Audience: We can hear you and the screen looks just fine, Avantika.
Avantika Singh: OK. Thanks, Bob. Perhaps you can give me a green light when it's a good time to start.
Moderator: I think we're two minutes after right now, Avantika, and whenever you're ready I think it will be fine for you to proceed. Really looking forward to it.
Avantika Singh: Perfect. Thank you. And just checking one more time, everyone can hear me OK?
And with that, welcome everyone to the third webinar in the series of Co-Optima capstone webinars. My name is Avantika and I am a research engineer in the Economic Sustainability and Market Analysis Group here at NREL, and I also serve as the deputy lead for analysis at Co-Optima. I'm joined by Troy Hawkins, who is the lead for analysis within Co-Optima and would be helping me keep an eye out on the chart along with the leadership team. I'm very thankful for that.
So the topic of today's webinar is what are the environmental and economic benefits that can be potentially realized by co-optimizing fuels and engines for light-duty passenger vehicles. This, again, I should say this has been a strong team effort with guidance and support from the Co-Optima leadership team: Dan Gaspar, Bob McCormick, Anthe George, and Robert Wagner; as well as our DOE leadership team, which is Alicia Lindauer and Kevin Stork; and Mike Weismiller from VTO and BETO.
And finally I'd like to thank you all for dialing in to hear about our findings from this work.
Moving to the next slide.
The way this webinar is organized is we will start by highlighting the goal of the program, which has basically been to integrate engine R&D with fuel R&D to get maximum benefits. And then I will mention the key takeaways from our analysis on specific environmental and economic benefits that can be realized by co-optimizing fuel and spark-ignition engines, particularly in the states, for light-duty passenger vehicles. Then I will talk about our research approach, and that being just from deploying a whole suite of analysis tools that can identify biofuel candidates as well as measure their environmental impacts, and also realize about the other environmental widescale deployment benefits from widescale adoption to sector-wide socioeconomic benefits.
And then I will dive into the notable outcomes from different aspects of these analyses to provide a holistic picture. And with next steps, I would highlight some of the key ideas that we are pursuing in the light of where some of the industry is headed in terms of electrification as well as looking at cost of abatement for CO2.
So moving to what Co-Optima has essentially been trying to do: we are seeking renewable fuel-engine combinations. The focus has been on liquid fuels that have been derived from non-food-based sources. So that is important because you are looking at different feedstock types, such as terrestrial biomass, wastes, and sludges, as well as algae. And the focus for this seminar has been light-duty, but the idea has been to assess well-to-wheels impacts for biofuel options, and medium- and heavy-duty would be the focus of the next webinar. So today we are talking mostly about light-duty.
And so depending on some of the tools that we have deployed, we have generated insights on specific aspects such as what would be the biofuel value to refiners, what would be the trajectory of vehicle adoption, and then some of the environmental and socioeconomic benefits. And with all of these different tools that are being deployed, the idea is to generate a rich data set that can provide knowledge and inform the broader stakeholder community.
So at Co-Optima we have looked at on-road transportation. It has ranged from light-duty to heavy-duty. The first one from Co-Optima was boosted spark-ignition, which was near the tangible targets that we could achieve by increasing in engine efficiency. And currently multimode combustion has been pursued, which I will allude to toward the end of my presentation. And then medium- and heavy-duty, which is diesel combustion and advanced compression ignition, are also key focused, which would be the subject of upcoming webinars.
And on the subject of upcoming webinars, I would like to give a shout out to the next one, which will be presented by Troy. Troy is going to talk about similar environmental and economic benefits that can be realized by co-optimizing fuels and engines for medium-duty and heavy-duty commercial vehicles. In August and September, Magnus would be presenting on what are some of the unconventional engine-fuel combinations that show promise for efficiency improvements beyond current light-duty, medium-duty, and heavy-duty technologies. And finally in September, Robert and Dan would be speaking about what we have learned from our work in Co-Optima and where we are headed.
So this is a URL for link to the previous webinars, as well as some of the upcoming ones. And I would encourage you to check this out.
So coming back to the goal for this work. The goal has been to quantify the economic and environmental benefits of using high-octane fuels. So today I'll describe our progress and findings from our analysis, as well as connecting these fuel properties, such as higher octane number and high sensitivity to potential sector-wide socioeconomic benefits from increased deployment.
