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AbstractChina is under pressure to improve its agricultural productivity to keep up with the demands of a growing population with increasingly resource‐intensive diets. This productivity improvement must occur against a backdrop of carbon intensity reduction targets, and a highly fragmented, nutrient‐inefficient farming system. Moreover, the Chinese government increasingly recognizes the need to rationalize the management of the 800 million tonnes of agricultural crop straw that China produces each year, up to 40% of which is burned in‐field as a waste. Biochar produced from these residues and applied to land could contribute to China's agricultural productivity, resource use efficiency and carbon reduction goals. However competing uses for China's straw residues are rapidly emerging, particularly from bioenergy generation. Therefore it is important to understand the relative economic viability and carbon abatement potential of directing agricultural residues to biochar rather than bioenergy. Using cost‐benefit analysis (CBA) and life‐cycle analysis (LCA), this paper therefore compares the economic viability and carbon abatement potential of biochar production via pyrolysis, with that of bioenergy production via briquetting and gasification. Straw reincorporation and in‐field straw burning are used as baseline scenarios. We find that briquetting straw for heat energy is the most cost‐effective carbon abatement technology, requiring a subsidy of $7 MgCO2e−1 abated. However China's current bioelectricity subsidy scheme makes gasification (NPV $12.6 million) more financially attractive for investors than both briquetting (NPV $7.34 million), and pyrolysis ($−1.84 million). The direct carbon abatement potential of pyrolysis (1.06 MgCO2e per odt straw) is also lower than that of briquetting (1.35 MgCO2e per odt straw) and gasification (1.16 MgCO2e per odt straw). However indirect carbon abatement processes arising from biochar application could significantly improve the carbon abatement potential of the pyrolysis scenario. Likewise, increasing the agronomic value of biochar is essential for the pyrolysis scenario to compete as an economically viable, cost‐effective mitigation technology.

A pot experiment was undertaken to investigate the effects of Cd and Cu mixtures to growth and nutrients (sugar, carotene or vitamin C) of carrot and pakchoi under greenhouse cultivation condition. The study included: (a) physical-chemical properties of soil and soil animals in response to Cd and Cu stress; (b) bioaccumulation of heavy metals, length, biomass, contents of sugar and carotene (vitamin C) of carrot and pakchoi; (c) estimation the effects of Cd and Cu mixtures by multivariate regression analysis. The results implied that heavy metals impacted negative influence on soil animals' abundance. The metals contents in plants increased obviously with Cd and Cu contamination in soil. The biomass production and nutrients declined with Cd and Cu contents increasing. Cd (20 mg kg-1) treatment caused maximum reduction of sugar content (45.29%) in carrot root; maximum reduction in carotene content (75.73%) in carrot, 75.1% sugar content reduction and 70.58% vitamin C content reduction in pakchoi shoots were observed with addition of Cd (20 mg kg-1) and Cu (400 mg kg-1) mixture. The results of multivariate regression analysis indicated that combination of Cd and Cu exerts negative effects to both carrot and pakchoi, and both growth and nutrients were negatively correlated with metals concentrations. It is concluded that the Cd and Cu mixtures caused toxic damage to vegetable plants as Cd and Cu gradient concentrations increased.

Farmland is the most basic material condition for guaranteeing rural livelihoods and national food security, and exploring management strategies that take both stable rural livelihoods and sustainable farmland use into account has vital significance in theory and practice. Farmland is a complex and self-adaptive system that couples human and natural systems, and natural and social factors that are related to its changing process need to be considered when modeling farmland changing processes. This paper uses Qianjingou Town in the Inner Mongolian farming–pastoral zone as a study area. From the perspective of the relationship between household livelihood and farmland use, this study establishes the process mechanism of farmland use change based on questionnaire data, and constructs a multi-agent simulation model of farmland use change using the Eclipse and Repast toolbox. Through simulating the relationship between natural factors (including geographical location) and household behavior, this paper systematically simulates household farmland abandonment and rent behaviors, and accurately describes the dynamic interactions between household livelihoods and the factors related to farmland use change. These factors include natural factors (net primary productivity, road accessibility, slope and relief amplitude) and social factors (household family structures, economic development and government policies). Ultimately, this study scientifically predicts the future farmland use change trend in the next 30 years. The simulation results show that the number of abandoned and sublet farmland plots has a gradually increasing trend, and the number of non-farming households and pure-outworking households has a remarkable increasing trend, whereas the number of part-farming households and pure-farming households has a decreasing trend. Household livelihood sustainability in the study area is confronted with increasing pressure, and household non-farm employment has an increasing trend, while regional appropriate-scale agricultural management is maintained. The research results establish the theoretical foundation and a basic method for developing sustainable farmland use management that can meet the willingness of households and guarantee grain and ecological security.

Abstract Biomass, as a renewable and sustainable energy resource, can be converted into environmentally friendly and practically valuable biofuels and chemical materials via pyrolysis. However, the process optimization and pyrolysis efficiency are restricted by the limited perception of the complicated mechanisms and kinetics for biomass pyrolysis. Here, to establish an in-depth mechanism model for biomass pyrolysis, we presented a novel investigation for the thermal evolutions and pyrolysis kinetics of the functional groups in peanut shell matrix by using in-situ Fourier transform infrared spectrometry (in-situ FTIR) and thermogravimetric analysis-Fourier transform infrared spectrometry-mass spectrometry (TG-FTIR-MS). The in-situ FTIR spectrum deconvolution for the solid matrix was innovatively introduced to identify and quantify the real-time evolution and thermal dynamics of the functional groups during peanut shell pyrolysis. The result for the first time proposed that the pyrolysis mechanisms of total OH at 20–380 °C, aliphatic C-Hn groups at 20–500 °C, C O groups at 260–500 °C, and C–O groups at 300–500 °C were dominant by diffusion and order-based chemical reactions. The TG-FTIR-MS analysis was conducted for the online monitoring of the released volatiles and gases, the amounts of which were in the sequence of C O > CO2 > aliphatic C–O-(H) > C–O-(C) in esters > aromatics > H2O > phenolic hydroxyl > aliphatic hydrocarbons > CO. The study established a novel methodology to evaluate the biomass pyrolysis mechanisms at the molecular level, which provided valuable information for developing advanced pyrolysis techniques on a large scale for sustainable ecosystem.

