Study on spatial correlation of air pollution and control effect of development plan for the city cluster in the Yangtze River Delta

2021 ◽  
pp. 101213
Author(s):  
Xianhua Wu ◽  
Zhiqing Tian ◽  
Yun Kuai ◽  
Shunfeng Song ◽  
Stephen M. Marson
Keyword(s):  
Air Pollution ◽  
Spatial Correlation ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
The Yangtze River ◽  
Control Effect ◽  
City Cluster ◽  
And Control ◽  
The City ◽  
The Yangtze River Delta

scholarly journals MAX-DOAS measurements of tropospheric NO<sub>2</sub> and HCHO in Nanjing and the comparison to OMI observations

2019 ◽  
Author(s):  
Ka Lok Chan ◽  
Zhuoru Wang ◽  
Aijun Ding ◽  
Klaus-Peter Heue ◽  
Yicheng Shen ◽  
...  
Keyword(s):  
Air Pollution ◽  
Pollution Control ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
Satellite Observations ◽  
River Delta ◽  
Control Measures ◽  
Air Pollution Control ◽  
The Yangtze River ◽  
The Yangtze River Delta

Abstract. In this paper, we present long term observations of atmospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) in Nanjing using a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. Ground based MAX-DOAS measurements were performed from April 2013 to February 2017. The MAX-DOAS measurements of NO2 and HCHO vertical column densities (VCDs) are used to validate OMI satellite observations over Nanjing. The comparison shows that the OMI observations of NO2 correlate well with the MAX-DOAS data with Pearson correlation coefficient (R) of 0.91. However, OMI observations are on average a factor of 3 lower than the MAX-DOAS measurements. Replacing the a priori NO2 profiles by the MAX-DOAS profiles in the OMI NO2 VCD retrieval would increase the OMI NO2 VCDs by ~ 30 % with correlation nearly unchanged. The comparison result of MAX-DOAS and OMI observations of HCHO VCD shows a good agreement with R of 0.75 and the slope of the regression line is 0.99. We developed a new technique to assemble the source contribution map using backward trajectory analysis. The age weighted backward propagation approach is applied to the MAX-DOAS measurements of NO2 and HCHO to reconstruct the spatial distribution of NO2 and HCHO over the Yangtze River Delta during summer and winter time. The reconstructed NO2 fields show a distinct agreement with OMI satellite observations. However, due to the short atmospheric lifetime of HCHO, the backward propagated HCHO data does not show a strong spatial correlation with the OMI HCHO observations. The result shows the MAX-DOAS measurements are sensitive to the air pollution transportation in the Yangtze River Delta, indicating the air quality in Nanjing is significantly influenced by regional transportation of air pollutants. The MAX-DOAS data are also used to evaluate the effectiveness of air pollution control measures implemented during the Youth Olympic Games 2014. The MAX-DOAS data show a significant reduction of ambient aerosol, NO2 and HCHO (30 %–50 %) during the Youth Olympic Games. Our results provide a better understanding of the transportation and sources of pollutants in over the Yangtze River Delta as well as the effect of emission control measures during large international event, which are important for the future design of air pollution control policies.

scholarly journals The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in the Yangtze River Delta

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8169
Author(s):  
Zaijun Li ◽  
Xiang Zheng ◽  
Dongqi Sun
Keyword(s):  
Spatial Correlation ◽  
Carbon Emissions ◽  
Yangtze River ◽  
Temporal Correlation ◽  
Yangtze River Delta ◽  
River Delta ◽  
Direct And Indirect Effects ◽  
The Yangtze River ◽  
Spatio Temporal ◽  
The Yangtze River Delta

