An Approach to Enhance the Conservation-Compatibility of Solar Energy Development

The rapid pace of climate change poses a major threat to biodiversity. Utility-scale renewable energy development (>1 MW capacity) is a key strategy to reduce greenhouse gas emissions, but development of those facilities also can have adverse effects on biodiversity. Here, we examine the synergy between renewable energy generation goals and those for biodiversity conservation in the 13 M ha Mojave Desert of the southwestern USA. We integrated spatial data on biodiversity conservation value, solar energy potential, and land surface slope angle (a key determinant of development feasibility) and found there to be sufficient area to meet renewable energy goals without developing on lands of relatively high conservation value. Indeed, we found nearly 200,000 ha of lower conservation value land below the most restrictive slope angle (<1%); that area could meet the state of California’s current 33% renewable energy goal 1.8 times over. We found over 740,000 ha below the highest slope angle (<5%) – an area that can meet California’s renewable energy goal seven times over. Our analysis also suggests that the supply of high quality habitat on private land may be insufficient to mitigate impacts from future solar projects, so enhancing public land management may need to be considered among the options to offset such impacts. Using the approach presented here, planners could reduce development impacts on areas of higher conservation value, and so reduce trade-offs between converting to a green energy economy and conserving biodiversity

Energy Sprawl or Energy Efficiency: Climate Policy Impacts on Natural Habitat for the United States of America

Concern over climate change has led the U.S. to consider a cap-and-trade system to regulate emissions. Here we illustrate the land-use impact to U.S. habitat types of new energy development resulting from different U.S. energy policies. We estimated the total new land area needed by 2030 to produce energy, under current law and under various cap-and-trade policies, and then partitioned the area impacted among habitat types with geospatial data on the feasibility of production. The land-use intensity of different energy production techniques varies over three orders of magnitude, from 1.9–2.8 km2/TW hr/yr for nuclear power to 788–1000 km2/TW hr/yr for biodiesel from soy. In all scenarios, temperate deciduous forests and temperate grasslands will be most impacted by future energy development, although the magnitude of impact by wind, biomass, and coal to different habitat types is policy-specific. Regardless of the existence or structure of a cap-and-trade bill, at least 206,000 km2 will be impacted without substantial increases in energy efficiency, which saves at least 7.6 km2 per TW hr of electricity conserved annually and 27.5 km2 per TW hr of liquid fuels conserved annually. Climate policy that reduces carbon dioxide emissions may increase the areal impact of energy, although the magnitude of this potential side effect may be substantially mitigated by increases in energy efficiency. The possibility of widespread energy sprawl increases the need for energy conservation, appropriate siting, sustainable production practices, and compensatory mitigation offsets

Green tradable certificates versus feed-in tariffs in the promotion of renewable energy shares

The paper analyzes the relationship between CO2 mitigation policy and promotion policies designed to deploy renewable energy sources for electricity production (RES-E). If an emission cap is the only policy target, an optimal mix consisting of high and low carbon use of fossil fuels, deployment of RES-E, and energy savings can best be achieved by either setting a uniform carbon tax or by implementing a cap-and-trade system covering all CO2 sources. An additional RES-E share target causes higher costs in achieving the cap. Conversely, a more ambitious emission target automatically increases the RES-E share. In a second step we investigate different policies for inducing an RES-E quota. Such a quota can be efficiently achieved either by a system of tradable green certificates or by a budget-balancing premium system. A budget-balancing FIT system, by contrast, is not efficient, since it generates excessive fiscal distortion. We also show that differentiated, technology-specific FITs are even more inefficient

Decision making under uncertainty using a qualitative TOPSIS method for selecting sustainable energy alternatives

The final publication is available at Springer via http://dx.doi.org/10.1007/s13762-016-0982-7Multi-criteria decision-making methods support decision makers in all stages of the decision-making process by providing useful data. However, criteria are not always certain as uncertainty is a feature of the real world. MCDM methods under uncertainty and fuzzy systems are accepted as suitable techniques in conflicting problems that cannot be represented by numerical values, in particular in energy analysis and planning. In this paper, a modified TOPSIS method for multi-criteria group decision-making with qualitative linguistic labels is proposed. This method addresses uncertainty considering different levels of precision. Each decision maker’s judgment on the performance of alternatives with respect to each criterion is expressed by qualitative linguistic labels. The new method takes into account linguistic data provided by the decision makers without any previous aggregation. Decision maker judgments are incorporated into the proposed method to generate a complete ranking of alternatives. An application in energy planning is presented as an illustrative case example in which energy policy alternatives are ranked. Seven energy alternatives under nine criteria were evaluated according to the opinion of three environmental and energy experts. The weights of the criteria are determined by fuzzy AHP, and the alternatives are ranked using qualitative TOPSIS. The proposed approach is compared with a modified fuzzy TOPSIS method, showing the advantages of the proposed approach when dealing with linguistic assessments to model uncertainty and imprecision. Although the new approach requires less cognitive effort to decision makers, it yields similar results.Peer ReviewedPostprint (author's final draft