So as we know, the premise for Co-Optima has been increasing efficiency, which can lower fuel consumption and carbon emissions. This is a slide that gives the context of the scale. So for example, today the average fuel economy is around 22 miles per gallon, which roughly, at least in the U.S. alone, is – the transportation sector in the U.S. alone is considered around 15.8 exajoules of energy, which corresponds to about 1,000 teragrams of CO₂ emissions.
And thinking about drastic efficiency improvements, let's say we can get to 50 miles per gallon, that reduces the energy consumption by half and CO₂ emissions by half. And if you're wondering what is an exajoule – I had to look it up – it translates to roughly about 24 million tons equivalent of oil. So thinking about 15 is just so much higher.
So in Co-Optima we are trying to improve or find fuels that by virtue of their properties can improve engine efficiency. And while that work was the focus from Dan and Jim's presentation with Capstone webinar one, that was discussed how fuel properties and engine combinations can increase engine efficiency. Today I am going to focus on what are some of the sector-wide and economy-wide environmental impacts, what are the costs of those biofuel production, and therefore what are some of the domestic job and socioeconomic benefits that we can realize.
So the search in Co-Optima has focused on addressing fundamental questions. The three fundamental questions that we have focused on are what do fuels – sorry, what do engines really want? And then for that, what fuel options work best? And finally, what will work in the real world?
So Dan and Jim have previously discussed the first two aspects of what engines really want and what fuel options work best. Today we will be discussing that based on those fuel options that have been identified with those of the desirable chemical structure, as shown in the middle box. And then we will just what would be the cost and environmental impacts of those biofuels production. And then thinking more broadly about what would work in the real world really? What are some of the barriers to scale up? What are some of the infrastructure compatibility issues and some of the supply chain sort of questions that we would answer by thinking about what can potentially work in the real world.
So before we go into the approach and outcomes, I just wanted to highlight the key takeaways. Essentially the story has been: because of the performance advantage of these biofuels, which are also low carbon, they can offer value to the economy. Notably there are four key takeaways that I'm going to highlight.
So for the first one, with downsized turbocharged engines, we can see that we get lower fuel costs per mile from higher efficiency of those co-optimized vehicles.
The second one that I would like to highlight is that we have identified several promising biofuels that have more than 60 percent greenhouse gas reductions compared to gasoline.
The third one is trying to look at potential value to refiners, and that will be realized based on several factors. The key ones are listed here. So it depends on two properties, as I alluded before, the research octane number and octane sensitivity. The blend level are combined. The refinery configuration, whether it is a large complex refinery versus a small simple refinery. And finally, how the fuel demand as we know will evolve over time. So we are trying to quantify the value to refiners.
And broadly, once those engines are deployed into the market and those powertrains are available for consumers, we can see that overall in the sector, there would be a reduction in petroleum consumption because of higher efficiency gains, there would be reductions in GHG emissions, there would be lower water consumption, and of course the air quality improves by lowering fine PM 2.5 emissions as well.
So switching gears a little bit and thinking about our research approach, I am going to introduce several of the integrated modeling tools that we have deployed to perform comprehensive analysis. And to organize the presentation a little bit, the way we have divided this comprehensive benefits and risk analysis approach are in those four pillars, and I'll keep coming back to this. So in the four pillars that we are looking for analysis, the first one that we are thinking about is biofuel production. So how cost effective is it to produce biofuels? And once those biofuels are produced, what would be supply chain impact, so how would the refinery willing to value of Co-Optima biofuel? And once fuels are produced at a refinery gate, how well they're used in engines that have co-optimized turbocharged engines from Co-Optima? And how would that vehicle technology penetrate the market over time? And with that fuel demand that is offered by the new drivetrains that are offered by the new drivetrains that are in the market, we can see how would the biofuels industry meet the fuel demand, how would the biorefinery reconstruction happen over time, and how would some of the jobs and overall sector impacts be measured?
So I keep coming back to the slide which talks about the different aspects of our analysis. So to begin with biofuel production, the approach that we have for biofuel cost and LCA is from developing process models that NREL and PNNL have expertise in developing, looking at process conditions, material consumption, product use. And the whole goal of the technoeconomic analysis is that it helps us identify what would be the biofuel production costs, so dollars per GGE. GGE is gasoline gallon equivalent, so thinking about analogous volume that you can displace of gasoline.
