As fossil fuels consumption and global warming are closely associated with each other, energy consumption has attracted great attention around the world. Especially when China overtook the U.S. as the world's biggest energy consumer in 2010, the time and value for China's peak energy consumption become the focus of world attention. Based on a brief review of existing peak energy consumption methods and models, population and economic development selected as two major driving factors, and using the variation rule of per capita energy consumption during economic development in developed countries as reference, the future energy consumption for China was projected up to 2050. The results showed that: 1) China has great potential to increase per capita energy consumption and the cumulative per capita energy consumption. The probable per capita energy consumption range for China is 4.75-9.31 tce/cap in 2050, the upper limit equivalent to only 76% of the United States' per capita consumption peaks. And the probable energy consumption range for China is 6.19-12.13 billion tce in 2050. While the probable range of cumulative per capita energy consumption for China for 1870-2050 is 207-294 tce,the upper limit equivalent to only 46% of the United States' (56% of Germany and 57% of United Kingdom) cumulative per capita consumption during 1870-2012. 2) Currently, most studies showed that the probable energy consumption peak range for China will be in 2035-2040, with the peak value range of 6.2-7.9 billion tce. This paper argues that in addition to the United States, United Kingdom and Germany Scenarios, the other national scenarios will be unlikely peaked. 3) Under France Scenario the “zero” growth of China's energy consumption will occur around 2040, while Japan, South Korea and Baseline scenarios project that a slow growth period of China's energy consumption will occur after 2035, with growth rate about 2%. To sum up, France, Japan and South Korea scenarios are more reasonable and China's energy consumption is likely to enter a slow growth period since 2035. At present, the level of GDP per capita in China is not high, and the level of per capita energy consumption especially for cumulative per capita energy consumption is low, so it would put ourselves in a passive position in climate change negotiations if we are too optimistic about China's peak energy consumption time and value. Based on national conditions of China, we need to leave more energy consumption space for China's social economic development. Last but not least, actively promoting energy-efficient production and adopting an energy-efficient lifestyle will be the key for China's sustainable socio-economic development, energy security and respondence to global climate change.
As highly efficient agricultural technologies are used widely, efficiency of labor got improved, and grain yield was on the increase, but so many negative effects appeared such as environmental problem, food safety and disappearance of traditional agricultural culture. As a GIAHS, the system of forest-village-paddy-river in Hani terrace, which had formed for a long time in history, has multiple values that include ecologic value, productive value and landscape value, therefore, it is of great significance to protect agricultural system of Hani terrace from being destroyed. The purpose of protecting agricultural system of Hani terrace will be achieved, if the price of agricultural products from Hani terrace region is improved by organic planting for the farmers going on planting paddy rice. However, it must go through a stage of organic conversion from non-organic production to organic production. In this stage, the agricultural products produced by organic planting are not brought at the price of organic products due to not having organic label. Therefore, the local government should give some compensation to the farmers who planted rice by organic production during organic conversion for the agriculture products per unit weight, so that the income of the farmers cannot be lost. In this paper, questionnaire and interview were used for gaining the information about input-output of agriculture in organic planting during organic conversion, earnings of farmers from work in city in Hani terrace region, and input-output of modern agricultural planting. By analyzing, contrasting and computing those informations, we had results as follows: 1) The directly input of organic planting of paddy rice in Hani terrace region is more than modern planting, but paddy rice yield from organic planting is lower than modern planting; 2) labors of young adults prefer to work or live in cities for higher income, therefore, the opportunity cost is higher; and 3) extra compensation of paddy rice from organic planting at 2.84 yuan/kg is reasonable for protecting terrace landscape and traditional planting pattern in Hani terrace region.
