Dwarakanath Ravikumar

Illustrating Anticipatory Life Cycle Assessment for Emerging Photovoltaic Technologies

Current research policy and strategy documents recommend applying life cycle assessment (LCA) early in research and development (R&D) to guide emerging technologies toward decreased environmental burden. However, existing LCA practices are ill-suited to support these recommendations. Barriers related to data availability, rapid technology change, and isolation of environmental from technical research inhibit application of LCA to developing technologies. Overcoming these challenges requires methodological advances that help identify environmental opportunities prior to large R&D investments. Such an anticipatory approach to LCA requires synthesis of social, environmental, and technical knowledge beyond the capabilities of current practices. This paper introduces a novel framework for anticipatory LCA that incorporates technology forecasting, risk research, social engagement, and comparative impact assessment, then applies this framework to photovoltaic (PV) technologies. These examples illustrate the potential for anticipatory LCA to prioritize research questions and help guide environmentally responsible innovation of emerging technologies.

Intertemporal Cumulative Radiative Forcing Effects of Photovoltaic Deployments

Current policies accelerating photovoltaics (PV) deployments are motivated by environmental goals, including reducing greenhouse gas (GHG) emissions by displacing electricity generated from fossil-fuels. Existing practice assesses environmental benefits on a net life-cycle basis, where displaced GHG emissions offset those generated during PV production. However, this approach does not consider that the environmental costs of GHG release during production are incurred early, while environmental benefits accrue later. Thus, where policy targets suggest meeting GHG reduction goals established by a certain date, rapid PV deployment may have counterintuitive, albeit temporary, undesired consequences. On a cumulative radiative forcing (CRF) basis, the environmental improvements attributable to PV might be realized much later than is currently understood, particularly when PV manufacturing utilizes GHG-intensive energy sources (e.g., coal), but deployment occurs in areas with less GHG-intensive electricity sources (e.g., hydroelectric). This paper details a dynamic CRF model to examine the intertemporal warming impacts of PV deployments in California and Wyoming. CRF payback times are longer than GHG payback times by 6-12 years in California and 6-11 years in Wyoming depending on the PV technology mix and deployment strategy. For the same PV capacity being deployed, early installations yield greater CRF benefits (calculated over 10 and 25 years) than installations occurring later in time. Further, CRF benefits are maximized when PV technologies with the lowest manufacturing GHG footprint (cadmium telluride) are deployed in locations with the most GHG-intensive grids (i.e., Wyoming).

The impact of photovoltaic (PV) installations on downwind particulate matter concentrations: Results from field observations at a 550-MWAC utility-scale PV plant

ABSTRACT With utility-scale photovoltaic (PV) projects increasingly developed in dry and dust-prone geographies with high solar insolation, there is a critical need to analyze the impacts of PV installations on the resulting particulate matter (PM) concentrations, which have environmental and health impacts. This study is the first to quantify the impact of a utility-scale PV plant on PM concentrations downwind of the project site. Background, construction, and post-construction PM2.5 and PM10 (PM with aerodynamic diameters <2.5 and <10 μm, respectively) concentration data were collected from four beta attenuation monitor (BAM) stations over 3 yr. Based on these data, the authors evaluate the hypothesis that PM emissions from land occupied by a utility-scale PV installation are reduced after project construction through a wind-shielding effect. The results show that the (1) confidence intervals of the mean PM concentrations during construction overlap with or are lower than background concentrations for three of the four BAM stations; and (2) post-construction PM2.5 and PM10 concentrations downwind of the PV installation are significantly lower than the background concentrations at three of the four BAM stations. At the fourth BAM station, downwind post-construction PM2.5 and PM10 concentrations increased marginally by 5.7% and 2.6% of the 24-hr ambient air quality standards defined by the U.S. Environmental Protection Agency, respectively, when compared with background concentrations, with the PM2.5 increase being statistically insignificant. This increase may be due to vehicular emissions from an access road near the southwest corner of the site or a drainage berm near the south station. The findings demonstrate the overall environmental benefit of downwind PM emission abatement from a utility-scale PV installation in desert conditions due to wind shielding. With PM emission reductions observed within 10 months of completion of construction, post-construction monitoring of downwind PM levels may be reduced to a 1-yr period for other projects with similar soil and weather conditions. Implications: This study is the first to analyze impact of a utility photovoltaic (PV) project on downwind particulate matter (PM) concentration in desert conditions. The PM data were collected at four beta attenuation monitor stations over a 3-yr period. The post-construction PM concentrations are lower than background concentrations at three of four stations, therefore supporting the hypothesis of post-construction wind shielding from PV installations. With PM emission reductions observed within 10 months of completion of construction, postconstruction monitoring of downwind PM levels may be reduced to a 1-yr period for other PV projects with similar soil and weather conditions.

Novel Method of Sensitivity Analysis Improves the Prioritization of Research in Anticipatory Life Cycle Assessment of Emerging Technologies

It is now common practice in environmental life cycle assessment (LCA) to conduct sensitivity analyses to identify critical parameters and prioritize further research. Typical approaches include variation of input parameters one at a time to determine the corresponding variation in characterized midpoints or normalized and weighted end points. Generally, those input parameters that cause the greatest variations in output criteria are accepted as the most important subjects of further investigation. However, in comparative LCA of emerging technologies, the typical approach to sensitivity analysis may misdirect research and development (R&D) toward addressing uncertainties that are inconsequential or counterproductive. This paper presents a novel method of sensitivity analysis for a decision-driven, anticipatory LCA of three emerging photovoltaic (PV) technologies: amorphous-Si (a-Si), CdTe and ribbon-Si. Although traditional approaches identify metal depletion as critical, a hypothetical reduction of uncertainty in metal depletion fails to improve confidence in the environmental comparison. By contrast, the novel approach directs attention toward marine eutrophication, where uncertainty reduction significantly improves decision confidence in the choice between a-Si and CdTe. The implication is that the novel method will result in better recommendations on the choice of the environmentally preferable emerging technology alternative for commercialization.

Life cycle considerations of nano-enabled agrochemicals: Are today’s tools up to the task?

Engineered nanomaterials (ENMs) used as fertilizers, pesticides and growth regulators will involve direct application of large quantities of ENMs to the environment and products intended for human consumption. Assessing their life cycle environmental impacts to mitigate unintended consequences poses several challenges. In this perspective, we identify obstacles to the application of life cycle assessment (LCA) for evaluating environmental tradeoffs of nano-enabled agrochemical applications. These include: (1) defining functional units that represent the function provided by nano-enabled agrochemicals and that are proportional to the scale of the study (nano-scale vs. field scale), (2) limitations in availability of comprehensive data necessary to inform life cycle material flow (resource use and emissions) for inventory development specific to nano-enabled agrochemical applications,(3) human and environmental exposure and effects data relevant to the agricultural context for impact assessment models, (4) spatial and temporal dependent components that can affect the results of an LCA of nano-enabled agrochemicals, and (5) high data uncertainties and the possibility of their reduction through collaborative efforts between life cycle practitioners and experimental researchers using anticipatory decision-based models. While several of these challenges are experienced in LCA of emerging technologies generally, they are highlighted herein due to their unique or heightened relevance to the use of ENMs in agriculture applications. Addressing challenges in these areas are intended to inform research prioritization to ensure safe and sustainable design, development, and implementation of nano-enabled agrochemicals.