And that goes on to inform the high-performance fuels teams within Co-Optima as well as broader stakeholders such as the external advisory board and the results are disseminated by publications. But with the modeling, we also integrate with LCA approach, where LCA helps us look at what would be the GHG emissions reductions, what would be the water and energy consumption reductions just performed by Argonne's lead model. So using a combination of TEA and LCA helps us inform the research direction.
The way we use these metrics is to classify the scale-up potential. And we look at three different aspects, or scalability metrics, I should say, which are: economic, environmental, and technology readiness levels. And we measured not just the current scenarios, but also trying to think where advancement and research can change the future targets in areas. And there are essentially 19 metrics that are – I will go back to the results and talk about them, but there are simply 19 metrics that we are measuring across economic, environmental, and readiness levels, and those metrics are classified as favorable, neutral, unfavorable, and in cases where data is not available, as unknown.
So we'll look at some of the examples of biofuels later on, but moving on for now to refinery benefits. Once we have these biofuels produced, we want to understand how finally we are going to adopt them, how can they blend it, and what would be some of the economic and environmental implications of blending.
So the idea here is to understand using the tools that refineries normally use, such as optimization and linear programming tools, such as Aspen PIMS. We want to understand what fuel properties would generate market pull from refiners. So as we identify the full octane number and sensitivity and to be some of those high-value properties, and then we want to not just understand the cost, but also the environmental performance of those refinery products. So we want to compare with business-as-usual case when a Co-Optima bio-blendstock would not be available, and then trying to understand what would be the cost and renewability implications from blending into the refinery products.
For this we have built three different refinery configurations in Aspen PIMS, which stands to be the most prevalent tool for refinery planning and optimization. We have one large complex refinery, another average medium-complexity refinery, and third, a small simple refinery, all based in [distorted audio], which has more than 50 percent of the nation's capacity. And what we are doing is we think the refinery has these Co-Optima bio-blendstocks available in the market and they would eventually be blended into gasoline or diesel. In this case, we are mostly focused on light-duty.
We have this special premium grade of gasoline called Co-Optima gasoline, which is made of reformulated medium grade. And the way we improve these models is by exhaustively incorporating different crude oils, built pricing models for those crude oils as a function of their quality. All of the finished products meet ASTM specifications as well as prevalent market conditions. And these pricing models have also been developed rigorously for finished products and not just crude. So deploying this Aspen PIMS has allowed us to look at what would be the value of these biofuels to the refiners.
And in conjunction to the Aspen PIMS tool, we also have built a PIMS LCA model, which is an Excel-based tool to inform carbon intensity of refinery emissions. This tool links with material flows coming out of Aspen PIMS as well as other LCA tools, such as PRELIM, GREET, and VOC Calculator, which allows us to look at refinery performance as a whole, or even like looking at specific refinery products to see what would be the greenhouse gas reduction, what would be some of the VOC emissions reduction and other criteria pollutants. I will share examples of those results later on during the presentation.
So switching gears a little bit and thinking about vehicle adoption, we want to see how some of the engine-efficiency improvements can lead to greater penetration of Co-Optima engines or drivetrains into the market. And for that the choice of tool is ADOPT, which allows us to look at evolution of automobile fleet into the market. And this is a tool that looks at all the existing makes and models of different powertrains as they exist in the market right now, and then what are some of the consumer preferences, which often tend to be non-linear or priced different and can impact vehicle adoption as well as regulations that might be in place, whether they are CAFÉ standards or any of the policy incentives. And then over time, as technology improvements occur, the fleet is continuously evolving and this is measured every year.
Some of the particular benefits that Co-Optima fuels and engines can offer are in terms of efficiency improvements as well as emissions reductions. So that is also rolled in as factors into this model, which allows us to see how the fleet is changing over time. We look at some of the results from this also in subsequent slides.
And finally, we also want to see the economy-wide benefits, so looking at socioeconomic benefits for Co-Optima tools and rates of adoption. And for that, we are deploying integrated tools that allow us to measure accumulative benefits. I will briefly talk about how these tools link with each other. So ADOPT, as I just mentioned, tells us how many vehicles, especially by type, can be sold, and this factors into the consumer choice, because consumers can realize the gains from efficiency improvement.
