scholarly journals Spatial Correlation, Influencing Factors and Environmental Supervision on Mechanism Construction of Atmospheric Pollution: An Empirical Study on SO2 Emissions in China

2019 ◽  
Vol 11 (6) ◽  
pp. 1742 ◽  
Author(s):  
Ruoyu Yang ◽  
Weidong Chen
Keyword(s):  
Air Pollution ◽  
Spatial Correlation ◽  
Influencing Factors ◽  
Atmospheric Pollution ◽  
Industrial Development ◽  
Population Pressure ◽  
Spatial Data Analysis ◽  
So2 Emissions ◽  
Political Movement ◽  
The Impact

In order to study the present situation regarding SO2 emissions in China, problems are identified and countermeasures and suggestions are put forward. This paper analyzes spatial correlation, influencing factors and regulatory tools of air pollution in 30 provinces on the Chinese mainland from 2006–2015. The results of exploratory spatial data analysis (ESDA) show that SO2 emissions have obvious positive spatial correlations, and atmospheric pollution in China shows obvious spatial overflow effects and spatial agglomeration characteristics. On this basis, the present study analyzes the impact of seven socioeconomical (SE) factors and seven policy tools on air pollution by constructing a STIRPAT model and a spatial econometric model. We found that population pressure, affluence, energy consumption (EC), industrial development level (ID), urbanization level (UL) and the degree of marketization can significantly promote the increase of SO2 emissions, but technology and governmental supervision of the environment have significant inhibitory effects. The reason why China’s air pollution is curbed at present is because the government has adopted a large number of powerful command-controlled supervision measures, to a large extent. Air pollution treatment is like a government-led “political movement”. The effect of the market is relatively weak and public force has not been effectively exerted. In the future, a comprehensive use of a variety of regulation tools is needed, as well as encouraging the public to participate, strengthening the supervision of third parties and building a diversified and all-encompassing supervision mechanism.

scholarly journals Spatial-Temporal Characteristics in Grain Production and Its Influencing Factors in the Huang-Huai-Hai Plain from 1995 to 2018

2020 ◽  
Vol 17 (24) ◽  
pp. 9193
Author(s):  
Chunshan Zhou ◽  
Rongrong Zhang ◽  
Xiaoju Ning ◽  
Zhicheng Zheng
Keyword(s):  
Influencing Factors ◽  
Spatial Data ◽  
Spatial Data Analysis ◽  
Grain Production ◽  
Temporal Characteristics ◽  
Spatial Panel ◽  
Geographically Weighted Regression Model ◽  
Northern Areas ◽  
Spatial Panel Data ◽  
The Impact

The Huang-Huai-Hai Plain is the major crop-producing region in China. Based on the climate and socio-economic data from 1995 to 2018, we analyzed the spatial–temporal characteristics in grain production and its influencing factors by using exploratory spatial data analysis, a gravity center model, a spatial panel data model, and a geographically weighted regression model. The results indicated the following: (1) The grain production of eastern and southern areas was higher, while that of western and northern areas was lower; (2) The grain production center in the Huang-Huai-Hai Plain shifted from the southeast to northwest in Tai’an, and was distributed stably at the border between Jining and Tai’an; (3) The global spatial autocorrelation experienced a changing process of “decline–growth–decline”, and the area of hot and cold spots was gradually reduced and stabilized, which indicated that the polarization of grain production in local areas gradually weakened and the spatial difference gradually decreased in the Huang-Huai-Hai Plain; (4) The impact of socio-economic factors has been continuously enhanced while the role of climate factors in grain production has been gradually weakened. The ratio of the effective irrigated area, the amount of fertilizer applied per unit sown area, and the average per capita annual income of rural residents were conducive to the increase in grain production in the Huang-Huai-Hai Plain; however, the effect of the annual precipitation on grain production has become weaker. More importantly, the association between the three factors and grain production was found to be spatially heterogeneous at the local geographic level.

scholarly journals Characteristics of the Spatio-Temporal Trends and Driving Factors of Industrial Development and Industrial SO2 Emissions Based on Niche Theory: Taking Henan Province as an Example

