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The proposal is much improved compared to the first round, and we thank the author for the long explanation. The proposal is quite innovative but needs more fleshing out as well as real test case with an actual nation. While the methodology is clearer, the implementation is not clear: how will the monetary valuation be turned into higher prices, which will then generate more revenues that can be used to select more expensive technologies which are beneficial for health and the environment? There are some inconsistencies between the Impact Assessment Result Table, the list of countries where the actions will be taken and the countries listed in the section "where will these actions be taken".
The suggested paper can be an important contribution to leverage the thinking on the approach to energy planning that takes into account health and environmental costs, but the study itself should be done by IEA, IPPC and other entities that can leverage on their role to facilitate implementation.
The author needs to address the judgemental assessment required to come up with a single monetary value for a given energy mix for power generation. This difficulty is inherent in all multi-criteria approach, as it requires an agreement on how to aggregate results, or at least on the monetary value to be used for each parameter. The proposal proposes an approach to energy planning that takes into account health and environmental costs, but does not propose a solution to internalise those externalities so that those costs can be reflected in electricity bills.
Nov 3, 2017
Thank you for your insightful comments.
My project presents a method and a model to internalize the large and often hidden environmental and health externalities by quantifying them in terms of dollars and incorporating them into energy planning cost minimization algorithms.
You hit the nail on the head, monetarily valuing all environmental and health impacts and representing them in terms of dollars (or the currency of the country of analysis) is crucial for internalizing these externalities. Several reasons for this include:
*When environmental and health impacts are expressed as dollars, they can be internalized in existing cost minimization algorithms and methods for capacity expansion planning and electricity dispatch optimization.
*Expressing environmental and health impacts as dollars makes their impact easier to understand for government, industry, academia and the public.
*More straightforward and optimization techniques can be used when a single dollar amount, the sum of total economic, environmental and health costs, is being minimized (as opposed to optimizing many variables). I also plan to test more advanced optimization methods, such as setting a range for acceptable economic costs, and then generating Pareto Curves for energy infrastructure scenarios that minimize environmental and health costs within the acceptable economic cost range.
*Economic, environmental and health costs can be easily compared between current and future (country-level) energy infrastructure scenarios when they are expressed as dollars. For example, many decadal electricity expansion plans have economic costs that differ 10-20%, but the environmental and health costs vary tremendously. By comparing the environmental and health costs of country level energy expansion plans, the environmental and health costs that society occurs can many times be drastically reduced without spending more money.
*The relative magnitude of impact for each of the 18 environmental and health impact can be compared and prioritized when they are monetarily valued. For example, of the 18 impact categories my model considers, the three categories that typically have the largest cost are respiratory impacts on human health due to particulate matter, climate change impacts on human health, and climate change impacts on ecosystem diversity.
*The magnitude of environmental and health costs can be compared to the magnitude of economic costs when they are expressed as dollars. Take 2015 for example, while the average retail price of electricity in the U.S. was $0.104 per kWh, my model estimates that the average cost of environmental and health externalities was $1.06 per kWh. This implies that in the U.S., the large and somewhat ignored external costs are approximately 10 times greater than the costs that are being considered by energy planners and policy makers.
To quantify and monetary value all environmental and health impacts, I use the ReCiPe 2008 method because it is one of the most widely accepted LCA endpoint methods and it is used by the IPCC (Goedkoop et al., 2013). The ReCiPe 2008 method maps 18 impact categories to three endpoints: human health, biodiversity extinction and resource depletion.
There are six human health impact categories in the ReCiPe 2008 LCA method, all of which are mapped to a common metric that quantifies the years of life lost due to illness or premature death, known as a Disability Adjusted Life Year (DALY). One DALY is equivalent to one year of life lost. I derive a monetarily value for a DALY by taking the EPA standard Value of a Statistical Life (VSL) and dividing it by the life expectancy for the country of analysis (Environmental Protection Agency 2016). In the U.S., the EPA recommended VSL for 2015 is $9,500,000, and the average life expectancy is 81 years, so each DALY is valued at $117,283 in 2015 dollars. A VSL can be derived for each country using the EPA recommended elasticity of 0.4 between income and willingness to pay to avoid adverse health outcomes (Shindell et al., 2006).
A commonly accepted single unit to express environmental impacts is species biodiversity loss. The ReCiPe 2008 LCA method maps all environmental impacts to a single unit that measures biodiversity loss, known as a potentially disappeared fraction of species (PDF). I use a monetary value of $157 million USD per species lost based on the Pizzol et al. (2015) review of monetary valuation in lifecycle assessment.
In the Recipe 2008 method, oil and mineral resource depletion impact categories are expressed as monetary values based on the increased cost of resource extraction. The water depletion category can be monetarily valued if desired based on a price per cubic meter of water consumed during the LCA processes.
My model can be run for any country or electricity grid and outputs economic, environmental and health costs in terms of dollars using the ReCiPe 2008 method. The cost minimization algorithm can then internalize the full spectrum of external costs when determining which mix of energy sources minimizes total economic, environmental and health costs for a given region or country.
Reflecting these costs in utility bills is an excellent idea. One of the ways this could be implemented is by presenting the average cost in dollars of environmental and health externalities per kWh (broken down by contributions per energy source by the consumers’ utility) alongside the retail electricity cost per kWh. Interestingly, while I was piloting a new fellowship program in 2016 between the U.S. Environmental Protection Agency (EPA) and U.S. National Science Foundation, I started discussions with the U.S. EPA EnviroAtlas team about a similar idea.
EnviroAtlas is a public website (https://www.epa.gov/enviroatlas), which that hosts an interactive GIS database that the public can use to learn about environmental services. I proposed publishing a GIS layer that includes the retail electricity cost for each state, and the monetary value of environmental and health costs produced by electricity consumption in each state, with a breakdown of how much each energy source contributes to the total externality costs (coal, oil, gas, hydro, solar, wind, geothermal etc...). The EnviroAtlas team expressed a desire to coordinate publishing my results in a scientific journal along with the release of the EnviroAtlas electricity cost GIS layer and an EPA press release. The purpose is to inform the public of the large and often hidden external costs of energy to help them vote in their best interest.
It is important to note that society is already incurring the external environmental and health costs of energy production, although they are unevenly distributed and incurred over a long-term horizon. To minimize these external costs alongside internal costs, I am advocating including these costs in the long-term energy planning strategies and methods used by national energy organizations to design long-term energy expansion policy. This can be done by using my model (or another country scale energy model that performs LCA analysis, although I have not found any and none were listed in the Connolly et al. (2010) review) to determine how environmental and health costs differ between the various future energy infrastructure scenarios a country is considering.
To take minimizing the internal and external costs of energy production a step further, the optimization module in my model can determine the mix of energy infrastructure that will minimize total economic, environmental and health costs for any country or region. This lowest cost mix could be set as a standard that the industry moves towards as capacity increases and infrastructure depreciates. Comparing and minimizing the economic, environmental and health costs of energy infrastructure scenarios can also be used to optimize current goals, such as the Intended Nationally Determined Contributions for climate change as set in the Paris Agreement and the Renewable Portfolio Standards in the U.S.
I hope this addresses your questions. I have updated the ‘Summary’ and ‘What actions do you propose’ sections of my proposal with this information. I am happy to provide further details wherever there is interest.