Workshop on Energy and Environmental Research

UH Mānoa is particularly strong in energy, environment and resource policy, which often requires interdisciplinary research. This workshop is organized by UHERO and facilitates interaction among faculty and graduate students in UHERO, Economics, Engineering, NREM, DURP, SOEST and more. We also hope to draw participation from visitors and professional economists and policy analysts around the State. Work in progress is strongly encouraged!

Seminars will take place online over Zoom on Mondays from 12:00pm – 1:15pm. Subscribe to the WEER mailing list to receive the Zoom link and further information on upcoming sessions.

Class Credit:
Graduate students can obtain ECON 696 credit from Professor Lynham.

Implications of a “Green Tariff” for the University of Hawai‘i, Hawaiian Electric Company, and other Customers

Michael Roberts UHERO Report

Abstract

To help address the shared interests of the University of Hawai‘i and Hawaiian Electric Company (HECO), a “Green Tariff” (officially proposed as “Rider Z”) has been proposed that would, in effect, allow the Mānoa campus to receive credit for solar installed at one of its off-site properties. Under this tariff, HECO would obtain a purchase power agreement (PPA) for solar to be installed on off-site land parcel. The cost of the PPA would be added to the Mānoa campus bill, and the University would receive a credit for energy provided by the solar installation. If the off-site solar installation and associated PPA were to include batteries, making the site dispatchable like a traditional power plant, then the University would receive additional credit under a “Virtual Rider M” that would act to reduce demand charges associated with the Mānoa campus peak load.

This report considers the implications of the proposed Rider Z on the University’s energy costs as well as its implications for HECO and its other customers. The impacts of this tariff depend on other decisions the University makes in managing its energy use over the coming decades, as well as on highly uncertain factors that are outside the control of the University. Most significantly, the value of Rider Z to the University, as well as its impact on other customers, depends on the path of future oil prices and how quickly HECO transitions away from fossil fuels. These factors matter because, under Rider Z, the credit provided to the University for off-site solar is tied to island-wide fuel costs as a share of total generation costs. Thus, the higher are oil prices, and the more slowly the island transitions from fossil fuels, the greater the credit to University.

An overarching concern with the structure of the Rider Z credit is that it is not tied to HECO’s avoided costs. Thus, the credit provided for the solar installation may exceed or fall short of its broader value to the system. Similarly, we find that the credit associated with the Virtual Rider M would generally exceed the value of the battery to HECO. On balance, we find that nearly all of the scenarios where the University would save money relative to the status quo imply an even larger indirect cost to other customers. In a typical mid-line scenario, we find that for every dollar the University saves with Rider Z and Virtual Rider M, other customers will collectively pay about $1.14 more.

 

Fishal Recognition: Combining Citizen Science and Machine Learning to Perform Stock Assessment in Tropical Multi-species Fisheries

John Lynham

Abstract

One of the major barriers to performing fish stock assessment is the effort and cost involved. We leverage a unique citizen science database (hand-labeled photographs of over one million fish, representing >150 different species) to test whether software (instead of hardware) can accurately identify fish species and measure their length. We used the Detectron2 instance-segmentation model to segment images of fish from background features and then used the Inception-ResNet V3 model to identify fish species. The segmentation model was also used to identify background features of uniform length, which then allowed us to use a random forest regression model to measure fish length. At present, we are able to correctly segment 99% of fish from their photographs, accurately identify the species of 91% of fish caught, and measure fish length within 2.2cm of actual length, on average. Perhaps surprisingly, length errors are not skewed towards smaller or larger fish sizes. This suggests that machine learning methods could be used to perform accurate, rapid, and low-cost fish stock assessments on photographs taken by fishers themselves.