2020 ◽  
Vol 12 (4) ◽  
pp. 1389 ◽  
Author(s):  
Pengyan Zhang ◽  
Yu Zhang ◽  
Jay Lee ◽  
Yanyan Li ◽  
Jiaxin Yang ◽  
...  
Keyword(s):  
Industrial Development ◽  
Industrial Structure ◽  
Temporal Trends ◽  
Driving Factors ◽  
Spatial Data Analysis ◽  
Energy Structure ◽  
Niche Theory ◽  
Industrial Output ◽  
So2 Emissions ◽  
Spatio Temporal

Industrial development is critical in improving a nation’s economy and in how it consumes energy resources. However, such development often causes environmental problems. Among others, the haze caused by industrial SO2 emissions is particularly prominent. Based on Niche theory and combined with Exploratory Spatial Data Analysis (ESDA, a decoupling index model, and a Logarithmic Mean Divisia Index (LMDI) factor decomposition model, this paper reports a study on the spatio-temporal distribution and the driving factors of industrial development and industrial SO2 emissions of cities in Henan, China between 2005 and 2014. The results showed that over the studied period in Henan: (1) SO2 emissions reduced by 4.56 × 105 tons and showed a slowly decreasing trend, which gradually transitioned to a “green health” industrial structure in Henan cities; (2) studied cities with high and low industrial niche values (0.038–0.139) showed an absolute decoupling relationship between industrial development and industrial SO2 emissions; (3) except for Zhengzhou city and Hebi city, other studied cities showed a trend of gradually increasing industrial output; (4) along with increases in the values of industrial output, studied cities showed increased levels of SO2 emissions but with energy intensity and energy structure showing a fluctuating trend of increases and decreases in their contributions to SO2 emissions; and (5) the energy consumption intensity and environmental technology were critical factors that were conducive to industrial SO2 emissions and the evolving industrial structure. These findings are important for the control of industrial SO2 emissions, though the levels of their influences are different in different cities. The scale of industrial production and the composition of energy structure in a region could lead to further deterioration of industrial SO2 emissions in the future.

scholarly journals Experience in using statistical and mathematical technologies to assess the impact of atmospheric pollution on public health in a large industrial center

2021 ◽  
Vol 100 (7) ◽  
pp. 663-667
Author(s):  
Dmitry V. Surzhikov ◽  
Vera V. Kislitsyna ◽  
Varvara A. Shtaiger ◽  
Roman A. Golikov
Keyword(s):  
Public Health ◽  
Air Pollution ◽  
Health Risk ◽  
Atmospheric Pollution ◽  
Carcinogenic Risk ◽  
Processing Plant ◽  
Coal Processing ◽  
Public Health Risk ◽  
The Impact ◽  
The City

Introduction. The issue of air pollution is relevant in cities where the majority of the population lives and a large number of industrial enterprises are concentrated in relatively small areas. Currently, the federal project “Clean Air” is being implemented in 12 industrial centres of Russia within the framework of the national project “Ecology”. The purpose of the work was to justify using statistical and mathematical methods for assessing the impact of atmospheric pollution on the health of the population in the city of Novokuznetsk, Kemerovo region. Materials and methods. The following methods were used: assessment and management of public health risk, statistical analysis methods: factor analysis, multiple regression analysis, discriminant analysis. Results. Statistical indices and public health risk parameters can be used to assess the impact. Examples of the effect of complex pollution indices (the main components of pollution, the integral indicator P) and the concentrations of individual impurities in the air basin (suspended substances, ozone) were given. The carcinogenic risk to the population of Novokuznetsk, calculated from the calculated concentrations of atmospheric pollutants, was found to exceed the acceptable risk threshold. The specific weight of carcinogens in the formation of the risk to other oncological incidence was determined. An assessment of the risk from the emissions of a coal-processing plant located near residential areas of the city was carried out. The values of the hazard indices showed an excess of the acceptable non-carcinogenic risk only from the emissions of the coal processing plant, taking into account the background level of air pollution in the air basin. Conclusion. In Novokuznetsk, it is proposed to use the method of ranking atmospheric protection measures in terms of the unit cost of risk reduction in health risk management. To manage the risk, it is proposed to calculate the population indices of aerogenic hazard or the probabilistic parameters of the individual threat associated with air pollution. It is noted that a 20-22% reduction in pollutant emissions for Novokuznetsk may not be enough. The reasonable measures for the further study of the aerogenic impact on the population of the city are presented.

scholarly journals The Energy Efficiency and the Impact of Air Pollution on Health in China