According to the sustainable livelihood theory, a research idea of “rural tourism development-farmers' livelihood changes-optimization of rural energy consumption in mountainous rural tourism destination” is established in this paper. Taking Jinsixia rural tourist destination as an example, the transformation of the livelihood, energy consumption patterns and comprehensive benefits of energy consumption are analyzed. Firstly, through household surveys and interviews, the local farmer households were divided into five types by the energy consumption-livelihood diversity model. Secondly, based on the energy consumption diversity model and benefits evaluation method, the energy consumption structures and comprehensive benefits of farmers who have different types of livelihood strategies are interpreted. Thirdly, with the method of grey correlation analysis, the study identifies the main livelihood capital factors that affect the farmers' energy consumption, and summarizes the driving mechanism of the transformation of farmers' energy consumption patterns. The results are as following: 1) Farmers' livelihood diversity level has an impact on the energy consumption diversity level, the latter will raise as the former goes up inside the non-tourism enterprises and tourism enterprises. 2) Compared with the farmers who are not engaged in tourism, the commercial energy consumption of farmers who are engaged in tourism increases significantly, which reflects the fact that the tourism causes the increase of new energy, the decrease of traditional energy consumption, and speeds the optimization and commercialization of farmers' energy consumption patterns. 3) There is a sharp distinction in energy consumption comprehensive benefits among different types of farmers, that the energy consumption comprehensive benefits of farmers who are engaged in tourism (16.96 yuan/kgce) are significantly greater than the farmers who are not engaged in tourism (13.53 yuan/kgce), which indicates that the former benefits more from the energy consumption. 4) Physical capital, human capital and financial capital are the main factors that affect the farmers' energy consumption pattern. Farmers' livelihood change which is brought by the tourism development is the important driver leading to the energy consumption transformation in rural tourism destination. To further improve the environmental policy and optimize the energy utilization, this paper puts forward the corresponding countermeasures and suggestions.
The contribution of forest land use change to the carbon source has been researched in most tropical regions, but it is poorly documented for arid forest ecosystem. Using Bookkeeping model, we estimated the sources and sinks of carbon caused by forest land use change between 1975 and 2005 in Central Asia. The results indicated that: The forest land use change performed as carbon sink overall, with total carbon sequestration of 3.07 Tg. The accelerated afforesting led to a strong carbon sequestration (12.97 Tg), while the deforestation was a main carbon source, releasing 5.80 Tg. The woodland transfer also performed as carbon source, releasing 4.10 Tg. We recommend that some efficient measures should be taken on increasing the quality and quantity of forest resources in the future to enhance the forestry carbon sequestration in Central Asia. Therefore, this can offset the carbon loss caused by industrial activities, so as to provide sufficient space for the sustained and healthy development of the economy in Central Asia. This study is conducive to profoundly understand the influence of human activities on global carbon balance.
Vegetation change is generally caused by the combined effects of various climate variables, which is further complicated by the impacts of human activities. Assessing the importance of each explanatory variable is critical for the study of vegetation change attribution. The responses of vegetation to temperature and precipitation in eastern China have been widely explored in previous studies. However, less attention has been paid to the influence of other climate variables in vegetation change. In this study, we introduced a statistical method called partial least squares (PLS) to investigate the relative importance of different climate variables. ThePLS regression, combining features of principal components analysis (PCA) and multiple regression, overcomes the multicollinearity problem which arises when two or more explanatory variables in a multiple regression model are highly correlated. Using GIMMS NDVI products and PLS method, we first investigated the relative effects of different climate variables (temperature, precipitation, sunrise, relative humidity, wind) on vegetation change in eastern China from the period 1982 to 2006. Then, the relative contribution of anthropogenic factors on the vegetation change was quantified in the region of Jiangsu Province where vegetation shows distinctive changes. The results indicated that: 1) there were distinct north -south differences among interannual variations of monthly NDVI in eastern China in the period of 1982-2006. A significant increase of NDVI was found in December through May in some areas north to the Huaihe River, while the drop of NDVI occurred in June through October in some areas south to the Huaihe River; 2) in the areas with significantly increased NDVI, the greatest contributor was temperature and it had the most significant effect on the increase of NDVI. In particular, the temperature rise could play a dominant role in driving the increase of NDVI in the Huang-Huai-Hai Plain in late winter and early spring (February-March). The decrease in NDVI, by contrast, might not be attributed to climate factors in many areas. However, it should be noted that there was no obvious change in NDVI trends in many parts of eastern China compared with the areas suffering significant NDVI change; 3) Jiangsu Province was mainly characterized by a significant decline of NDVI in June from 1982 to 2006. However, such large regional concentration of NDVI change was not observed in other months and regions. Statistical analysis showed that the agricultural structural adjustment played a key role in controlling the NDVI change in June in Jiangsu Province. The decline of NDVI in June was mainly attributed to the decrease in sown area of cotton across a large spatial extent.