 

Incorporating historical spring discharge protection into groundwater management: A case study from Pearl Harbor Aquifer, Hawai‘i

Kimberly Burnett

Abstract

Groundwater management policy around the world increasingly seeks to protect groundwater-dependent ecosystems. This includes human uses tied to natural spring discharge that is important for these linked systems. There are few examples of practical tools to balance human groundwater use with ecological water demand related to spring discharge. Using a simulation optimization framework, we directly incorporate a spring discharge constraint into an analysis of groundwater management as an example of how to operationalize groundwater policy in the state of Hawai‘i. Our application on the island of O‘ahu is a spring discharge-dependent watercress farm with historical, cultural, and ecological significance. This research provides decision makers in Hawai‘i with information regarding the trade-off between groundwater withdrawal and spring discharge, which is connected to multiple benefits, including historical and cultural values in line with codified state beneficial use protections.

 

Assessing the impact of COVID-19 on global fossil fuel consumption and CO2 emissions

Nori Tarui

Abstract

We assess the effect of the COVID-19 pandemic on global fossil fuel consumption and CO2 emissions over the two-year horizon 2020Q1-2021Q4. We apply a global vector autoregressive (GVAR) model, which captures complex spatial-temporal interdependencies across countries associated with the international propagation of economic impact due to the virus spread. The model makes use of a unique quarterly data set of coal, natural gas, and oil consumption, output, exchange rates and equity prices, including global fossil fuel prices for 32 major CO2 emitting countries in 1984-2019. We produce forecasts of coal, natural gas and oil consumption, conditional on GDP growth scenarios based on alternative IMF World Economic Outlook forecasts that were made before and after the outbreak. We also simulate the effect of a relative price change in fossil fuels, due to global scale carbon pricing, on consumption and output. Our results predict fossil fuel consumption and CO2 emissions to return to their pre-crisis levels, and even exceed them, within the two-year horizon despite the large reductions in the first quarter following the outbreak. Our forecasts anticipate more robust growth for emerging than for advanced economies. The model predicts recovery to the pre-crisis levels even if another wave of pandemic occurs within a year. Our counterfactual carbon pricing scenario indicates that an increase in coal prices is expected to have a smaller impact on GDP than on fossil fuel consumption. Thus, the COVID-19 pandemic would not provide countries with a strong reason to delay climate change mitigation efforts.

 

 

Groundwater Economics Made Easy: Sustainability, Ecosystems, Dynamics, and Bathtubs

Jim Roumasset

Abstract

We will discuss the simple economics of groundwater without mathematics and using only the Nike Principle of Microeconomics. When is maximum sustainable yield a good long-term target for aquifer management and how many years should it take to get there? What if the aquifer interacts with upstream and downstream stocks, such as watersheds and nearshore marine ecosystems? What are the uses and limitations of more complex models?

The The Impact of Earthquake on Housing Prices near Nuclear Power Plants: Focusing on Kyungju City in Korea

Dongkyu Park

Abstract

This study focused on estimating the willingness to pay for housing to measure the value of potential risk of Nuclear Power Plant (NPP) in Korea by using Hedonic price model. This paper employed house transaction data with difference-in-differences method for estimating the value of NPP by comparing the impacts of two exogenous shocks on housing prices near Gori NPP in South Korea. One is the Fukushima nuclear accident in 2011 and another is the earthquake of Pohang city in 2017. The Fukushima accident does not affect housing prices near the NPP. On the other hand, there was a long term negative effect for the Pohang earthquake. The result shows that the potential risk of the NPP is well reflected in South Korea real estate market after the Pohang earthquake.

Does Information About Climate Risk Affect Property Values?

Miyuki Hino

Abstract

Floods and other climate hazards pose a widespread and growing threat to housing and infrastructure around the world. By incorporating climate risk into asset prices, markets can discourage excessive development in hazardous areas. However, the extent to which markets actually price these risks remains poorly understood. Here we measure the effect of information about flood risk on residential property values in the United States. Using multiple empirical approaches and two decades of sales data covering the universe of homes in the US, we find little evidence that housing markets fully price information about flood risk in aggregate. However, the price penalty for flood risk is larger for commercial buyers and in states where sellers must disclose information about flood risk to potential buyers, suggesting that policies to improve risk communication could influence market outcomes. Our findings indicate that floodplain homes in the US are currently overvalued by a total of $34B, raising concerns about the stability of real estate markets as climate risks become more salient and severe.

