Recently, research on food loss and foodwaste and the related environmental impacts has increased globally. Food loss and food waste occur in all aspects of the food supply chain from farm to table. A better understanding of the scales and trends of food loss and food waste is very important for any mitigation strategies. The food waste reflects directly the civilization of a society, and we need to understand the causes and consequences of food waste from multiple perspectives. Addressing food loss and food waste issue requires a wide range of actions from reducing, to promoting a healthy diet culture, learning from international experience, and building intelligent food systems.
Over the past decades, the low agricultural labor productivity is one of the main bottlenecks in restricting agricultural development in China, which related to the peasants’ income growth and agricultural sustainable development. It is extremely urgent to improve agricultural labor productivity. With the large-scale of farmland management, understanding the relationship between farmland management scale and agricultural labor productivity is very important. In view of this, balanced panel data of 31 provinces in the mainland of China during the period of 2000-2013 from National Bureau of Statistics were used in econometric models to quantitatively analyze the relationship between them in this paper. The results show that the quantitative relationship between the two variables is similar in different scales. It indicates that there is a distinct inverted-“L” relationship between the labor productivity and farm land scale across the country in different landforms and in the three economic belts. In the short term, expansion of farm land scale can significantly improve the labor productivity, but there are obvious differences among regions; in the long term, labor productivity will reach a stable value. At present, the farmland scale is much smaller than the optimal management scale of farmland, so farmland scale concentration is the important measure to improve labor productivity, and there is still space to promote moderate scale management policy. The government should reduce the transaction cost of land transfer, guide and promote scale management of agriculture land in multiple forms.
The paper studies the influence of topography and economics on the evolution process of landscape pattern and its spatial-temporal difference in the rapid urbanization area, taking the main urban area of Chongqing City as the research object. Seven transects in north-south direction and east-west direction were selected on the basis of the unique geomorphologic characteristics and the economic environment in the study area. With the help of the Fragstats 4.2 and ArcGIS 9.3, the responses of transacts to the evolution of landscape pattern in the period of 1995-2014 in the study area were compared and the driving mechanism was analyzed with combined methods of gradient analysis and landscape pattern analysis. Results are shown as follows: 1) In terms of the change characteristics of landscape fragmentation and landscape diversity in the same period and direction transects, the values of PD and SHDI of the north-south transect c and the east-west transect f were the lowest and the highest values near the urban center, but away from the city center of the same direction transects are just the opposite. It is obvious that the differences of the whole landscape features are influenced by the urbanization level, terrain factors and policy-driven in the same period. 2) With the increased distance from the center of city (or hills and plateaus), the landscape fragmentation and landscape diversity of both the north-south and east-west transects continued increasing, while the landscape aggregation continued decreasing, and the connectivity between patches decreased. After the year of 2001, the impact of urbanization on the landscape pattern in the study area enhanced, but the impact of terrain factors weakened, and the dominant landscape changed from farmland to urban landscape. 3) During the period of 1995-2014, in the southern 18 km section of north-south transect c and the western 8 km section of east-west transect f where it is close to the urban and rural residents, the values of LPI were the highest. With urban sprawl, the LPI value became 100% at 6 km in the north of north-south transect c. Because of internal renovation of the old urban area since 2001, the AWMPFD values at 18 km in the south of north-south transect c and at 8 km in the west of east-west transect f dropped from the peak value to the lowest value close to 1. The research results show that the evolution of landscape pattern of Chongqing city has significant characteristics of spatial heterogeneity.
This paper took Shixing village in Sanxing town, Shizhu County as the sample area. Based on the forest landscape pattern in 2004, the Logistic stepwise regression was adopted to select factors playing essential roles in the forest landscape pattern in different periods, which were terrain, altitude, drainage course, transportation and distribution of the settlement. CLUE-S was applied to simulate the distribution of the forest landscape pattern in Shixing village in 2014, and the result was validated by comparing with the actual pattern. Then the forest landscape pattern ten years later was simulated based on three scenarios: the historical development trend, the boom of returning home of the second generation of farmers, and the intervention of industrial and commercial fund. Besides, this paper analyzed the landscape dynamics from 2004 to 2024 by using the landscape pattern index. There are four aspects of the result. Firstly, based on the distribution pattern of the forest landscape in 2014, the precision of forest landsacpe pattern in 2014 was 85%, and the average Kappa coefficient was over 0.816, which illustrated the applicability of CLUE-S. Secondly, in the three scenarios, the forest landscape always occupied the main position in the landscape matrix during the 20 years from 2004, and the result illustrates that the total area of the forest increased compared with that in 2004. In addition, the degraded forest lands decreased in all three scenarios. In the second scenario, the reductions of the degraded forest land accompanied with the increase of the artificial forest and the agricultural land. In the third scenario, the reductions of the degraded forest land accompanied with the increase of the artificial forest and the decrease of agricultural land. Thirdly, the spatial distributions of the forest lands are regular. The degraded primary forests are mainly seen in the hills and deep hillock areas, while the secondary forests, degraded forest land and artificial forests are in mosaic structure, being scattered in some matrix landscape. Fourthly, the degree of forest landscape fragmentation is different in three simulated scenarios. Generally, the recoveries of forest landscape are better in the second and the third scenarios. The result of this study will provide the reference and support to the administration, planning, and policy making of the forest landscape in following years.
