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In this paper we ask two questions: Does a multiscalar urban land-change model that couples a region-scale system dynamics model with a local-scale spatial logit model better predict the amount of urban land change than either model alone? Does a multiscalar urban land-change model that couples regional and local-scale factors better predict the spatial patterns of urban land change than a standalone local-scale spatial logit model? To examine these questions, we develop a coupled system dynamics spatial logit (CSDSL) model for the Pearl River Delta, China, that incorporates region-scale population and economic factors with local-scale biophysical and accessibility factors. In terms of predicting the amounts of urban land change, the CSDSL model is 15% and 18% more accurate than the standalone spatial logit and system dynamics models, respectively. In terms of predicting the spatial pattern of urban land change, the CSDSL model slightly outperforms the spatial logit model as measured by four spatial pattern metrics: number of urban patches, urban edge density, average urban patch size, and spatial irregularity of the urban area. Both the CSDSL and spatial logit models underpredict the number of discrete urban patches (by 64% and 80%, respectively) and the urban edge density (by 42% and 62%, respectively). While both models overpredict the average urban patch size, the spatial logit model overpredicts by over 316%, while the CSDSL overpredicts by 192%. Finally, the models perform equally well in predicting the spatial irregularity of urban areas and the location of urban change. Taken together, these results demonstrate that the CSDSL model outperforms a standalone spatial logit or system dynamics model in predicting the amount and spatial complexity of urban land change. The results also show that predicting urban land-change patterns remains more diffi cult than predicting total amounts of change. [ABSTRACT FROM AUTHOR]

Abstract: China is home to one-fifth of the world''s population and that population is increasingly urban. The landscape is also urbanizing. Although there are studies that focus on specific elements of urban growth, there is very little empirical work that incorporates feedbacks and linkages to assess the interactions between the dynamics of urban growth and their environmental impacts. In this study, we develop a system dynamics simulation model of the drivers and environmental impacts of urban growth, using Shenzhen, South China, as a case study. We identify three phases of urban growth and develop scenarios to evaluate the impact of urban growth on several environmental indicators: land use, air quality, and demand for water and energy. The results show that all developable land will be urban by 2020 and the increase in the number of vehicles will be a major source of air pollution. Demand for water and electricity will rise, and the city will become increasingly vulnerable to shortages of either. The scenarios also show that there will be improvements in local environmental quality as a result of increasing affluence and economic growth. However, the environmental impacts outside of Shenzhen may increase as demands for natural resources increase and Shenzhen pushes its manufacturing industries out of the municipality. The findings may also portend to changes other cities in China and elsewhere in the developing world may experience as they continue to industrialize. [Copyright &y& Elsevier]

The relationship between energy consumption and economic growth has deservedly received much attention in the literature due to its significance to sustainable development, particularly in countries such as China with rapid economic growth. However, few studies have explored the spatial heterogeneous nature of this relationship within countries where there are spatial variations in terms the level and speed of economic development. This study analyzes how industrial GDP and employment are related to industrial electricity consumption at prefecture city level across China using Multiscale Geographically Weighted Regression (MGWR). It also examines the role of foreign direct investment (FDI) and research/development (RD) in mediating the relationship between economic growth and electricity consumption. The results show that, during the study period, industrial electricity consumption became increasingly related to industrial GDP while the influence of employment diminished. However, this relationship varied over space and time with clear differences between the cities in the developed east coast and the rest of the country. Also, the FDI and RD improved efficiency in electricity consumption especially in less developed central and western regions during the study period. • Identify the spatial heterogeneity of energy-economy relationship across China. • MGWR models are used. • Results on spatial variations correspond to the knowledge of regional gaps in China. • Results on temporal effects examine the predictability of energy consumption. [ABSTRACT FROM AUTHOR]

An improved understanding of global Urban Exposure to Flooding (UEF) is essential for developing risk-reduction strategies for sustainable urban development. This study is the first to assess the long-term historical global UEF at a fine spatial resolution (i.e., 30 m) and annual temporal frequency, with consideration of smaller urban areas in the exposure assessment compared to those using coarse resolution data. We assessed the UEF by investigating the spatially explicit urban expansion in the 100-year floodplain extents. The global UEF increased more than four-fold from 16,443 km 2 in 1985 to 92,233 km 2 in 2018 with accelerated temporal trends. The most notable growth in UEF occurred in Asia (74.1%), followed by Europe (11.6%), Northern America (8.7%), Africa (2.9%), Southern America (2.2%), and Australia (0.5%). Notably, China and US were the two countries with the largest UEF, accounting for about 61.5% of global growth in UEF. In addition, only 1.2% of global floodplains were occupied by urban expansion by 2018, whereas this percentage reached 20% in the basins of Western Europe, Eastern Asia, and Northeastern US. Moreover, although the floodplains only accounted for 5.5% of the global land areas, 12.6% of the urban expansion occurred in the floodplains from 1985 to 2018, with the most rapid increases in the basins in Southeastern and Eastern China. Our findings highlight that the trends of accelerated increasing urban exposure to flooding have been occurring for at least the past three decades., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

China has high biodiversity and is rapidly urbanizing. However, there is limited understanding of how urban expansion in the country is likely to affect its habitats and biodiversity. In this study, we examine urban expansion patterns and their likely impacts on biodiversity in China by 2030. Our analysis shows that most provinces are expected to experience urban expansion either near their protected areas or in biodiversity hotspots. In a few provinces such as Guangdong in the south, urban expansion is likely to impinge on both protected areas and biodiversity hotspots. We show that policies that could facilitate the integration of natural resource protection into urban planning exist on paper, but the prevailing incentives and institutional arrangements between the central and local governments prevent this kind of integration. Removing these obstacles will be necessary in order to safeguard the country's rich biodiversity in light of the scale of urbanization underway.