Healthcare ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 29 ◽  
Author(s):  
Xianhui He ◽  
Yung-ho Chiu ◽  
Tzu-Han Chang ◽  
Tai-Yu Lin ◽  
Zebin Wang
Keyword(s):  
Air Pollution ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
So2 Emissions ◽  
Lower Efficiency ◽  
The Past ◽  
High Level ◽  
The Impact ◽  
China’S Economy

The rapid growth of China’s economy in recent years has greatly improved its citizens’ living standards, but economic growth consumes many various energy sources as well as produces harmful air pollution. Nitrogen oxides, SO2 (sulfur dioxide), and other polluting gases are damaging the environment and people’s health, with a particular spike in incidences of many air pollution-related diseases in recent years. While there have been many documents discussing China’s energy and environmental issues in the past, few of them analyze economic development, air pollution, and residents’ health together. Therefore, this study uses the modified undesirable dynamic two-stage DEA (data envelopment analysis) model to explore the economic, environmental, and health efficiencies of 30 provinces in China. The empirical results show the following: (1) Most provinces have lower efficiency values in the health stage than in the production stage. (2) Among the provinces with annual efficiency values below 1, their energy consumption, CO2 (carbon dioxide), and NOx (nitrogen oxide) efficiency values have mostly declined from 2013 to 2016, while their SO2 efficiency values have increased (less SO2 emissions). (3) The growth rate of SO2 efficiency in 2016 for 10 provinces is much higher than in previous years. (4) The health expenditure efficiencies of most provinces are at a lower level and show room for improvement. (5) In most provinces, the mortality rate is higher, but on a decreasing trend. (6) Finally, as representative for a typical respiratory infection, most provinces have a high level of tuberculosis efficiency, indicating that most areas of China are highly effective at respiratory disease governance.

scholarly journals The Oakville Oil Refinery Closure and Its Influence on Local Hospitalizations: A Natural Experiment on Sulfur Dioxide

2018 ◽  
Vol 15 (9) ◽  
pp. 2029 ◽  
Author(s):  
Wesley Burr ◽  
Robert Dales ◽  
Ling Liu ◽  
Dave Stieb ◽  
Marc Smith-Doiron ◽  
...  
Keyword(s):  
Air Pollution ◽  
Sulfur Dioxide ◽  
Natural Experiment ◽  
Cold Season ◽  
Oil Refinery ◽  
So2 Emissions ◽  
Greater Toronto Area ◽  
Ambient Concentrations ◽  
Potential Factors ◽  
The Impact

Background: An oil refinery in Oakville, Canada, closed over 2004–2005, providing an opportunity for a natural experiment to examine the effects on oil refinery-related air pollution and residents’ health. Methods: Environmental and health data were collected for the 16 years around the refinery closure. Toronto (2.5 million persons) and the Greater Toronto Area (GTA, 6.3 million persons) were used as control and reference populations, respectively, for Oakville (160,000 persons). We compared sulfur dioxide and age- and season-standardized hospitalizations, considering potential factors such as changes in demographics, socio-economics, drug prescriptions, and environmental variables. Results: The closure of the refinery eliminated 6000 tons/year of SO2 emissions, with an observed reduction of 20% in wind direction-adjusted ambient concentrations in Oakville. After accounting for trends, a decrease in cold-season peak-centered respiratory hospitalizations was observed for Oakville (reduction of 2.2 cases/1000 persons per year, p = 0.0006 ) but not in Toronto (p = 0.856) and the GTA (p = 0.334). The reduction of respiratory hospitalizations in Oakville post closure appeared to have no observed link to known confounders or effect modifiers. Conclusion: The refinery closure allowed an assessment of the change in community health. This natural experiment provides evidence that a reduction in emissions was associated with improvements in population health. This study design addresses the impact of a removed source of air pollution.

scholarly journals Prediction of atmospheric pollution using neural networks model of fine particles in the town of Kennedy in Bogota

2020 ◽  
Vol 10 (6) ◽  
pp. 6574
Author(s):  
Juan Camilo Pedraza ◽  
Oswaldo Alberto Romero ◽  
Helbert Eduardo Espitia
Keyword(s):  
Neural Networks ◽  
Air Pollution ◽  
Atmospheric Pollution ◽  
Fine Particles ◽  
Particulate Material ◽  
High Impact ◽  
Geographical Environment ◽  
Using Data ◽  
The Impact ◽  
The Town