Then once we project what would be the vehicle demand over time, we can see how the buyer feels industry would grow. That is informed by BSM. And based on how many biorefineries must be constructed, as well as TEA-related information on what would be the capital infrastructure as well as fixed costs for building those biorefineries, we can understand what would be the net or gross jobs benefits over time.
And also based on the fuel demand that is projected overtime, as well as from GREET, we get what would be the emissions, water, and energy intensity reduction of these vehicles – they can all feed into bioeconomy AGE, which is a tool that we use to look at what would be the energy and environmental impacts of biofuels. And all of these tools eventually help us understand what would be the annual petroleum use, what would be the water consumption, GHG emissions, air criteria pollutants, and everything else from the transportation sector, as well as a side benefit, we also get to see what would be the effects on jobs and the domestic economy over time.
So some of the notable outcomes are that we have identified promising performance-enhancing biofuels that reduce GHG emissions and improve air quality and spur domestic job growth. And I'll talk about the specific results in these upcoming slides.
So circling back to biofuels production, there have been many bio-blendstocks that have been identified, which very often, depending on the different functional groups, but all of these bio-blendstocks have a high octane number and high sensitivity. And the best thing is that they all blend synergistically in terms of octane. Synergistic blending for octane means that you have the final octane number, which is higher than expected from linear volumetric blending alone of bio-blendstock with base petroleum gasoline.
So many of these [distorted audio] groups are alcohols. We also have olefins, furans, and ketones. Most of the results from gasoline, like bio-blendstocks, have been reported in the Boosted SI report, which link is mentioned here, but we are also working on multimode and some of these bio-blendstocks, especially where gasoline range, tends to be fairly similar across maybe more than boosted SI.
Here is an example of the metrics that I had alluded to before. So the 19 metrics that we measure across technology readiness levels, economic viability, and environmental performance. So for example, in technology readiness, we look at feedstock availability and we assume that feedstocks are available at reasonable costs and quantity. This is being explored further to come up with volumes of biofuels that can be produced.
What we also are looking at is blending behavior. And we realize that sometimes oxygen can limit the blend levels for many of these alcohols because of regulatory constraints. So we are looking at testing toward certification as well. In economic viability, we are trying to see what is the current production cost as well as what would be the target production cost, and in some cases dependence on co-product. And on the environmental side, we are looking at what is the carbon efficiency in the base case as well as target case when an advancements has been made, as well as we are looking at lifecycle greenhouse gas, fossil energy use, and water consumption.
The key takeaways are that many of these biofuels can be produced at less than $4.00 per GGE, and in terms of economics – I'll talk about that, but these pathways actually already across biochemical and thermochemical chemical conversion costs.
So for GHG emissions, we noticed that many of these biofuels produce GHG emissions. For reference, petroleum gasoline emissions are around 90 grams CO₂ per megajoule, and anything below this line here is something that offers more than 60 percent GHG reduction relative to petroleum gasoline. And that means it qualifies for advanced biofuel criteria. So this is from measuring those two well-to-wheels GHG emission.
What we really notice is that feedstocks, sodium hydroxide and chemical consumption are the primary contributors to GHG emissions. And most pathways are energy independent because, especially from biochemical pathways, because lignin is burnt and not diverted to a coal product, and therefore burning off lignin provides a bioenergy – energy demand for the biorefinery.
So thinking about once these biofuels are produced, how would a refinery value these biofuels. We noticed that octane number and sensitivity drive the majority of economic benefits. So we try to quantify what would be the potential value of a biofuel to a refiner. And that is measured by breakeven values. So I'm trying to understand how much would a refinery be willing to pay for a biofuel. And that tends to range quite a bit from $10 to $120 per barrel. And the reason for that is it depends on several factors, such as what is the crude pricing, what is the biofuel blending level, what are the octane properties, as well as sensitivity for the biofuels, and at what blend level they're measured.
So as you can see in this plot, we have four different biofuels: ethanol, isobutanol, furans, and cyclopentanone. And they're all – furan and ethanol have the highest octane numbers, which is why they eventually have also the highest breakeven value. And that also tends to vary a little bit with bio-blendstock blending volume percent.
