Evaluating the Global Plastic Waste Management System with Markov Chain Material Flow Analysis.

We present a global Markov chain-based material flow analysis of plastic waste of all types to estimate global virgin waste generation and waste mismanagement rates. We model nine alternative scenarios related to the elimination of plastic waste trade and improvements at various stages of the recycling chain, including "limitless" recycling promised by certain new chemical recycling technologies. We found that the elimination of trade increased global mismanagement when displaced waste was disposed but decreased mismanagement when it was instead recycled. Recycling scenarios showed little benefit for limitless recycling without prior increases in collection rates, which are currently the main constraint in the recycling chain. The most ambitious scenario only led to a 34% decrease in virgin waste generation. While significant, this implies that, given our current 40% mismanagement rate and 2050 forecasts of waste generation, landfilling and incineration capacity must increase 2.5-fold in addition to these extreme recycling targets to eliminate waste mismanagement. These results highlight the requirement for waste exporters to increase domestic recycling capacity as trade restrictions become tighter and express the urgent global need for alternative waste reduction interventions in addition to recycling.

Consumption-Based Accounting for Tracing Virtual Water Flows Associated with Beef Supply Chains in the United States.

Enhancing the environmental sustainability of food systems requires an understanding of both production- and consumption-based impacts. As food supply chains become increasingly complex and connected, they also present a unique context in which to understand the environmental impacts of consumption. This is critical for understanding the disconnect between production- and consumption-based impacts of food systems and ultimately designing, evaluating, and implementing interventions for improving security, resilience, and sustainability of food systems. Using publicly available datasets and an optimization-based framework, we present a county-to-county level network model of beef supply chains in the United States. The model is used to connect and attribute the consumption-based impacts of beef consumption to production in distant locations, specifically focusing on water-based impacts. We specifically focus on the beef system because of its importance in the diet of U.S. consumers and in environmental sustainability discourse. The findings from this work show the spatial disconnect between the consumption and production counties with approximately 22 billion m3 of blue virtual water being transferred for the year 2017, mainly from the northern and southern plains toward the coasts. These results highlight the importance of understanding environmental impacts from both production and consumption perspectives.

Economic Dependence and Vulnerability of United States Agricultural Sector on Insect-Mediated Pollination Service.

Deficits in insect-mediated pollination service undermine ecosystem biodiversity and function, human nutrition, and economic welfare. Global pollinator supply continues to decline, while production of pollination-dependent crops increases. Using publicly available price and production data and existing pollination field studies, we quantify economic dependence of United States crops on insect-mediated pollination service at the county level and update existing coefficients of insect dependence of sample crops when possible. Economic value dependent on pollination service totals 34.0 billion USD in 2012. Twenty percent of US counties produce 80% of total economic value attributable to insect pollinators. We compile county-level data and consider the spatial relationship between economic value dependent on insect-mediated pollination, region-specific forage suitability, and crop-specific agricultural areas within US landscapes. We identify vulnerable, highly dependent areas where habitat for wild pollinators has been reduced. These results can help inform future efforts to conserve and bolster managed and wild pollinator populations to ensure sustainable production of key agricultural crops.

Network Analysis for Prioritizing Biodegradation Metabolites of Polycyclic Aromatic Hydrocarbons.

Polycyclic aromatic hydrocarbons (PAHs) are a diverse group of environmental contaminants released during the combustion of organic materials and the production and utilization of fossil fuels. Once released, PAHs deposit in soil and water bodies where they are subjected to environmental transport and transformations. As they degrade, intermediate transformation products may play an important role in their environmental impact. However, studying the effects of these degradation products has proven challenging because of the complexity, transience, and low concentration of many intermediates. Herein, a novel integration of a pathway prediction system and network theory was developed and applied to a set of four PAHs to demonstrate a possible solution to this challenge. Network analysis techniques were employed to refine the thousands of potential outputs and elucidate compounds of interest. Using these tools, we determined correlations between PAH degradation network data and intermediate metabolite structures, gaining information about the chemical characteristics of compounds based on their placement within the degradation network. Upon applying our developed filtering algorithm, we are able to predict up to 48% of the most common transformation products identified in a comprehensive empirical literature review. Additionally, our integrated approach uncovers potential metabolites which connect those found by past empirical studies but are currently undetected, thereby filling in the gaps of information in PAH degradation pathways.

