scholarly journals Population Aging Can Aggravate Air Pollution: Evidence from China

2018 ◽  
Vol 11 (2) ◽  
pp. 41
Author(s):  
Hui Shi
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Technological Innovation ◽  
Positive Impact ◽  
Population Aging ◽  
Household Consumption ◽  
Policy Recommendations ◽  
Fossil Energy ◽  
The Impact ◽  
The Relationship

Population, resources and environment have always attracted much attention from the society. Nowadays, pollution and population aging are urgent problems to be solved in China, and many scholars have found a strong correlation between pollution and aging. This paper constructs a KAYA model with aging variables, making an empirical analysis of the relationship between population aging and air pollution based on the panel data of 82 cities in China from 2011 to 2016. We found that population aging has a significant and positive impact on air pollution. 1% change of the population aging will lead to a 0.203% change in AQI. The deepening of China’s aging level will lead to ineffective improvement of air quality and even lead to more serious air pollution. Then we make the further analysis of the impact mechanism of population aging on air quality, the results show that population aging could have a positive impact on air pollution by improving labor productivity, promoting technological innovation, increasing fossil energy consumption and the household consumption, and changing the structure of household consumption. At last, in order to improve the air pollution under the background of population aging, we put forward the policy recommendations according to the conclusion of this paper.

scholarly journals The impact of air quality on its Baidu index: grey model analysis

2021 ◽  
Author(s):  
Leping Tu ◽  
Yan Chen
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Quality Index ◽  
Air Quality Index ◽  
Grey Correlation ◽  
Convolution Model ◽  
Grey Correlation Analysis ◽  
And Control ◽  
The Impact ◽  
The Relationship

Abstract To investigate the relationship between air quality and its Baidu index, we collect the annual Baidu index of air pollution hazards, causes and responses. Grey correlation analysis, particle swarm optimization and grey multivariate convolution model are used to simulate and forecast the comprehensive air quality index. The result shows that the excessive growth of the comprehensive air quality index will lead to an increase in the corresponding Baidu index. The number of search for the causes of air quality has the closest link with the comprehensive air quality index. Strengthening the awareness of public about air pollution is conducive to the improvement of air quality. The result provides a reference for relevant departments to prevent and control air pollution.

scholarly journals Evaluation of the impact of meteorological conditions on the amount of air pollution in Krakow

2019 ◽  
Vol 108 ◽  
pp. 02012
Author(s):  
Małgorzata Piaskowska-Silarska ◽  
Krzysztof Pytel ◽  
Stanisław Gumuła ◽  
Wiktor Hudy
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Measurement Data ◽  
Ecological Monitoring ◽  
Meteorological Conditions ◽  
Pollution Problem ◽  
Air Quality Improvement ◽  
Meteorological Elements ◽  
The Impact ◽  
The Relationship

Abstract. The publication presents an assessment of the impact of meteorological conditions on air quality in a given location. The subject matter of the work is related to problem-review issues in the field of environmental protection and energy management. The publication draws attention to the fact that despite several decades of ecological monitoring of air pollution, only in recent years attention has been paid to the scale of air pollution problem. The study examined the relationship between meteorological elements (wind velocity, relative humidity on the amount of air pollution immissions. Significant impact of precipitation, atmospheric pressure and thermal braking layer was indicated. The possibilities of air quality improvement were presented based on the measurement data concerning the immission of impurities.

Air Pollution and Seasonality Effects on Mode Choice in China

2017 ◽  
Vol 2634 (1) ◽  
pp. 101-109 ◽  
Author(s):  
Weibo Li ◽  
Maria Kamargianni
Keyword(s):  
Air Pollution ◽  
Developing Countries ◽  
Air Quality ◽  
Positive Impact ◽  
Mode Choice ◽  
Urban Transport ◽  
Modal Shift ◽  
Pollution Levels ◽  
Study Results ◽  
The Impact