The other thing to note here is that by this dotted line, this shows the average spot price of [distorted audio] ethanol, which is currently what refiners anywhere are paying for blending ethanol into gasoline, which is E10. So there are scenarios over which and blend levels over which these bio-blendstocks offer value, and that depends on several conditions, as indicated.
The other interesting thing that we found was that analysis or the previous analysis was based on large, complex refineries. But we noticed the effect of changing refinery configuration. So here we can see that the value, the orange bar, shows the value to a small less-complex refiner, whereas the blue lines show the value to a large, complex refinery in bold, in PADD3. And we noticed that higher value to smaller, less complex refiners of these biofuels is because they are often octane-constrained and they do not produce as many gasoline varieties or they do not typically produce premium gasoline. So blending of these biofuels allows refiners to make gasoline that is a premium grade, and therefore more valuable to go over our profit [distorted audio] refinery.
The other thing is that this breakeven value changes over time, and that's because EIA projects and also from some of our internal analysis as well, that gasoline demand is expected to decline over time, and therefore the premium – the value of premium gasoline – will only rise. So with that in mind, there is some change in breakeven value of biofuels over time.
And combining the [distorted audio] with LCA, we see that now I'm going to focus on two fuels. And for a 20 percent blend level, we can see that if ethanol and furan are available to refiners, that actually leads to lower emissions. You can see the lower emissions by these dotted values. BAU is the business-as-usual case when the refinery is only producing an E10 kind of gasoline. But with 20 percent blend levels of ethanol and furan into gasoline, you can see that it drives significant GHG reductions compared to BAU case. And most of those carbon reductions are because of the CO₂ uptake during feedstock growth, as can be seen here.
So moving on to vehicle adoption, we can see for boosted, turbocharged spark ignition, we looked at the effect of introducing Co-Optima vehicles into the market in the year 2028 for three different bio-blendstocks: ethanol, furan, and isopropanol. So in the business-as-usual case, when we do not have drivetrain that offers 10 percent efficiency gain, in an engine you can see that conventional gasoline makes up most of the market, with hybridized – conventional gasoline hybridized, as well as plug-in hybridized being the second and the third-largest contributors, but once Co-Optima drivetrains that have higher efficiency are introduced into the market, you can see that they quickly become one of the better-selling vehicles, attributed mostly because of their performance as well as lower fuel cost per mile compared to especially conventional, as well as conventional plug-in electric vehicles, which is pink and blue. So you can see by green, which is where Co-Optima hybridized trains as well as co-optimized trains are introduced into the market are all shown by green.
And once these – I will link these results with what that means for biofuel demand and how that biofuel demand can lead to more biorefinery construction in the next slides. That also goes into how or what are some of the socioeconomic benefits of Co-Optima fuels and vehicle adoption. So going back to the furan case, looking at how when you have all of these vehicle technologies or drivetrains into the market that need co-optimized fuels, you can see that the blended fuels, especially for furan case, can reach up to 61 billion liters by 2050.
So this fuel demand is estimated from potential fleet evolution using Co-Optima engines. And just to give you an idea of what 61 billion liters by 2050 means is just in the year 2019 alone, the gasoline demand in the U.S. was over 560 billion liters. So this is somewhat less than 10 percent of what that can mean.
There is a lot of potential. And again, with all of that biorefinery demand, something that I don't quite have a plot for, but I would encourage you to check out this publication by Jennifer [distorted audio], is to look at how that can also affect the job growth. So to make all of the fuel that can be blended into gasoline, you need different fuel bases and different resources – that leads to significant job creation, especially in rural areas for all the biorefinery construction. So that information is in the publication.
But we also noticed that there is a reduction in greenhouse gases, criteria pollutants, and water use. So as you can see here, the black is business-as-usual case, but then we evaluate two other cases where biofuel is used in like with Co-Optima vehicle adoption is case, and in cases where there is higher or more increased Co-Optima vehicle adoption, which leads to upper bound cases. So we can see in all of these three cases, GHG reductions, for example, just in the year 2050, because of blended biofuel is lowered by 7 percent, water consumption is not shown here, but that's known to be lowered by 9 percent, and PM 2.5 emissions can be reduced also by 9 percent.
So there can be significant potential deployment effects on the air quality as well as water used from looking at Co-Optima adoption at systemwide levels.