In order to investigate the contribution of vegetation to the reduction of runoff and sediment yield of the Yellow River in recent years, the Yanhe River catchment, which has experienced significant vegetation changes in last decade, was chosen as the study area. In this paper, the new version of Morgan-Morgan-Finney (MMF) model (Morgan-Duzant version) was used to simulate the impact of land cover changes on the runoff and sediment yield of the catchment, and the effect of vegetation and rainfall on runoff and sediment yield were estimated through scenario simulations of series of vegetation and precipitation. Then a correlation analysis was carried out to explore the relationships between vegetation variables and the runoff and sediment yield in the catchment. The data used in the present study included Landsat remote sensing images, the hydrologic and meteorological data, and DEM data (25 m× 25 m) of the catchment. The results showed that: 1) the MMF model provided a better prediction of the average annual runoff volume than the average annual sediment production in the Yanhe River catchment. However, when the impact of terraces and soil-retaining dams was incorporated into the MMF model, it also provided a good prediction of sediment production. 2) The relationships between vegetation factors and runoff volume and sediment discharge did not show evident spatial patterns. There was obvious correlation between runoff volume and indirect vegetation variables (such as canopy interception, throughfall eroding force, sediment rate of the slope, et al.), while vegetation cover was more closely related to the sediment discharge. 3) The scenario simulation of 1990, 2000 and 2006 indicated that the vegetation cover of the Yanhe River catchment had been increased greatly in 2006. Compared with 1990 and 2000, the increased vegetation cover reduced the runoff volume by 45.88% and 25.74%, and reduced the sediment discharge by 12.10% and 27.57% in 2006.
In order to understand the relationship between soil moisture and vegetation after extremely heavy rainfall on the hilly-gullied Loess Plateau, the soil moisture was observed and analyzed under five different vegetation types (Robinia psendoacacia, Caragana intermedia, Artemisia gmelinii, Stipa bungeana and Bothriochloa ischaemun) after a series of heavy rainfall in July 2013. The results show that: 1) Vegetation became the main factor that affected soil moisture after extremely heavy rainfall. 2) The soil moisture under grassland was higher than that under the artificial forests. The soil under Stipa bungeana had the highest soil moisture, soil water storage and available soil water storage, which were 17.8%, 961.2 mm and 691.2 mm, while the soil under 31 years old Robinia psendoacacia had the lowest soil moisture. 3) The infiltration depth of soil under artificial forests was about 300 cm, and about 500 cm under the grassland. It was difficult to recover the moisture in the deep soil under the artificial forest.
Average air temperature has been popularly and extensively used to assess the effect of temperature on crop yield. However, it would substantially remove the impacts of the extremes on the yield, consequently resulting in a potential bias on the result. Given this fact, we raised the theory of Three-interval Temperature to characterize the responses of crops to different air temperature conditions: extremely low, normal and extremely high. Heilongjiang Province is a thermal-sensitive region to current climate change and a very important production area of maize. In this study, we constructed statistical models by using the indices of Growing Degree Days (GDD) and precipitation to quantify the influence of climatic variables on maize yield in Heilongjiang Province. We also introduced three temperature indices to compare with the results based on the Three-interval Temperature Theory. The result showed that the heat injury has become a non-neglectable factor that causes the detriment of maize production in Heilongjiang Province while the chilling injury has been moderating since the 1980s. Also, the latter method we raised, denoted as the Three-interval Temperature Theory, had a better performance in the assessment of climate change effects on maize yield, which provided new insights into related studies in other cultivation areas.
