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The consideration of tariffs on China’s imports of US agricultural products has focused on economic impacts, while the environmental consequences have received less attention. Here we use a global computable general equilibrium model to evaluate long-term crop portfolio changes induced by China’s retaliatory agricultural tariffs and thereby assess the environmental stresses imposed by different crop production portfolios based on region-specific and crop-specific databases. We show that China’s tariffs cause unintended increases in nitrogen and phosphorus pollution and blue water extraction in the United States as farmers shift from soybeans to more pollution-causing crops. If diverted to Brazil, China’s soybean demands would reduce Brazilian stresses of nitrogen pollution and water use through crop portfolio changes, but may add additional pressures on phosphorus pollution and deforestation. On a global scale, trade policies could help to reduce nutrient pollution and water source depletion by promoting crop production where it is most efficient in terms of nutrient and water use. The potential environmental consequences driven by US–China crop trade tension are considerable and could spill over to other countries, especially Brazil and other South American countries, through international trade. Such consequences are predominantly driven by China’s proposed retaliation on US soybeans.

To improve the surface quality of GCr15 steel parts, research on GCr15 steel strengthening is of great significance. In the present study, the variation in the surface roughness and the surface res...

International agricultural trade has changed land uses in trading countries, altering global food security and environmental sustainability. Studies have concluded that local land-use drivers are largely from global sources (e.g., trade increases deforestation in exporting countries). However, little is known about how these local land-use changes affect distant locations, namely the feedback between them. Yet these distant impacts and feedbacks can be significant for governing local land systems. The framework of telecoupling (i.e., socioeconomic-environmental interactions between distant places) has been shown to be an effective conceptual tool to study international trade and the associated socio-economic and environmental impacts. However, a systems simulation tool to quantify the telecoupled causes and effects is still lacking. Here, we construct a new type of agent-based model (ABM) that can simulate land-use changes at multiple distant places (namely TeleABM, telecoupled agent-based model). We use soybean trade between Brazil and China as an example, where Brazil is the sending system and China is the receiving system because they are the world?s largest soybean exporter and importer respectively. We select one representative county in each country to calibrate and validate the model with spatio-temporal analysis of historical land-use changes and the empirical analysis of household survey data. We describe the model following the ODD+D protocol, and validate the model results in each location respectively. We then illustrate how the aggregated farmer agents? land-use behaviors in the sending system result in land-use changes in the receiving system, and vice versa. One scenario example (i.e., a high-tariff scenario) is given to demonstrate the results of TeleABM. Such a model allows us to advance the understanding of telecoupling features and the influence on land system science, and to test hypotheses about complex coupled human-natural systems (e.g., cascading effect). Made available in DSpace on 2020-08-14T11:11:17Z (GMT). No. of bitstreams: 1 AP-Land-use-change-2020.pdf: 1685927 bytes, checksum: 2745faebef29dafc24524c47f74b2f42 (MD5) Previous issue date: 2020 Article 11.

Nitrogen is a critical component of the economy, food security, and planetary health. Many of the world's sustainability targets hinge on global nitrogen solutions, which, in turn, contribute lasting benefits for (i) world hunger; (ii) soil, air, and water quality; (iii) climate change mitigation; and (iv) biodiversity conservation. Balancing the projected rise in agricultural nitrogen demands while achieving these 21st century ideals will require policies to coordinate solutions among technologies, consumer choice, and socioeconomic transformation. Fil: Houlton, Benjamin Z.. University of California; Estados Unidos Fil: Almaraz, Maya. University of California; Estados Unidos Fil: Aneja, Viney. North Carolina State University; Estados Unidos Fil: Austin, Amy Theresa. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Bai, Edith. Chinese Academy of Sciences; República de China. Northeast Normal University; China Fil: Cassman, Kenneth G.. University of Nebraska; Estados Unidos Fil: Compton, Jana E.. Environmental Protection Agency; Estados Unidos Fil: Davidson, Eric A.. University of Maryland; Estados Unidos Fil: Willem Erisman, Jan. Department of Earth Sciences; Países Bajos. Louis Bolk Institute; Países Bajos Fil: Galloway, James N.. University of Virginia; Estados Unidos Fil: Gu, Baojing. Zhejiang University; China Fil: Yao, Guolin. University of Maryland; Estados Unidos Fil: Martinelli, Luiz A.. Universidade de Sao Paulo; Brasil Fil: Scow, Kate. University of California; Estados Unidos Fil: Schlesinger, William H.. Cary Institute of Ecosystem Studies; Estados Unidos Fil: Tomich, Thomas P.. University of California; Estados Unidos Fil: Wang, Chao. Chinese Academy of Sciences; República de China Fil: Zhang, Xin. University of Maryland; Estados Unidos

