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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.

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.