This paper aims to demonstrate the relationship between economic growth and the urban core area in order to help urban planners reach a better understanding of the pressures that are leading to changes in land use. Using a unique panel dataset with measures of China’s land use, it is shown that, during the late 1980s and 1990s, China’s urban land area rose significantly. Descriptive statistics and multivariate analysis are then used to identify the determinants of urban land use change. In addition to using more standard regression approaches such as ordinary least squares, the analysis is augmented with spatial statistical analysis. The analysis demonstrates the overwhelming importance of economic growth in the determination of urban land use. Overall, it is found that urban land expands by 3 per cent when the economy, measured by gross domestic product, grows by 10 per cent. It is also shown that the expansion of the urban core is associated with changes in China’s economic structure. If urban planners have access to forecasts of economic growth, using these results they should be able to have a better basis for planning the expansion of the built-up area in the urban core.

Ecosystem services are substantial elements for human society. The central challenge to meet the human needs from ecosystems while sustain the Earth’s life support systems makes it urgent to enhance efficient natural resource management for sustainable ecological and socioeconomic development. Trade-off analysis of ecosystem services can help to identify optimal decision points to balance the costs and benefits of the diverse human uses of ecosystems. In this sense, the aim of this paper is to provide key insights into ecosystem services trade-off analysis at different scales from a land use perspective, by comprehensively reviewing the trade-offs analysis tools and approaches that addressed in ecology, economics and other fields. The review will significantly contribute to future research on trade-off analysis to avoid inferior management options and offer a win-win solution based on comprehensive and efficient planning for interacting multiple ecosystem services.

Increases in atmospheric carbon dioxide (CO₂) concentrations is the main driver of global warming due to fossil fuel combustion. Satellite observations provide continuous global CO₂ retrieval products, that reveal the nonuniform distributions of atmospheric CO₂ concentrations. However, climate simulation studies are almost based on a globally uniform mean or latitudinally resolved CO₂ concentrations assumption. In this study, we reconstructed the historical global monthly distributions of atmospheric CO₂ concentrations with 1° resolution from 1850 to 2013 which are based on the historical monthly and latitudinally resolved CO₂ concentrations accounting longitudinal features retrieved from fossil-fuel CO₂ emissions from Carbon Dioxide Information Analysis Center. And the spatial distributions of nonuniform CO₂ under Shared Socio-economic Pathways and Representative Concentration Pathways scenarios were generated based on the spatial, seasonal and interannual scales of the current CO₂ concentrations from 2015 to 2150. Including the heterogenous CO₂ distributions could enhance the realism of global climate modeling, to better anticipate the potential socio-economic implications, adaptation practices, and mitigation of climate change.