scholarly journals Reexamining the Impact of Industrial Structure on Haze Pollution Based on the Yangtze River Delta

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 613
Author(s):  
Lu Wang ◽  
Shumin Jiang ◽  
Hua Xu
Keyword(s):  
Yangtze River ◽  
Industrial Structure ◽  
Spillover Effect ◽  
Inhibitory Effect ◽  
Yangtze River Delta ◽  
River Delta ◽  
Spatial Spillover ◽  
Haze Pollution ◽  
The Impact ◽  
Spatial Spillover Effect

In this study, the static and dynamic spatial Durbin model between industrial structure and haze pollution in Yangtze River Delta is constructed. Later, the spatial spillover effect and time lag effect of haze pollution in Yangtze River Delta are analyzed. The impact of rationalization and upgrading of industrial structure on haze pollution and its spatial spillover effect are discussed. The results show that: (i) PM2.5 has a significant positive spatial spillover effect and time lag effect; (ii) in the short run, the rationalization and upgrading of industrial structure has no inhibitory effect on haze pollution, while the rationalization and upgrading of industrial structure of surrounding cities has an inhibitory effect on local haze pollution; (iii) in the long run, the rationalization and upgrading of industrial structure of surrounding cities have an inhibitory effect on local haze pollution; (iv) economic growth, FDI, the number of Industrial Enterprises above Designated Size, and population density also have spatial spillover effects on haze pollution. Therefore, considering the spatial spillover effect of haze pollution from the perspective of urban agglomeration and long-term, strengthening the joint prevention and control and comprehensive treatment among cities, further promoting the rationalization and upgrading of industrial structure is conducive to reducing haze pollution.

scholarly journals Will Policy Uncertainty Deteriorate Haze Pollution? A Spatial Spillover Perspective

2021 ◽  
Vol 18 (19) ◽  
pp. 10229
Author(s):  
Xiulin Qi ◽  
Xin Wang ◽  
Xiao Jin ◽  
Zhenyu M. Wang ◽  
Beibei Zhang ◽  
...  
Keyword(s):  
Direct Effect ◽  
Local Level ◽  
Spillover Effect ◽  
Sustainable Growth ◽  
Policy Uncertainty ◽  
Severe Problem ◽  
Spatial Spillover ◽  
Haze Pollution ◽  
The Impact ◽  
Spatial Spillover Effect

Haze has been a severe problem in China for some time, jeopardizing air quality, public health and sustainable growth. This paper examines the direct effect and spatial spillover effect of policy uncertainty on haze pollution with a spatial panel model, using prefecture-level data from 2004 to 2016. This study shows that: (1) policy uncertainty has increased the level of local haze pollution and has a significant spatial spillover effect on surrounding areas; (2) although local policy uncertainty has increased the haze pollution in geographically adjacent cities, it only affects the cities within the province with similar economic distances; and (3) the policy at the central level can effectively alleviate the impact of policy uncertainty at the local level on haze pollution, especially in relation to the spatial spillover effect, but still has limitations in eliminating the direct effect, which is due to the ineradicable nature of policy uncertainty.

scholarly journals The Moderating Effect of Innovation on the Relationship between Urbanization and CO2 Emissions: Evidence from Three Major Urban Agglomerations in China

2019 ◽  
Vol 11 (6) ◽  
pp. 1633 ◽  
Author(s):  
Yanwen Sheng ◽  
Yi Miao ◽  
Jinping Song ◽  
Hongyan Shen
Keyword(s):  
Co2 Emissions ◽  
Spillover Effect ◽  
Yangtze River Delta ◽  
River Delta ◽  
Policy Implications ◽  
Spatial Spillover ◽  
Urban Agglomerations ◽  
The Yrd ◽  
The Relationship ◽  
Spatial Spillover Effect

This study investigates the relationship between urbanization, innovation, and CO2 emissions, with particular attention paid to the issue of how innovation influences the effect of urbanization on CO2 emissions in urban agglomerations, considering the spatial spillover effect between cities. Therefore, based on panel data on 48 cities in the three major urban agglomerations in China from 2001–2015, a spatial econometric model is used to estimate the effect of urbanization and innovation on CO2 emissions. The empirical results indicate that the relationship between urbanization and CO2 emissions follows a U-shaped curve in the Beijing-Tianjin-Hebei (BTH), an N-shaped curve in the Yangtze River Delta (YRD) and an inverted N-shaped pattern in the Pearl River Delta (PRD). Additionally, innovation shows a significantly positive effect on reducing CO2 emissions in the YRD, but does not exert a significantly direct effect on CO2 emissions in the BTH and the PRD. More importantly, innovation played an important moderating role between urbanization and CO2 emissions in the YRD and PRD, suggesting that reducing the positive impacts of urbanization on CO2 emissions depends on innovative development. In addition, urban CO2 emissions presented a clearly negative spatial spillover effect among the cities in the three urban agglomerations. These findings and the following policy implications will contribute to reducing CO2 emissions.

scholarly journals Internet Development and Environmental Quality—Evidence from the Development of Chinese Cities

2021 ◽  
Vol 13 (20) ◽  
pp. 11308
Author(s):  
Xiaoying Zhong ◽  
Ruhe Xie ◽  
Peng Chen ◽  
Kaili Ke
Keyword(s):  
Environmental Quality ◽  
Industrial Structure ◽  
Spillover Effect ◽  
Mediating Effect ◽  
The Internet ◽  
Eastern Region ◽  
Spatial Spillover ◽  
Internet Development ◽  
The Impact ◽  
Spatial Spillover Effect