China’s food demand is projected to grow and reshape its production and trade relations. A new study evaluates the consequent challenges for agricultural land, greenhouse gas emissions, fertilizer and irrigation water use in China and its trading partners.

Agriculture is fundamental to all three pillars of sustainability, environment, society, and economy. However, the definition of sustainable agriculture and the capacities to measure it remain elusive. Independent and transparent measurements of national sustainability are needed to gauge progress, encourage accountability, and inform policy. Here, we developed a Sustainable Agriculture Matrix (SAM) to quantify national performance indicators in agriculture and to investigate the trade-offs and synergies based on historical data for most countries of the world. The results reveal priority areas for improvement by each country and show that the trade-offs and synergies among indicators often differ. Exceptions to common economic-versus-environmental trade-offs, for example, offer opportunities to learn from countries with synergistic pathways for multiple sustainability indicators. These SAM indicators will improve as data become more available, but this version offers a useful starting point for evaluating progress, identifying priorities for improvement, and informing national policies and actions toward sustainable agriculture., One Earth, 4 (9), ISSN:2590-3322

The ratification of Sustainable Development Goals (SDGs) by all member countries of the United Nations demonstrates the determination of the international community in moving towards a sustainable ...

Telecoupling is a novel concept describing simultaneous multiscale interactions between human and natural systems across long distances. One important vehicle for telecoupling is international agricultural trade, which has previously been addressed using multiregional input-output (MRIO) methods. This study advances that work by accounting for market-mediating factors based on the GTAP-BIO model. We apply this framework to analyze the economic and environmental consequences of the Brazilian soybean boom. We decompose the drivers of this telecoupled system into five groups – macroeconomic growth, soybean productivity, other crop productivity, government policies, and pasture and forestry factors – quantifying each socio-economic driver’s local and distant contributions to all human and natural changes in this system. We find that China’s macroeconomic growth boosted soybean production and exports from Brazil and the US, whereas macroeconomic growth in the latter two regions actually dampened soybean exports over the 2004–2011 period under examination. Brazil’s strong soybean productivity growth over this period, allowed that country to become dominant in the global soybean market. It also had strong spillover effects, displacing the US in the Chinese market and reducing overall growth in soybean output in the US. This strong soybean productivity growth also contributed to cropland expansion in Brazil.

The aim of this work is to control the physical and mechanical properties of a spline surface and achieve a reasonable choice of high-speed cold roll-beating processing parameters. The surface residual stress and surface work hardening at the indexing circle serve as the main evaluation indices of the physical and mechanical properties of the spline surface. The influence degree of the processing parameters on each evaluation index is analyzed using Taguchi theory. An optimized model for improving the Taguchi process capability index that combines Taguchi theory with entropy theory is established, and the integral process capacity index is optimized via the generalized price reduction gradient method. The results of the optimization and the verification test are implemented in a high-speed cold roll forming test for comparison. The results show that the influence of processing parameters on the physical and mechanical properties of the splash surface of the cold roll can be ordered as follows: feed rate > roll round radius > cold roll-beating speed. In addition, the spline surface physical and mechanical properties of the optimal processing parameters were obtained for the combination of a cold rolling speed of 1581 r/mm, feed rate of 42 mm/min, and roll round radius of 2 mm.

