• Energy Research

The main objective of this article was to analyse the impacts of emerging bioenergy markets on traditional forest product sector markets in the USA. An econometric model was developed to obtain the equilibrium estimates for the bioenergy and traditional forest markets. The results from the econometric model, using data-set for the state of Florida, suggested that biomass for bioenergy and pulpwood and biomass for bioenergy and sawtimber act as substitutes while sawtimber and pulpwood act as complements to each other. A price subsidy policy scenario was considered to simulate a 30% increase in the demand for biomass for bioenergy. The simulation results suggested that inclusion of this policy scenario might generate additional benefits to forest landowners and bioenergy sector, while sawmill and pulpmill sectors might face adverse financial impacts.

Co-firing wood pellets with coal is an attractive alternative energy generation method with economic, social, and environmental benefits for the US energy generation sector. One way to sustainably use wood pellets for co-firing is to create consumer-supported green pricing programs (GPPs). Our study surveyed residents of five states (Alabama, New Jersey, New York, Pennsylvania, and Virginia) to investigate preferences for the attributes of a hypothetical GPP. The study applied the Best Worst Choice method, which employs the Best Worst Scaling (BWS) and binary choice (BC) task. The BWS analysis showed that residents of all five states most value the flexibility of contracts, the location of energy generation, and the reduction of carbon emissions as attributes of GPPs. The BC analysis, however, showed that residents are willing to pay a premium for length of contract, followed by reduction of carbon emissions and variability of payments. This study shows that the adoption of optimal GPP attributes can create real customer value. The success of GPPs will depend on increasing enrollment and public support; hence, the next step will be to increase awareness levels and green consciousness through sensitization in the form of public education exercises and media campaigns. Such measures will serve to inform and educate residents on the benefits of GPPs and lessen the gap between intrinsic value and willingness to pay for select attributes.

article i nfo This paper contrasts alternate methodological approaches of investigating public preferences, the random parameter logit (RPL) where tastes and preferences of respondents are assumed to be heterogeneous and the conditional logit (CL) approach where tastes and preferences remain fixed for individuals. We conducted a choice experiment to assess preferences for woody biomass based electricity in Arkansas, Florida, and Virginia. Reduction of CO2 emissions and improvement of forest habitat by decreasing risk of wildfires and pest outbreaks were presented to respondents as attributes of using green electricity. The results indicate that heterogeneous preferences might be a better fit for assessing preferences for green electricity. All levels of both attributes were positive contributors to welfare but they were no statistically significant. Respondents expressed a positive mean marginal willingness to pay (WTP) for each attribute level. The total WTP for green electricity per kilowatt hour was $0.049 kWh or $40.5 per capita year −1 when converted into future total annual expenditures.

Abstract Kenya has made considerable policy efforts to expand its renewable energy portfolio to meet energy demand and mitigate greenhouse gas (GHG) emissions. Development of proper policies requires a robust framework for analyzing the benefits of renewable energy investments. Towards this end, this study applied a choice experiment analysis to determine how attributes (type of energy, ownership, impact on environment, distance and visibility, community job creation, and yearly renewable energy tax) impact the public willingness to pay for renewable energy development in Kenya. A nationwide survey of 1020 households was conducted in nine counties using conditional logit (MNL) and random parameter logit (RPL) frameworks. The results reveal that the Kenyan public places a high value on environmental impact, followed by type of renewable energy and community job creation, respectively. On the other hand, respondents do not place much emphasis on ownership or distance and visibility. Policy simulation suggests that while renewable energy adoption is highly valued by households, the total willingness to pay is not enough to cover the higher capital cost for the development of various renewable energy technologies.

In this study, we assessed the impacts of climate change on the production of pulpwood and biomass for bioenergy, and the profitability of slash pine stands in the Southeastern United States. We employed the 3-PG (Physiological Processes Predicting Growth) model to determine the effects of future climates on forest growth and integrated it with a stand-level economic model to determine their impacts on optimal forest management. We found that the average production of pulpwood increased for all sites by 7.5 m3 ha−1 for all climatic scenarios and productivity conditions. In the case of forest biomass for bioenergy, the average increase was less than 1 Mg ha−1. Considering a payment for forest biomass for bioenergy of $4.2 per green Mg−1, the land expectation values (LEVs), on average, increased by $242.1 ha−1 under extreme climatic conditions and high productivity conditions. However, the increase in LEVs due to payments for biomass for bioenergy was small, accounting for $23 ha−1. We also found that the combined effect of increased site productivity and climate change reduced the optimal harvest age of slash pine. Our results confirm that emerging bioenergy markets coupled with changing climatic conditions can increase the economic returns for landowners.

