Daniel Steinberg

Lidar remote sensing variables predict breeding habitat of a Neotropical migrant bird.

A topic of recurring interest in ecological research is the degree to which vegetation structure influences the distribution and abundance of species. Here we test the applicability of remote sensing, particularly novel use of waveform lidar measurements, for quantifying the habitat heterogeneity of a contiguous northern hardwoods forest in the northeastern United States. We apply these results to predict the breeding habitat quality, an indicator of reproductive output of a well-studied Neotropical migrant songbird, the Black-throated Blue Warbler (Dendroica caerulescens). We found that using canopy vertical structure metrics provided unique information for models of habitat quality and spatial patterns of prevalence. An ensemble decision tree modeling approach (random forests) consistently identified lidar metrics describing the vertical distribution and complexity of canopy elements as important predictors of habitat use over multiple years. Although other aspects of habitat were important, including the seasonality of vegetation cover, the canopy structure variables provided unique and complementary information that systematically improved model predictions. We conclude that canopy structure metrics derived from waveform lidar, which will be available on future satellite missions, can advance multiple aspects of biodiversity research, and additional studies should be extended to other organisms and regions.

Exploring the market for third-party-owned residential photovoltaic systems: insights from lease and power-purchase agreement contract structures and costs in California

Over the past several years, third-party-ownership (TPO) structures for residential photovoltaic (PV) systems have become the predominant ownership model in the US residential market. Under a TPO contract, the PV system host typically makes payments to the third-party owner of the system. Anecdotal evidence suggests that the total TPO contract payments made by the customer can differ significantly from payments in which the system host directly purchases the system. Furthermore, payments can vary depending on TPO contract structure. To date, a paucity of data on TPO contracts has precluded studies evaluating trends in TPO contract cost. This study relies on a sample of 1113 contracts for residential PV systems installed in 2010–2012 under the California Solar Initiative to evaluate how the timing of payments under a TPO contract impacts the ultimate cost of the system to the customer. Furthermore, we evaluate how the total cost of TPO systems to customers has changed through time, and the degree to which contract costs have tracked trends in the installed costs of a PV system. We find that the structure of the contract and the timing of the payments have financial implications for the customer: (1) power-purchase contracts, on average, cost more than leases, (2) no-money-down contracts are more costly than prepaid contracts, assuming a customer’s discount rate is lower than 17% and (3) contracts that include escalator clauses cost more, for both power-purchase agreements and leases, at most plausible discount rates. In addition, all contract costs exhibit a wide range, and do not parallel trends in installed costs over time.

Cost-effectiveness and Economic Incidence of a Clean Energy Standard

A Clean Energy Standard (CES) is a flexible, market-based policy instrument that could be adopted to reduce greenhouse gas emissions from the U.S. electricity system over time. This paper uses several well-known energy system and electricity models to analyze a CES that reflects broad principles outlined in President Obamas January 2011 State of the Union Address and in the Administrations subsequent Blueprint for a Secure Energy Future. 1 In particular, it examines three different design options for a CES that would each lead to approximately 80% clean electricity by 2035. These different design options provide broadly similar economic incentives for clean energy deployment and yield similar overall welfare impacts, but they exhibit different distributional outcomes. The most inclusive CES crediting approach favors producers over consumers in competitive electricity markets as well as regions with larger initial endowments of clean energy. On the other hand, the most restrictive crediting approach favors consumers over producers and reduces preferences for regions with larger initial endowments of clean energy. While specific technology outcomes vary across the four models used in this study, key insights about cost-effectiveness and economic incidence are largely robust to the underlying modeling platform. These insights may be important considerations in future CES policy design efforts.

Preliminary Analysis of the Jobs and Economic Impacts of Renewable Energy Projects Supported by the ..Section..1603 Treasury Grant Program

This analysis responds to a request from the Department of Energy Office of Energy Efficiency and Renewable Energy to the National Renewable Energy Laboratory (NREL) to estimate the direct and indirect jobs and economic impacts of projects supported by the Section 1603 Treasury grant program. The analysis employs the Jobs and Economic Development Impacts (JEDI) models to estimate the gross jobs, earnings, and economic output supported by the construction and operation of the large wind (greater than 1 MW) and solar photovoltaic (PV) projects funded by the Section 1603 grant program.

Energy efficiency and emissions intensity standards

We investigate the role of energy efficiency in rate-based emissions intensity standards, a particularly policy-relevant consideration given that the Environmental Protection Agency’s Clean Power Plan allows crediting of electricity savings as a means of complying with state-specific emissions standards. We show that with perfectly inelastic energy services demand, crediting efficiency measures can recover the first-best allocation. However, when demand for energy services exhibits some elasticity, crediting energy efficiency can no longer recover first-best. While crediting removes the relative distortion between energy generation and energy efficiency, it distorts the absolute level of energy services. Building on these results, we derive the conditions determining the second-best intensity standard and crediting rule. Simulations calibrated to the electricity sector in Texas find that while some form of crediting is generally welfare-improving, the proposed one-for-one crediting of energy savings is unlikely to achieve efficient outcomes.

Trade-Offs in Trade: Examining the Impacts of Interstate Cooperation under Alternative Clean Power Plan Compliance Scenarios

The EPA’s recently finalized Clean Power Plan (CPP) establishes several pathways for compliance, including category-specific rate standards, state rate standards, and state mass targets. For each compliance pathway, states are allowed to cooperate in order to reduce compliance costs. While cooperation through trade will unambiguously lower total compliance costs, at the state level it can either lower costs for both states, or for one at the expense of the other. Moreover, the impacts of cooperation on total emissions are ambiguous in the context of rate policy. In this paper, we develop a simple two-state electricity model to illustrate the potential implications of cooperation for state costs and total emissions within each compliance pathway. For the category-specific rate standards, we show that cooperation typically, though not always, lowerscosts in both states. However, it can also result in increased CO2 emissions, an outcome that becomes increasingly likely as renewable energy costs diverge across the states. For the state rate standards, the CPP requires cooperating states to blend their state-specific rates into a single weighted-average rate. We demonstrate two counteracting effects of cooperation faced by the state with the more lenient standard: a “trade effect” that lowers state costs through a shared compliance credit market, and an “averaging effect” that raises state costs for one state through the adoption of a more stringent standard. For the state mass targets, we show that for a cap-and-trade policy with auctioned allowances, lump-sum rebating back to the states on the basis of their initial caps will benefit both states.