How is water-use efficiency of terrestrial ecosystems distributed and changing on Earth?

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Environmental impact assessments of the Three Gorges Project in China: issues and interventions

The paper takes China's authoritative Environmental Impact Statement for the Yangzi (Yangtze) Three Gorges Project (TGP) in 1992 as a benchmark against which to evaluate emerging major environmental outcomes since the initial impoundment of the Three Gorges reservoir in 2003. The paper particularly examines five crucial environmental aspects and associated causal factors. The five domains include human resettlement and the carrying capacity of local environments (especially land), water quality, reservoir sedimentation and downstream riverbed erosion, soil erosion, and seismic activity and geological hazards. Lessons from the environmental impact assessments of the TGP are: (1) hydro project planning needs to take place at a broader scale, and a strategic environmental assessment at a broader scale is necessary in advance of individual environmental impact assessments; (2) national policy and planning adjustments need to react quickly to the impact changes of large projects; (3) long-term environmental monitoring systems and joint operations with other large projects in the upstream areas of a river basin should be established, and the cross-impacts of climate change on projects and possible impacts of projects on regional or local climate considered. © 2013 Elsevier B.V.Xibao Xu, Yan Tan, Guishan Yan

Antitumor Effect of Malaria Parasite Infection in a Murine Lewis Lung Cancer Model through Induction of Innate and Adaptive Immunity

BACKGROUND: Lung cancer is the most common malignancy in humans and its high fatality means that no effective treatment is available. Developing new therapeutic strategies for lung cancer is urgently needed. Malaria has been reported to stimulate host immune responses, which are believed to be efficacious for combating some clinical cancers. This study is aimed to provide evidence that malaria parasite infection is therapeutic for lung cancer. METHODOLOGY/PRINCIPAL FINDINGS: Antitumor effect of malaria infection was examined in both subcutaneously and intravenously implanted murine Lewis lung cancer (LLC) model. The results showed that malaria infection inhibited LLC growth and metastasis and prolonged the survival of tumor-bearing mice. Histological analysis of tumors from mice infected with malaria revealed that angiogenesis was inhibited, which correlated with increased terminal deoxynucleotidyl transferase-mediated (TUNEL) staining and decreased Ki-67 expression in tumors. Through natural killer (NK) cell cytotoxicity activity, cytokine assays, enzyme-linked immunospot assay, lymphocyte proliferation, and flow cytometry, we demonstrated that malaria infection provided anti-tumor effects by inducing both a potent anti-tumor innate immune response, including the secretion of IFN-γ and TNF-α and the activation of NK cells as well as adaptive anti-tumor immunity with increasing tumor-specific T-cell proliferation and cytolytic activity of CD8(+) T cells. Notably, tumor-bearing mice infected with the parasite developed long-lasting and effective tumor-specific immunity. Consequently, we found that malaria parasite infection could enhance the immune response of lung cancer DNA vaccine pcDNA3.1-hMUC1 and the combination produced a synergistic antitumor effect. CONCLUSIONS/SIGNIFICANCE: Malaria infection significantly suppresses LLC growth via induction of innate and adaptive antitumor responses in a mouse model. These data suggest that the malaria parasite may provide a novel strategy or therapeutic vaccine vector for anti-lung cancer immune-based therapy

Deep Reinforcement Learning-Based Accurate Control of Planetary Soft Landing

Planetary soft landing has been studied extensively due to its promising application prospects. In this paper, a soft landing control algorithm based on deep reinforcement learning (DRL) with good convergence property is proposed. First, the soft landing problem of the powered descent phase is formulated and the theoretical basis of Reinforcement Learning (RL) used in this paper is introduced. Second, to make it easier to converge, a reward function is designed to include process rewards like velocity tracking reward, solving the problem of sparse reward. Then, by including the fuel consumption penalty and constraints violation penalty, the lander can learn to achieve velocity tracking goal while saving fuel and keeping attitude angle within safe ranges. Then, simulations of training are carried out under the frameworks of Deep deterministic policy gradient (DDPG), Twin Delayed DDPG (TD3), and Soft Actor Critic (SAC), respectively, which are of the classical RL frameworks, and all converged. Finally, the trained policy is deployed into velocity tracking and soft landing experiments, results of which demonstrate the validity of the algorithm proposed

Deep Reinforcement Learning-Based Accurate Control of Planetary Soft Landing

Planetary soft landing has been studied extensively due to its promising application prospects. In this paper, a soft landing control algorithm based on deep reinforcement learning (DRL) with good convergence property is proposed. First, the soft landing problem of the powered descent phase is formulated and the theoretical basis of Reinforcement Learning (RL) used in this paper is introduced. Second, to make it easier to converge, a reward function is designed to include process rewards like velocity tracking reward, solving the problem of sparse reward. Then, by including the fuel consumption penalty and constraints violation penalty, the lander can learn to achieve velocity tracking goal while saving fuel and keeping attitude angle within safe ranges. Then, simulations of training are carried out under the frameworks of Deep deterministic policy gradient (DDPG), Twin Delayed DDPG (TD3), and Soft Actor Critic (SAC), respectively, which are of the classical RL frameworks, and all converged. Finally, the trained policy is deployed into velocity tracking and soft landing experiments, results of which demonstrate the validity of the algorithm proposed

Changing pattern and driving factors of ecosystem service value of the lakes in Northern China since 1990