Using rainfall use efficiency (RUE) as index, we carried out the ecological assessment of typical rangeland types in Hexi Corridor, including temperate desert, alpine meadow and temperate rangeland. By extracting vegetation index, interpreting rainfall with Co-Kriging method and overlying multiple maps, we obtained RUE(NDVI), RUE(PVI) and RUE(TSAVI) in Hexi Corridor. By crrelation analysis between different RUEs and aboveground biomass, suitable RUE for each type of rangeland is selected as index to evaluate the ecological process. The result showed that: 1) The correlation between RUE(PVI) and aboveground biomass is the highest in temperate desert, correlation coefficient being 0.879. The correlation between RUE(NDVI) and aboveground biomass is the highest in alpine meadow, correlation coefficient being 0.876. The correlation between RUE(TSAVI) and aboveground biomass is the highest in temperate rangeland, correlation coefficient being 0.895. 2) The temperate desert is in ecological degraded process, since RUE(PVI) in the range of -11.291--2.000, -1.999-0.000 and 2.001-6.000 is in increasing trend and RUE(PVI) in the range of 0.001-2.000 and 6.001-43.918 is in decreasing trend. The temperate rangeland is also in ecological degraded process, since RUE(TSAVI) in the range of -3.2×10-3-0.8×10-3 and 1.4×10-3-2.4×10-3 is in increasing trend and RUE(TSAVI) in the range of 0.8×10-3-1.4×10-3 and 2.4×10-3-3.4×10-3 is in decreasing trend. On opposite, alpine meadow is in ecological recovery process, since RUE(NDVI) in the range of 18.001-36.000 is in decreasing trend and RUE(NDVI) in the range of -6.765-6.000, 6.001-10.000 and 10.001-18.000 is in increasing trend. We believe that selecting appropriate RUE for different type of rangeland as the assessment index is feasible and reliable in theory and practice.
In this paper, the evaluation index system of urban ecological well-being performance (hereinafter referred to as UEWP) is established in the first step by means of DEA. Resource indicators including energy consumption per capita, water use per capita and construction land use per capita, and environmental indicators such as waste water discharge per capita, waste gas emission per capita and waste solid discharge per capita are selected as the ecological input, and GDP per capita, life expectance at birth and education, which are the three dimensions of Human Development Index (HDI), are selected as the proxy index of well-being to be the output at city level. The principal component analysis (PCA) is employed during the index processing. In the empirical part, a comparative analysis is conducted based on DEA model (BCC and Super-DEA) and revised DEA model—super-SBM model with cross-sectional data of the year of 2013 from 35 major cities (provincial and sub-provincial cities) in China. Then, on the basis of the DEA value acquired with the super-SBM model, the Tobit regression model is employed to analyze the influencing factors of UEWP. The research result shows that the super-SBM model is a better choice during the evaluation of UEWP since it can solve the radial issue. Main conclusions are as follows: 1) 35 major cities are at overall low level of UEWP in 2013, but there are big gaps among cities, cities with top ranks of UEWP being tourist cities such as Qingdao and Haikou instead of the economically developed cities such as Shanghai or Beijing, the capital city of China. 2) Spatially, the east of China ranks first, and the middle and the west of China are in the second and the third place respectively. 3) The Tobit regressive analysis on the influencing factors of UEWP demonstrates that urban population density and green space are positive factors, and economic scale and industrial structure are negative factors of UEWP. Finally, some constructive suggestions are proposed.
