Thomas Buchholz

A Global Meta-Analysis of Forest Bioenergy Greenhouse Gas Emission Accounting Studies

The potential greenhouse gas benefits of displacing fossil energy with biofuels are driving policy development in the absence of complete information. The potential carbon neutrality of forest biomass is a source of considerable scientific debate because of the complexity of dynamic forest ecosystems, varied feedstock types, and multiple energy production pathways. The lack of scientific consensus leaves decision makers struggling with contradicting technical advice. Analyzing previously published studies, our goal was to identify and prioritize those attributes of bioenergy greenhouse gas (GHG) emissions analysis that are most influential on length of carbon payback period. We investigated outcomes of 59 previously published forest biomass greenhouse gas emissions research studies published between 1991 and 2014. We identified attributes for each study and classified study cases by attributes. Using classification and regression tree analysis, we identified those attributes that are strong predictors of carbon payback period (e.g. the time required by the forest to recover through sequestration the carbon dioxide from biomass combusted for energy). The inclusion of wildfire dynamics proved to be the most influential in determining carbon payback period length compared to other factors such as feedstock type, baseline choice, and the incorporation of leakage calculations. Additionally, we demonstrate that evaluation criteria consistency is required to facilitate equitable comparison between projects. For carbon payback period calculations to provide operational insights to decision makers, future research should focus on creating common accounting principles for the most influential factors including temporal scale, natural disturbances, system boundaries, GHG emission metrics, and baselines.

Regional variation in forest harvest regimes in the northeastern United States

Logging is a larger cause of adult tree mortality in northeastern U.S. forests than all other causes of mortality combined. We used Forest Inventory and Analysis (FIA) data to develop statistical models to quantify three different aspects of aggregate regional forest harvest regimes: (1) the annual probability that a plot is logged, as a function of total aboveground tree biomass, (2) the fraction of adult tree basal area removed if a plot was logged, and (3) the probability that an individual tree within a plot was removed, as a function of the fraction of basal area removed at the plot level, the species of tree, and its size. Results confirm that relatively frequent partial harvesting dominates the logging regimes, but with significant variation among different parts of the region and different forest types. The harvest regimes have similarities with natural disturbance regimes in imposing spatially and temporally dynamic mortality that varies predictably as a function of stand structure as well as tree species and size.

Considerations of Project Scale and Sustainability of Modern Bioenergy Systems in Uganda

Energy supply and accessibility has a major impact on the development of societies. Modern bioenergy production in the form of heat, electricity, and liquid transportation fuels is increasingly cost competitive as prices of fossil fuels continue to increase. However, the large potential benefits associated with bioenergy come with a price tag and risks that may be disproportionately carried by tropical and non-industrialized countries. This analysis focuses on the influence of project scale on economic, social, and environmental impacts of bioenergy production in the tropics using the framework of two wood fueled bioenergy projects in Uganda—a large (50 MW) and a small-scale (200 kW). There are indications that less sustainable practices often come with increasing project-scale. This study found that a distributed, small-scale infrastructure indeed can be more desirable in terms of resource efficiency, impacts on ecosystems and local societies, and financial risks and benefits compared with those associated with one large-scale. To support the implementation of small-scale projects, there is a need for policies fostering distributed energy infrastructure and participatory tools beyond traditional cost-benefit analysis to assess sustainability of bioenergy systems.

Forest biomass energy: assessing atmospheric carbon impacts by discounting future carbon flows

Although forest biomass energy was long assumed to be carbon neutral, many studies show delays between forest biomass carbon emissions and sequestration, with biomass carbon causing climate change damage in the interim. While some models suggest that these primary biomass carbon effects may be mitigated by induced market effects, for example, from landowner decisions to increase afforestation due to higher biomass prices, the delayed carbon sequestration of biomass energy systems still creates considerable scientific debate (i.e., how to assess effects) and policy debate (i.e., how to act given these effects). Forests can be carbon sinks, but their carbon absorption capacity is finite. Filling the sink with fossil fuel carbon thus has a cost, and conversely, harvesting a forest for biomass energy – which depletes the carbon sink – creates potential benefits from carbon sequestration. These values of forest carbon sinks have not generally been considered. Using data from the 2010 Manomet Center for Conservation Sciences ‘Biomass sustainability and carbon policy study’ and a model of forest biomass carbon system dynamics, we investigate how discounting future carbon flows affects the comparison of biomass energy to fossil fuels in Massachusetts, USA. Drawing from established financial valuation metrics, we calculate internal rates of return (IRR) as explicit estimates of the temporal values of forest biomass carbon emissions. Comparing these IRR to typical private discount rates, we find forest biomass energy to be preferred to fossil fuel energy in some applications. We discuss possible rationales for zero and near‐zero social discount rates with respect to carbon emissions, showing that social discount rates depend in part on expectations about how climate change affects future economic growth. With near‐zero discount rates, forest biomass energy is preferred to fossil fuels in all applications studied. Higher IRR biomass energy uses (e.g., thermal applications) are preferred to lower IRR uses (e.g., electricity generation without heat recovery).

Use of Remotely Sensed Climate and Environmental Information for Air Quality and Public Health Applications

Earth’s environment has direct and dramatic effects on its inhabitants in the realms of health and air quality. The climate, even in an unaltered state, poses great challenges but also presents great opportunity for the mankind to survive and flourish. Anthropogenic factors lead to even greater stress on the global ecosystem and to mankind, particularly with respect to air quality and the concomitant health issues. While the use of remote sensing technology to address issues is in its infancy, there is tremendous potential for using remote sensing as part of systems that monitor and forecast conditions that directly or indirectly affect health and air quality. This chapter discusses current status and future prospects in this field and presents three case studies showing the great value of remote sensing assets in distinct disciplines.