食物-能源-水钮带关系研究能否与农业创新保持同步?

1.Introduction,The interconnection among food-energy-water(FEW)systems in meeting societal demands is broadly acknowledged[1].Similarly,competitive or synergistic allocations of water and energy resources for agricultural production,manufacturing,and human consumption are understood,and their economic impacts can be predicted[2].Far less appreciated and understood are the outcomes of the FEW nexus in response to operation changes in agricultural practices and the associated technological innovations for future generations[3,4].Also,the inter-scale and feedback effects of emerging technology-driven resource reallocation and decision-making on FEW systems are largely unknown.For example,how do the agroeconomic feedbacks of intelligent technologies influence the FEW nexus of agricultural production under environmental and demographic changes?How does the necessary water allocation for powering non-powered dams and pumped-storage hydropower generation influence agricultural production and municipal water supply maintenance?How do solar and wind energy farms influence land use for agriculture and the rural economy?

Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades

Fire is a major type of disturbance that has important influences on ecosystem dynamics and carbon cycles.Yet our understanding of ecosystem fires and their carbon cycle consequences is still limited,largely due to the difficulty of large-scale fire monitoring and the complex interactions between fire,vegetation,climate,and anthropogenic factors.Here,using data from satellite-derived fire observations and ecosystem model simulations,we performed a comprehensive investigation of the spatial and temporal dynamics of China’s ecosystem fire disturbances and their carbon emissions over the past two decades(1997–2016).Satellite-derived results showed that on average about 3.47-4.53×10^(4) km^(2) of the land was burned annually during the past two decades,among which annual burned forest area was about 0.81-1.25×10^(4) km^(2),accounting for 0.33-0.51%of the forest area in China.Biomass burning emitted about 23.02 TgC per year.Compared to satellite products,simulations from the Energy Exascale Earth System Land Model(ELM)strongly overestimated China’s burned area and fire-induced carbon emissions.Annual burned area and fire-induced carbon emissions were high for boreal forest in Northeast China’s Daxing’anling region and subtropical dry forest in South Yunnan,as revealed by both the satellite product and the model simulations.Our results suggest that climate and anthropogenic factors play critical roles in controlling the spatial and seasonal distribution of China’s ecosystem fire disturbances.Our findings highlight the importance of multiple complementary approaches in assessing ecosystem fire disturbance and its carbon consequences.Further studies are required to improve the methods of observing and modelling China’s ecosystem fire disturbances,which will provide valuable information for fire management and ecosystem sustainability in an era when both human activities and the natural environment are rapidly changing.

High-sensitivity infrared vibrational nanospectroscopy in water

Mid-infrared vibrational spectroscopy is a universal label-free tool for identifying molecular compounds in chemical and biological samples on the basis of their‘fingerprint’vibrational absorption lines.Vibrational spectroscopy with nanometer spatial resolution can reveal the chemical composition of samples at the nanoscale,and several scanning-probe techniques have been developed to address this need1–22.It is also highly desirable to study biological and chemical samples in their native aqueous environments rather than in air.In aqueous environments,however,the sensitivity of the current vibrational nanospectroscopy techniques deteriorates dramatically7,23.Here,we report the first mid-infrared nanospectroscopy technique that retains nanoscale sensitivity and spatial resolution when the sample and the scanning probe are completely immersed in water.This method overcomes challenges including water absorption and scattering and the mechanical damping of cantilever vibrations.We further demonstrate spectroscopy and imaging of 20-to 50-nmthick polymer samples with a 25-nm spatial resolution in the biologically relevant Amide I and II spectral regions.

Incorporating transportation network modeling tools within transportation economic impact studies of disasters

Transportation system disruption due to a disaster results in ＂ripple effects＂ throughout the entire transportation system of a metropolitan region. Many researchers have focused on the economic costs of transportation system disruptions in transportation-related industries, specifically within commerce and logistics, in the assessment of the regional economic costs. However, the foundation of an assessment of the regional economic costs of a disaster needs to include the evaluation of consumer surplus in addition to the direct cost for reconstruction of the regional transportation system. The objective of this study is to propose a method to estimate the regional consumer surplus based on indirect economic costs of a disaster on intermodal transportation systems in the context of diverting vehicles and trains. The computational methods used to assess the regional indirect economic costs sustained by the highway and railroad system can utilize readily available state departments of transportation （DOTs） and metropolitan planning organizations （MPOs） traffic models allowing prioritization of regional recovery plans after a disaster and strengthening of infrastructure before a disaster. Hurricane Katrina is one of the most devastating hurricanes in the history of the United States. Due to the significance of Hurricane Katrina, a case study is presented to evaluate consumer surplus in the Gulf Coast Region of Mississippi. Results from the case study indicate the costs of rerouting and congestion delays in the regional highway system and the rent costs of fight-of-way in the regional railroad system are major factors of the indirect costs in the consumer surplus.

Interannual variability and climatic sensitivity of global wildfire activity

Understanding historical wildfire variations and their environmental driving mechanisms is key to predicting and mitigating wildfires. However, current knowledge of climatic responses and regional contributions to the interannual variability (IAV) of global burned area remains limited. Using recent satellite-derived wildfire products and simulations from version v1.0 of the land component of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM land model [ELM] v1) driven by three different climate forcings, we investigated the burned area IAV and its climatic sensitivity globally and across nine biomes from 1997 to 2018. We found that 1) the ELM simulations generally agreed with the satellite observations in terms of the burned area IAV magnitudes, regional contributions, and covariations with climate factors, confirming the robustness of the ELM to the usage of different climate forcing sources;2) tropical savannas, tropical forests, and semi-arid grasslands near deserts were primary contributors to the global burned area IAV, collectively accounting for 71.7%–99.7% of the global wildfire IAV estimated by both the satellite observations and ELM simulations;3) precipitation was a major fire suppressing factor and dominated the global and regional burned area IAVs, and temperature and shortwave solar radiation were mostly positively related with burned area IAVs;and 4) noticeable local discrepancies between the ELM and remote-sensing results occurred in semi-arid grasslands, croplands, boreal forests, and wetlands, likely caused by uncertainties in the current ELM fire scheme and the imperfectly derived satellite observations. Our findings revealed the spatiotemporal diversity of wildfire variations, regional contributions and climatic responses, and provided new metrics for wildfire modeling, facilitating the wildfire prediction and management.