Techno-economic analysis (TEA) is a well-established modeling process for evaluating the economic feasibility of emerging technologies. Most previous TEA studies focused on creating reliable cost estimates but returned deterministic net present values (NPV) and deterministic breakeven prices which cannot convey the considerable uncertainties embedded in important techno-economic variables. This study employs stochastic techno-economic analysis in which Monte Carlo simulation is incorporated into traditional TEA. The distributions of NPV and breakeven price are obtained. A case of cellulosic biofuel production from fast pyrolysis and hydroprocessing pathway is used to illustrate the method of modeling stochastic TEA and quantifying the breakeven price distribution. The input uncertainties are translated to outputs so that the probability density distribution of both NPV and breakeven price are derived. Two methods, a mathematical method and a programming method, are developed to quantify breakeven price distribution in a way that can consider future price trend and uncertainty. Two scenarios are analyzed, one assuming constant real future output prices, and the other assuming that future prices follow an increasing trend with stochastic disturbances. It is demonstrated that the breakeven price distributions derived using the developed methods are consistent with the corresponding NPV distributions regarding the percentile value and the probability of gain/loss. The results demonstrate how breakeven price distributions communicate risks and uncertainties more effectively than NPV distributions. The stochastic TEA and the methods of creating breakeven price distribution can be applied to evaluating other technologies.

Background Alcohol-to-jet (ATJ) is one of the technical feasible biofuel technologies. It produces jet fuel from sugary, starchy, and lignocellulosic biomass, such as sugarcane, corn grain, and switchgrass, via fermentation of sugars to ethanol or other alcohols. This study assesses the ATJ biofuel production pathway for these three biomass feedstocks, and advances existing techno-economic analyses of biofuels in three ways. First, we incorporate technical uncertainty for all by-products and co-products though statistical linkages between conversion efficiencies and input and output levels. Second, future price uncertainty is based on case-by-case time-series estimation, and a local sensitivity analysis is conducted with respect to each uncertain variable. Third, breakeven price distributions are developed to communicate the inherent uncertainty in breakeven price. This research also considers uncertainties in utility input requirements, fuel and by-product outputs, as well as price uncertainties for all major inputs, products, and co-products. All analyses are done from the perspective of a private firm. Results The stochastic dominance results of net present values (NPV) and breakeven price distributions show that sugarcane is the lowest cost feedstock over the entire range of uncertainty with the least risks, followed by corn grain and switchgrass, with the mean breakeven jet fuel prices being $0.96/L ($3.65/gal), $1.01/L ($3.84/gal), and $1.38/L ($5.21/gal), respectively. The variation of revenues from by-products in corn grain pathway can significantly impact its profitability. Sensitivity analyses show that technical uncertainty significantly impacts breakeven price and NPV distributions. Conclusions Technical uncertainty is critical in determining the economic performance of the ATJ fuel pathway. Technical uncertainty needs to be considered in future economic analyses. The variation of revenues from by-products plays a significant role in profitability. With the distribution of breakeven prices, potential investors can apply whatever risk preferences they like to determine an appropriate bid or breakeven price that matches their risk profile., United States. Federal Aviation Administration. Office of Environment and Energy (ASCENT Project [107208] under FAA Award Number [13-C-AJFE-PU])

Additional file 1. Supplementary materials and descriptions of regression functions of each sub-process of ATJ production, first-order and second-order stochastic dominance, and Welch's t-test result for breakeven price distribution.