Non-Renewable Resources, Extraction Technology and Endogenous Growth (with Gregor Schwerhoff, IMF)

Martin Stürmer (Federal Reserve Bank of Dallas / International Monetary Fund)

Abstract

We document increasing extraction but constant real price trends for 65 non-renewable resources from 1700 to 2018. Why have resources not become scarcer with global economic growth? Resource stocks are not fixed but a function of geology and endogenous innovation in extraction technology. Rising resource demand incentivizes firms to innovate and allows extraction from lower grade deposits. Prices stay constant because resource quantities increase exponentially with lower grade deposits, which follows from a geological law. This offsets diminishing returns in innovation. As a result, the interaction between geology and innovation determines the long-run growth rate of aggregate output. There is no depletion effect. If innovation in extraction continues, a flat long-run supply curve of fossil fuels is a reasonable assumption. A rising carbon tax could discourage such innovation, limiting fossil fuel extraction and greenhouse gas emissions.

Adaptation to Water Scarcity in Irrigated Agriculture

Nick Hagerty

Abstract

How much can societies adapt to environmental change? I provide evidence on this question by studying the response of irrigated agriculture to surface water scarcity. To identify adaptation, I compare the long-run and short-run effects of water scarcity on cropping decisions, which I estimate using institutional variation in water allocation in California. First, I estimate long-run effects using spatial discontinuities in average water supplies at the borders between neighboring water utilities, where farmland is otherwise similar. Then, I estimate short-run effects using weather-driven fluctuations in water supplies from year to year. Using high-resolution satellite data on land use, I find that short-run water scarcity reduces crop area and crop revenue (as predicted by crop choices). Long-run water scarcity shifts land-use patterns in different ways but reduces predicted crop revenue by 85 percent as much as in the short run, implying adaptation is limited. Absent new investments or policy changes, future declines in surface water supplies are likely to notably reduce the land area and output of agriculture.

Mountain-to-sea ecological-resource management: Forested watersheds, coastal aquifers, and groundwater dependent ecosystems

Christopher Wada

Abstract

Improving the understanding of connections spanning from mountain to sea and integrating those connections into decision models have been increasingly recognized as key to effective coastal resource management. In this paper, we aim to improve our understanding of the relative importance of linkages between a forested watershed, a coastal groundwater aquifer, and a nearshore marine groundwater-dependent ecosystem (GDE) using a dynamic groundwater optimization framework and simple ecosystem equations. Data from the Kiholo aquifer on the Kona Coast of Hawai’i Island are used to numerically illustrate optimal joint management strategies and test the sensitivity of those strategies to variations in physical and behavioral parameter values. We find that for a plausible range of watershed management costs, protecting part of the recharge capture area is always optimal. Without watershed protection, maintaining a safe minimum standard growth rate for a GDE-dependent marine indicator species, reduces net present value non-trivially, but optimal investment in watershed conservation offsets that potential reduction by 75%. In general, we find that optimal watershed management and groundwater pumping are most sensitive to changes in water demand growth and parameters that describe nearshore salinity.

Pathways to Decarbonization for O‘ahu: 2020-2045

Makena Coffman and Sherilyn Hayashida

Abstract

In 2018, City Council Resolution 18-221 requested the creation of a Climate Action Plan (CAP) to establish comprehensive milestones to transition O‘ahu to 100 percent renewable energy on the path to carbon neutrality by 2045. This presentation focuses on the variety of policies and programs that reduce GHG emissions, from 2020 to 2045, for O‘ahu. Decarbonization strategies are also assessed with public input from an island-wide representative survey.

