David E. Meyer

The use of life cycle tools to support decision making for sustainable nanotechnologies

Nanotechnology is a broad-impact technology with applications ranging from materials and electronics to analytical methods and metrology. The many benefits that can be realized through the utilization of nanotechnology are intended to lead to an improved quality of life. However, numerous concerns have been expressed regarding the unchecked growth of nanotechnology and the unforeseen consequences it may bring. To address the concerns, nanotechnology must be examined under the microscope of sustainability. This work applies the life cycle perspective to provide an understanding of the challenges facing the development of sustainable nanotechnology. A discussion of the holistic tools used to assess the components of sustainability serves as the basis to examine how a harmony between policy and product development can be maintained using decision making for sustainability. This harmony will be most readily achieved using an enhanced risk management strategy for sustainability that combines sustainability assessment with sustainable chemical design.

Mining Available Data from the United States Environmental Protection Agency to Support Rapid Life Cycle Inventory Modeling of Chemical Manufacturing

Demands for quick and accurate life cycle assessments create a need for methods to rapidly generate reliable life cycle inventories (LCI). Data mining is a suitable tool for this purpose, especially given the large amount of available governmental data. These data are typically applied to LCIs on a case-by-case basis. As linked open data becomes more prevalent, it may be possible to automate LCI using data mining by establishing a reproducible approach for identifying, extracting, and processing the data. This work proposes a method for standardizing and eventually automating the discovery and use of publicly available data at the United States Environmental Protection Agency for chemical-manufacturing LCI. The method is developed using a case study of acetic acid. The data quality and gap analyses for the generated inventory found that the selected data sources can provide information with equal or better reliability and representativeness on air, water, hazardous waste, on-site energy usage, and production volumes but with key data gaps including material inputs, water usage, purchased electricity, and transportation requirements. A comparison of the generated LCI with existing data revealed that the data mining inventory is in reasonable agreement with existing data and may provide a more-comprehensive inventory of air emissions and water discharges. The case study highlighted challenges for current data management practices that must be overcome to successfully automate the method using semantic technology. Benefits of the method are that the openly available data can be compiled in a standardized and transparent approach that supports potential automation with flexibility to incorporate new data sources as needed.

A new data architecture for advancing life cycle assessment

IntroductionLife cycle assessment (LCA) has a technical architecture that limits data interoperability, transparency, and automated integration of external data. More advanced information technologies offer promise for increasing the ease with which information can be synthesized within an LCA framework.VisionA new architecture is described that combines, stores, and annotates data for life cycle assessment. The Resource Description Framework is proposed for managing LCA data. To explore the capabilities of this approach, the LCA Harmonization Tool (LCA-HT) is being developed to map and store data from different sources and to clearly capture user-defined relationships between nomenclatures for easy use. It will enable increased interoperability of LCA data and more structured and automated incorporation of non-LCA data into LCA models.Moving forwardThe LCA-HT is intended to be a core component of LCA data architecture (a data commons) used by US federal agencies and other data providers to make data representing US conditions more accessible for public use. It will also be used to bring together data from human health exposure models with traditional LCA for evaluating near-field human health risk in the life cycle context to demonstrate the practical advancements possible with this new architecture. The tool will remain open source and freely available.

Evaluating the Environmental Impacts of a Nano-Enhanced Field Emission Display Using Life Cycle Assessment: A Screening-Level Study

Carbon nanotube (CNT) field emission displays (FEDs) are currently in the product development stage and are expected to be commercialized in the near future because they offer image quality and viewing angles comparable to a cathode ray tube (CRT) while using a thinner structure, similar to a liquid crystal display (LCD), and enable more efficient power consumption during use. To address concerns regarding the environmental performance of CNT-FEDs, a screening-level, cradle-to-grave life cycle assessment (LCA) was conducted based on a functional unit of 10,000 viewing hours, the viewing lifespan of a CNT-FED. Contribution analysis suggests the impacts for material acquisition and manufacturing are greater than the combined impacts for use and end-of-life. A scenario analysis of the CNT paste composition identifies the metal components used in the paste are key contributors to the impacts of the upstream stages due to the impacts associated with metal preparation. Further improvement of the manufacturing impacts is possible by considering the use of plant-based oils, such as rapeseed oil, as alternatives to organic solvents for dispersion of CNTs. Given the differences in viewing lifespan, the impacts of the CNT-FED were compared with a LCD and a CRT display to provide more insight on how to improve the CNT-FED to make it a viable product alternative. When compared with CRT technology, CNT-FEDs show better environmental performance, whereas a comparison with LCD technology indicates the environmental impacts are roughly the same. Based on the results, the enhanced viewing capabilities of CNT-FEDs will be a more viable display option if manufacturers can increase the products expected viewing lifespan.

USEEIO: A new and transparent United States environmentally-extended input-output model

National-scope environmental life cycle models of goods and services may be used for many purposes, not limited to quantifying impacts of production and consumption of nations, assessing organization-wide impacts, identifying purchasing hotspots, analyzing environmental impacts of policies, and performing streamlined life cycle assessment. USEEIO is a new environmentally-extended input-output model of the United States fit for such purposes and other sustainable materials management applications. USEEIO melds data on economic transactions between 389 industry sectors with environmental data for these sectors covering land, water, energy and mineral usage and emissions of greenhouse gases, criteria air pollutants, nutrients and toxics, to build a life cycle model of 385 US goods and services. In comparison with existing US models, USEEIO is more current with most data representing year 2013, more extensive in its coverage of resources and emissions, more deliberate and detailed in its interpretation and combination of data sources, and includes formal data quality evaluation and description. USEEIO is assembled with a new Python module called the IO Model Builder capable of assembling and calculating results of user-defined input-output models and exporting the models into LCA software. The model and data quality evaluation capabilities are demonstrated with an analysis of the environmental performance of an average hospital in the US. All USEEIO files are publicly available bringing a new level of transparency for environmentally-extended input-output models.

