent the spread of SARS-COV-2 across Turkey.

The Impact of Building Tianfu New Area on Chengdu City Air Quality

2013 ◽  
Vol 726-731 ◽  
pp. 1396-1399 ◽  
Author(s):  
Ping Liu ◽  
Hong Ling Guo
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Positive Measure ◽  
Air Pollutant ◽  
The Government ◽  
And Control ◽  
The Impact

This study analyzed the impact of building Tianfu new area in Sichuan on Chengdu city air quality. The paper insists the characteristics of terrain and climate in Tianfu new area lead to the difficult to convect and diffuse air pollutant, and the trend of air quality deteriorating has already emerged as the activities of a large number of industries and population. Absolutely ,building Tianfu new area will further aggravate this trend. And the paper suggests the government should take positive measure in management and policy to prevent and control air pollution.

scholarly journals European atmosphere in 2050, a regional air quality and climate perspective under CMIP5 scenarios

2013 ◽  
Vol 13 (15) ◽  
pp. 7451-7471 ◽  
Author(s):  
A. Colette ◽  
B. Bessagnet ◽  
R. Vautard ◽  
S. Szopa ◽  
S. Rao ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Air Quality ◽  
Regional Scale ◽  
Air Pollutant ◽  
External Factors ◽  
Pollutant Emissions ◽  
Reference Scenario ◽  
Regional Air Quality ◽  
The Impact

Abstract. To quantify changes in air pollution over Europe at the 2050 horizon, we designed a comprehensive modelling system that captures the external factors considered to be most relevant, and that relies on up-to-date and consistent sets of air pollution and climate policy scenarios. Global and regional climate as well as global chemistry simulations are based on the recent representative concentration pathways (RCP) produced for the Fifth Assessment Report (AR5) of the IPCC (Intergovernmental Panel on Climate Change) whereas regional air quality modelling is based on the updated emissions scenarios produced in the framework of the Global Energy Assessment. We explored two diverse scenarios: a reference scenario where climate policies are absent and a mitigation scenario which limits global temperature rise to within 2 °C by the end of this century. This first assessment of projected air quality and climate at the regional scale based on CMIP5 (5th Coupled Model Intercomparison Project) climate simulations is in line with the existing literature using CMIP3. The discrepancy between air quality simulations obtained with a climate model or with meteorological reanalyses is pointed out. Sensitivity simulations show that the main factor driving future air quality projections is air pollutant emissions, rather than climate change or intercontinental transport of pollution. Whereas the well documented "climate penalty" that weights upon ozone (increase of ozone pollution with global warming) over Europe is confirmed, other features appear less robust compared to the literature, such as the impact of climate on PM2.5. The quantitative disentangling of external factors shows that, while several published studies focused on the climate penalty bearing upon ozone, the contribution of the global ozone burden is somewhat overlooked in the literature.

scholarly journals European atmosphere in 2050, a regional air quality and climate perspective under CMIP5 scenarios

2013 ◽  
Vol 13 (3) ◽  
pp. 6455-6499 ◽  
Author(s):  
A. Colette ◽  
B. Bessagnet ◽  
R. Vautard ◽  
S. Szopa ◽  
S. Rao ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Scale ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Reference Scenario ◽  
Regional Air Quality ◽  
The Impact

Abstract. To quantify changes in air pollution in Europe at the 2050 horizon, we designed a comprehensive modelling system that captures the external factors considered to be most relevant and relies on up-to-date and consistent sets of air pollution and climate policy scenarios. Global and regional climate as well as global chemistry simulations are based on the recent Representative Concentrations Pathways (RCP) produced for the Fifth Assessment Report (AR5) of IPCC whereas regional air quality modelling is based on the updated emissions scenarios produced in the framework of the Global Energy Assessment. We explored two diverse scenarios: a reference scenario where climate policies are absent and a mitigation scenario which limits global temperature rise to within 2 °C by the end of this century. This first assessment of projected air quality and climate at the regional scale based on CMIP5 (5th Climate Model Intercomparison Project) climate simulations is in line with the existing literature using CMIP3. The discrepancy between air quality simulations obtained with a climate model or with meteorological reanalyses is pointed out. Sensitivity simulations show that the main factor driving future air quality projections is air pollutant emissions, rather than climate change or long range transport. Whereas the well documented "climate penalty" bearing upon ozone over Europe is confirmed, other features appear less robust compared to the literature: such as the impact of climate on PM2.5. The quantitative disentangling of each contributing factor shows that the magnitude of the ozone climate penalty has been overstated in the past while on the contrary the contribution of the global ozone burden is overlooked in the literature.

scholarly journals Study of the Effects of Air Pollutants on Human Health Based on Baidu Indices of Disease Symptoms and Air Quality Monitoring Data in Beijing, China