Tourism and water scarcity: The impact of hotels and vacation rentals on water resources

Nathan DeMaagd

Abstract

In many parts of the world, tourism is beginning to have a negative effect on natural resource sustainability. This is particularly true of small, isolated islands whose economies rely heavily on tourism, but have limited sources of freshwater. In these cases, the islands often rely on freshwater aquifers with withdrawal rates potentially exceeding sustainable yield. Changes in future climate may put further strains on the aquifers if recharge from rainfall decreases. Our study follows others who have investigated tourism-heavy islands by examining the relationship between tourism and water use on the Hawaiian island of Oahu, while contributing to the literature in two key ways: (1) unlike other studies that focus on islands in developing countries, we focus on an island in a highly industrialized nation with much different demographics, economy, and institutions; and (2) to our knowledge, we are the first to separately consider the effects of traditional hotels and resorts, and the increasingly-popular transient vacation rentals like Airbnb, VRBO, and Home Away. Using a 7-year panel of monthly billing data, along with information gathered about tourism, hotels, and Airbnbs, we find hotel water use is positively associated with hotel occupancy, but there is no significant relationship between residential water use and Airbnb occupancy. Limitations of the study are considered, and potential strategies for water resource sustainability in light of global tourism growth are discussed.

Sea Level Rise Impacts on Property Value in Honolulu

Nori Tarui

Abstract

Sea level rise (SLR) associated with climate change will affect assets, their value, and land use decisions in many coastal areas around the world. Recent studies find that exposure to the risk of future SLR is associated with lower current property values in many coastal areas. In this study we apply property transaction data in the City & County of Honolulu (Oʻahu) between 1994 and 2019 to investigate the effect of current and expected SLR exposure on residential property prices. Using detailed state data on properties under various SLR scenarios (including bathtub modeling as well as considering impacts of seasonal wave run-up and exacerbated coastal erosion patterns), we find that exposed properties have already suffered negative impacts to transaction prices at around 8%. The estimated economic impacts provide implications to coastal management strategies as a climate change adaptation measure; and how alternative strategies such as managed retreat, managed buyback and coastal armoring compare in terms of relative benefits and costs.

Is Air Pollution Regulation Too Stringent?

Reed Walker (UC Berkeley) Working Paper Appendix

Abstract

This paper describes a new approach to estimating the marginal cost of air pollution regulation, then applies it to assess whether a large set of existing U.S. air pollution regulations are too stringent or lenient. The approach utilizes an important yet underexplored provision of the Clean Air Act requiring new or expanding plants to pay incumbents in the same or neighboring counties to reduce their pollution emissions. These “offset” regulations create hundreds of decentralized, local markets for pollution that differ by pollutant and location. We show how offset transaction prices can be interpreted as measures of the marginal cost of abatement, and we compare them to estimates of the marginal benefit of abatement from leading air quality models. We find that for most regions and pollutants, regulation is too lenient; marginal abatement costs are persistently and substantially below marginal abatement benefits. In at least one market, however, regulation is too stringent—the marginal costs of abatement significantly exceed the marginal benefits of abatement. Marginal abatement costs have increased in real terms by over 6 percent annually. Notably, our revealed preference estimates of marginal abatement costs differ enormously from typical engineering estimates. Theory and evidence suggest that using price rather than existing quantity regulation in these markets could increase social welfare.

A benchmark renewable energy plan for performance-based regulation in Hawaii

Matthias Fripp

Abstract

Hawaii recently adopted landmark laws requiring 100% renewable generation by 2045 and performance-based regulation of our electric utilities by 2021. The Hawaii Public Utilities Commission is now finishing a 2.5 year process to establish performance metrics and incentives for the Hawaiian Electric companies. I will give a brief overview of the issues addressed in this proceeding and discuss my role in this process. I will focus primarily on my work with the Ulupono Initiative to develop a forecast for the future design of the Oahu power system, for parties to use in benchmarking the financial effect of performance incentives on the utility. I will contrast this least-cost system design with a dirtier and costlier plan put forward by Hawaiian Electric. This will show some of the factors in play in performance-based ratemaking and highlight concerns to watch for as Hawaiian Electric moves ahead with integrated resource planning next year.

