Search

This study proposed the measuring models for the energy efficiency and carbon efficiency of the tourism industry in destination by the detailed bottomup analysis method, the theory of life cycle assessment, and material flow. TheWulingyuan Scenic and Historic Interest Area (WSHIA) in China was chosen as the research area; the energy efficiency and carbon efficiency of tourism industry in the WSHIA were measured and analyzed from 1979 to 2015. The research results showed that energy efficiency and carbon efficiency of tourism sectors and the whole tourism industry were improved with the evolution of the stage of tourism life cycle. There was a big discrepancy in energy efficiency and carbon efficiency among different sectors of tourism industry. Tourism activity had the highest of direct and total energy efficiencies and carbon efficiencies. Compared with the industries, the tourism industry in the WSHIA belonged to the low energy consumption and green low-carbon industry. The energy and environmental policies and the different strategies on the improvement of energy efficiency and carbon efficiency of tourism industry should be formulated and implemented by the government sector of tourism management and the tourism enterprises for green and low-carbon development of tourism destination. [ABSTRACT FROM AUTHOR]

It is of great practical significance to construct a water-based ecological network in arid and semi-arid areas. The spatial distribution of water resources is one of the most important factors in determining the ecological stability of such areas. In this study, groundwater level trends were analyzed with a model called Empirical Mode Decomposition (EMD). The temporal and spatial evolution of groundwater depth data from 1990 to 2016 were analyzed. The surface water bodies were analyzed using a point pattern analysis method. Based on this, a water-based ecological network was constructed with a minimum cumulative resistance surface model. The study indicated that the trend lines for the groundwater tables of 17 wells could be divided into five types in Denko County. The landscape types that changed from a desert landscape to an oasis landscape had a positive impact on groundwater. Precipitation trend was related to the spatial distribution of the groundwater depth, and the spatial pattern of the water nodes was characterized by a small-scale highly aggregated distribution and a large-scale uniform distribution in Denko County. These results suggest that for the stability of arid and semi-arid ecological environments, the appropriate human intervention (such as construction of an artificial oasis) is of great significance. Based on the analysis of groundwater and surface water bodies, a water-based ecological network in Denko County, which consisted of 391 ecological sources and 7360 ecological corridors, was constructed in 2016. The water-based ecological network constructed in this study was more sustainable and stable, and also suitable for arid and semi-arid areas, which is of great practical significance and application value. [ABSTRACT FROM AUTHOR]

Copyright of Agricultural Science & Technology is the property of Hunan Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Forestland dynamics can affect the ecological security of a country and even the global environment, and therefore it is of great practical significance to understand the characteristics of temporal and spatial variations of forestland. Taking Jiangxi Province as the study area, this study first explored the driving mechanism of the natural environment and social economy on deforestation and afforestation using a simultaneous equation model. The results indicate that population size, topographic and geomorphologic factors, climate, and location play leading roles in influencing forestland density fluctuations. Specifically, the population size, economic development level, gross value of forestry production, climate conditions, and government policies are key influencing factors of afforestation. Deforestation is mainly influenced by agricultural population, non-agricultural economy, forestry production, forestry density, location, transportation, and climate. In addition, this study simulated the spatial distribution of land use and analyzed the spatial characteristics and variation trends of forestland area and quality under the Representative Concentration Pathways (RCPs) climate scenarios from 2010 to 2030 using the Conversion of Land Use and its Effects (CLUE) model. The results indicate that forestland declines under the Asia-Pacific integrated model (AIM) climate scenario. The environment tends to be heavily damaged under this kind of scenarios, and measures should be taken in order to protect the environment. Although the model for energy supply strategy alternatives and their general environmental impact (MESSAGE) scenario is to some extent better than the AIM scenario, destruction of the environment will still occur, and it is necessary to restrain deforestation and convert shrub land intoforestland or garden land. These results can provide significant information for environmental protection, forest resource exploitation, and utilization in the areas experiencing deforestation and afforestation. [ABSTRACT FROM AUTHOR]

This study applies the Dynamics of Land System (DLS) model to simulating the land cover under the designed scenarios and then analyzes the effects of land cover conversion on energy flux in the semiarid grassland area of China with the Weather Research and Forecasting (WRF) model. The results indicate that the grassland will show a steadily upgrowing trend under the coordinated environmental sustainability (CES) scenario. Compared to the CES scenario, the rate of increase in grassland cover is lower, while the rate of increase in urban land cover will be higher under the rapid economic growth (REG) scenario. Although the conversion from cropland to grassland will reduce the energy flux, the expansion of urban area and decreasing of forestry area will bring about more energy flux. As a whole, the energy flux of near surface will obviously not change under the CES scenario, and the climate therefore will not be possible to be influenced greatly by land cover change. The energy flux under the REG scenario is higher than that under the CES scenario. Those research conclusions can offer valuable information for the land use planning and climate change adaptation in the semiarid grassland area of China. [ABSTRACT FROM AUTHOR]

With the water and soil conservation forests of Robinia pseudoacacia in the Malian beach of Hongqi farm, Ji County, Shanxi province, as the research object, this study estimated the potential evapotranspiration in the open space outside the forest and at the heights of 3m, 6m, and 10min the forests with the climate data during 2011-2012 and the upgraded Penman-Monteith formula; then, this study explored the microclimate characteristics inside and outside the Robinia pseudoacacia forest and thereafter revealed the vertical variation rules of potential evapotranspiration of Robinia pseudoacacia. The results indicate that the air temperature, relative humidity, wind speed, and potential evapotranspiration at different heights above the ground surface showed similar changing trends, but with some variation during different periods. In addition, the weather also had impacts on the potential evapotranspiration. In April, July, and October, the change of potential evapotranspiration of the Robinia pseudoacacia forests showed a bimodal curve in the sunny days and rainy days, while it showed a single-peak curve with quite small fluctuation in the rainy days. However, it showed a single-peak pattern even in the sunny days in January, and it showed no fluctuation in the snowy days in January. [ABSTRACT FROM AUTHOR]