Based on the data of the 283 prefecture-level cities in China from 2003 to 2018, this paper examines the impact of Internet development on environmental quality. The results show that China’s urban PM2.5 has a significant spatial spillover effect. In general, the Internet has a significant negative direct effect on urban environmental pollution, which means that the development of the Internet can improve urban environmental quality. This result remains robust under different methods. As the Internet has evolved over the years, its influence on environmental quality has increased and became more and more significant. In terms of regions, the spatial spillover effect of PM2.5 shows a pattern of eastern region < central region < western region < northeast region, where the eastern region is the only region with a statistically significant negative value for the coefficient, which indicates the direct effects of Internet development on the environmental quality. In addition, the statistic testing on mediating effect shows that the Internet’s effect on urban environment quality is mainly transmitted through the upgrading of industrial structure. With the industrial structure being used as the threshold variable, the influence of Internet development on environmental quality could be divided into two stages.

scholarly journals The effect of total factor productivity of forestry industry on CO2 emissions: a spatial econometric analysis of China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shen Zhong ◽  
Hongli Wang
Keyword(s):  
Total Factor Productivity ◽  
Industrial Structure ◽  
Spillover Effect ◽  
Factor Productivity ◽  
Spatial Econometric ◽  
Spatial Spillover ◽  
Negative Case ◽  
Forestry Industry ◽  
The Impact ◽  
Spatial Spillover Effect

AbstractForestry plays an essential role in reducing CO2 emissions and promoting green and sustainable development. This paper estimates the CO2 emissions of 30 provinces in China from 2008 to 2017, and uses Global DEA-Malmquist to measure the total factor productivity of the forestry industry and its decomposition index. On this basis, by constructing a spatial econometric model, this paper aims to empirically study the impact of forestry industry's total factor productivity and its decomposition index on CO2 emissions, and further analyze its direct, indirect and total effects. The study finds that the impact of forestry industry's total factor productivity on CO2 emissions shows an "inverted U-shaped" curve and the inflection point is 0.9395. The spatial spillover effect of CO2 emissions is significantly negative. The increase of CO2 emissions in adjacent areas will provide a "negative case" for the region, so that the region can better address its own energy conservation and emission reduction goals. TFP of forestry industry also has positive spatial spillover effect. However, considering the particularity of forestry industry, this effect is not very significant. For other factors, such as foreign direct investment, urbanization level, industrial structure and technology market turnover will also significantly affect regional CO2 emissions.

scholarly journals Absorption coefficient of urban aerosol in Nanjing, west Yangtze River Delta, China

2015 ◽  
Vol 15 (23) ◽  
pp. 13633-13646 ◽  
Author(s):  
B. L. Zhuang ◽  
T. J. Wang ◽  
J. Liu ◽  
Y. Ma ◽  
C. Q. Yin ◽  
...  
Keyword(s):  
Absorption Coefficient ◽  
Urban Area ◽  
Yangtze River ◽  
Temporal Variations ◽  
Yangtze River Delta ◽  
River Delta ◽  
Near Surface ◽  
Absorbing Aerosols ◽  
The Impact ◽  
532 Nm

Abstract. Absorbing aerosols can significantly modulate short-wave solar radiation in the atmosphere, affecting regional and global climate. The aerosol absorption coefficient (AAC) is an indicator that assesses the impact of absorbing aerosols on radiative forcing. In this study, the near-surface AAC and absorption Ångström exponent (AAE) in the urban area of Nanjing, China, are characterized on the basis of measurements in 2012 and 2013 using the seven-channel Aethalometer (model AE-31, Magee Scientific, USA). The AAC is estimated with direct and indirect corrections, which result in consistent temporal variations and magnitudes of AAC at 532 nm. The mean AAC at 532 nm is about 43.23 ± 28.13 M m−1 in the urban area of Nanjing, which is much lower than that in Pearl River Delta and the same as in rural areas (Lin'an) in Yangtze River Delta. The AAC in the urban area of Nanjing shows strong seasonality (diurnal variations); it is high in cold seasons (at rush hour) and low in summer (in the afternoon). It also shows synoptic and quasi-2-week cycles in response to weather systems. Its frequency distribution follows a typical log-normal pattern. The 532 nm AAC ranging from 15 to 65 M m−1 dominates, accounting for more than 72 % of the total data samples in the entire study period. Frequent high pollution episodes, such as those observed in June 2012 and in winter 2013, greatly enhanced AAC and altered its temporal variations and frequency distributions. These episodes are mostly due to local emissions and regional pollution. Air masses flowing from northern China to Nanjing can sometimes be highly polluted and lead to high AAC at the site. AAE at 660/470 nm from the Schmid correction (Schmid et al., 2006) is about 1.56, which might be more reasonable than from the Weingartner correction (Weingartner et al., 2003). Low AAEs mainly occur in summer, likely due to high relative humidity (RH) in the season. AAC increases with increasing AAE at a fixed aerosol loading. The RH–AAC relationship is more complex. Overall, AAC peaks at RH values of around 40 % (1.3 < AAE < 1.6), 65 % (AAE < 1.3 and AAE > 1.6), and 80 % (1.3 < AAE < 1.6).

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