This page has only limited features, please log in for full access.

Unclaimed
Shijie Li
Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 31 January 2019 in Science of The Total Environment
Reads 0
Downloads 0

Environmental sustainability has become a significant goal for policymakers and practitioners since increasing environmental degradation owing to anthropogenic activities. Energy-environment efficiency, linked to a progressive reduction in the environmental impacts that may occur throughout their life cycle to levels that should be below or equal the Earth's estimated carrying capacity, is a crucial point for constructing an environment friendly society while maintaining rapid economic growth. Thus, this study combined a slack-based measure (SBM) with environmental impacts as undesirable outputs with spatial analysis techniques to measure energy-environment efficiency of 21 cities in Guangdong and its changing patterns during the period 2006–2016. What and how socioeconomic factors affecting energy-environment efficiency over time and space was further examined using heterogeneous panel data model. Here are the main findings: during the study period, energy-environment efficiency showed apparent spatiotemporal diversity with high values predominantly concentrated in coastal areas, especially in the center area of the Pearl River Delta. Energy-environment efficiency increased continuously in the western Guangdong and the Pearl River Delta, while it of eastern Guangdong showed a decreasing trend and of northern Guangdong remained stable at a low level. The results of the heterogeneous panel data model revealed that technological progress exerted the greatest positive effects on energy-environment efficiency, followed by population density, economic growth. Conversely, Openness was evaluated as an inhibiting factor. Interestingly, this study found that industrial structure demonstrated significant negative correlations with respect to energy-environment efficiency in the Pearl River Delta while it exerted significant positive influence in the peripheral areas of Guangdong. And foreign trade and energy-environment efficiency had a significant positive correlation in the Pearl River Delta, unlike the negative correlation in the peripheral areas of Guangdong. This study's findings hold a helpful reference for both policymakers and practitioners to coordinate the economy, energy and environment and established environment-friendly society in the fast-developed areas like Guangdong.

ACS Style

Jieyu Wang; Shaojian Wang; Shijie Li; Qiaoxian Cai; Shuang Gao. Evaluating the energy-environment efficiency and its determinants in Guangdong using a slack-based measure with environmental undesirable outputs and panel data model. Science of The Total Environment 2019, 663, 878 -888.

AMA Style

Jieyu Wang, Shaojian Wang, Shijie Li, Qiaoxian Cai, Shuang Gao. Evaluating the energy-environment efficiency and its determinants in Guangdong using a slack-based measure with environmental undesirable outputs and panel data model. Science of The Total Environment. 2019; 663 ():878-888.

Chicago/Turabian Style

Jieyu Wang; Shaojian Wang; Shijie Li; Qiaoxian Cai; Shuang Gao. 2019. "Evaluating the energy-environment efficiency and its determinants in Guangdong using a slack-based measure with environmental undesirable outputs and panel data model." Science of The Total Environment 663, no. : 878-888.

Journal article
Published: 29 January 2019 in Science of The Total Environment
Reads 0
Downloads 0

Modernization refers to the general trend of developmental progress that occurs within human societies. We now know that global warming, a result of carbon dioxide emissions, severely threatens the sustainability of human society. It is therefore of significant theoretical and practical implications that the scientific community more thoroughly investigate the impacts of modernization on CO2 emissions. Surprisingly, only a limited number of studies have addressed this topic previously. As the world's largest developing economy and carbon emitter, China faces the dual challenge of peaking carbon emissions by 2030 while realizing basic modernization by 2035. With the purpose of identifying the implications of China's 2035 modernization goal for its 2030 emission peak goal, this study explored the effects of modernization on carbon dioxide emissions in China. Using a comprehensive indicator system, five modernization indexes—addressing industrialization, agricultural modernization, informatization, urbanization, and ecological modernization—were estimated, along with carbon dioxide emissions, for the period 1997–2016, for 30 Chinese provinces. Panel data modeling was then used to examine the impacts of the five modernization indexes on CO2 emissions in China. The results demonstrate that industrialization, agricultural modernization, informatization, and urbanization exerted positive effects on CO2 emissions during the study period, suggesting these aspects of modernization led to increased carbon dioxide emissions. A negative correlation between ecological modernization and carbon dioxide emission was identified, indicating that ecological modernization helped to abate CO2 emissions. The findings emerging from this study hold significant implications for China's policy makers in promoting decarbonization, suggesting the utility of pursuing new-type industrialization, developing organic agriculture and eco-agriculture, popularizing electronic equipment with low power dissipation, building low-carbon cities, and promoting the ecology-oriented transformation of the modernization model.

ACS Style

Shijie Li; Chunshan Zhou; Shaojian Wang. Does modernization affect carbon dioxide emissions? A panel data analysis. Science of The Total Environment 2019, 663, 426 -435.