A modal shift from motorized to nonmotorized vehicles is imperative to reduce air pollution in developing countries. Nevertheless, whether better air quality will improve the willingness to use nonmotorized transport remains unclear. If such a reciprocal effect could be identified, a sort of virtuous circle could be created (i.e., better air quality could result in higher nonmotorized transport demand, which in turn could further reduce air pollution). Developing countries may, therefore, be more incentivized to work on air pollution reduction from other sources to exploit the extra gains in urban transport. This study investigated the impact of air pollution on mode choices and whether nonmotorized transport was preferred when air quality was better. Revealed preference data about the mode choice behavior of the same individuals was collected during two seasons (summer and winter) with different air pollution levels. Two discrete mode choice models were developed (one for each season) to quantify and compare the impacts of different air pollution levels on mode choices. Trip and socioeconomic characteristics also were included in the model to identify changes in their impacts across seasons. Taiyuan, a Chinese city that operates a successful bikesharing scheme, was selected for a case study. The study results showed that air quality improvement had a significant, positive impact on nonmotorized transport use, which suggested that improvements in air quality and promotion of nonmotorized transport must be undertaken simultaneously because of their interdependence. The results of the study could act as a harbinger to policy makers and encourage them to design measures and policies that lead to sustainable travel behavior.

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.

scholarly journals The Impact of Innovation Investment Volatility on Technological Innovation of Enterprises in Different Life Cycles

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Miaomiao Li ◽  
Zhaoxing Hao ◽  
Meng Luan ◽  
Haibo Li ◽  
Guikun Cao
Keyword(s):  
Technological Innovation ◽  
Positive Impact ◽  
Punctuated Equilibrium ◽  
Life Cycles ◽  
Moderating Effect ◽  
Mature Stage ◽  
Punctuated Equilibrium Theory ◽  
Emerging Industries ◽  
The Impact ◽  
The Relationship

Empirical findings from the impact of innovation investment volatility on enterprise technological innovation are mixed. Based on the punctuated equilibrium theory, this study explores the impact of innovation investment volatility on enterprise technological innovation in different life cycles and whether innovation subsidy has expected effects on enterprises’ technological innovation. By using the 205 Chinese listed enterprises in strategic emerging industries from 2010 to 2019 as the research sample, the results show that the innovation investment volatility has a positive impact on technological innovation of enterprise in the growing stage, while it has no significant effect on enterprise technological innovation in the mature and declining stages. In addition, the negative moderating effect of innovation subsidy on the relationship between innovation investment volatility and technological innovation is the most significant for enterprises in the growing stage, weakly significant for enterprises in the mature stage, and insignificant for enterprises in the declining stage.

scholarly journals The Effect of Unemployment Rate on the Gross Domestic Product in Nigeria (A Bayesian Approach)

2021 ◽  
Author(s):  
Victor Agboli
Keyword(s):  
Economic Growth ◽  
Regression Analysis ◽  
Gross Domestic Product ◽  
Positive Impact ◽  
Linear Regression Analysis ◽  
Domestic Product ◽  
Policy Recommendations ◽  
Bayesian Linear Regression ◽  
The Impact ◽  
The Relationship

This study investigates the impact of unemployment on the Gross Domestic Product (GDP) of Nigeria for a period of 28 years (1990-2018). The study focuses on the relationship between unemployment and economic growth in Nigeria (GDP). The method used in this study is the Bayesian Linear Regression Analysis, the major findings were that unemployment has a positive impact on the economic growth of Nigeria. Some suggestions and policy recommendations were made based on the findings.

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.

scholarly journals How Does Environmental Regulation Affect the Relationship between FDI and Technological Innovation: From the Perspective of Technology Transactions

Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1264
Author(s):  
Meng Zeng ◽  
Lihang Liu ◽  
Fangyi Zhou ◽  
Yigui Xiao
Keyword(s):  
Environmental Regulation ◽  
Technological Innovation ◽  
Pollutant Emissions ◽  
Regulatory Effect ◽  
Host Countries ◽  
Regional Heterogeneity ◽  
Industrial Sectors ◽  
Reduction Effect ◽  
The Impact ◽  
The Relationship

Many studies have found that FDI can reduce the pollutant emissions of host countries. At the same time, the intensity of environmental regulation would affect the emission reduction effect of FDI in the host country. This study aims to reveal the internal mechanisms of this effect. Specifically, this paper studies the impact of FDI on technological innovation in China’s industrial sectors from the perspective of technology transactions from 2001 to 2019, and then analyzes whether the intensity of environmental regulation can promote the relationship. Results indicate that FDI promotes technological innovation through technology transactions. In addition, it finds that the intensity of environmental regulation significantly positively moderates the relationship between FDI and technological innovation, which is achieved by positively moderating the FDI–technology transaction relationship. Regional heterogeneity analysis is further conducted, and results show that in the eastern and western regions of China, FDI can stimulate technological innovation within regional industrial sectors through technology trading. Moreover, environmental regulation has a significant positive regulatory effect on the above relationship, but these effects are not supported by evidence in the central region of China.

