Vikas Khanna

Microalgal biomass production pathways: evaluation of life cycle environmental impacts

BackgroundMicroalgae are touted as an attractive alternative to traditional forms of biomass for biofuel production, due to high productivity, ability to be cultivated on marginal lands, and potential to utilize carbon dioxide (CO2) from industrial flue gas. This work examines the fossil energy return on investment (EROIfossil), greenhouse gas (GHG) emissions, and direct Water Demands (WD) of producing dried algal biomass through the cultivation of microalgae in Open Raceway Ponds (ORP) for 21 geographic locations in the contiguous United States (U.S.). For each location, comprehensive life cycle assessment (LCA) is performed for multiple microalgal biomass production pathways, consisting of a combination of cultivation and harvesting options.ResultsResults indicate that the EROIfossil for microalgae biomass vary from 0.38 to 1.08 with life cycle GHG emissions of −46.2 to 48.9 (g CO2 eq/MJ-biomass) and direct WDs of 20.8 to 38.8 (Liters/MJ-biomass) over the range of scenarios analyzed. Further anaylsis reveals that the EROIfossil for production pathways is relatively location invariant, and that algae’s life cycle energy balance and GHG impacts are highly dependent on cultivation and harvesting parameters. Contrarily, algae’s direct water demands were found to be highly sensitive to geographic location, and thus may be a constraining factor in sustainable algal-derived biofuel production. Additionally, scenarios with promising EROIfossil and GHG emissions profiles are plagued with high technological uncertainty.ConclusionsGiven the high variability in microalgae’s energy and environmental performance, careful evaluation of the algae-to-fuel supply chain is necessary to ensure the long-term sustainability of emerging algal biofuel systems. Alternative production scenarios and technologies may have the potential to reduce the critical demands of biomass production, and should be considered to make algae a viable and more efficient biofuel alternative.

Process Based Life-Cycle Assessment of Natural Gas from the Marcellus Shale

The Marcellus Shale (MS) represents a large potential source of energy in the form of tightly trapped natural gas (NG). Producing this NG requires the use of energy and water, and has varying environmental impacts, including greenhouse gases. One well-established tool for quantifying these impacts is life-cycle assessment (LCA). This study collected information from current operating companies to perform a process LCA of production for MS NG in three areas--greenhouse gas (GHG) emissions, energy consumption, and water consumption--under both present (2011-2012) and past (2007-2010) operating practices. Energy return on investment (EROI) was also calculated. Information was collected from current well development operators and public databases, and combined with process LCA data to calculate per-well and per-MJ delivered impacts, and with literature data on combustion for calculation of impacts on a per-kWh basis during electricity generation. Results show that GHG emissions through combustion are similar to conventional natural gas, with an EROI of 12:1 (90% confidence interval of 4:1-13:1), lower than conventional fossil fuels but higher than unconventional oil sources.

Understanding resilience in industrial symbiosis networks: insights from network analysis.

Industrial symbiotic networks are based on the principles of ecological systems where waste equals food, to develop synergistic networks. For example, industrial symbiosis (IS) at Kalundborg, Denmark, creates an exchange network of waste, water, and energy among companies based on contractual dependency. Since most of the industrial symbiotic networks are based on ad-hoc opportunities rather than strategic planning, gaining insight into disruptive scenarios is pivotal for understanding the balance of resilience and sustainability and developing heuristics for designing resilient IS networks. The present work focuses on understanding resilience as an emergent property of an IS network via a network-based approach with application to the Kalundborg Industrial Symbiosis (KIS). Results from network metrics and simulated disruptive scenarios reveal Asnaes power plant as the most critical node in the system. We also observe a decrease in the vulnerability of nodes and reduction in single points of failure in the system, suggesting an increase in the overall resilience of the KIS system from 1960 to 2010. Based on our findings, we recommend design strategies, such as increasing diversity, redundancy, and multi-functionality to ensure flexibility and plasticity, to develop resilient and sustainable industrial symbiotic networks.

