Switchgrass displays an excellent potential to serve as a non-food bioenergy feedstock for bioethanol production in China due to its high potential yield on marginal lands. However, few studies have been conducted on the spatial distribution of switchgrass-based bioethanol production potential in China. This study created a land surface process model (Environmental Policy Integrated Climate GIS (Geographic Information System)-based (GEPIC) model) coupled with a life cycle analysis (LCA) to explore the spatial distribution of potential bioethanol production and present a comprehensive analysis of energy efficiency and environmental impacts throughout its whole life cycle. It provides a new approach to study the bioethanol productivity and potential environmental impact from marginal lands based on the high spatial resolution GIS data, and this applies not only to China, but also to other regions and to other types of energy plant. The results indicate that approximately 59 million ha of marginal land in China are suitable for planting switchgrass, and 22 million tons of ethanol can be produced from this land. Additionally, a potential net energy gain (NEG) of 1.75 × 10 6 million MJ will be achieved if all of the marginal land can be used in China, and Yunnan Province offers the most significant one that accounts for 35% of the total. Finally, this study obtained that the total environmental effect index of switchgrass-based bioethanol is the equivalent of a population of approximately 20,300, and a reduction in the global warming potential (GWP) is the most significant environmental impact.
As bio-ethanol is developing rapidly, its impacts on food security, water security and the environment begin to receive worldwide attention, especially within the Water-Energy-Food nexus framework. The aim of this study is to present an integrated method of assessing sweet sorghum-based ethanol potential in China in compliance with the Water-Energy-Food nexus principles. Life cycle assessment is coupled with the DSSAT (the Decision Support System for Agrotechnology Transfer) model and geographic information technology to evaluate the spatial distribution of water consumption, net energy gain and Greenhouse Gas emission reduction potentials of developing sweet sorghum-based ethanol on marginal lands instead of cultivated land in China. Marginal lands with high water stress are excluded from the results considering their unsuitability of developing sweet sorghum-based ethanol due to possible energy-water conflicts. The results show that the water consumption, net energy gain and Greenhouse Gas emission reduction of developing sweet sorghum-based ethanol in China are evaluated as 348.95 billion m 3 , 182.62 billion MJ, and 2.47 million t carbon per year, respectively. Some regions such as Yunnan Province in south China should be given priority for sweet sorghum-based ethanol development, while Jilin Province and Heilongjiang Province need further studies and assessment.
Background
The key problem of non-grain energy plants’ scale development is how to estimate the potential of GHG emission reduction accurately and scientifically. This study presents a method coupled DSSAT (the Decision Support System for Agrotechnology Transfer) and the life cycle assessment (LCA) method to simulate the spatial distribution of sweet sorghum-based ethanol production potential on saline–alkali land. The GHG (greenhouse gas) emission mitigation and net energy gains of the whole life of sweet sorghum-based ethanol production were then analyzed.
Results
The results of the case study in Dongying, Shandong Province, China showed that developing sweet sorghum-based ethanol on saline–alkali land had GHG emission mitigation and energy potentials. The LC-GHG emission mitigation potential of saline–alkali land in Dongying was estimated at 63.9 thousand t CO2 eq, equivalent to the carbon emission of 43.4 Kt gasoline. The LC-NEG potential was predicted at 5.02 PJ, equivalent to the caloric value of 109 Kt gasoline. On average, LC-GHG emission mitigation and LC-NEG were predicted at 55.09 kg CO2 eq/t ethanol and 4.33 MJ/kg ethanol, respectively.
Conclusions
The question of how to evaluate the potential of sweet sorghum-based ethanol development scientifically was solved primarily in this paper. The results will provide an important theoretical support for planning the bioenergy crops on saline–alkali land and develop the fuel ethanol industry.
Bioenergy is expected to play a key role in achieving a future sustainable energy system. Sweet sorghum-based fuel ethanol, one of the most promising bioenergy sources in China, has been receiving considerable attention. However, the conflict between sweet sorghum development and traditional water use has not been fully considered. The article presents an integrated method for evaluating water stress from sweet sorghum-based fuel ethanol in China. The region for developing sweet sorghum was identified from the perspective of sustainable development of water resources. First, the spatial distribution of the water demand of sweet sorghum-based fuel ethanol was generated with a Decision Support System for Agrotechnology Transfer (DSSAT) model coupled with Geo-Information System (GIS). Subsequently, the surplus of water resources at the provincial scale and precipitation at the pixel scale were considered during the growth period of sweet sorghum, and the potential conflicts between the supply and demand of water resources were analyzed at regional scale monthly. Finally, the development level of sweet sorghum-based fuel ethanol was determined. The results showed that if the pressure of water consumption of sweet sorghum on regional water resources was taken into account, about 23% of the original marginal land was not suitable for development of sweet sorghum-based fuel ethanol, mainly distributed in Beijing, Hebei, Ningxia, Shandong, Shanxi, Shaanxi, and Tianjin. In future energy planning, the water demand of energy plants must be fully considered to ensure its sustainable development.
Epidemiological studies conducted around the world have reported that the under-five mortality rate (U5MR) is closely associated with income and educational attainment. However, geographic elements should also remain a major concern in further improving child health issues, since they often play an important role in the survival environment. This study was undertaken to investigate the relationship between the U5MR, geographic, and socioeconomic factors, and to explore the associated spatial variance of the relationship in China using the geographically weighted regression (GWR) model. The results indicate that the space pattern of a high U5MR had been narrowed notably during the period from 2001 to 2010. Nighttime lights (NL) and the digital elevation model (DEM) both have obvious influences on the U5MR, with the NL having a negative impact and DEM having a positive impact. Additionally, the relationship between the NL and DEM varied over space in China. Moreover, the relevance between U5MR and DEM was narrowed in 2010 compared to 2001, which indicates that the development of economic and medical standards can overcome geographical limits.
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