2019 ◽  
Vol 16 (6) ◽  
pp. 1014 ◽  
Author(s):  
Shaobo Zhong ◽  
Zhichen Yu ◽  
Wei Zhu
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Human Health ◽  
Air Pollutants ◽  
Pearson Correlation ◽  
Additive Model ◽  
Health Impact ◽  
Cerebrovascular Diseases ◽  
Relative Risks ◽  
The Impact

There is an increasing body of evidence showing the impact of air pollutants on human health such as on the respiratory, and cardio- and cerebrovascular systems. In China, as people begin to pay more attention to air quality, recent research focused on the quantitative assessment of the effects of air pollutants on human health. To assess the health effects of air pollutants and to construct an indicator placing emphasis on health impact, a generalized additive model was selected to assess the health burden caused by air pollution. We obtained Baidu indices (an evaluation indicator launched by Baidu Corporation to reflect the search popularity of keywords from its search engine) to assess daily query frequencies of 25 keywords considered associated with air pollution-related diseases. Moreover, we also calculated the daily concentrations of major air pollutants (including PM10, PM2.5, SO2, O3, NO2, and CO) and the daily air quality index (AQI) values, and three meteorological factors: daily mean wind level, daily mean air temperature, and daily mean relative humidity. These data cover the area of Beijing from 1 March 2015 to 30 April 2017. Through the analysis, we produced the relative risks (RRs) of the six main air pollutants for respiratory, and cardio- and cerebrovascular diseases. The results showed that O3 and NO2 have the highest health impact, followed by PM10 and PM2.5. The effects of any pollutant on cardiovascular diseases was consistently higher than on respiratory diseases. Furthermore, we evaluated the currently used AQI in China and proposed an RR-based index (health AQI, HAQI) that is intended for better indicating the effects of air pollutants on respiratory, and cardio- and cerebrovascular diseases than AQI. A higher Pearson correlation coefficient between HAQI and RRTotal than that between AQI and RRTotal endorsed our efforts.

scholarly journals Is Compact Urban Form Good for Air Quality? A Case Study from China Based on Hourly Smartphone Data

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 504
Author(s):  
Man Yuan ◽  
Mingrui Yan ◽  
Zhuoran Shan
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Form ◽  
Urban Areas ◽  
Census Data ◽  
Population Distribution ◽  
Pearson Correlation ◽  
Air Pollutant ◽  
Compact Development ◽  
Pollution Exposure

In previous studies, planners have debated extensively whether compact development can improve air quality in urban areas. Most of them estimated pollution exposure with stationary census data that linked exposures solely to residential locations, therefore overlooking residents’ space–time inhalation of air pollutants. In this study, we conducted an air pollution exposure assessment by scrutinizing one-hour resolution population distribution maps derived from hourly smartphone data and air pollutant concentrations derived from inverse distance weighted interpolation. We selected Wuhan as the study area and used Pearson correlation analysis to explore the effect of compactness on population-weighted concentrations. The results showed that even if a compact urban form helps to reduce pollution concentrations by decreasing vehicle traveling miles and tailpipe emissions, higher levels of building density and floor area ratios may increase population-weighted exposure. With regard to downtown areas with high population density, compact development may locate more people in areas with excessive air pollution. In all, reducing density in urban public centers and developing a polycentric urban structure may aid in the improvement of air quality in cities with compact urban forms.

scholarly journals Using proxies to explore ensemble uncertainty in climate impact studies: the example of air pollution

2015 ◽  
Vol 15 (20) ◽  
pp. 28361-28393
Author(s):  
V. E. P. Lemaire ◽  
A. Colette ◽  
L. Menut
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Eastern Europe ◽  
Climate Model ◽  
Climate Impact ◽  
Northern Italy ◽  
Air Pollutant ◽  
Mitigation Measures ◽  
Training Dataset ◽  
The Impact

Abstract. Because of its sensitivity to unfavorable weather patterns, air pollution is sensitive to climate change so that, in the future, a climate penalty could jeopardize the expected efficiency of air pollution mitigation measures. A common method to assess the impact of climate on air quality consists in implementing chemistry-transport models forced by climate projection. However, the computing cost of such method requires optimizing ensemble exploration techniques. By using a training dataset of deterministic projection of climate and air quality over Europe, we identified the main meteorological drivers of air quality for 8 regions in Europe and developed simple statistical models that could be used to predict air pollutant concentrations. The evolution of the key climate variables driving either particulate or gaseous pollution allows concluding on the robustness of the climate impact on air quality. The climate benefit for PM2.5 was confirmed −0.96 (±0.18), −1.00 (±0.37), −1.16 ± (0.23) μg m−3, for resp. Eastern Europe, Mid Europe and Northern Italy and for the Eastern Europe, France, Iberian Peninsula, Mid Europe and Northern Italy regions a climate penalty on ozone was identified 10.11 (±3.22), 8.23 (±2.06), 9.23 (±1.13), 6.41 (±2.14), 7.43 (±2.02) μg m−3. This technique also allows selecting a subset of relevant regional climate model members that should be used in priority for future deterministic projections.

