Systematically Incorporating Environmental Objectives into Shale Gas Pipeline Development: A Binary Integer, Multiobjective Spatial Optimization Model

Abstract

Shale gas pipeline development can have negative environmental impacts, including adverse effects on species and ecosystems through habitat degradation and loss. From a societal perspective, pipeline development planning processes should account for such externalities. We develop a multiobjective binary integer-programming model, called the Multi Objective Pipeline Siting (MOPS) model, to incorporate habitat externalities into pipeline development and to estimate the trade-offs between pipeline development costs and habitat impacts. We demonstrate the utility of the model using an application from Bradford and Susquehanna counties in northeastern Pennsylvania. We find that significant habitat impacts can be avoided for relatively low cost, but the avoidance of the additional habitat impacts becomes gradually and increasingly costly. For example, 10% of the habitat impacts can be avoided at less than a two percent pipeline cost increase relative to a configuration that ignores habitat impacts. MOPS or a similar model could be integrated into the pipeline siting and permitting process so oil and gas companies, communities, and states can identify cost-effective options for habitat conservation near shale gas development.

Modeling Ecological Constraints on a CO2 Pipeline Network

“…An increasing number of studies have incorporated environmental concerns into spatially explicit energy infrastructure siting models. − They have found that significant environmental protections can be realized with little additional cost. The framework developed by Wu et al integrates different environmental considerations and data sets to create a spectrum of protection levels in a national energy model, so that output and impacts can be compared under a range of protection scenarios.…”

“…Other research has employed land cover and other publicly accessible information to contrast the effects of different options, such as an alternative shale pipeline in Pennsylvania or the establishment of a solar energy infrastructure in Texas. Kroetz et al developed a spatial optimization model with multiple objectives to integrate environmental goals into the planning of shale gas pipeline expansion in Pennsylvania. Similarly, Shawhan et al harnessed land cover and other openly available data to assess the interplay between environmental and economic factors when imposing restrictions on solar farm siting restrictions in Texas.…”