Lakes in Northern China are widely distributed with large surface areas, and play a crucial role in maintaining ecological security in the northern regions of China. In this study, based on the relationship between ecosystem services (ES) value and lake key indicators, including lake area, potential evapotranspiration, comprehensive trophic level index (TLI), precipitation, and lake volume, the lake ecoservice production functions (LEPFs) were constructed to evaluate lake ecosystem service value (LESV) in Northern China. Subsequently, the driving factors influencing LESV were identified at the lake-basin scale. The results showed that the total LESV in Northern China increased from 5,088.7 billion yuan in 1990 to 5,112.9 billion yuan in 2020, by increasing 0.47%. The total LESV of Xinjiang (XJ) and Tibetan Plateau (TP) lake regions showed an increasing trend, with rates of 5.39% and 2.32%, respectively. However, those of Inner Mongolia Plateau (IMP), Northeast Plain and Mountains (NPM), and Eastern Plain (EP) lake regions showed a decrease, with rates of 19.83%, 6.29%, and 1.72%, respectively. The changing rate in LESV varied significantly among different lake regions. Approximately 30% and 40% of the lakes in XJ and TP lake regions had a growth rate exceeding 0.3 billion yuan, while 86% and 14% of lakes in NPM and IMP lake regions experienced a decline exceeding 0.3 billion yuan, respectively. 40% of the lakes in EP lake region had a growth rate of less than 0.05 billion yuan, and 60% of the lakes had a decline rate of less than 0.05 billion yuan. The average temperature, precipitation, impervious area, and water area within the lake-basins had a significant impact on LESV. Among them, the effect of climate change on LESV was higher than that of the anthropogenic factors. These findings can provide helpful references for the assessing methods of the LESV at a large regional scale and developing lake conservation policies

Modelling the Impacts of Different Policy Scenarios on Urban Growth in Lanzhou with Remote Sensing and Cellular Automata

Abstract-Integration of remote sensing and CA has been the frontier edge of the urban research. This paper presents an application of remote sensing and cellular automata in modelling the impacts of different policy scenarios on urban growth in Lanzhou, China. SLEUTH urban growth model, was introduced and coupled with remote sensing loosely. SLEUTH was an extended cellular automata model, developed with predefined growth rules applied spatially to grid maps of cities, and designed to be both scaleable and universally applicable. SLEUTH is an acronym for the input layers that the model uses in gridded map form: Slope, Land Use, Exclusion, Urban Extent, Transportation and Hillshade. In this paper, the main built-up area of Lanzhou is chose as the study area, which is a typical valley-basin city. Historical data sets derive from aerial photos of 1980 (1:10000) and 2001(1:4000), and Landsat TM images collected in 1986 and 1993.And three different policy scenarios were designed to explore its different impacts on urban growth, respective to calibration and prediction of the model. The first scenario was without any consideration given to urban planning or policy; the second scenario considered urban planning and policies, but only 50% implementation of the overall plan or policies; the third scenario considered full implementation of the urban plan and polices. The calibrations of the three scenarios all reflect the restrictive land use for development in Lanzhou, and the intentions to control the sprawl strictly. The progressive urban developments are projected into the future 20 years under three different scenarios. Compared with statistic and spatial distribution under different scenarios, it can be concluded the impacts of policies on urban growth in Lanzhou are profound, and the government plays a very important role in urban growth. And the second scenario is more close to the reality, the implementation of urban planning and policies in the reality is not very good and there are still many problems about urban planning and decision-making in urban growth of Lanzhou, such as arbitrary and scientific

Three Gorges Project: effects of resettlement on nutrient balance of the agroecosystems in the reservoir area

This paper reports on the effects of human resettlement on the nutrient balance of the agroecosystems in Three Gorges Reservoir Area (TGRA) of China. The analysis used is the OECD (Organisation for Economic Co-operation and Development) 'Soil Surface Nitrogen Balance Model' and agricultural statistical data for the county level in 1985-2005. Spatial and temporal changes of nutrient balance and the impacts of resettlement on such changes were examined. The results demonstrate that rural resettlement has significantly increased soil surface nitrogen and phosphorous surplus since 2000. The structural transformation of agricultural activities from grain production to horticulture or forestry should be encouraged, and more people may need to be moved out of the TGRA to reduce nutrient water pollution.Three Gorges Project, resettlement, nutrient balance, agroecosystems,

Urban household carbon emission and contributing factors in the Yangtze River Delta, China.

Carbon reduction at the household level is an integral part of carbon mitigation. This study analyses the characteristics, effects, contributing factors and policies for urban household carbon emissions in the Yangtze River Delta of China. Primary data was collected through structured questionnaire surveys in three cities in the region--Nanjing, Ningbo, and Changzhou in 2011. The survey data was first used to estimate the magnitude of household carbon emissions in different urban contexts. It then examined how, and to what extent, each set of demographic, economic, behavioral/cognitive and spatial factors influence carbon emissions at the household level. The average of urban household carbon emissions in the region was estimated to be 5.96 tonnes CO2 in 2010. Energy consumption, daily commuting, garbage disposal and long-distance travel accounted for 51.2%, 21.3%, 16.0% and 11.5% of the total emission, respectively. Regulating rapidly growing car-holdings of urban households, stabilizing population growth, and transiting residents' low-carbon awareness to household behavior in energy saving and other spheres of consumption in the context of rapid population aging and the growing middle income class are suggested as critical measures for carbon mitigation among urban households in the Yangtze River Delta