Using Temperature Sensitivity to Estimate Shiftable Electricity Demand

Sisi Zhang, Eleanor Yuan, Matthias Fripp, and Michael J. Roberts

Abstract

On a levelized basis, wind and solar photovoltaic are now among the least costly sources of power but have output that fluctuates with weather and sunlight. While cheaper batteries can help manage intermittency, many uses of electricity may be flexible in their timing, aided by demand-side thermal storage, especially heating and cooling. We estimate potentially shiftable heating and cooling demand by linking hourly electricity demand across the continental United States to fine-grained estimates of hourly temperature over space and time. We find a large share of potentially flexible demand, ranging from 1.3% to 47% depending on the time of day, season and balancing authority. Assuming half the temperature-sensitive demand is shiftable, average daily peak load can be reduced by 8% and daily base load can be increased by an average of 18.3%, and the standard deviation of demand within a day can be reduced by an average of 68.7%. A new rule issued by the Federal Energy Regulatory Commission may incentivize development of markets to enable this potential demand flexibility.

The Effects of the Low Emission Zone Policy on Air Quality: Evidence from Seoul, South Korea

Dongkyu Park

Abstract

The air pollution is an undetachable issue from people’s life and is a perennial problem in South Korea. As a way to improve air quality in Seoul, the Low Emission Zone (LEZ) policy started in Jan 2017. The main purpose of the policy is to restrict the entry of old diesel vehicles into Seoul. To identify effects of the policy on air quality, I use daily frequency of weather and air pollutants data and apply Regression Discontinuity in Time. The threshold is the starting date of the policy, Jan 1st 2017, and the time series is 2 years periods before and after the policy. The targeted pollutants are NO2 and PM10 because the high levels of the pollutants are attributed to the diesel engine system. The result shows that the policy reduced the NO2 concentration by 4.9% and PM10 by 2.1%, but the effect on PM10 is not statistically significant. While this is the first study on the effects of LEZ in South Korea, it also investigates the mechanism behind the policy impact. In particular, we find how vehicle owners react to the policy via traffic data.

Testing the Pollution Haven Hypothesis on the High Seas

Sarah Medoff and John Lynham

Abstract

The stringency of environmental regulation of tuna production in the Pacific Ocean varies temporally, spatially, and cross-sectionally for US-registered firms. We use this variation, which is exogenous to changes in trade policy, to test a central tenet of the pollution haven hypothesis: more stringent environmental regulations causes firms to relocate to less regulated regions and may not reduce aggregate environmental harm. Double- and triple-difference tests on changes in daily production decisions provide causal evidence in support of the hypothesis. Firms relocate over 600 miles within a few weeks of new regulatory measures. We do not observe reductions in aggregate environmental damage and preliminary results suggest that, in some years, more stringent regulations cause more environmental harm than would be observed in the absence of these regulations.

What's a beach day worth? Economic valuation of Waikiki Beach

Marcus Peng

Abstract

Waikiki Beach is one of the leading tourism destinations around the world, and is a large economic driver of the Hawaii state economy. As an artificial beach, it requires ongoing management and intermittent beach renourishment, exacerbated by climate change and sea-level rise. As part of ongoing and public investment into this valuable recreational resource, it is important to understand the function and value of beach characteristics and the nearshore environment. We estimate the value of changes in the beach width and water quality by applying a stated preference discrete choice experiment. Outcomes can inform policy decisions and justify public expenditures for the maintenance and improvement of Waikiki Beach.

 

Breaking Into Industry for Economists (and their grad students)

Jonathan Eyer

Abstract

Jonathan Eyer is an economist/data scientist at HP, Inc where he works on the Future Pricing Strategy team within the Pricing Analytics Center. The Pricing Analytics group serves as an internal consulting firm for internal HP stakeholders and customers, providing guidance on how to modify pricing behavior to meet strategic goals. The Future Pricing Strategy team provides an interface with newly developed data science and econometric approaches to consider “atypical” problems and to imagine new ways to model pricing and consumer behavior. He will provide an overview of how empirical economists can carve out a comparative advantage within the growing data science field. There will be discussion of the specific econometric and data science methods that are transferable, the soft skills that aren’t (typically) taught in grad school, and how to frame yourself to get through an HR screen and hiring committee. Prior to joining HP, Jonathan was a Research Assistant Professor at the University of Southern California’s Sol Price School of Public Policy where he focused on environmental and energy economics and risk.