Disequilibrium and Indivisibility of Pollution Control Equipment Under a Permit-Trading System: A Case Study of Kao-Hsiung and Ping-Tung Counties in Taiwan

A mixed-integer programming model that minimizes the social abatement cost is used to investigate whether a market equilibrium condition could be reached in a newly proposed permit-trading market for nitrogen oxide control in Taiwan. Unlike in previous studies, unit pollution abatement cost is determined endogenously by incorporating technology adoption as a binary decision variable. The results show that when technologies are lumpy and irreversible, disequilibrium might occur due to firms’ inability to manage their emission levels after installing equipment with fixed size and control capacity.

Incorporating species relocation in reserve design models: An example from Ft. Benning GA

Given the increasing expansion of human dominated landscapes it often becomes necessary to relocate endangered and at-risk species from existing habitat areas. Further, there is growing research stating that climatic and atmospheric changes attributed to climate change are already affecting species distributions and geographic ranges, requiring endangered species to be relocated. Existing reserve design models mostly focus on choosing the optimal land area given existing species distributions and have not incorporated species relocation as a criterion. This paper introduces linear integer programming formulations for the relocation of multiple populations of a species at risk to clustered conservation areas. We present a basic clustered relocation model and extend the model to minimize the distances of relocation. We apply the models to a dataset related to Gopher Tortoise (GT), a keystone species currently considered ‘at risk’, at Ft. Benning Georgia where expanding military training needs require the relocation of GTs. We present the results and discuss the trade-off between compactness and relocation considerations using an efficiency frontier.     

Alternative transportation fuel standards: Welfare effects and climate benefits

This paper develops an integrated model of the fuel and agricultural sectors to analyze the welfare and greenhouse gas emission (GHG) effects of the existing Renewable Fuel Standard (RFS), a Low Carbon Fuel Standard (LCFS) and a carbon price policy. The conceptual framework shows that these policies differ in the incentives they create for the consumption and mix of different types of biofuels and in their effects on food and fuel prices and GHG emissions. We also simulate the welfare and GHG effects of these three policies which are normalized to achieve the same level of US GHG emissions. By promoting greater production of food-crop based biofuels, the RFS is found to lead to a larger reduction in fossil fuel use but also a larger increase in food prices and a smaller reduction in global GHG emissions compared to the LCFS and carbon tax. All three policies increase US social welfare compared to a no-biofuel baseline scenario due to improved terms-of-trade, even when environmental benefits are excluded; global social welfare increases with a carbon tax but decreases with the RFS and LCFS due to the efficiency costs imposed by these policies, even after including the benefits of mitigating GHG emissions.     

Optimal design of compact and connected nature reserves for multiple species

When designing a conservation reserve system for multiple species, spatial attributes of the reserves must be taken into account at species level. The existing optimal reserve design literature considers either one spatial attribute or when multiple attributes are considered the analysis is restricted only to one species. We built a linear integer programing model that incorporates compactness and connectivity of the landscape reserved for multiple species. The model identifies multiple reserves that each serve a subset of target species with a specified coverage probability threshold to ensure the species' long‐term survival in the reserve, and each target species is covered (protected) with another probability threshold at the reserve system level. We modeled compactness by minimizing the total distance between selected sites and central sites, and we modeled connectivity of a selected site to its designated central site by selecting at least one of its adjacent sites that has a nearer distance to the central site. We considered structural distance and functional distances that incorporated site quality between sites. We tested the model using randomly generated data on 2 species, one ground species that required structural connectivity and the other an avian species that required functional connectivity. We applied the model to 10 bird species listed as endangered by the state of Illinois (U.S.A.). Spatial coherence and selection cost of the reserves differed substantially depending on the weights assigned to these 2 criteria. The model can be used to design a reserve system for multiple species, especially species whose habitats are far apart in which case multiple disjunct but compact and connected reserves are advantageous. The model can be modified to increase or decrease the distance between reserves to reduce or promote population connectivity.     

Designing a conservation reserve network with minimal fragmentation: A linear integer programming approach

In the biological conservation literature, the optimum reserve site selection problem has often been addressed by using the prototype set covering and maximal covering formulations, assuming that representation of species is the only criterion in site selection. This approach usually results in a small but highly fragmented reserve, which is not useful for practical conservation planning. To improve the chances of species' persistence, it may be desirable to reduce habitat fragmentation. This paper presents a linear integer programming formulation to minimize spatial gaps between selected sites in a reserve network, which is applied to a data set on breeding birds. The authors express their willingness to share the database used in this study. Those readers who wish to have access to the data may contact Robert A. Briers at r.briers@napier.ac.uk.