Coupling Computer-Aided Process Simulation and Estimations of Emissions and Land Use for Rapid Life Cycle Inventory Modeling

A methodology is described for developing a gate-to-gate life cycle inventory (LCI) of a chemical manufacturing process to support the application of life cycle assessment in the design and regulation of sustainable chemicals. The inventories were derived by first applying process design and simulation to develop a process flow diagram describing the energy and basic material flows of the system. Additional techniques developed by the United States Environmental Protection Agency for estimating uncontrolled emissions from chemical processing equipment were then applied to obtain a detailed emission profile for the process. Finally, land use for the process was estimated using a simple sizing model. The methodology was applied to a case study of acetic acid production based on the Cativa process. The results reveal improvements in the qualitative LCI for acetic acid production compared to commonly used databases and top-down methodologies. The modeling techniques improve the quantitative LCI results for inputs and uncontrolled emissions. With provisions for applying appropriate emission controls, the proposed method can provide an estimate of the LCI that can be used for subsequent life cycle assessments.

Exploring the relevance of spatial scale to life cycle inventory results using environmentally-extended input-output models of the United States

The accuracy of direct and indirect resource use and emissions of products as quantified in life cycle models depends in part upon the geographical and technological representativeness of the production models. Production conditions vary not just between nations, but also within national boundaries. Understanding the level of geographic resolution within large industrial nations needed to reach acceptable accuracy has not been well-tested across the broad spectrum of goods and services consumed. Using an aggregate 15-industryenvironmentally-extended input-output model of the US along with detailed interstate commodity flow data, we test the accuracy of regionalizing the national model into two-regions (state - rest of US) versus 51 regions (all US states + DC). Our findings show the two-region form predicts life cycle emissions and resources used within 10-20% of the more detailed 51-region form for most of the environmental flows studied. The two-region form is less accurate when higher variability exists in production conditions for a product.

Comparative Human Health Impact Assessment of Engineered Nanomaterials in the Framework of Life Cycle Assessment.

For safe innovation, knowledge on potential human health impacts is essential. Ideally, these impacts are considered within a larger life-cycle-based context to support sustainable development of new applications and products. A methodological framework that accounts for human health impacts caused by inhalation of engineered nanomaterials (ENMs) in an indoor air environment has been previously developed. The objectives of this study are as follows: (i) evaluate the feasibility of applying the CF framework for NP exposure in the workplace based on currently available data; and (ii) supplement any resulting knowledge gaps with methods and data from the life cycle approach and human risk assessment (LICARA) project to develop a modified case-specific version of the framework that will enable near-term inclusion of NP human health impacts in life cycle assessment (LCA) using a case study involving nanoscale titanium dioxide (nanoTiO2 ). The intent is to enhance typical LCA with elements of regulatory risk assessment, including its more detailed measure of uncertainty. The proof-of-principle demonstration of the framework highlighted the lack of available data for both the workplace emissions and human health effects of ENMs that is needed to calculate generalizable characterization factors using common human health impact assessment practices in LCA. The alternative approach of using intake fractions derived from workplace air concentration measurements and effect factors based on best-available toxicity data supported the current case-by-case approach for assessing the human health life cycle impacts of ENMs. Ultimately, the proposed framework and calculations demonstrate the potential utility of integrating elements of risk assessment with LCA for ENMs once the data are available.

A process systems framework for rapid generation of life cycle inventories for pollution control and sustainability evaluation

Life cycle assessment (LCA) is a tool that aids in sustainable decision-making among product and process alternatives. When implementing LCA, the efficient and accurate modeling of chemical processes for life cycle inventory (LCI) generation is still challenging. Challenges include a lack of systematic design and simulation tools and approaches to develop chemical process models for obtaining and analyzing more realistic LCI results. In this contribution, a novel process systems framework is proposed for estimating LCI results when implementing pollution control technologies. This framework involves the development and incorporation of pollution control unit (PCU) modules into process simulation and generation of LCI data associated with the PCUs for use in a sustainability evaluation. Different pollution control modules are designed for rapid LCI estimation and applied to obtain emissions, utility consumption, material, and land footprint results related to waste streams of a process simulation. Then, the LCI results are analyzed with the objectives of minimizing the environmental impact and utility consumption. The proposed framework is illustrated via a biomass/coal gasification process for syngas production with the end goal of acetic acid manufacturing. Results associated with this case study show that the developed framework can provide guidelines for sustainable decision-making based on generated LCI results.

LCA in Relation to Risk Assessment

Life cycle assessment (LCA) and risk assessment (RA) are both tools used in policy fields to inform environmentally based decisions. As such, there are several areas of overlap, but also fundamental differences in perspectives, methodologies, and decision-making endpoints. One fundamental difference between these two fields is that LCA evaluates and integrates information across multiple impact categories such as water use, climate change, ozone depletion, with the multiimpact considerations meant to avoid burden shifting (e.g., reductions in one impact category lead to increases in other impact categories). RA, on the other hand, is generally limited to a single endpoint such as human or ecosystem health. Although, in some cases RA can be used to assess risks to both of these endpoints. With this in mind, this article begins with a review of key RA principles using human health (HH) RA of chemicals as an example. This will lay the foundation for a thoughtful comparison of HHRA and human toxicity in LCA that will identify both the overlaps and divergences of the two methods. Specific examples of how the tools have been or could possibly be combined are then discussed to illustrate the comprehensiveness such integration can add to decision making.