Based on the research and analysis about the characteristics of the evolution path of China’s residential natural gas consumption during 2000-2014, we calculated the contribution rate of China’s eight regions to the evolution of the gravity center with Shapley value. Then, using the method of LMDI decomposition, the growth of China’s residential natural gas consumption was decomposed into three influencing factors, which were infrastructure, service efficiency and demand, and the reasons and rules of regional contribution to the gravity center evolution were discussed. The results show that: the migration of the gravity center has undergone three stages: to northwest, to southeast and to northeast during 2000-2014. The main forces of gravity center migration of residential natural gas consumption were the northwest, the southwest and the northeast during 2000-2003, the east coast and the southern coast during 2003-2008, the east coast, the northern coast and the middle reach of Yangtze River during 2008-2014. During 2000-2014, infrastructure factor was always the main driving force of the growth of residential natural gas consumption in China and in each region, while service efficiency and demand factor will gradually become the main driving forces in most regions in the future.
Agricultural flood and drought are the major factors that constrain the agricultural production in China. In view of the deficiency of information diffusion theory model, an entropy information diffusion theory model for agricultural flood and drought risk assessment was built in this paper, and a case was taken which verified that the entropy information diffusion theory model is superior to the information diffusion theory model in the aspect of estimation results. Then, the entropy information diffusion theory model is employed to assess the risk of agricultural flood and drought in the 30 provinces/municipalities/autonomous regions of the mainland of China (Chongqing city is contained in Sichuan Province) based on the data gathered during the period of 1985-2013, and a comprehensive comparative analysis is conducted on the agricultural flood and drought risks in China based on the assessment result. According to the evaluation and the analysis, China is faced with serious agricultural flood and drought risk; the agricultural drought risk is obviously higher than the agricultural flood risk in China; agricultural flood and drought risks exhibit a remarkable spatial pattern; the high and medium risk area of agricultural flood are mainly found in the middle and lower reaches of Yangtze River and Northeast China, while the high risk area of agricultural drought disaster are mainly observed in the northern part of China and Northeast China. According to the spatial distribution pattern of agricultural floods and droughts in China, the southern part of China is susceptible to flood, the northern part of China is susceptible to drought, and Northeast China is faced with the overlapped effect of flood and drought.
This study aims to evaluate the impact of land use/cover change (LUCC), especially rapid urbanization, on annual runoff change in Taihu Basin, where monsoonal flood is prone to happen. Xitiaoxi River Basin, one of the main sub-basins of Taihu Lake Basin, was chosen as study area to study the spatial variation of runoff under different land use conditions. A new spatial analysis method called geographically weighted regression model (GWR) was employed to quantitatively evaluate the impact of LUCC on runoff variation. The monthly runoff process was generated by SWAT model (Soil and Water Assessment Tool). The results showed that: 1) All R2 and Nash-Sutcliffe efficiency ENS were above 0.85, and the relative errors |Re| were all less than 15% in the calibration and validation period, suggesting SWAT model perform well. 2) The runoff change was spatially nonstationary, and was significantly correlated with the mostly changed type of land use in the sub-basin, among which the influence of urban land-use had the greatest influence, followed by the forest-grass land and cultivated land. Urban land-use expansion could increase local regional runoff depth by 37.6%-45.2%, while the forest-grass land and cultivated land shrinking could increase local regional runoff depth by 16%-26.2% and 9.2%-15.4% respectively. 3) Spatially, the influence of urban land-use change on runoff depth increased gradually from upstream to downstream in the basin. On the contrary, the impacts of the forest-grass land and cultivated land on runoff process presented decline trend from upstream to downstream. 4) Compared with single-factor GWR model, the multifactorial GWR model had better prediction accuracy and was more suitable to analyze the spatial relationship between runoff and LUCC.
Research of shrub encroachment is becoming an important field in the researches of the global change of terrestrial ecosystem, because grasslands have undergone a period of change in community structure and composition in the arid and semiarid regions on the earth. This study investigated effects of encroachment of Caragana microphylla Lam. on soil and soil hydrological processes in grassland of Inner Mongolia, with field observation and laboratory experiment, wishing to provide theoretical foundation for environment protection and restoration in arid and semiarid regions. Results showed that, soil organic matter, total nitrogen, sand content, silt content, clay content, soil bulk density and the position of upper surface of caliches in soil layers under canopies of shrub patches were 1.54, 1.16, 0.87, 1.34, 1.35, 0.97 and 1.27 times of those under canopies of grass patches, respectively. In addition, topography was one of the important natural factors which formed soil spatial heterogeneity. Soil organic matter, total nitrogen, soil bulk density and the position of caliches in soil layers under canopies of shrub and grass patches all had increasing trend from the top position to the lower position at slope scale. Results of dye tracing experiment showed that wetting front on soil profiles and velocity of soil water infiltration in soil layers under canopies of shrub patches were 1.36 and 5.16 times of those under canopies of grass patches, respectively. Soil water was more sensitive at the upper 0-10 cm soil layers under canopies of grass patches, but it was more sensitive at the soil layers below 25 cm under shrub patches. This study suggested that shrub encroachment strengthened soil heterogeneity, soil water under canopies of shrub patches can be rapidly transported to the deeper soil layers, and soil layers under canopies of shrub could capture more soil nutrients and water. There were positive feedbacks between the development and settlement of C. microphylla and soil morphology in the typical steppe in Inner Mongolia.
