• Energy Research

This paper attempts to propose hybrid methodology of compiling water resource extended input-output (IO) table at county level (According to administrative structure of China, a county is subordinate to its province, and provincial level is parallel to state level of other countries). By combining Non-Survey-based RAS-technique for possible iterated results and Partial-Survey-based current situation for actual ongoing resource-consumption, we aimed to depict a more accurate structure for water resource consumption and regional economic impact analysis at a county level in the arid area. Additionally, non-parameter methodology was adopted to interpolate missing data. Since human interventions continually have impacted on the natural environment that would finally lead to over-consumption of natural resources, we introduced water consumption caused by cultivation in the Primary Industry and water usage in other industries into a local input-output matrix of Shandan County in Gansu Province, China. Evidence of empirical analysis shows that the modified IO table can more accurately describe economic structure than weighted provincial average IO table does. Moreover, industrialization is ongoing with economic diversity and continually generating water use demand even though also stimulating imports of light industrial products according to the Partial-Survey reports. It demonstrates that industrialization and increasing household consumption drive a high speed of economic growth but with a high cost of water consumption through the Secondary and Tertiary Industries, even at a far rural area. Hence, water scarcity would be a constraint on sustainable development in regions such as Shandan County when taking economic valuation of natural water consumption into account.

This paper attempts to propose hybrid methodology of compiling water resource extended input-output (IO) table at county level (According to administrative structure of China, a county is subordinate to its province, and provincial level is parallel to state level of other countries). By combining Non-Survey-based RAS-technique for possible iterated results and Partial-Survey-based current situation for actual ongoing resource-consumption, we aimed to depict a more accurate structure for water resource consumption and regional economic impact analysis at a county level in the arid area. Additionally, non-parameter methodology was adopted to interpolate missing data. Since human interventions continually have impacted on the natural environment that would finally lead to over-consumption of natural resources, we introduced water consumption caused by cultivation in the Primary Industry and water usage in other industries into a local input-output matrix of Shandan County in Gansu Province, China. Evidence of empirical analysis shows that the modified IO table can more accurately describe economic structure than weighted provincial average IO table does. Moreover, industrialization is ongoing with economic diversity and continually generating water use demand even though also stimulating imports of light industrial products according to the Partial-Survey reports. It demonstrates that industrialization and increasing household consumption drive a high speed of economic growth but with a high cost of water consumption through the Secondary and Tertiary Industries, even at a far rural area. Hence, water scarcity would be a constraint on sustainable development in regions such as Shandan County when taking economic valuation of natural water consumption into account.

This study focuses on the potential impacts of large-scale land use and land cover changes (LUCC) on surface temperature from a global perspective. As important types of LUCC, urbanization, deforestation, cultivated land reclamation, and grassland degradation have effects on the climate, the potential changes of the surface temperature caused by these four types of large-scale LUCC from 2010 to 2050 are downscaled, and this issue analyzed worldwide along with Representative Concentration Pathways (RCPs) of the Intergovernmental Panel on Climate Change (IPCC). The first case study presents some evidence of the effects of future urbanization on surface temperature in the Northeast megalopolis of the United States of America (USA). In order to understand the potential climatological variability caused by future forest deforestation and vulnerability, we chose Brazilian Amazon region as the second case study. The third selected region in India as a typical region of cultivated land reclamation where the possible climatic impacts are explored. In the fourth case study, we simulate the surface temperature changes caused by future grassland degradation in Mongolia. Results show that the temperature in built-up area would increase obviously throughout the four land types. In addition, the effects of all four large-scale LUCC on monthly average temperature change would vary from month to month with obviously spatial heterogeneity.

This study focuses on the potential impacts of large-scale land use and land cover changes (LUCC) on surface temperature from a global perspective. As important types of LUCC, urbanization, deforestation, cultivated land reclamation, and grassland degradation have effects on the climate, the potential changes of the surface temperature caused by these four types of large-scale LUCC from 2010 to 2050 are downscaled, and this issue analyzed worldwide along with Representative Concentration Pathways (RCPs) of the Intergovernmental Panel on Climate Change (IPCC). The first case study presents some evidence of the effects of future urbanization on surface temperature in the Northeast megalopolis of the United States of America (USA). In order to understand the potential climatological variability caused by future forest deforestation and vulnerability, we chose Brazilian Amazon region as the second case study. The third selected region in India as a typical region of cultivated land reclamation where the possible climatic impacts are explored. In the fourth case study, we simulate the surface temperature changes caused by future grassland degradation in Mongolia. Results show that the temperature in built-up area would increase obviously throughout the four land types. In addition, the effects of all four large-scale LUCC on monthly average temperature change would vary from month to month with obviously spatial heterogeneity.