AMA Style

Shijie Li, Chunshan Zhou, Shaojian Wang. Does modernization affect carbon dioxide emissions? A panel data analysis. Science of The Total Environment. 2019; 663 ():426-435.

Chicago/Turabian Style

Shijie Li; Chunshan Zhou; Shaojian Wang. 2019. "Does modernization affect carbon dioxide emissions? A panel data analysis." Science of The Total Environment 663, no. : 426-435.

Journal article
Published: 17 January 2019 in Sustainability
Reads 0
Downloads 0

It is of great significance to investigate the determinants of urban form for shaping sustainable urban form. Previous studies generally assumed the determinants of urban form did not vary across spatial units, without taking spatial heterogeneity into account. In order to advance the theoretical understanding of the determinants of urban form, this study attempted to examine the spatial heterogeneity in the determinants of urban form for 289 Chinese prefecture-level cities using a geographically weighted regression (GWR) method. The results revealed the spatially varying relationship between urban form and its underlying factors. Population growth was found to promote urban expansion in most Chinese cities, and decrease urban compactness in part of the Chinese cities. Cities with larger administrative areas were more likely to have dispersed urban form. Industrialization was demonstrated to have no impact on urban expansion in cities located in the eastern coastal region of China, which constitutes the country’s most developed regions. Local financial revenue was found to accelerate urban expansion and increase urban shape irregularity in many Chines cities. It was found that fixed investment exerted a bidirectional impact on urban expansion. In addition, urban road networks and public transit were also identified as the determinants of urban form for some cities, which supported the complex urban systems (CUS) theory. The policy implications emerging from this study lies in shaping sustainable urban form for China’s decision makers and urban planners.

ACS Style

Shijie Li; Chunshan Zhou; Shaojian Wang; Shuang Gao; Zhitao Liu. Spatial Heterogeneity in the Determinants of Urban Form: An Analysis of Chinese Cities with a GWR Approach. Sustainability 2019, 11, 479 .

AMA Style

Shijie Li, Chunshan Zhou, Shaojian Wang, Shuang Gao, Zhitao Liu. Spatial Heterogeneity in the Determinants of Urban Form: An Analysis of Chinese Cities with a GWR Approach. Sustainability. 2019; 11 (2):479.

Chicago/Turabian Style

Shijie Li; Chunshan Zhou; Shaojian Wang; Shuang Gao; Zhitao Liu. 2019. "Spatial Heterogeneity in the Determinants of Urban Form: An Analysis of Chinese Cities with a GWR Approach." Sustainability 11, no. 2: 479.

Journal article
Published: 24 September 2018 in Science of The Total Environment
Reads 0
Downloads 0

This study comprehensively investigated the impacts of demographic structure on CO2 emissions in China at the national level and the regional level for the first time. Panel cointegration modeling was employed to test the long-run relationships between CO2 emissions and six demographic structure variables, namely, dependency ratio, sex ratio, higher education ratio, industrial employment ratio, urbanization ratio, and average household size. The fully modified ordinary least squares method was then applied to estimate the long-run elasticity of CO2 emissions for the six demographic structure variables. The results suggested that long-run relationships between CO2 emissions and demographic structure existed at both the national level and the regional level. Dependency ratio was found to exert negative effects on CO2 emissions in China and its three sub-regions. Positive associations between sex ratio and CO2 emissions were revealed to exist in China and West China, and CO2 emissions elasticity for sex ratio was relatively high in West China. Higher education ratio had a positive effect on CO2 emissions in East China. Industrial employment ratio was found to positively correlate with CO2 emissions in China, East China, and Central China. Urbanization ratio was demonstrated to increase CO2 emissions at the national level and the regional level, and CO2 emissions elasticity for urbanization ratio decreased from West China to Central China, and then to East China. Negative correlations between average household size and CO2 emissions were detected at both the national level and the regional level. Based on the findings of this study, several practical recommendations were proposed, including optimizing age structure, promoting gender equality, advocating low-carbon lifestyles and low-carbon consumption patterns, promoting industrial upgrading and industrial structure optimization, building low-carbon cities and less carbon-intensive public infrastructure systems, and improving residential energy efficiency.

ACS Style

Shijie Li; Chunshan Zhou. What are the impacts of demographic structure on CO2 emissions? A regional analysis in China via heterogeneous panel estimates. Science of The Total Environment 2018, 650, 2021 -2031.

AMA Style

Shijie Li, Chunshan Zhou. What are the impacts of demographic structure on CO2 emissions? A regional analysis in China via heterogeneous panel estimates. Science of The Total Environment. 2018; 650 ():2021-2031.