Life Cycle Energy Analysis and Environmental Life Cycle Assessment of Carbon Nanofibers Production

Life cycle assessment of nanotechnology has been suggested to evaluate claims about the potential benefits of this emerging technology. This paper presents one of the first LCAs and life cycle energy analysis of vapor grown carbon nanofibers (CNF) synthesis. Life cycle inventory data is compiled with data reported in the open literature. CNFs are compared with traditional materials on an equal mass basis to quantify the life cycle energy intensity and environmental burden. The results of the study indicate significantly higher life cycle energy requirements and higher environmental impact of CNFs as compared to traditional materials like aluminum, steel and polypropylene. Savings in life cycle energy consumption and possibly a reduction in environmental burden are envisaged if higher process yields of these fibers can be achieved in continuous operations. Since the comparisons are performed on an equal mass basis, these results cannot be generalized for CNF based nanoproducts and quantity of their use may decide their cradle to grave impact. Specific CNF based applications need to be studied to evaluate their environmental performance and are the topics of future work.

Comparative life cycle assessment: Reinforcing wind turbine blades with carbon nanofibers

Wind energy conversion (WEC) is dependent on wind power density, which increases with elevation and swept area of the rotor. Many components are readily scalable and size-independent; whereas, turbine blades have presented a new frontier in aerodynamic design. As the limits of glass fiber-reinforced plastics (GFRP) have been reached in this field, there is now a materials development problem in achieving outlooks for larger, more resilient WEC systems. A hybrid material is under development, which uses vapor-grown carbon nanofibers (VGCNF or CNF) to reinforce the interface of a glass fiber/epoxy matrix. This research aims to determine life cycle effects of substituting GFRP in large turbine blades with the hybrid material. A review of literature, databases, and industry reports on life cycle data for wind turbines helped to establish a baseline descriptive life cycle assessment (LCA). Trends of new installations were assessed to determine appropriate boundaries for comparison. Results indicate that cradle-to-gate processing energy of the new material is 1.4–7.7 times greater than for the original GFRP material on a MJ/kg basis under implicit assumptions of weight savings. Effects on energetic return on investment (EROI) vary from insignificant to substantial according to upstream process choices for CNF manufacture and solvent handling. All conclusions inherently assume that CNF-incorporation would lead to realizable technologies for substantially increasing either size or life span of turbine blades concomitant with weight savings. It is not yet substantiated whether replacement of long carbon fibers is advantageous both mechanically and energetically.

Assessing life cycle environmental implications of polymer nanocomposites

Research into the holistic evaluation of emerging nanotechnologies using systems analysis is pivotal for guiding their safe and sustainable development. This work presents the first energetic life cycle assessment of polymer nanocomposites (PNCs) that evaluates both thermoplastic and thermoset resins. Both simple carbon nanofiber (CNF) and carbon nanofiber-glass fiber (CNF-GF) hybrid nanocomposites are evaluated and compared with steel. The issue of life cycle inventory is tackled based on published literature and best available engineering information. A cradle-to-gate comparison reveals that CNF reinforced PNCs are 1.3-10 times more energy intensive than steel and thus the product use phase is likely to govern whether any net savings in life cycle energy consumption can be realized for PNC based products. A case study involving the use of CNF and CNF-GF reinforced PNCs in the body panels of automobiles is further presented and highlights that the use of PNCs with lower CNF loading ratios may result in net life cycle fossil energy savings relative to steel. Other factors such as cost, toxicity impact of CNF, and end-of-life issues specific to CNFs need to be considered to evaluate the final economic and environmental performance of CNF reinforced PNC materials. The results of this study can easily be used for evaluating other CNF based PNC applications.

Modeling the risks to complex industrial networks due to loss of natural capital

Several recent events in the U.S. have highlighted the criticality and vulnerability of infrastructure systems to sudden shocks such as natural disasters, terrorist attacks, and food shortages. Proper understanding of such disruptive scenarios and their impact using holistic and integrated systems modeling techniques is crucial for effective resource allocation and disaster management. An Input-Output (IO) based framework is presented for studying the effect of sudden shocks and quantifying the associated risks on complex industrial networks. We are specifically using the IO model to understand the impact of changes in the availability of natural resources including natural capital on industrial systems. This includes understanding the potential impact of loss of services such as pollination, water scarcities, and soil fertility. The utility of the framework is highlighted using two case studies involving loss of pollination services provided by managed honeybees and reduction in the availability of crude oil. The approach is suitable for modeling the effect of sudden perturbations such as resource shortage on the complex industrial systems and identifying industrial sectors with greatest sensitivity to a given perturbation. This work is expected to complement the traditional biophysical models and methods by including the behavior of complex industrial networks under sudden shocks, quantifying the associated risks and support a decision-making framework for risk management.