A Systems Approach To Assess Trade Dependencies in U.S. Food-Energy-Water Nexus.

We present a network model of the United States (U.S.) interstate food transfers to analyze the trade dependency with respect to participating regions and embodied irrigation impacts from a food-energy-water (FEW) nexus perspective. To this end, we utilize systems analysis methods including the pointwise mutual information (PMI) measure to provide an indication of interdependencies by estimating probability of trade between states. PMI compares observed trade with a benchmark of what is statistically expected given the structure and flow in the network. This helps assess whether dependencies arising from empirically observed trade occur due to chance or preferential attachment. The implications of PMI values are demonstrated by using Texas as an example, the largest importer in the U.S. grain transfer network. We find that strong dependencies exist not only just with states (Kansas, Oklahoma, Nebraska) providing high volume of transfer to Texas but also with states that have comparatively lower trade (New Mexico). This is due to New Mexico's reliance on Texas as an important revenue source compared to its other connections. For Texas, import interdependencies arise from geographical proximity to trade. As these states primarily rely on the commonly shared High Plains aquifer for irrigation, overreliance poses a risk for water shortage for food supply in Texas. PMI values also indicate the capacity to trade more (the states are less reliant on each other than expected), and therefore provide an indication of where the trade could be shifted to avoid groundwater scarcity. However, some of the identified states rely on GHG emission intensive fossil fuels such as diesel and gasoline for irrigation, highlighting a potential tradeoff between crop water footprint and switching to lower emissions pumping fuels.

Life Cycle Impact and Benefit Trade-Offs of a Produced Water and Abandoned Mine Drainage Cotreatment Process.

A cotreatment process for produced water and abandoned mine drainage (AMD) has been established and demonstrated at the pilot-scale. The present study evaluates the potential of the proposed process to aid in management of two high volume wastewater resources in Pennsylvania. A systems-level approach is established to evaluate the primary trade-offs, including cotreatment process environmental impacts, transportation impacts, and environmental benefits realized from precluding direct AMD release to the environment. Life cycle impact assessment was used to quantify the environmental and human health impacts as well as to identify "hot spots" of the cotreatment process. Electricity use was found to be the dominant contributor to all impact categories. Extending the system boundary to include transportation of the two wastewaters to a to-be-determined cotreatment site revealed the important impact of transportation. An optimization approach was employed (using the region of Southwest Pennsylvania) to evaluate minimization of transportation distance considering the location and number of treatment sites. Finally, a quantitative analysis of environmental benefits realized by precluding direct AMD release to the environment was performed. The results suggest that the magnitude of benefit realized in treating a highly polluted AMD is greater than the magnitude of impacts from the cotreatment process.

Evaluating the Life Cycle Environmental Benefits and Trade-Offs of Water Reuse Systems for Net-Zero Buildings.

Aging water infrastructure and increased water scarcity have resulted in higher interest in water reuse and decentralization. Rating systems for high-performance buildings implicitly promote the use of building-scale, decentralized water supply and treatment technologies. It is important to recognize the potential benefits and trade-offs of decentralized and centralized water systems in the context of high-performance buildings. For this reason and to fill a gap in the current literature, we completed a life cycle assessment (LCA) of the decentralized water system of a high-performance, net-zero energy, net-zero water building (NZB) that received multiple green building certifications and compared the results with two modeled buildings (conventional and water efficient) using centralized water systems. We investigated the NZB's impacts over varying lifetimes, conducted a break-even analysis, and included Monte Carlo uncertainty analysis. The results show that, although the NZB performs better in most categories than the conventional building, the water efficient building generally outperforms the NZB. The lifetime of the NZB, septic tank aeration, and use of solar energy have been found to be important factors in the NZB's impacts. While these findings are specific to the case study building, location, and treatment technologies, the framework for comparison of water and wastewater impacts of various buildings can be applied during building design to aid decision making. As we design and operate high-performance buildings, the potential trade-offs of advanced decentralized water treatment systems should be considered.