Huadu experienced economic soaring during 1999-2009. The ever-changing urban landscape pattern impacted the distribution of the thermal environment. The land surface temperature (LST) and land use types in the study area were obtained from Landsat TM/ETM+ remote sensing images. Using the mean-standard deviation method, land surface temperatures were classified and the thermal centroids of low and high temperatures were calculated. And the moving paths of the thermal centroids during 1999-2009 were compared with that of the construction land centroid. Visual landscape metrics, including SHDI, construction land PLAND, FRAC_MN, and DIVISION, were obtained by moving window to analyze their correlations with LST. The results show that: the southern part of Huadu was strongly impacted by human activities. Land use was not the single factor which influenced the distribution of land surface temperature. SHDI and LST were positively correlated, even though the increasing degree of landscape diversity would cause the decrease of the relevance. The correlation between LST and construction land PLAND/DIVISION was stable. The regions with large construction land PLAND or low construction land DIVISION were usually high temperature regions. With the increase of the shape complexity and the area of the construction lands, the correlationship between LST and construction land FRAC_MN become stronger.
As one of the most vital grain production areas in China, Heilongjiang Province plays an important role in guaranteeing Chinese's grain security. This paper examines the spatio-temporal pattern and driving factors of grain production in Heilongjiang Province based on the models of ESDA, K-Means Cluster and multi-regression, and the aim is to illuminate the current situation of grain production and provide the scientific basis for promoting the regional ability of guaranteeing national grain security and sustainable development of agriculture inHeilongjiang Province. The results show that the scale of grain production in Heilongjiang Province keeps increasing, and both the seeding area and proportion of soybean experience a wave of “ascent-descent”, while the seeding areas and proportions of corn and rice expand constantly, and they both exceed soybean in 2009 and 2011, respectively. By the end of 2012, the planted acreage of soybean, corn and rice accounted for 17.73%, 45.12% and 26% of the total grain acreages, respectively. Moreover, corn and rice has become the main grain crops in Heilongjiang Province, while the importance of soybean decreased in some way. In addition, the grain production in Heilongjiang Province has certain characteristics of spatial correlation. Of which, the soybean has significant spatial agglomeration, and its Moran's I is 0.6011. Corn takes the second place and shows a weakening trend after 2004, for its Moran's I decreased from 0.6135 in 2004 to 0.48 in 2012. The spatial gathering of rice is the least evident but it began to increase since 2009, and its Moran's I was 0.3709 in 2012. The results also show that the regional types of grain production have a significant spatio-temporal variation and the trend of specialization and regionalization is enhanced. The northern Songnen Plain, Da Hinggan and Xiao Hinggan mountains, as well as the north of Sanjiang Plain have respectively formed the typical areas of soybean, corn and rice. Moreover, multi-regression analysis demonstrates that the agricultural investment, economic environment, technical level and market factor are the main factors that influence the structure and the spatio-temporal variation of grain production in Heilongjiang Province.
There is growing global concern over food loss and waste and its impacts on resources and environmental issues, and curbing food loss and food waste is becoming another way to ensure food security. However, knowledge of food loss and waste is entirely inadequate worldwide. Here, based on a great amount of literatures and documents at home and abroad, we gave a whole review of research progress on food loss and waste on global scale and found that there is still a long way to go to reduce food loss and waste globally, however, there has been considerable researches. Firstly, it was lack of standardized theoretical framework that includes the definition of food loss and food waste, the demarcation of study segments and the research methods, which caused the difficulty to compare the previous findings. Secondly, there were few researches focusing on economic underdeveloped countries and regions, and the researches about countries in economic transformation mainly concentrated in the 70-80s of the 20th century, so there were less researches about current situation of these countries, especially food loss in postharvest segments. So it was urgent to strengthen case studies of the countries and regions above. Thirdly, reducing food waste by changing consumer behavior was also an important aspect to be strengthened, which can provide policy makers with effective interventions to curbing food waste in consumer segments. In the end, this research gave a prospect that the reduce of food loss and waste will be of great importance in the future and called for cutting down food loss and waste by different ways.