Guangxi was known as “the hometown of nonferrous metals”, and the problem of heavy metal pollution in soil was very prominent. Based on the published papers about arsenic(As) in Guangxi since 1989 and our previous work in Guilin, Nandan and Huanjiang, this study explored the concentration and pollution distribution of As in soils and sediments in Guangxi. Totally, 3 045 soil samples and 477 sediment samples were collected. Results showed that: 1) In Guangxi, the As polluted soil mainly distributed in the northwest of Guangxi, especially in the Diaojiang and Jinchengjiang River basins. 2) Mining activity affected the accumulation of As in soil significantly. The soils with concentrations of As from high to low in order were non-agricultural soil in industrial and mining areas (140.5 mg/kg), agricultural soil in industrial and mining areas (80.68 mg/kg), agricultural soil in non-industrial and mining areas (19.11 mg/kg) and urban soil (18.35 mg/kg). Compared with the standard of soil environment quality in China (GB15618-1995), 89.4%, 69.0%, 18.7% and 12.1% of the above four types of soil samples exceeded the standard limit. The most seriously polluted samples in agricultural soil were all in Nandan. 3) The accumulation of As in marine sediments (8.76 mg/kg) and river sediments in non-industrial and mining areas (16.11 mg/kg) were not remarkable. As for river sediments, the pollution levels of As in industrial and mining areas (283.5 mg/kg) were much higher than those in non-industrial and mining areas. The affected areas mainly distributed in the Diaojiang and Dahuanjiang basins. In order to control the environmental risk, it is recommended to carry out the survey of As pollution in the surface sediments of the main river systems in Guangxi, especially in the river of Diaojiang, Dahuanjiang and Jinchengjiang, and the pollution in Nandan areas should be controlled and prevented and the contaminated soil should be repaired.
The quantitative assessment on spatial pattern of ecosystem service of water yield in a basin has important significance for management and optimal allocation of water resource, and improvement of ecological and environmental conservation capacity. Based on basic geographical data of land use, meteorology and soil attribute in the study area, the paper used InVEST model to evaluate the amount of water yield in Nansi Lake Basin, quantitatively assessing the spatial distribution feature of water supply ability from 1990 to 2013 in the whole basin. The relationships between the dynamic spatial pattern of water yield and natural geographic elements such as precipitation, landform, and socioeconomic factors such as GDP and population were discussed. The basin was divided into several zones according to the water resources function. The result showed that the spatial pattern of water yield presents a decreasing trend from east to west, water yield being high in the east and northeast, and water yield being relatively low in west and other regions in Nansi Lake Basin. Affected by natural geographical elements, the spatial distribution of water yield is inconsistent with the spatial distribution of social economic development level, namely GDP and population. Water yield in the basin was in decreasing trend in past 25 years, and the peak area of water yield shifted from the northeast to the south area, but low yield area shifted from the west to the central region. There are significant positive correlations between the variation of water yield and physical geographical environment factors, such as precipitation, DEM and slope, and the correlation between the variation of water yield and precipitation is the strongest. There are significant positive correlations between variation of water yield and social economic factors of GDP and population, since urbanization caused the increase of urban construction land and other impervious surfaces which promoted water yield. The results of the study provide scientific support for water resources policy, social and economic development planning, and macro decision making.
