Accommodating variable wind power poses a critical challenge for electric power systems that are heavily dependent on combined heat and power (CHP) plants, as is the case for north China. An improved unit-commitment model is applied to evaluate potential benefits from pumped hydro storage (PHS) and electric boilers (EBs) in West Inner Mongolia (WIM), where CHP capacity is projected to increase to 33.8 GW by 2020. A business-as-usual (BAU) reference case assumes deployment of 20 GW of wind capacity. Compared to BAU, expanding wind capacity to 40 GW would allow for a reduction in CO2 emissions of 33.9 million tons, but at a relatively high cost of US$25.3/ton, reflecting primarily high associated curtailment of wind electricity (20.4%). A number of scenarios adding PHS and/or EBs combined with higher levels of wind capacity are evaluated. The best case indicates that a combination of PHS (3.6 GW) and EBs (6.2 GW) together with 40 GW of wind capacity would reduce CO2 emissions by 43.5 million tons compared to BAU, and at a lower cost of US$16.0/ton. Achieving this outcome will require a price-incentive policy designed to ensure the profitability of both PHS and EB facilities.
In the recent past Beijing has experienced rapid development. This growth has been accompanied by many problems including traffic congestion and air pollution. Understanding what stimulates urban growth is important for sustainable development in the coming years. In this paper, we first estimate a binary auto-logistic model of land use change, using physical and socioeconomic characteristics of the location and its access to major centers within the city as predictors. We find that variables determining regional access, like time distance to the city center, the Central Business District (CBD), industrial centers, employment centers, and the transportation system, significantly impact urban land conversion. By using measures of access to predict land use change we believe that we can better understand the planning implications of urban growth not only in Beijing but other rapidly developing cities.
China has been experiencing an unprecedented urbanization process. In 2011, China’s urban population reached 691 million with an urbanization rate of 51.27%. Urbanization level is expected to increase to 70% in China in 2030, reflecting the projection that nearly 300 million people would migrate from rural areas to urban areas over this period. At the same time, the total fertility rate of China’s population is declining due to the combined effect of economic growth, environmental carrying capacity, and modern social consciousness. The Chinese government has loosened its “one-child policy” gradually by allowing childbearing couples to have the second child as long as either of them is from a one-child family. In such rapidly developing country, the natural growth and spatial migration will consistently reshape spatial pattern of population. An accurate prediction of the future spatial pattern of population and its evolution trend are critical to key policy-making processes and spatial planning in China including urbanization, land use development, ecological conservation and environmental protection. In this paper, a top-down method is developed to project the spatial distribution of China’s future population with considerations of both natural population growth at provincial level and the provincial migration from 2010 to 2050. Building on this, the spatial pattern and evolution trend of Chinese provincial population are analyzed. The results suggested that the overall spatial pattern of Chinese population will be unlikely changed in next four decades, with the east area having the highest population density and followed by central area, northeast and west area. Four provinces in the east, Shanghai, Beijing, Tianjin and Jiangsu, will remain the top in terms of population density in China, and Xinjiang, Qinghai and Tibet will continue to have the lowest density of population. We introduced an index system to classify the Chinese provinces into three categories in terms of provincial population densities: Fast Changing Populated Region (FCPR), Low Changing Populated Region (LCPR) and Inactive Populated Region (IPR). In the FCPR, China’s population is projected to continue to concentrate in net immigration leading type (NILT) area where receives nearly 99% of new accumulated floating population. Population densities of Shanghai, Beijing, Zhejiang will peak in 2030, while the population density in Guangdong will keep increasing until 2035. Net emigration leading type (NELT) area will account for 75% of emigration population, including Henan, Anhui, Chongqing and Hubei. Natural growth will play a dominant role in natural growth leading type area, such as Liaoning and Shandong, because there will be few emigration population. Due to the large amount of moving-out labors and gradually declining fertility rates, population density of the LCPR region exhibits a downward trend, except for Fujian and Hainan. The majority of the western provinces will be likely to remain relatively low population density, with an average value of no more than 100 persons per km2.
Urban systems, with the overall fluxes of energy, water, material, and wastes, can be modeled with a range of metabolic processes. To quantify the urban metabolism, we use the “emergy” assessment method (all materials and energy are transformed to solar energy equivalents) and then present a group of urban metabolic indicators, which quantify urban metabolic balance, capacity, and outputs to assess a city’s metabolic efficiencies. In this paper, we use 31 Chinese cities as a sample to illustrate how the model can be operated to evaluate the urban metabolism by emergy analysis. Our results indicate that metropolises and coastal cities were more metabolically efficient with higher metabolic balance, capacities, and outputs; but with more external dependency on imported resources. Central and western cities had lower metabolic efficiencies, with a high ratio of non-renewable emergy reliance. Policy implications highlight the need for renewable energy sources and improved management of imported services, goods, and fuels to achieve higher urban resilience and sustainability.
The Harvard-China Project adopted an Open Access policy in September 2017. Most journal articles published henceforth are available in the Harvard University open-access repository, DASH.