Dynamic Life Cycle Assessment Modeling Approaches for Transboundary Energy Feedstocks

The rise of the twenty-first century has seen the further increase in the industrialization of Earth’s resources, as society aims to meet the needs of a growing population while still protecting our environmental and natural resources. The advent of the industrial bioeconomy – which encompasses the production of renewable biological resources and their conversion into food, feed, and bio-based products – is seen as an important step in transition towards sustainable development and away from fossil fuels. One sector of the industrial bioeconomy which is rapidly being expanded is the use of biobased feedstocks in electricity production as an alternative to coal, especially in the European Union.

As bioeconomy policies and objectives increasingly appear on political agendas, there is a growing need to quantify the impacts of transitioning from fossil fuel-based feedstocks to renewable biological feedstocks. Specifically, there is a growing need to conduct a systems analysis and potential risks of increasing the industrial bioeconomy, given that the flows within it are inextricably linked. Furthermore, greater analysis is needed into the consequences of shifting from fossil fuels to renewable feedstocks, in part through the use of life cycle assessment modeling to analyze impacts along the entire value chain.

To assess the emerging nature of the industrial bioeconomy, three objectives are addressed: (1) quantify the global industrial bioeconomy, linking the use of primary resources with the ultimate end product; (2) quantify the impacts of the expaning wood pellet energy export market of the Southeastern United States; (3) conduct a comparative life cycle assessment, incorporating the use of dynamic life cycle assessment, of replacing coal-fired electricity generation in the United Kingdom with wood pellets that are produced in the Southeastern United States.

To quantify the emergent industrial bioeconomy, an empirical analysis was undertaken. Existing databases from multiple domestic and international agencies was aggregated and analyzed in Microsoft Excel to produce a harmonized dataset of the bioeconomy. First-person interviews, existing academic literature, and industry reports were then utilized to delineate the various intermediate and end use flows within the bioeconomy. The results indicate that within a decade, the industrial use of agriculture has risen ten percent, given increases in the production of bioenergy and bioproducts. The underlying resources supporting the emergent bioeconomy (i.e., land, water, and fertilizer use) were also quantified and included in the database.

Following the quantification of the existing bioeconomy, an in-depth analysis of the bioenergy sector was conducted. Specifically, the focus was on quantifying the impacts of the emergent wood pellet export sector that has rapidly developed in recent years in the Southeastern United States. A cradle-to-gate life cycle assessment was conducted in order to quantify supply chain impacts from two wood pellet production scenarios: roundwood and sawmill residues. For reach of the nine impact categories assessed, wood pellet production from sawmill residues resulted in higher values, ranging from 10-31% higher.

The analysis of the wood pellet sector was then expanded to include the full life cycle (i.e., cradle-to-grave). In doing to, the combustion of biogenic carbon and the subsequent timing of emissions were assessed by incorporating dynamic life cycle assessment modeling. Assuming immediate carbon neutrality of the biomass, the results indicated an 86% reduction in global warming potential when utilizing wood pellets as compared to coal for electricity production in the United Kingdom. When incorporating the timing of emissions, wood pellets equated to a 75% or 96% reduction in carbon dioxide emissions, depending upon whether the forestry feedstock was considered to be harvested or planted in year one, respectively.

Finally, a policy analysis of renewable energy in the United States was conducted. Existing coal-fired power plants in the Southeastern United States were assessed in terms of incorporating the co-firing of wood pellets. Co-firing wood pellets with coal in existing Southeastern United States power stations would result in a nine percent reduction in global warming potential.

The Life Cycle of Corporate Venture Capital

This paper establishes the life-cycle dynamics of Corporate Venture Capital (CVC) to explore the information acquisition role of CVC investment in the process of corporate innovation. I exploit an identification strategy that allows me to isolate exogenous shocks to a firm's ability to innovate. Using this strategy, I first find that the CVC life cycle typically begins following a period of deteriorated corporate innovation and increasingly valuable external information, lending support to the hypothesis that firms conduct CVC investment to acquire information and innovation knowledge from startups. Building on this analysis, I show that CVCs acquire information by investing in companies with similar technological focus but have a different knowledge base. Following CVC investment, parent firms internalize the newly acquired knowledge into internal R&D and external acquisition decisions. Human capital renewal, such as hiring inventors who can integrate new innovation knowledge, is integral in this step. The CVC life cycle lasts about four years, terminating as innovation in the parent firm rebounds. These findings shed new light on discussions about firm boundaries, managing innovation, and corporate information choices.

Genetics and the Life Course

A life-course perspective is committed to the proposition that from conception to death, all human outcomes are the result of a continual interaction between the indi- vidual and all of the environments that he or she inhabits at any given point in time. Early development is a critical period, a window of time during the life course when a given exposure can have a critical or permanent in uence on later outcomes. But the impact of exposures upon outcomes does not end at any speci c point in time, inasmuch as life is a continuing interactive and adaptive process. We now know that what applies to human beings also applies to their genomes. The “outcome” of any gene at any given point in time (whether or not it is used to transcribe a particular protein, what form of that protein, and how much) is a product of the interaction between the gene and the multiple environments of which it is a part, which include the epigenome, the cell, the biological human, and the assorted environments he or she occupies (e.g., geographical, socioeconomic, ethnic, etc.). Early life experiences can permanently “reprogram” the epigenome and gene transcription with life-long behavioral consequences. At the same time, the epigenome as well as the genome continue to be environmentally responsive throughout the life course.