AbstractAlthough the process of microbial degradation of coal to produce biomethane has got much attention from many research works, the products profiles of coal at the initial stage of methanogenic bioconversion are not clear yet. In this study, five coal‐degrading bacterial strains (CD1, CD10, CD20, CD24, and CD25) from a methanogenic community were isolated and identified. Among them, CD1 and CD24 belong to Paenibacillus sp., CD10 and CD20 belong to Bacillus sp., and CD25 belongs to Stenotrophomonas sp. After biotreatment of lignite and bituminous coal, the kinds of newly produced compounds were 33 and 45, respectively. Metabolomics analysis showed that a large number of alkane compounds and heterocyclic aromatic compounds were produced after degradation of bituminous coal and lignite by isolated bacteria, and most of the compounds had been produced in a hydroxylated or acylated manner, indicating that the initial microbial treatment enhanced the bioavailability of coal. Some alkaloids and biosurfactants were also detected in the aforementioned products, such as glycerophosphocholine, proveratrol A, proveratrol B, surfactin, etc. These microbial metabolites may play an important role in solubilization during the degradation of coal. This study added to the understanding of the complicated metabolic process of methanogenic coal bioconversion and enabled effective production of biomethane with appropriate metabolic strategies.

The first decade of the new millennium saw a boom in rubber prices. This led to rapid and widespread land conversion to monoculture rubber plantations in continental SE Asia, where natural rubber production has increased >50% since 2000. Here, we analyze the subsequent spread of rubber between 2005 and 2010 in combination with environmental data and reports on rubber plantation performance. We show that rubber has been planted into increasingly sub-optimal environments. Currently, 72% of plantation area is in environmentally marginal zones where reduced yields are likely. An estimated 57% of the area is susceptible to insufficient water availability, erosion, frost, or wind damage, all of which may make long-term rubber production unsustainable. In 2013 typhoons destroyed plantations worth US$ >250 million in Vietnam alone, and future climate change is likely to lead to a net exacerbation of environmental marginality for both current and predicted future rubber plantation area. New rubber plantations are also frequently placed on lands that are important for biodiversity conservation and ecological functions. For example, between 2005 and 2010 >2500 km(2) of natural tree cover and 610 km(2) of protected areas were converted to plantations. Overall, expansion into marginal areas creates potential for loss-loss scenarios: clearing of high-biodiversity value land for economically unsustainable plantations that are poorly adapted to local conditions and alter landscape functions (e.g. hydrology, erosion) - ultimately compromising livelihoods, particularly when rubber prices fall. (C) 2015 Elsevier Ltd. All rights reserved.

Asseng, S. et al. Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time. We thank the Agricultural Model Intercomparison and Improvement Project and its leaders C. Rosenzweig from NASA Goddard Institute for Space Studies and Columbia University (USA), J. Jones from University of Florida (USA), J. Hatfield from United States Department of Agriculture (USA) and J. Antle from Oregon State University (USA) for support. We also thank M. Lopez from CIMMYT (Turkey), M. Usman Bashir from University of Agriculture, Faisalabad (Pakistan), S. Soufizadeh from Shahid Beheshti University (Iran), and J. Lorgeou and J-C. Deswarte from ARVALIS—Institut du Végétal (France) for assistance with selecting key locations and quantifying regional crop cultivars, anthesis and maturity dates and R. Raymundo for assistance with GIS. S.A. and D.C. received financial support from the International Food Policy Research Institute (IFPRI). C.S. was funded through USDA National Institute for Food and Agriculture award 32011-68002-30191. C.M. received financial support from the KULUNDA project (01LL0905L) and the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (BMBF). F.E. received support from the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (2812ERA115) and E.E.R. was funded through the German Science Foundation (project EW 119/5-1). M.J. and J.E.O. were funded through the FACCE MACSUR project by the Danish Strategic Research Council. K.C.K. and C.N. were funded by the FACCE MACSUR project through the German Federal Ministry of Food and Agriculture (BMEL). F.T., T.P. and R.P.R. received financial support from FACCE MACSUR project funded through the Finnish Ministry of Agriculture and Forestry (MMM); F.T. was also funded through National Natural Science Foundation of China (No. 41071030). C.B. was funded through the Helmholtz project ‘REKLIM—Regional Climate Change: Causes and Effects’ Topic 9: ‘Climate Change and Air Quality’. M.P.R. and P.D.A. received funding from the CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS). G.O’L. was funded through the Australian Grains Research and Development Corporation and the Department of Environment and Primary Industries Victoria, Australia. R.C.I. was funded by Texas AgriLife Research, Texas A&M University. E.W. and Z.Z. were funded by CSIRO and the Chinese Academy of Sciences (CAS) through the research project ‘Advancing crop yield while reducing the use of water and nitrogen’ and by the CSIRO-MoE PhD Research Program. Peer reviewed