The aim of this paper is to examine the environmental consequences of beef meat production in the EU, using a life cycle approach. Four beef production systems were studied – three from intensively reared dairy calves and one from suckler herds. According to the results of the analysis, the contributions from the production of 1 kg beef meat (slaughter weight) to global warming, acidification, eutrophication, land use and non-renewable energy use were lower for beef from dairy calves than from suckler herds (16.0–19.9 versus 27.3 kg CO2e, 101–173 versus 210 g SO2e, 622–1140 versus 1651 g NO3e, 16.5–22.7 versus 42.9 m2year, and 41.3–48.2 versus 59.2 MJ, respectively). The breakdown analysis helped identify the key areas in the “cradle to farm gate” beef production system where sustainable management strategies are needed to improve environmental performance. The study also included a sensitivity analysis to preliminarily estimate GHG emissions from beef production systems if land opportunity cost and land use change related to grazing and feed crop production for beef were taken into account. If so, the contribution from the production of 1 kg beef to global warming would increase by a factor of 3.1–3.9, based on a depreciation period of 20 years. This highlights the importance of taking into account the impacts of land use in assessing the environmental impacts of livestock production. 相似文献
The electric power grid is a critical societal resource connecting multiple infrastructural domains such as agriculture, transportation, and manufacturing. The electrical grid as an infrastructure is shaped by human activity and public policy in terms of demand and supply requirements. Further, the grid is subject to changes and stresses due to diverse factors including solar weather, climate, hydrology, and ecology. The emerging interconnected and complex network dependencies make such interactions increasingly dynamic, posing novel risks, and presenting new challenges to manage the coupled human–natural system. This paper provides a survey of models and methods that seek to explore the significant interconnected impact of the electric power grid and interdependent domains. We also provide relevant critical risk indicators (CRIs) across diverse domains that may be used to assess risks to electric grid reliability, including climate, ecology, hydrology, finance, space weather, and agriculture. We discuss the convergence of indicators from individual domains to explore possible systemic risk, i.e., holistic risk arising from cross-domain interconnections. Further, we propose a compositional approach to risk assessment that incorporates diverse domain expertise and information, data science, and computer science to identify domain-specific CRIs and their union in systemic risk indicators. Our study provides an important first step towards data-driven analysis and predictive modeling of risks in interconnected human–natural systems.