China increasingly relies on agricultural imports, driven by its rising population and income, as well as dietary shifts. International trade offers an opportunity to relieve pressures on resource depletion and pollution, such as nitrogen (N) pollution, while it poses multiple socioeconomic challenges, such as food availability. To quantify such trade-offs considering the roles of different crop types, we developed a unique crop-specific N budget database and assessed the impacts of the crop trade on multiple sustainability concerns including N pollution caused by crop production, crop land area, independence of food supply, and trade expenditures. We quantified the ‘virtual’ N inputs and harvested areas, which are the amount of N inputs and land resources used in exporting countries for China’s crop import. In addition, we proposed the concepts of ‘alternative’ N inputs and harvested area to quantify the resources needed if imported crops were produced in China. By comparing results from ‘alternative’ and ‘virtual’ concepts, we assessed the role of trade in Chinese crops over the past 30 years (i.e. 1986–2015) in alleviating N pollution and saving cropland in China and the world. Crop imports accounted for 31% of Chinese crop N consumption in 2015, and these crop imports eased the need for an additional cropland area of 62 million ha. It also avoided an N surplus by 56 and 36 Tg (Tg = 109 kg) for China and the world respectively but led to $621 billion crop trade expenditures over the 30 year period. The N pollution damage avoided by crop imports in economic terms was priced at $22 ± 16 billion in 2015, which is lower than the crop trade expenditures but may be surpassed in the future with the development of the Chinese economy. Optimizing a crop trade portfolio can shift domestic production from N-intensive crop production (e.g. maize, fruits, and vegetables) to N-efficient crop production (e.g. soybeans), and consequently mitigate an N surplus by up to 12%. Improving N use efficiency for individual crops can further increase the mitigation potential of N surplus to 30%–50%, but requires technology advancement and policy incentives.

Techno-economic analysis (TEA) is a well-established modeling process in which benefit-cost analysis (BCA) is used to evaluate the economic feasibility of emerging technologies. Most previous TEA studies focused on creating reliable cost estimates but returned deterministic net present values (NPV) and deterministic breakeven prices. Nevertheless, the deterministic results cannot convey the considerable uncertainties embedded in techno-economic variables such as capital investment, conversion technology yield, and output prices. We obtain distributions of NPV, IRR, and breakeven price. The breakeven price is the most important indicator in TEA because it is independent of scale and communicates results effectively. The deterministic breakeven price is the price for which there is a 50 percent probability of earning more or less than the stipulated rate of return. For an investment under relatively high uncertainty, it is unlikely that investors would provide financing to a project with a 50 percent probability of loss. The point estimate breakeven price, therefore, does not represent the threshold under which investment would occur. In this study, we introduce the stochastic techno-economic analysis in which we incorporate Monte Carlo simulation into traditional TEA. A case of cellulosic biofuel production from fast pyrolysis and hydroprocessing pathway is used to illustrate the method of modeling stochastic TEA and quantifying the breakeven price distribution. The input uncertainties are translated to outputs so that the probability density distribution of both NPV and breakeven price are derived. Two methods, a mathematical method and a programming method, are developed to quantify breakeven price distribution in a way that can consider future price trend and uncertainty. We analyze two scenarios, one assuming constant real future output prices, and the other assuming that future prices follow an increasing trend with stochastic disturbances. We demonstrate that the breakeven price distributions derived using our methods are consistent with the corresponding NPV distributions regarding the percentile value and the probability of gain/loss.

In order to reveal the impact of the rolling thermal coupling friction on the cold roll-beating during high speedcold roll-beating forming process, involute spline as the research object, established a high-speed cold roll-beating finite element model, the changes of elasto-plastic deformation and thermo-mechanical coupling stress during involute spline cold roll-beating contact are studied; and the distribution of temperature, stress and strain field under a single stroke; the stress, strain and temperature curves of the key elements are extracted, and the influence of temperature on the thermal coupling stress and strain is analyzed. The results show: in the process of cold roll-beating, the gradient distribution of strain field, temperature field and stress field in the area of severe deformation is very large, while the temperature, stress and strain of other small deformation areas are low; high strain and high temperature are mainly distributed in the direct contact with the rolling wheel surface area; the temperature generated during cold roll-beating reduces stress and increases the effectiveness of metal flow.