A network-based framework for assessing infrastructure resilience: a case study of the London metro system

Modern society is increasingly dependent on the stability of a complex system of interdependent infrastructure sectors. It is imperative to build resilience of large-scale infrastructures like metro systems for addressing the threat of natural disasters and man-made attacks in urban areas. Analysis is needed to ensure that these systems are capable of withstanding and containing unexpected perturbations, and develop heuristic strategies for guiding the design of more resilient networks in the future. We present a comprehensive, multi-pronged framework that analyses information on network topology, spatial organization and passenger flow to understand the resilience of the London metro system. Topology of the London metro system is not fault tolerant in terms of maintaining connectivity at the periphery of the network since it does not exhibit small-world properties. The passenger strength distribution follows a power law, suggesting that while the London metro system is robust to random failures, it is vulnerable to disruptions on a few critical stations. The analysis further identifies particular sources of structural and functional vulnerabilities that need to be mitigated for improving the resilience of the London metro network. The insights from our framework provide useful strategies to build resilience for both existing and upcoming metro systems.

Biofuels via fast pyrolysis of perennial grasses: a life cycle evaluation of energy consumption and greenhouse gas emissions.

A well-to-wheel (WTW) life cycle assessment (LCA) model is developed to evaluate the environmental profile of producing liquid transportation fuels via fast pyrolysis of perennial grasses: switchgrass and miscanthus. The framework established in this study consists of (1) an agricultural model used to determine biomass growth rates, agrochemical application rates, and other key parameters in the production of miscanthus and switchgrass biofeedstock; (2) an ASPEN model utilized to simulate thermochemical conversion via fast pyrolysis and catalytic upgrading of bio-oil to renewable transportation fuel. Monte Carlo analysis is performed to determine statistical bounds for key sustainability and performance measures including life cycle greenhouse gas (GHG) emissions and Energy Return on Investment (EROI). The results of this work reveal that the EROI and GHG emissions (gCO2e/MJ-fuel) for fast pyrolysis derived fuels range from 1.52 to 2.56 and 22.5 to 61.0 respectively, over the host of scenarios evaluated. Further analysis reveals that the energetic performance and GHG reduction potential of fast pyrolysis-derived fuels are highly sensitive to the choice of coproduct scenario and LCA allocation scheme, and in select cases can change the life cycle carbon balance from meeting to exceeding the renewable fuel standard emissions reduction threshold for cellulosic biofuels.

Multistage torrefaction and in situ catalytic upgrading to hydrocarbon biofuels: analysis of life cycle energy use and greenhouse gas emissions

A well-to-wheel life cycle assessment (LCA) model is developed to characterize the life cycle energy consumption and greenhouse gas emissions profiles of a series of novel multistage torrefaction and pyrolysis systems for targeted thermochemical conversion of short rotation woody crops to bio-oil and in situ catalytic upgrading to hydrocarbon transportation fuels, and to benchmark the results against a base-case fast pyrolysis and hydrodeoxygenation (HDO) platform. Multistage systems utilize a staged thermal gradient to fractionate bio-oil into product streams consisting of distinct functional groups, and multi-step chemical synthesis for downstream processing of bio-oil fractions to hydrocarbon fuels. Results at the process scale reveal that multistage systems have several advantages over the base-case including: (1) ∼40% reduction in process hydrogen consumption and (2) the product distribution for multistage systems are skewed towards longer carbon chain compounds that are fungible with diesel-range fuels. LCA reveals that the median Energy Return On Investment (EROI) and life cycle greenhouse gas (GHG) emissions for multistage systems range from 1.32 to 3.76 MJ-fuel/MJ-primary fossil energy and 17.1 to 52.8 gCO2e/MJ-fuel respectively, over the host of co-product scenarios and allocation schemes analyzed, with fossil-derived hydrogen constituting the principle GHG and primary energy burden across all systems. These results are compelling and indicate that multistage systems exhibit comparatively higher gasoline/diesel-range fuel yield relative to current technology, and produce a high quality infrastructure-compatible hydrocarbon transportation fuel capable of achieving over 80% reduction in life cycle GHG emissions relative to baseline petroleum diesel.