A low-carbon economy is the most important requirement to realize high-quality integrated development of the Yangtze River Delta. Utilizing the following models: a super-efficiency slacks-based measure model, a spatio-temporal correlation model, a bivariate LISA model, a spatial econometric model, and a geographically weighted random forest model, this study measured urban industrial eco-efficiency (IEE) and then analyzed its influencing effects on carbon emission in the Yangtze River Delta from 2000 to 2017. The influencing factors included spatio-temporal correlation intensity, spatio-temporal association type, direct and indirect impacts, and local importance impacts. Findings showed that: (1) The temporal correlation intensity between IEE and scale efficiency (SE) and carbon emissions exhibited an inverted V-shaped variation trend, while the temporal correlation intensity between pure technical efficiency (PTE) and carbon emissions exhibited a W-shaped fluctuation trend. The negative spatial correlation between IEE and carbon emissions was mainly distributed in the developed cities of the delta, while the positive correlation was mainly distributed in central Anhui Province and Yancheng and Taizhou cities. The spatial correlation between PTE and carbon emissions exhibited a spatial pattern of being higher in the central part of the delta and lower in the northern and southern parts. The negative spatial correlation between SE and carbon emissions was mainly clustered in Zhejiang Province and scattered in Jiangsu and Anhui provinces, with the cities with positive correlations being concentrated around two locations: the junction of Anhui and Jiangsu provinces, and within central Jiangsu Province. (2) The direct and indirect effects of IEE on carbon emissions were significantly negative, indicating that IEE contributed to reducing carbon emissions. The direct impact of PTE on carbon emissions was also significantly negative, while its indirect effect was insignificant. Both the direct and indirect effects of SE on carbon emissions were significantly negative. (3) It was found that the positive effect of IEE was more likely to alleviate the increase in carbon emissions in northern Anhui City. Further, PTE was more conducive to reducing the increase in carbon emissions in northwestern Anhui City, southern Zhejiang City, and in other cities including Changzhou and Wuxi. Finally, it was found that SE played a relatively important role in reducing the increase in carbon emissions only in four cities: Changzhou, Suqian, Lu’an, and Wenzhou.

Stable and transport indices applied to winter air pollution over the Yangtze River Delta, China

2020 ◽  
pp. 115954
Author(s):  
Xiaohui Liu ◽  
Bin Zhu ◽  
Hanqing Kang ◽  
Xuewei Hou ◽  
Jinhui Gao ◽  
...  
Keyword(s):  
Air Pollution ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
The Yangtze River Delta

scholarly journals The Spatiotemporal Coupling Characteristics of Regional Urbanization and Its Influencing Factors: Taking the Yangtze River Delta as an Example

2019 ◽  
Vol 11 (3) ◽  
pp. 822 ◽  
Author(s):  
Dong Xu ◽  
Guolin Hou
Keyword(s):  
Spatial Autocorrelation ◽  
Spatial Correlation ◽  
Influencing Factors ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
Spatiotemporal Characteristics ◽  
The Yangtze River Delta ◽  
Coordination Degree

The research on the coupling coordination of regional urbanization is of great significance for achieving sustainable urbanization. Based on the theories of coordinated development, this paper constructs an index system for comprehensive evaluation of the three sub-systems of urbanization (population, economy and land urbanization). Then, the entropy method, coupling coordination degree model and spatial autocorrelation analysis are used to explore the spatiotemporal characteristics of overall and pairwise coordination among population, land and economy urbanization. Finally, the geographic detector model is used to analyze the influencing factors in the urbanization process. The results show that: (1) the levels of population, land and economy urbanization in the Yangtze River Delta have been improved from 2001 to 2016. The overall and pairwise coupling coordination degrees among them also continue to improve and the stage characteristics are presented. (2) The spatial distribution of low-level and high-level coupling coordination cities shows a certain spatial dependence and a Z-shaped pattern, respectively. The spatiotemporal characteristics of pairwise coupling coordination indicate regional imbalance of the urbanization. (3) The overall coupling coordination degree of urbanization has an apparent spatial autocorrelation, with its local spatial correlation patterns dominated by the High–High and Low–Low type agglomeration. Significant differences in local spatial correlation patterns of the pairwise coupling coordination suggest that regional synergy should not be neglected. (4) The economic development level is the main factor influencing the spatiotemporal differentiation of the coupling coordination of urbanization. Location traffic conditions and population agglomeration effect are the second most influencing factors. The evolution mechanisms of coupling coordination of urbanization are affected by factors in change. The findings highlight the importance of dealing with the relationship among population, land and economy in the process of regional urbanization and have implications for promoting the integration of urban agglomerations.

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