scholarly journals The modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rui Zhang ◽  
Yujie Meng ◽  
Hejia Song ◽  
Ran Niu ◽  
Yu Wang ◽  
...  
Keyword(s):  
Air Pollution ◽  
High Temperature ◽  
Air Pollutants ◽  
Meteorological Data ◽  
Effect Of Temperature ◽  
Distributed Lag ◽  
Modification Effect ◽  
Incidence Risk ◽  
The Impact ◽  
The Relationship

Abstract Background Although exposure to air pollution has been linked to many health issues, few studies have quantified the modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China. Methods The data of daily incidence of influenza and the relevant meteorological data and air pollution data in Ningbo from 2014 to 2017 were retrieved. Low, medium and high temperature layers were stratified by the daily mean temperature with 25th and 75th percentiles. The potential modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo was investigated through analyzing the effects of air pollutants stratified by temperature stratum using distributed lag non-linear model (DLNM). Stratified analysis by sex and age were also conducted. Results Overall, a 10 μg/m3 increment of O3, PM2.5, PM10 and NO2 could increase the incidence risk of influenza with the cumulative relative risk of 1.028 (95% CI 1.007, 1.050), 1.061 (95% CI 1.004, 1.122), 1.043 (95% CI 1.003, 1.085), and 1.118 (95% CI 1.028, 1.216), respectively. Male and aged 7–17 years were more sensitive to air pollutants. Through the temperature stratification analysis, we found that temperature could modify the impacts of air pollution on daily incidence of influenza with high temperature exacerbating the impact of air pollutants. At high temperature layer, male and the groups aged 0–6 years and 18–64 years were more sensitive to air pollution. Conclusion Temperature modified the relationship between air pollution and daily incidence of influenza and high temperature would exacerbate the effects of air pollutants in Ningbo.

scholarly journals Functional ANOVA approaches for detecting changes in air pollution during the COVID-19 pandemic

2021 ◽  
Author(s):  
Christian Acal ◽  
Ana M. Aguilera ◽  
Annalina Sarra ◽  
Adelia Evangelista ◽  
Tonio Di Battista ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Functional Data ◽  
Central Italy ◽  
Principal Component ◽  
Functional Principal Component Analysis ◽  
Area Of Interest ◽  
Pm 10 ◽  
The Impact ◽  
Monitoring Stations

AbstractFaced with novel coronavirus outbreak, the most hard-hit countries adopted a lockdown strategy to contrast the spread of virus. Many studies have already documented that the COVID-19 control actions have resulted in improved air quality locally and around the world. Following these lines of research, we focus on air quality changes in the urban territory of Chieti-Pescara (Central Italy), identified as an area of criticality in terms of air pollution. Concentrations of $$\hbox {NO}_{{2}}$$ NO 2 , $$\hbox {PM}_{{10}}$$ PM 10 , $$\hbox {PM}_{2.5}$$ PM 2.5 and benzene are used to evaluate air pollution changes in this Region. Data were measured by several monitoring stations over two specific periods: from 1st February to 10 th March 2020 (before lockdown period) and from 11st March 2020 to 18 th April 2020 (during lockdown period). The impact of lockdown on air quality is assessed through functional data analysis. Our work makes an important contribution to the analysis of variance for functional data (FANOVA). Specifically, a novel approach based on multivariate functional principal component analysis is introduced to tackle the multivariate FANOVA problem for independent measures, which is reduced to test multivariate homogeneity on the vectors of the most explicative principal components scores. Results of the present study suggest that the level of each pollutant changed during the confinement. Additionally, the differences in the mean functions of all pollutants according to the location and type of monitoring stations (background vs traffic), are ascribable to the $$\hbox {PM}_{{10}}$$ PM 10 and benzene concentrations for pre-lockdown and during-lockdown tenure, respectively. FANOVA has proven to be beneficial to monitoring the evolution of air quality in both periods of time. This can help environmental protection agencies in drawing a more holistic picture of air quality status in the area of interest.

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