Summary Life‐cycle assessment (LCA) practitioners build models to quantify resource consumption, environmental releases, and potential environmental and human health impacts of product systems. Most often, practitioners define a model structure, assign a single value to each parameter, and build deterministic models to approximate environmental outcomes. This approach fails to capture the variability and uncertainty inherent in LCA. To make good decisions, decision makers need to understand the uncertainty in and divergence between LCA outcomes for different product systems. Several approaches for conducting LCA under uncertainty have been proposed and implemented. For example, Monte Carlo simulation and fuzzy set theory have been applied in a limited number of LCA studies. These approaches are well understood and are generally accepted in quantitative decision analysis. But they do not guarantee reliable outcomes. A survey of approaches used to incorporate quantitative uncertainty analysis into LCA is presented. The suitability of each approach for providing reliable outcomes and enabling better decisions is discussed. Approaches that may lead to overconfident or unreliable results are discussed and guidance for improving uncertainty analysis in LCA is provided.

By reducing the energy and materials required to provide goods and services, nanotechnology has the potential to provide more appealing products while improving environmental performance and sustainability. Whether and how soon this potential could be realized depends on phrasing the right research and development (R&D) questions and pursuing commercialization intelligently. A sufficiently broad perspective at the outset is required to understand economic and technical feasibility, estimate life cycle environmental implications, and minimize unanticipated negative impacts. The rapid rise in federally funded nanotechnology R&D dictates that consideration of societal benefits will have a large role in setting the R&D agenda. We estimate potential selected economic and environmental impacts associated with the use of nanotechnology in the automotive industry. In particular, we project the material processing and fuel economy benefits associated with using a clay-polypropylene nanocomposite instead of steel or aluminum in light-duty vehicle body panels. Although the manufacturing cost is currently higher, a life cycle analysis shows potential benefits in reducing energy use and environment discharges by using a nanocomposite design.

Due to advances in nanotechnology, the approach to catalytic design is transitioning from trial-and-error to planned design and control. Expected advances should enable the design and construction of catalysts to increase reaction speed, yield, and catalyst durability while also reducing active species loading levels. Nanofabrication techniques enabling precise control over the shape, size, and position of nanoscale platinum-group metal (PGM) particles in automotive catalysts should result in reduced PGM loading levels. These reductions would decrease energy consumption, improve environmental quality, and contribute to sustainable resource usage. We estimate the amount of PGM required to meet U.S. vehicle emissions standards through 2030 based on current catalysttechnology. We then estimate the range of PGM that could be saved from potential nanotechnology advances. Finally, we employ economic input-output and process-based life cycle assessment models to estimate the direct and life cycle benefits from reducing PGM mining and refining.

While large companies routinely announce greenhouse gas emissions targets, few have derived targets based on global climate goals. This changed in 2015 with the creation of the science based targets (SBTs) initiative, which provides guidelines for setting emission targets in line with the temperature goal of the Paris Agreement. SBTs have now been set by more than 500 companies. Methods for setting such targets are not presented in a comparable way in target-setting guidelines and concerns that certain methods may lead to overshoot of the temperature goal have not been investigated. Here, we systematically characterize and compare all seven broadly applicable target-setting methods and quantify the balance between collective corporate SBTs and global allowable emissions for individual methods and different method mixes. We use a simplified global production scenario composed of eight archetypical companies to evaluate target-setting methods across a range of company characteristics and global emission scenarios. The methods vary greatly with respect to emission allocation principles, required company variables and embedded global emission scenarios. Some methods treat companies largely the same, while others differentiate between company types based on geography, economic sector, projected growth rate or baseline emission intensity. The application of individual target-setting methods as well as different mixes of methods tend to result in an imbalance between time-integrated aggregated SBTs and global allowable emissions. The sign and size of this imbalance is in some cases sensitive to the shape of the global emission pathway and the distribution of variables between the company archetypes. We recommend that the SBT initiative (a) use our SBT method characterisation to present methods in a systematic way, (b) consider our emission imbalance analysis in its method recommendations, (c) disclose underlying reasons for its method recommendations, and (d) require transparency from companies on the calculation of established SBTs.

Summary Integrating occupational safety and health (OSH) into life cycle assessment (LCA) may provide decision makers with insights and opportunities to prevent burden shifting of human health impacts between the nonwork environment and the work environment. We propose an integration approach that uses industry‐level work environment characterization factors (WE‐CFs) to convert industry activity into damage to human health attributable to the work environment, assessed as disability‐adjusted life years (DALYs). WE‐CFs are ratios of work‐related fatal and nonfatal injuries and illnesses occurring in the U.S. worker population to the amount of physical output from U.S. industries; they represent workplace hazards and exposures and are compatible with the life cycle inventory (LCI) structure common to process‐based LCA. A proof of concept demonstrates application of the WE‐CFs in an LCA of municipal solid waste landfill and incineration systems. Results from the proof of concept indicate that estimates of DALYs attributable to the work environment are comparable in magnitude to DALYs attributable to environmental emissions. Construction and infrastructure‐related work processes contributed the most to the work environment DALYs. A sensitivity analysis revealed that uncertainty in the physical output from industries had the most effect on the WE‐CFs. The results encourage implementation of WE‐CFs in future LCA studies, additional refinement of LCI processes to accurately capture industry outputs, and inclusion of infrastructure‐related processes in LCAs that evaluate OSH impacts.