scholarly journals Land Misallocation and Urban Air Quality in China 

Author(s):  
Jianjiang Liu ◽  
Zhuqing Jiang ◽  
Weitao Chen

Abstract In China, local government's "land for development" strategy has led to a large number of urban construction land allocated to the industrial field, which has promoted the rapid development of industry and economy in the short term, but also brought serious environmental quality losses. This paper systematically sets out how land misallocation works on urban air quality and employs the spatial Durbin model (SDM) to conduct an empirical analysis on the panel data of 283 China's cities at or above the prefecture level. The result shows that, stimulated by financial maximization and political promotion, in order to obtain more fiscal revenue and growth performance, local governments prefer to allocate a large number of urban construction land to industry and related fields, which leads to the underestimation of industrial land price and the misallocation of land resources. Land misallocation has exerted significant inhibiting effects on the air quality of local and their surrounding cities through inhibiting the upgrading of industrial structure. Further analysis reveals that the bigger the city, the less the inhibition effects of land misallocation on upgrading of industrial structure and urban air quality, and vice versa. The conclusions of this paper can provide useful reference for local governments to optimize land allocation, promote economic restructuring and environmental quality upgrading. JEL Classification: R52; E62; P28

2020 ◽  
Vol 165 ◽  
pp. 02014
Author(s):  
Haotian Jing ◽  
Yingchun Wang

In recent years, with the rapid development of China’s economy and the continuous improvement of people’s quality of life, air pollution caused by a large amount of energy consumption has become increasingly serious. Air quality index (AQI) has become an important basis to measure air quality. At present, the research on air quality assessment and prediction methods has become increasingly active at home and abroad, which is of great significance to guide people’s production and life. In this paper, Taking Shijiazhuang, Hebei Province as an example and using the XGBoost model of the machine learning ensemble algorithm, regression fitting was performed on the six pollutant concentrations that currently mainly affect air quality, and the hourly prediction of AQI was achieved.The trained model has lower mean absolute error (MAE) and higher correlation coefficient (R-square), which improves the prediction ability of urban air quality prediction, provides a new idea for urban air quality prediction, and has a broad application prospect in the future urban air quality prediction.


2021 ◽  
Vol 138 ◽  
pp. 104976
Author(s):  
Juan José Díaz ◽  
Ivan Mura ◽  
Juan Felipe Franco ◽  
Raha Akhavan-Tabatabaei

2021 ◽  
Vol 13 (2) ◽  
pp. 496
Author(s):  
Xiaojian Hu ◽  
Nuo Chen ◽  
Nan Wu ◽  
Bicheng Yin

The Shanghai government has outlined plans for the new vehicles used for the public transportation, rental, sanitation, postal, and intra-city freight to be completely powered by electricity by 2020. This paper analyzed the characteristics of vehicle emissions in Shanghai in the past five years. The potential reduction in road traffic related emissions due to the promotion and application of electric vehicle in Shanghai was evaluated. The potential reduction was quantified by vehicular emissions. The vehicular emissions inventories are calculated by the COPERT IV model under the different scenarios, of which the results indicate that promoting electric vehicles is the efficient measure to control all road traffic related emissions and improve urban air quality. The results also provided basis and support for making policies to promote and manage electric vehicles.


2021 ◽  
pp. 108120
Author(s):  
Margareth Viecco ◽  
Héctor Jorquera ◽  
Ashish Sharma ◽  
Waldo Bustamante ◽  
Harindra J.S. Fernando ◽  
...  

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