Production of bioenergy from cellulosic sources is likely to increase due to mandates, tax incentives, and subsidies. However, unchecked growth in the bioenergy industry has the potential to adversely influence land use, biodiversity, greenhouse gas (GHG) emissions, and water resources. It may have unintended environmental and socioeconomic consequences. Against this backdrop, it is important to develop standards and protocols that ensure sustainable bioenergy production, promote the benefits of biofuels, and avoid or minimize potential adverse outcomes. This paper highlights agronomic information on switchgrass, a high-potential bioenergy feedstock, and the role of specialized certification programs. The existing sustainability standards and protocols were reviewed in order to identify key gaps that justify a certification program specifically for switchgrass-based bioenergy. The criteria and indicators that should be considered for such a certification program are outlined.

Renewable energy remains Sub-Saharan Africa's (SSAs) best option to leapfrog and escape the learning curve in energy access while simultaneously combating climate change. Consequently, it is imperative to understand the relationships between SSAs renewable energy consumption and social, economic, and environmental explanatory variables. This paper puts forward an empirical model to outline the factors that can promote renewable energy consumption. We considered the panel autoregressive distributed lags (ARDL) panel models of 23 SSA countries with annual data from 1998 to 2014. From the main findings, the dependent variable renewable energy consumption is significant and positively correlates with the independent variables gross domestic product (GDP) per capita and education index in the long run as expected. Whereas renewable energy consumption is significant and negatively correlates with the independent variables, CO2 emissions per capita, and life expectancy index in the long run. The study highlights the potential of effective management and implementation of renewable energy development in promoting social indicators such education indexes, while improving economies and reducing CO2 emissions.

Abstract Studies have shown that woody bioenergy can have potential economic, social, and environmental benefits. One of the ways to meet the growing biomass demand for woody bioenergy is by allocating currently non-forested land for growing feedstocks such as pine. Towards this end, we conducted a survey on 900 randomly selected private forestland owners in Virginia and asked what proportion of their non-forested land they would allocate for loblolly pine at given bid prices. We then used recursive partitioning based Tobit regression to analyze data. Our results suggest that the experience of having supplied wood for chip-n-saw mills in the past five years, large land holding, prior experience with state/federal financial/technical support programs, among other factors, lead to smaller proportion of non-forested land being allocated for pine. However, a higher price offer, stronger preference for producing non-timber forest products such as evergreen boughs and grapevine, and lesser dependence on working the land for annual income lead to larger proportion of non-forested land being allocate for pine. Our results could assist policy makers in developing and improving land use and energy policies, certification programs, and extension and outreach services. Our contribution also includes the use of threshold analyses to delineate tipping points in variables associated with different response rates and showing the different effect of variables in terms of how they affect the supply of biomass and the supply of land for bioenergy purposes.

Abstract Production of biofuels from cellulosic sources, such as switchgrass, is being encouraged through mandates, incentives, and subsidies. However, uncertainty in future prices coupled with large establishment costs often inhibit their cultivation. Owing to their inability to incorporate uncertainty and dynamic decision-making, standard discounted cash flow techniques are ineffective for analyzing such investments. We formulate a discrete-time binomial framework to model output prices, allowing us to incorporate price uncertainty, stand age, and variable crop yields into the analytical framework. We analyze the feasibility of investments in switchgrass cultivation under varying price transition paths, evaluate the relationship between risk and profitability, and estimate the value of flexible decision-making options wherein the farmer can alter cultivation choices. We find that switchgrass cultivation is only 32% likely to be profitable in the base model and infer that on-farm management could play an important role in entry and exit decisions. We also find that subsidies are important for project viability and policymakers could consider incorporating payments for ecosystem services to encourage adoption.