Chicago/Turabian Style

Shijie Li; Chunshan Zhou. 2018. "What are the impacts of demographic structure on CO2 emissions? A regional analysis in China via heterogeneous panel estimates." Science of The Total Environment 650, no. : 2021-2031.

Journal article
Published: 24 August 2018 in Cities
Reads 0
Downloads 0

The improvement of CO2 emission efficiency is of great significance to realizing energy-saving and emission reduction targets and achieving low-carbon development. While it is increasingly recognized that urban form could significantly influence the CO2 emissions of urban areas, few studies have been able to quantify the implications of urban form in relation to CO2 emission efficiency. The purpose of this paper is thus to contribute to existing literature by empirically quantifying how urban form influences CO2 emission efficiency. CO2 emission efficiency in this study is presented in terms of CO2 economic efficiency (CEE) and CO2 social efficiency (CSE). Firstly, we calculated the CEE and CSE of nine cities in the Pearl River Delta (Guangzhou, Shenzhen, Zhuhai, Foshan, Jiangmen, Zhaoqing, Huizhou, Dongguan, and Zhongshan) using locally important socioeconomic variables over the period 1990–2013. Then, seven landscape metrics were selected in order to quantify three dimensions of urban form (extension, irregularity, and compactness) using remote sensing data. Finally, panel data models were utilized to estimate the associations between urban form and CO2 emission efficiency. We identified a negative correlation between urban sprawl and CEE as well as CSE, a finding that indicates that urban growth decreases CO2 economic efficiency. Further, increasing irregularity in the form of cities was found to decrease both CEE and CSE—a larger degree of irregularity, in other words, results in lower CO2 emission efficiency. Conversely, urban compactness was identified as having a significant positive influence on both CEE and CSE, indicating that the compact development of cities can actually help to improve CO2 emission efficiency. The findings of this study hold important implications for building low-carbon cities in China.

ACS Style

Shaojian Wang; Jieyu Wang; Chuanglin Fang; Shijie Li. Estimating the impacts of urban form on CO2 emission efficiency in the Pearl River Delta, China. Cities 2018, 85, 117 -129.

AMA Style

Shaojian Wang, Jieyu Wang, Chuanglin Fang, Shijie Li. Estimating the impacts of urban form on CO2 emission efficiency in the Pearl River Delta, China. Cities. 2018; 85 ():117-129.

Chicago/Turabian Style

Shaojian Wang; Jieyu Wang; Chuanglin Fang; Shijie Li. 2018. "Estimating the impacts of urban form on CO2 emission efficiency in the Pearl River Delta, China." Cities 85, no. : 117-129.

Journal article
Published: 23 August 2018 in Applied Energy
Reads 0
Downloads 0

Despite the fact that the relationship between socioeconomic development and PM2.5 concentrations has drawn much attention from multidisciplinary scholars in recent years, the causal links between PM2.5 concentrations and energy consumption, energy intensity, economic growth, and urbanization in countries with different income levels remain poorly understood. The present study categorized countries into four panels based on their income levels, in order to investigate the casual relationship between energy consumption, energy intensity, economic growth, urbanization, and PM2.5 concentrations for the period 1998–2014. To achieve this goal, balanced panel data and econometric methods were utilized. The results revealed that cointegration relationships existed between PM2.5 concentrations and the variables studied, in all panels. Findings of a panel Granger causality test based on a Vector Error-Correction Model showed that energy consumption, energy intensity, economic growth, and urbanization led to increased PM2.5 concentrations in the long term. Economic growth was the principal variable that impacted on PM2.5 concentrations in the global panel, the high-income panel, and the upper-middle income panel. PM2.5 concentrations can, we argue, be decreased by improving energy intensity in the short term in all countries except those belonging to the low-income group. In contrast, reducing the urbanization level in the short term is not an efficient way to mitigate PM2.5 concentrations. Our findings further indicated that the energy consumption structure was the greatest factor impacting on PM2.5 concentrations in lower-middle-income and low-income countries.

ACS Style

Jing Chen; Chunshan Zhou; Shaojian Wang; Shijie Li. Impacts of energy consumption structure, energy intensity, economic growth, urbanization on PM2.5 concentrations in countries globally. Applied Energy 2018, 230, 94 -105.

AMA Style

Jing Chen, Chunshan Zhou, Shaojian Wang, Shijie Li. Impacts of energy consumption structure, energy intensity, economic growth, urbanization on PM2.5 concentrations in countries globally. Applied Energy. 2018; 230 ():94-105.

Chicago/Turabian Style

Jing Chen; Chunshan Zhou; Shaojian Wang; Shijie Li. 2018. "Impacts of energy consumption structure, energy intensity, economic growth, urbanization on PM2.5 concentrations in countries globally." Applied Energy 230, no. : 94-105.