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.

Economic Dependence of U.S. Industrial Sectors on Animal-Mediated Pollination Service.

Declining animal pollinator health and diversity in the U.S. is a matter of growing concern and has particularly gained attention since the emergence of colony collapse disorder (CCD) in 2006. Failure to maintain adequate animal-mediated pollination service to support increasing demand for pollination-dependent crops poses risks for the U.S. economy. We integrate the Economic Input-Output (EIO) model and network analysis with data on pollinator dependence of crops to understand the economic dependence of U.S. industrial sectors on animal-mediated pollination service. The novelty of this work lies in its ability to identify industrial sectors and industrial communities (groups of closely linked sectors) that are most vulnerable to scarcity of pollination service provided by various animal species. While the economic dependence of agricultural sectors on pollination service is significant (US$14.2-23.8 billion), the higher-order economic dependence of the rest of the U.S. industrial sectors is substantially high as well (US$10.3-21.1 billion). The results are compelling as they highlight the critical importance of animal-induced pollination service for the U.S. economy, and the need to account for the role of ecosystem goods and services in product life cycles.

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.

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.

Microalgal biomass production pathways: evaluation of life cycle environmental impacts.

BACKGROUND: Microalgae 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. RESULTS: Results 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. CONCLUSIONS: Given 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.

Reinforced wind turbine blades--an environmental life cycle evaluation.

A fiberglass composite reinforced with carbon nanofibers (CNF) at the resin-fiber interface is being developed for potential use in wind turbine blades. An energy and midpoint impact assessment was performed to gauge impacts of scaling production to blades 40 m and longer. Higher loadings force trade-offs in energy return on investment and midpoint impacts relative to the base case while remaining superior to thermoelectric power generation in these indicators. Energy-intensive production of CNFs forces impacts disproportionate to mass contribution. The polymer nanocomposite increases a 2 MW plant's global warming potential nearly 100% per kWh electricity generated with 5% CNF by mass in the blades if no increase in electrical output is realized. The relative scale of impact must be compensated by systematic improvements whether by deployment in higher potential zones or by increased life span; the trade-offs are expected to be significantly lessened with CNF manufacturing maturity. Significant challenges are faced in evaluating emerging technologies including uncertainty in future scenarios and process scaling. Inventories available for raw materials and monte carlos analysis have been used to gain insight to impacts of this development.

Carbon nanofiber polymer composites: evaluation of life cycle energy use.

Holistic evaluation of emerging nanotechnologies using systems analysis is pivotal for guiding their safe and sustainable development. While toxicity studies of engineered nanomaterials are essential, understanding of the potential large scale impacts of nanotechnology is also critical for developing sustainable nanoproducts. This work evaluates the life cycle energetic impact associated with the production and use of carbon nanofiber (CNF) reinforced polymer nanocomposites (PNC). Specifically, both simple CNF and carbon nanofiber-glass fiber (CNF-GF) hybrid PNCs are evaluated and compared with steel for equal stiffness design. Life cycle inventory is developed based on published literature and best available engineering information. A cradle-to-gate comparison suggests that for equal stiffness design, CNF reinforced PNCs are 1.6-12 times more energy intensive than steel. It is anticipated that the product use phase may strongly influence whether any net savings in life cycle energy consumption can be realized. A case study involving the use of CNF and CNF-GF reinforced PNCs in the body panels of automobiles highlights that the use of PNCs with lower CNF loading ratios has the potential for net life cycle energy savings relative to steel owing to improved fuel economy benefits. 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.