Variation of industrial air pollution emissions based on VIIRS thermal anomaly data

2020 ◽  
Vol 244 ◽  
pp. 105021
Author(s):  
Shuang Sun ◽  
Lingjun Li ◽  
Zhihong Wu ◽  
Atul Gautam ◽  
Jinxiang Li ◽  
...  
Keyword(s):  
Air Pollution ◽  
Thermal Anomaly ◽  
Industrial Air Pollution ◽  
Pollution Emissions ◽  
Air Pollution Emissions

scholarly journals The Environmental Effects of International Trade in China: Measuring the Mediating Effects of Technology Spillovers of Import Trade on Industrial Air Pollution

2021 ◽  
Vol 13 (12) ◽  
pp. 6895
Author(s):  
Shiyue Zhang ◽  
Alan R. Collins ◽  
Xiaoli L. Etienne ◽  
Rijia Ding
Keyword(s):  
Air Pollution ◽  
Technological Innovation ◽  
Industrial Structure ◽  
Technology Spillovers ◽  
Mediating Effects ◽  
Industrial Air Pollution ◽  
Pollution Emission ◽  
Pollution Emissions ◽  
Import Trade ◽  
Air Pollution Emissions

China is in a strategic phase of an industrial green transformation. Industrial air pollution is a key environmental target for governance. Because import trade is a core channel through which advanced environmental protection technology is absorbed, the question of whether technology spillovers brought about by import trade can reduce industrial air pollution emissions is a topic worth exploring. This paper uses a generalized spatial two-stage least-square (GS2SLS) model to explore the impact of import trade technology spillovers on industrial air pollution emission intensities using panel data from 30 provinces and cities between 2000 and 2017. Economic scale, industrial structure, and technological innovation are used as intermediary variables to test whether they play mediating effects. The results show that: (1) capital and intermediate goods technology spillovers directly reduce industrial air pollution emission intensity and (2) import trade technology spillovers indirectly reduce emission intensities by expanding economic scale, optimizing industrial structure, and enhancing technological innovation through mediating variables. Furthermore, industrial structure optimization and technological innovation have the largest mediating effects on industrial SO2, while economic expansion has the most significant mediating effect on industrial smoke and dust. The mediating effects of technology spillovers from intermediate goods exceed those of capital technology spillovers. Finally, industrial air pollution emission intensity demonstrates both spatial agglomeration and time lag effects. Environmental regulations and energy structure are shown to increase industrial air pollution emissions, while urbanization and foreign direct investment reduce industrial air pollution. Based upon these research results, some pertinent policy implications are proposed for China.

scholarly journals Socio-economic inequalities in exposure to industrial air pollution emissions in Quebec public schools

2017 ◽  
Vol 108 (5-6) ◽  
pp. e503-e509 ◽  
Author(s):  
Emmanuelle Batisse ◽  
Sophie Goudreau ◽  
Jill Baumgartner ◽  
Audrey Smargiassi
Keyword(s):  
Air Pollution ◽  
Public Schools ◽  
Industrial Air Pollution ◽  
Pollution Emissions ◽  
Air Pollution Emissions ◽  
Economic Inequalities

scholarly journals COVID-19 and Air Pollution: Measuring Pandemic Impact to Air Quality in Five European Countries

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 290
Author(s):  
Akvilė Feiferytė Skirienė ◽  
Žaneta Stasiškienė
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Social Services ◽  
Pollution Monitoring ◽  
Air Pollution Monitoring ◽  
Rapid Spread ◽  
Air Quality Improvement ◽  
Environment Agency ◽  
Pollution Emissions ◽  
Air Pollution Emissions

The rapid spread of the coronavirus (COVID-19) pandemic affected the economy, trade, transport, health care, social services, and other sectors. To control the rapid dispersion of the virus, most countries imposed national lockdowns and social distancing policies. This led to reduced industrial, commercial, and human activities, followed by lower air pollution emissions, which caused air quality improvement. Air pollution monitoring data from the European Environment Agency (EEA) datasets were used to investigate how lockdown policies affected air quality changes in the period before and during the COVID-19 lockdown, comparing to the same periods in 2018 and 2019, along with an assessment of the Index of Production variation impact to air pollution changes during the pandemic in 2020. Analysis results show that industrial and mobility activities were lower in the period of the lockdown along with the reduced selected pollutant NO2, PM2.5, PM10 emissions by approximately 20–40% in 2020.

scholarly journals Status of Air Pollution Regulations Affecting Gas Turbines in 80 Nations

1974 ◽  
Author(s):  
R. J. Ketterer ◽  
N. R. Dibelius
Keyword(s):  
Air Pollution ◽  
Carbon Monoxide ◽  
Sulfur Dioxide ◽  
Gas Turbines ◽  
Ground Level ◽  
Oxides Of Nitrogen ◽  
Ground Level Concentration ◽  
Pollution Emissions ◽  
Air Pollution Emissions

This paper summarizes regulations from 80 countries covering air pollution emissions from gas turbines. The paper includes emission and ground level concentration standards for particulates, sulfur dioxide, oxides of nitrogen, visible emissions, and carbon monoxide.

scholarly journals Application of an Adaptive Nudging Scheme in Air Quality Forecasting in China

2008 ◽  
Vol 47 (8) ◽  
pp. 2105-2114 ◽  
Author(s):  
Xiangde Xu ◽  
Lian Xie ◽  
Xinghong Cheng ◽  
Jianming Xu ◽  
Xiuji Zhou ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Weather Forecasting ◽  
Initial Conditions ◽  
Primary Source ◽  
Emission Data ◽  
Weather Observations ◽  
Pollution Emissions ◽  
Air Pollution Emissions ◽  
Source Of Error

Abstract A major challenge for air quality forecasters is to reduce the uncertainty of air pollution emission inventory. Error in the emission data is a primary source of error in air quality forecasts, much like the effect of error in the initial conditions on the accuracy of weather forecasting. Data assimilation has been widely used to improve weather forecasting by correcting the initial conditions with weather observations. In a similar way, observed concentrations of air pollutants can be used to correct the errors in the emission data. In this study, a new method is developed for estimating air pollution emissions based on a Newtonian relaxation and nudging technique. Case studies for the period of 1–25 August 2006 in 47 cities in China indicate that the nudging technique resulted in improved estimations of sulfur dioxide (SO2) and nitrogen dioxide (NO2) emissions in the majority of these cities. Predictions of SO2 and NO2 concentrations in January, April, August, and October using the emission estimations derived from the nudging technique showed remarkable improvements over those based on the original emission data.

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