Journal article
Published: 21 August 2018 in Journal of Cleaner Production
Reads 0
Downloads 0

In addition to socioeconomic factors, urban morphology is increasingly being recognized for the potential role it might play in tackling climate change. Meanwhile, improving CO2 emission efficiency has become a significant aim in reducing CO2 emissions without sacrificing economic development. Hence, investigating the effects of urban landscape pattern on CO2 emission efficiency is of great importance. As thus, this study is designed to quantitatively estimate the associations between urban landscape pattern and CO2 emission efficiency, using panel data for five megacities in China in the period 1990–2013. A series of landscape metrics were first selected to quantify three dimensions of urban landscape pattern, namely urban expansion, urban shape complexity, and urban compactness. CO2 emission efficiency was then evaluated using three quantitative indicators, namely per capita CO2 emission, CO2 emission intensity, and CO2 emission performance. Finally, panel data models were performed to estimate the influences of urban landscape pattern on CO2 emission efficiency. The results demonstrate that both urban expansion and urban shape complexity inhibited the improvement of CO2 emission performance. In addition, urban compactness was found to be conducive to the reduction of CO2 emission per capita and CO2 emission intensity, as well as the improvement of CO2 emission performance. The findings obtained through this study cast a new light on the significance of city planning and the optimization of spatial structure in improving CO2 emission efficiency, providing decision makers and urban planners with a scientific basis from which to approach the task of reducing CO2 emissions whilst maintaining economic development.

ACS Style

Shijie Li; Chunshan Zhou; Shaojian Wang; Jincan Hu. Dose urban landscape pattern affect CO2 emission efficiency? Empirical evidence from megacities in China. Journal of Cleaner Production 2018, 203, 164 -178.

AMA Style

Shijie Li, Chunshan Zhou, Shaojian Wang, Jincan Hu. Dose urban landscape pattern affect CO2 emission efficiency? Empirical evidence from megacities in China. Journal of Cleaner Production. 2018; 203 ():164-178.

Chicago/Turabian Style

Shijie Li; Chunshan Zhou; Shaojian Wang; Jincan Hu. 2018. "Dose urban landscape pattern affect CO2 emission efficiency? Empirical evidence from megacities in China." Journal of Cleaner Production 203, no. : 164-178.

Journal article
Published: 24 July 2018 in International Journal of Environmental Research and Public Health
Reads 0
Downloads 0

Urban form is increasingly being identified as an important determinant of air pollution in developed countries. However, the effect of urban form on air pollution in developing countries has not been adequately addressed in the literature to date, which points to an evident omission in current literature. In order to fill this gap, this study was designed to estimate the impacts of urban form on air pollution for a panel made up of China’s five most rapidly developing megacities (Beijing, Tianjin, Shanghai, Chongqing, and Guangzhou) using time series data from 2000 to 2012. Using the official Air Pollution Index (API) data, this study developed three quantitative indicators: mean air pollution index (MAPI), air pollution ratio (APR), and continuous air pollution ratio (CAPR), to evaluate air pollution levels. Moreover, seven landscape metrics were calculated for the assessment of urban form based on three aspects (urban size, urban shape irregularity, and urban fragmentation) using remote sensing data. Panel data models were subsequently employed to quantify the links between urban form and air pollution. The empirical results demonstrate that urban expansion surprisingly helps to reduce air pollution. The substitution of clean energy for dirty energy that results from urbanization in China offers a possible explanation for this finding. Furthermore, urban shape irregularity positively correlated with the number of days with polluted air conditions, a result could be explained in terms of the influence of urban geometry on traffic congestion in Chinese cities. In addition, a negative association was identified between urban fragmentation and the number of continuous days of air pollution, indicating that polycentric urban forms should be adopted in order to shorten continuous pollution processes. If serious about achieving the meaningful alleviation of air pollution, decision makers and urban planners should take urban form into account when developing sustainable cities in developing countries like China.

ACS Style

Chunshan Zhou; Shijie Li; Shaojian Wang. Examining the Impacts of Urban Form on Air Pollution in Developing Countries: A Case Study of China’s Megacities. International Journal of Environmental Research and Public Health 2018, 15, 1565 .

AMA Style

Chunshan Zhou, Shijie Li, Shaojian Wang. Examining the Impacts of Urban Form on Air Pollution in Developing Countries: A Case Study of China’s Megacities. International Journal of Environmental Research and Public Health. 2018; 15 (8):1565.

Chicago/Turabian Style

Chunshan Zhou; Shijie Li; Shaojian Wang. 2018. "Examining the Impacts of Urban Form on Air Pollution in Developing Countries: A Case Study of China’s Megacities." International Journal of Environmental Research and Public Health 15, no. 8: 1565.