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This article examines land-use, market and welfare implications of lignocellulosic bioethanol production in Hawaii to satisfy 10% and 20% of the State's gasoline demand in line with the State's ethanol blending mandate and Alternative Fuels Standard (AFS). A static computable general equilibrium (CGE) model is used to evaluate four alternative support mechanisms for bioethanol. Namely: (i) a federal blending tax credit, (ii) a long-term purchase contract, (iii) a state production subsidy financed by a lump-sum tax and (iv) a state production subsidy financed by an ad valorem gasoline tax. We find that because Hawaii-produced bioethanol is relatively costly, all scenarios are welfare reducing for Hawaii residents: estimated between -0.14% and -0.32%. Unsurprisingly, Hawaii.s economy and its residents fair best under the federal blending tax credit scenario, with a positive impact to gross state product of $49 million. Otherwise, impacts to gross state product are negative (up to -$63 million). We additionally find that Hawaii-based bioethanol is not likely to offer substantial greenhouse gas emissions savings in comparison to imported biofuel, and as such the policy cost per tonne of emissions displaced ranges between $130 to $2,100/tonne of CO2e. The policies serve to increase the value of agricultural lands, where we estimate that the value of pasture land could increase as much as 150% in the 20% AFS scenario.

AbstractClimate change poses new and unique challenges that threaten lives and livelihoods. Given the increasing risks and looming uncertainty of climate change, increasing attention has been directed towards adaptation, or the strategies that enable humanity to persist and thrive through climate change the best it can. Though climate change is a global problem often discussed at the national scale, urban areas are increasingly seen as having a distinct role, and distinctive motivation and capacity, for adaptation. The 12 articles in this special issue explore ways of understanding and addressing climate change impacts on urban areas. Together they reveal young but rapidly growing scholarship on how to measure, and then overcome, challenges of climate change. Two key themes emerge in this issue: 1) that we must identify and then overcome current barriers to urban adaptation and 2) frameworks/metrics are necessary to identify and track adaptation progress in urban settings. Both of these themes point to the power of indicators and other quantitative information to inform priorities and illuminate the pathway forward for adaptation. As climate change is an entirely new challenge, careful measurement that enables investment by private and public parties is necessary to provide efficient outcomes that benefit the greatest number of people.

Abstract With promising benefits such as traffic emission reduction, traffic congestion alleviation, and parking problem solving, Electric Vehicle (EV)-sharing systems have attracted large attentions in recent years. Different from other business modes, customers in sharing economy systems are usually price sensitive. Therefore, it is possible to shift the usage of shared EVs through a well-designed Dynamic Pricing Scheme (DPS), with the objective of maximizing the system operator's total profit. In this study, we propose a novel DPS for a large-scale EV-sharing network to address the EV unbalancing issue and satisfy the vehicle-grid-integration (VGI) service based on accurate station-level demand prediction. The proposed DPS is formulated as a complex optimization problem, which includes two Price Adjustment Level (PAL) decision variables for every origin-destination pair of stations. The two PALs are employed to affect the EV-sharing demand and travel time between each station pair, respectively. Physical and operational constraints from both EV demand and VGI service aspects are also included in the proposed model. Two case study are conducted to validate the effectiveness of the proposed method.

Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.

Aggregate and limestone mining in San Antonio’s Bexar and Comal counties in Texas, USA, has caused considerable health concerns as of late. Aggregate mining actions can result in localized air quality issues in any neighborhood. Furthermore, heavy truck traffic, hauling, and transportation of the mined material contribute to pollution. In this research, PM species were sampled at four locations north of the San Antonio city limits. The data were collected using a TSI Air Quality Sampler that sampled PM1, PM2.5, PM4, PM10, wind speed, wind direction, temperature, and relative humidity. Continuous data with 1 min averages were recorded during the study period from August to September 2019. The instrument was stationed at every location for a period of 7 days each. The four locations were a ranch, an open field, a residential compound, and an elementary school. PM1 and PM2.5 concentration levels were lower compared to PM10 concentrations at all four studied sites. Our results suggest that PM concentrations are primarily impacted by mining activities. PM species were highest at the residential compound due to its proximity to an active mining area, resulting in deleterious health effects for neighbors living in the vicinity of the sampled site.

The Houston-Dallas (I-45) corridor is the busiest route among 18 traffic corridors in Texas, USA. The expected population growth and the surge in passenger mobility may result in a significant impact on the regional environment. This study uses a life cycle framework to predict and evaluate the net changes of environmental impact associated with the potential development of a high-speed rail (HSR) System along the I-45 corridor through its life cycle. The environmental impact is estimated in terms of CO2 and greenhouse gas (GHG) emissions per vehicle/passenger-kilometers traveled (V/PKT) using life cycle assessment. The analyses are performed referring to the Ecoinvent 3.4 inventory database through the phases: material extraction and processing, infrastructure construction, vehicle manufacturing, system operation, and end of life. The environmental benefit is evaluated by comparing the potential development of the HSR system with those of the existing transportation systems. The vehicle component, especially operation and maintenance of vehicles, is the primary contributor to the total global warming potential with about 93% of the life cycle GHG emissions. For the infrastructure component, 56.76% of GHG emissions result from the material extraction and processing phase (23.75 kgCO2eq/VKT). Various life cycle emissions of HSR except PM are significantly lower than for passenger cars.