A Two-Way Fixed Effects Estimation on the Impact of Industrial Land Supply on Environmental Pollution in Urban China.

Despite the great economic growth and fast urbanization process in the past four decades, China is now suffering severely from environmental pollution. Local governments' industrial land supply behaviors have a great impact on local investment, economic growth, and environmental pollution, which has not been effectively evaluated. To fill this gap, this paper quantitatively investigates the impact of industrial land supply by local governments on environmental pollution based on a two-way fixed effects model. A comprehensive and reliable data set for 277 Chinese prefecture-level cities from 2009 to 2017 has been collected for analysis. The findings suggest that the increase of the ratio of industrial and mining storage land to total land supply significantly increases the concentration of PM2.5. The results remain significant and robust after a series of robustness tests. The negative impacts on environmental quality caused by differences in land supply behavior are greater in the central and western regions. We further explored intermediate mechanisms for the environmental impact of local governments' allocations of industrial land. The findings suggest that greater industrial land transfer by local governments leads to an expansion in the scale of regional secondary industry and increases in local fiscal deficit. Unbalanced industrial development, insufficient corporate innovation, and insufficient investment in environmental protection will increase pollution. This study provides a reference for improving regulatory measures on land transactions and for formulating regional polices for environmental protection.

Status and Influencing Factors of Physical Exercise among College Students in China: A Systematic Review.

The status of the physical exercise of college students has been a popular topic in China. This study systematically reviewed the exercise status of Chinese college students and its influencing factors. A keyword and reference search were conducted in the Web of Science, PubMed, Cochrane library, and the China National Knowledge Infrastructure. Additionally, Google Scholar was searched to collect literatures related to physical activity of Chinese university students published in Chinese and English from 1 January 2017 to 30 July 2022. Fifteen studies met the selection criteria and were included in the review. The results show that the main motivation for Chinese college students to exercise is to strengthen their bodies, with running and walking ranking first and ball games ranking second in importance. Most of the college students exercised three times a week, which is the recommended minimum, and most of their workouts were of moderate intensity. Additionally, the workouts lasted for 30 min to 60 min. The main factors affecting college students' exercise are lack of time due to academic pressure, facilities constraints, and lack of professional exercise guidance. In conclusion, the physical fitness of university students should not be underestimated, and this study provides additional reference to promote healthier lifestyles among Chinese college students.

Prediction of large-scale demolition waste generation during urban renewal: A hybrid trilogy method.

As a result of land resources constraining in China, demolition and reconstruction of existing buildings become an important means to meet the requirement of urban renewal, in which a large amount of demolition waste is generated. However, it is difficult to predict the generation of large-scale demolition waste with high efficiency due to the lack of basic data and technical support. This study aims to propose a hybrid trilogy method for predicting the generation of large-scale demolition waste during urban renewal based on two indicators of waste generation rate (WGR) and gross floor area (GFA). WGR was measured based on on-site measurement and existing industry standard data according to different building types and structure types. Composition and proportion of demolition waste were correspondingly analyzed. GFA was obtained based on image recognition technology and Google Earth. Two hundred buildings were selected as samples to verify GFA accuracy, whose error ranges were mostly controlled within 10%. Finally, prediction of large-scale demolition waste generation in Shenzhen was conducted as a case study during urban renewal for verification of the hybrid trilogy method proposed. Results show that 49.40 million tons of demolition waste will be generated. Findings of this study improve the accuracy and speed of existing prediction methods for large-scale demolition waste, indicating great potential for wide application. The current research provides guidance for demolition enterprises, transportation enterprises, recycling enterprises, and government departments to manage large-scale demolition waste precisely during urban renewal.