Based on monthly temperature data from 80 stations in Anhui Province, the long term daily temperature were analyzed during 1960-2014. The characteristics of temperature change were analyzed by using the linear regression, Mann-Kendall (M-K) test, rescaled range (R/S) analysis, wavelet transforms and other mathematic statistic methods. Important results were obtained as follows: 1) There was a significant climate warming trend in Anhui Province during recent 55 years (0.19 ℃/10 a, P = 0.005). Significant increase trends were also found in the spring, autumn and winter temperature. The spring average temperature had the largest and most obvious trend of increase (0.29 ℃/10 a, P < 0.001). The trend of average summer temperature was not obvious (0.01 ℃/10 a, P = 0.069). The annual average temperature showed big fluctuation in 1990s. 2) An abrupt change of the temperature wavelike rising tendency in 1996 was detected by M-K test. The temperature increased by 0.82 ℃ after the change point. The annual average temperature had a great change and the warming trend was very significant. There were significant change points of average spring temperature, autumn temperature and winter temperature in 1999, 1998 and 1986, respectively. And there were no significant change point of average summer temperature. 3) The oscillating periods of average temperature in the past 55 years was complex, being a nested structure of multiple time scales. The wavelet analysis showed that there were two periods of 5-8 years and 10-15 years for the oscillation of temperature in Anhui Province. After the analysis of wavelet variance plots, it was found that main cycles of annual mean temperature were 6 years and 11 years. 4) Hurst indexes of annual mean temperature and seasonal temperature were all greater than 0.5. It indicated that there will be obvious Hurst phenomenon in the future (Hurst index was 0.891), which means that there is tendency of the climate change in Anhui Province during recent 55 years. The Hurst index was higher in spring and winter, and the warming rate in winter was higher than that in summer and autumn. It could be deduced that the increase of temperature in spring and winter was the main contributor to the increase of annual average temperature. The result of this paper can be used as a reference for further analysis of climate change as well as the impacts of climate change and the responses of water resources to climate change in Anhui Province.
Air quality is directly related to human health and sustainable development of economy and society. Based on the air quality data of four key cities in Heilongjiang Province in 2014, combined with the conventional meteorological data during the same time, the basic characteristics of air quality index (AQI) in Heilongjiang Province and the relationship with meteorological elements were analyzed. The results show that annual average AQI in Harbin was the largest (slightly polluted), followed by Mudanjiang, Daqing, Qiqihar (good). The highest value of daily AQI happened in Daqing (500), followed by Harbin (490). The highest single day values in Mudanjiang and Qiqihar were 264 and 251, respectively. Winter had the highest seasonal average of AQI, followed by autumn and spring, and summer had the lowest average value. The primary pollutant was PM2.5, followed by PM10, NO2 and ozone for 8 hours. The AQI index and the average temperature were negatively correlated at the annual scale, while mainly positively correlated at the monthly and seasonal scale. AQI index was negatively correlated with precipitation, and positively correlated with the relative humidity in coldest months (January-February), while negatively related with the relative humidity in warmer months (May-June). There was significant negative correlation between AQI and maximum wind speed in heating season. And AQI is positively related to the station pressure, and negatively related to the sunshine hours in winter.
The form and function of rural dwelling are closely related to livelihood strategies of famers. This article takes three villages (Hetaoyuan, Gaoqiao and Tangjiazhuangzi) in Yishui County, Shandong Province as the case studies, and explores livelihood changes of famers and their relationship with the evolution of rural dwelling form and function in Yimeng Mountain with participatory rural appraisal method. The results are shown as follows: 1) Before the reform and opening-up, farming was the main livelihood activity of famers. Being compatible with their demand of livelihood, the farmers built dwellings with bungalows and courtyards, and cultivated vegetables in the courtyards. 2) After the reform and opening-up, livestock breeding became one important livelihood activity of farmers. They built pigsties in their dwellings to raise pigs, and raised poultries in the courtyards. Meanwhile, there were more non-agricultural livelihoods and the livelihoods diversified. Farmers in Gaoqiao Village developed non-agricultural industry in their village. Being compatible with their demand of livelihood, they built two-story houses and used the ground floor for business. 3) Since the 21st century, livelihoods of farmers became more and more non-agricultural and differentiated. Farming and cross-regional non-agricultural employment were the main livelihood strategies in Hetaoyuan Village. Farmers made hard ground of their courtyards for grain drying, and transformed the pigsties to storage room for grain and agricultural implements. In order to expand non-agricultural industry space, farmers in Gaoqiao Village built three-story houses and used the ground floor and second floor for their individual businesses. Most farmers in Tangjiazhuangzi Village went to the county for non-agricultural employment. In order to improve the living environment, they built two-story houses without spaces for business. This paper suggested that the form and function of rural dwelling are adapted to the livelihood of farmers. The government should respect the livelihoods of farmers when building dwellings during the rural residential land consolidation.