This work shows an application based on neural networks to determine the prediction of air pollution, especially particulate material of 2.5 micrometers length. This application is considered of great importance due to the impact on human health and high impact due to the agglomeration of people in cities. The implementation is performed using data captured from several devices that can be installed in specific locations for a particular geographical environment, especially in the locality of Kennedy in Bogotá. The model obtained can be used for the design of public policies that control air quality.

scholarly journals SEASONAL AND SPATIAL VARIATION OF PM10 IN AN URBAN AREA FROM ROMANIA

2019 ◽  
Vol 6 (3-4) ◽  
pp. 7-14
Author(s):  
MARIANA CARMELIA BĂLĂNICĂ DRAGOMIR ◽  
CRISTIAN MUNTENIȚĂ ◽  
AUREL GABRIEL SIMIONESCU ◽  
DANIELA ECATERINA ZECA ◽  
IRYNA KRAMAR ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Area ◽  
Air Temperature ◽  
Atmospheric Pollution ◽  
Meteorological Parameters ◽  
Influence Factor ◽  
Dispersion Models ◽  
Research Results ◽  
The Impact

The cyclic variance of PM10 mass concentration in the urban area in the South-East of Romania has been analysed in the article. SE of Romania is considered to be a territory which has medium level of pollution for a period of last ten years, from 2009 to 2018. The spatial dispersion of PM10 concentration was obtained using the METI-LIS soft wear for each season. The objective of dispersion models is to evaluate how pollutant concentration is spread out taking into account the diffusion. The average measurements of PM10 and meteorological parameters as inputs has been used. An evident seasonal change of PM10 concentrations is observed in the article. In order to establish national measures for the improvement of the atmospheric pollution control it was analysed the mechanism of atmospheric pollution. It was observed that the air quality was overall better in spring and in summer in comparison to the other two periods. With regard to the seasonal variation characteristics of PM10 significant differences for the air quality registered in different months in the researched region were observed. The impact of air temperature on atmospheric pollution was insignificant in spring and autumn; moreover, precipitation was defined as an important influence factor upon the atmospheric pollution. The impact of precipitation on the possibility of atmospheric pollution was obviously different in the four seasons. The research results indicate the meteorological parameters that influence the air pollution become active during the cold seasonal days. It was shown that relative humidity and wind speed are the meteorological parameters that impact the PM10. It was found out that the probability of atmospheric pollution decreased with the increase of air temperature in summer. The research results also testify that the air pollution mapping could be enhanced using atmospheric dispersion models and in-situ measurements.

scholarly journals Evolving Temporal–Spatial Trends, Spatial Association, and Influencing Factors of Carbon Emissions in Mainland China: Empirical Analysis Based on Provincial Panel Data from 2006 to 2015

2018 ◽  
Vol 10 (8) ◽  
pp. 2809 ◽  
Author(s):  
Weidong Chen ◽  
Ruoyu Yang
Keyword(s):  
Panel Data ◽  
Spatial Correlation ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Industrial Structure ◽  
Spatial Association ◽  
Mainland China ◽  
Population Pressure ◽  
Spatial Trends ◽  
Investment In Fixed Assets

Based on provincial panel data from 2005 to 2016, this paper analyzes evolving temporal–spatial trends, spatial correlation and influencing factors of carbon emissions in China. The results show that there is a great heterogeneity in the evolving temporal–spatial trends of carbon emissions among provinces and regions in China, with the heterogeneity in eastern provinces most obvious. At the same time, there exists significant spatial correlation and agglomeration of carbon emissions in 30 provinces. It is found that the distribution characteristics of carbon emissions are affected by various economic and social factors based on the extended STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model. Population pressure, affluence, energy intensity, industrial structure, urbanization level and investment in fixed assets can significantly promote the increase of carbon emissions. The technological level and government environmental supervision have significant inhibitory effects on carbon emissions, but foreign direct investment (FDI) has no significant impact. Therefore, it is necessary to strengthen environmental supervision and upgrade technology level to promote carbon emission reduction.

scholarly journals Features of air pollution the cities of the North-Western Black Sea region

2020 ◽  
Keyword(s):  
Air Pollution ◽  
Black Sea ◽  
Atmospheric Pollution ◽  
Pollutant Emissions ◽  
Black Sea Region ◽  
Atmospheric Air ◽  
The North ◽  
Mobile Sources ◽  
The Impact ◽  
North Western