scholarly journals Measured and modelled air quality trends in Italy over the period 2003–2010

2021 ◽  
Vol 21 (13) ◽  
pp. 10825-10849
Author(s):  
Ilaria D'Elia ◽  
Gino Briganti ◽  
Lina Vitali ◽  
Antonio Piersanti ◽  
Gaia Righini ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Transport Model ◽  
Statistical Significance ◽  
Average Concentration ◽  
Air Pollutant ◽  
Chemical Transport Model ◽  
Spatial Coverage ◽  
Significant Downward Trend ◽  
The Impact

Abstract. Air pollution harms human health and the environment. Several regulatory efforts and different actions have been taken in the last decades by authorities. Air quality trend analysis represents a valid tool in assessing the impact of these actions taken both at national and local levels. This paper presents for the first time the capability of the Italian national chemical transport model, AMS-MINNI, in capturing the observed concentration trends of three air pollutants – NO2, inhalable particles having diameter less than 10 µm (PM10), and O3 – in Italy over the period 2003–2010. We firstly analyse the model performance finding it in line with the state of the art of regional air quality modelling. The modelled trends result in a general significant downward trend for the three pollutants and, in comparison with observations, the values of the simulated trends were of a similar magnitude for NO2 (in the range −3.0 to −0.5 µg m−3 yr−1), while a smaller range of trends was found than those observed for PM10 (−1.5 to −0.5 µg m−3 yr−1) and O3 maximum daily 8 h average concentration (−2.0 to −0.5 µg m−3 yr−1). As a general result, we find good agreement between modelled and observed trends; moreover, the model provides a greater spatial coverage and statistical significance of pollutant concentration trends with respect to observations, in particular for NO2. We also conduct a qualitative attempt to correlate the temporal concentration trends to meteorological and emission variability. Since no clear tendency in yearly meteorological anomalies (temperature, precipitation, geopotential height) was observed for the period investigated, we focus the discussion of concentration trends on emission variations. We point out that, due to the complex links between precursor emissions and air pollutant concentrations, emission reductions do not always result in a corresponding decrease in atmospheric concentrations, especially for those pollutants that are formed in the atmosphere such as O3 and the major fraction of PM10. These complex phenomena are still uncertain and their understanding is of the utmost importance in planning future policies for reducing air pollution and its impacts on health and ecosystems.

Abstract 13654: Air Pollution, Environmental Greenness, and Total Cardiovascular Disease Mortality

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
William W Aitken ◽  
Kefeng Wang ◽  
Abraham Parrish ◽  
Diego Celli ◽  
Joanna Lombard ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Air Pollution ◽  
Air Quality ◽  
Mediation Analysis ◽  
Vegetation Index ◽  
The United States ◽  
Death Rates ◽  
The Impact ◽  
The Relationship ◽  
Cvd Mortality

Introduction: Air quality is a major environmental determinant of health. Environmental greenness – a measure of vegetative presence – has been associated with reduced risk of cardiovascular disease. However, the impact of greenness on the relationship between air pollution and cardiovascular disease (CVD) has been less studied. Hypothesis: Environmental greenness is associated with reduced total CVD mortality and mediates some of the relationship between air pollution and CVD mortality. Methods: The Centers for Disease Control and Prevention Interactive Atlas of Heart Disease provided national CVD death rates, Environmental Protection Agency air quality measurements (particulate matter PM2.5), and Census sociodemographic information (age, race, education, and income) by county across the United States. These data were matched to mean county normalized difference vegetation index (NDVI) derived from National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m spatial resolution data. Linear regression modeling estimated the relationship between air pollution and greenness on CVD mortality using SAS version 9.4 software. Mediation analysis of greenness on the relationship between air pollution and CVD mortality was then conducted. Results: Ambient concentration of PM2.5 ranged from 3 to 19.7 μg/m3 with a mean of 9 μg/m3 ± 1.9 μg/m3 and NDVI ranged from 0.00 to 0.80 with mean of 0.41 ± 0.13. For every 0.1-unit increase in NDVI, CVD mortality decreased by 13.2 deaths per 100,000 adults (p = 0.0001). For every 1 μg/m3 increase in PM2.5, CVD mortality increased by 38.8 deaths per 100,000 adults (p < 0.0001). Mediation analysis suggests that NDVI is a statistically significant mediator of the PM2.5 to CVD mortality relationship, with NDVI explaining 4.3% of this relationship (p=0.0009). Conclusions: Our analysis of air quality, environmental greenness, and CVD death rates demonstrates that greenness is independently associated with reduced CVD morality and also mediates the relationship between air pollution and CVD mortality. The evidence suggests that environmental interventions to increase greenness and reduce air pollution may reduce excess cardiovascular mortality.

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