Introduction. According to official statistics, regions of Ukraine are characterized by a significant amount of pollutant emissions from stationary sources. But in many areas the dominant contribution to the formation of general levels of air pollution is made by mobile sources. Such regions include the Odessa, Mykolaiv and Kherson regions of the North-Western Black Sea. Regions of the North-Western Black Sea are characterized by a sufficiently high level of technogenic load and have a high recreational potential. This territory is characterized by unique natural resource potential. However, due to the development of urbanization processes, the impact of industrial, transport and agrarian sectors is worsening the overall environmental situation, including the state of the atmospheric air. Review of previous publications. The work of many authors is devoted to the question of the level of air pollution in the cities of the North-Western Black Sea. Most of the works are complex studies of the level of pollution of the regions of Ukraine as a whole. Some works are devoted to the assessment of the technogenic load on the environment of the regions of Ukraine. An analysis of recent research has shown that the vast majority of work is devoted to the regions of Ukraine as a whole. Also, the list of pollutants and the study period are quite limited. Usually, the content of the main pollutants is analyzed. At the same time, the content of specific pollutants is very important in the regions of the North-Western Black Sea in the formation of high levels of atmospheric pollution. Purpose. The purpose of this work is to evaluate and analyze the level of air pollution of individual cities of the North-Western Black Sea over a multi-year period. The complex atmospheric pollution index, which are currently one of the main indicators of atmospheric air quality, were used for the assessment. Results. The level of air pollution in Odessa is in most cases classified as "heavily polluted", Izmail – the only category "slightly polluted" (maximum concentrations in the air pool are marked by the content of formaldehyde). In Mykolayiv maximum concentrations with significant exceedances of the maximum permissible concentration are also noted for formaldehyde content, and the level of atmospheric air pollution was classified as "poorly polluted" – "contaminated". In Kherson, the highest content was observed for substances such as formaldehyde and nitrogen dioxide. The level of pollution, as in the city of Mykolaiv, was classified as "poorly contaminated" – "contaminated". Conclusions. Odessa, by the content of the vast majority of the pollutants, is in the category of cities with high levels of atmospheric pollution, Mykolaiv, Kherson and Izmail – in the category with the permissible level. The results of the study are the basis for the development of environmental recommendations for reducing the emissions of pollutants into the atmospheric air of the region, primarily from mobile sources.

scholarly journals Investigation on the Impacts of COVID-19 Lockdown and Influencing Factors on Air Quality in Greater Bangkok, Thailand

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Parichat Wetchayont
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Influencing Factors ◽  
Anthropogenic Emissions ◽  
Emission Sources ◽  
Pollution Levels ◽  
Absolute Reduction ◽  
The Impact ◽  
Co Concentrations

With the outbreak of the COVID-19 pandemic around the world, many countries announced lockdown measures, including Thailand. Several scientific studies have reported on improvements in air quality due to the impact of these COVID-19 lockdowns. This study aims to investigate the effects of the COVID-19 lockdown and its driving influencing factors on air pollution in Greater Bangkok, Thailand, using in situ measurements. Overall, PM2.5, PM10, O3, and CO concentrations presented a significant decreasing trend during the COVID-19 outbreak year based on three periods: the Before Lockdown, Lockdown, and After Lockdown periods, for PM2.5: −0.7%, −15.8%, and −20.7%; PM10: −4.1%, −31.7%, and −6.1%; and O3: −0.3%, −7.1%, and −4.7%, respectively, compared to the same periods in 2019. CO concentrations, especially which had increased by 14.7% Before Lockdown, decreased by −8.0% and −23.6% during the Lockdown and After Lockdown periods, respectively. Meanwhile, SO2 increased by 54.0%, 41.5%, and 84.6%, and NO2 increased by 20.1%, 3.2%, and 26.6%, respectively, for the Before Lockdown, Lockdown, and After Lockdown periods. PCA indicated a significant combination effect of atmospheric mechanisms that were strongly linked to emission sources such as traffic and biomass burning. It has been demonstrated that the COVID-19 lockdown did pause some of these anthropogenic emissions, i.e., traffic and commercial and industrial activities, but not all of them. Even low traffic emissions, on their own, did not cause an absolute reduction in air pollution since there are several primary emission sources that dominate the air quality over Greater Bangkok. Finally, these findings highlight the impact of COVID-19 lockdown measures not only on air pollution levels but on their effects on air pollution characteristics, as well.

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