And finally, I would like to also talk about what is ongoing. So the current work that we are exploring is looking at trends with electrification. So we want to understand especially more relevant with the multimode, what are some of the tradeoffs between engine efficiency gains, which you can see by this access vertical here, and deployment costs for those engines, which is shown by decreasing deployment costs in this case, what are some of the potential tradeoffs between engine efficiency and vehicle adoption, especially with hybridized and co-optimized vehicles?
So those powertrains, as you can probably expect with higher engine efficiency and decreased deployment costs, would lead to greater adoption, but we are exploring this with aggressive electrification scenarios, which is projected for like leading passenger fleet. So that work is ongoing.
And also I want to give a shout out to some of the other interesting approaches that we are looking at, which is more specific to multimode, but we are trying to understand what is the marginal abatement costs. And this is an interesting concept, because this metric and link economic and environmental dimensions of our technology. So it can describe what is the relative cost of removing one additional unit of pollution from the atmosphere.
So we can estimate what is the marginal abatement cost of greenhouse gas emissions using Co-Optima multimode fuels and engines. And in this case it would be compared with business as usual, which is conventional gasoline engines. And this will allow us to understand how you can avoid GHG and what is the price that you would have to pay to afford those avoided GHGs.
In case marginal abatement cost is negative, that just means that the low-carbon option is much cheaper than the business-as-usual option. So as you can see, most of these are higher, but the underlying idea is that we are exploring, for example, across three different biofuels: ethanol, isopropanol, isobutanol; we can see that for Co-Optima multimode ethanol, the GHG marginal cost of abatement is around $135 metric tons CO₂ equivalent avoided.
This is, again, based on several different parameters that we are exploring. This loops into the increment vehicle cost, this loops in the engine-efficiency gain that can be achieved, the gasoline price, as well as other factors, such as biofuel prices as well. So that analysis is undergoing.
But coming to – taking a step back and thinking about our broad accomplishments, from this analysis as well as through the Co-Optima program as a whole, we have attempted to provide technology options that would increase renewability of transportation fuels. In the light-duty space, we aimed at getting a 10 percent fuel economy gain over 2015 baseline, which we have shown from experimental as well as merit function deployment that is achieved. And in fact, we can see that petroleum consumption, GHG emissions, water consumption, and PM 2.5 emissions are all reduced when Co-Optima fuels and engines are deployed at scale.
Our [distorted audio] of scale for biofuels, we have shown all the different diversity resource base options [distorted audio] space that originate from terrestrial biomass, waste biomass, as well as algae. And providing some of the economic options to adapt those biofuels to changing demands and viability needs constrain most of the industries moving toward lowering emissions faster. And then we have also identified what are the market opportunities for these performance-advantage biofuels, whether it's to refiners or whether it's to the engine and the power drivetrain.
In terms of crosscutting goals, we have shown that we can reduce GHG emissions by at least 20 percent. This has been demonstrated by blending 30 percent biofuel into base gasoline. Many of these options are renewable energy options and they would help decrease dependence on petroleum imports. And with the construction of biorefineries, that would stimulate domestic economy and add to new bioeconomy jobs.
And those were most of our takeaways from analysis on the boosted SI. And I would really like to thank our sponsors at DOE, which is Michael Berube, Valerie Reed, Alicia, who has been involved in guiding very closely on everything analysis related, David, Jim, Gurpreet, Kevin, and Mike Weismiller from VTO offices, who we often interact with to ask for direction and guidance. And on a day-to-day basis, super thankful to the leadership team – Dan, Anthe, Bob, and Robert – for your help and guidance throughout.
And most of this work is done by this very talented team. Thank you everybody for your expertise and hard work. This is the work that I presented from this very strong and capable team today. So thank you all.
And finally, some of the upcoming Capstone webinars that are coming up. Troy is going to present similar analysis for medium-duty and heavy-duty commercial vehicles and June, and Magnus and Dan and Robert will be wrapping it up in September to discuss what all we have learned. So you can check out and register for the upcoming Capstone webinars here.
And with this I would like to thank you all for your attention. Troy probably was keeping an eye out on the chat along with everybody else. I did not know who else was writing, but with this I'm happy to take any questions.
And before that, one final thing is you can check out all the Co-Optima publications at our database here, which is the link.
Moderator: Hi, Avantika. Thank you very much. Very nice. There are three questions in the chat. Let's start with the first one, from Matt Ratcliff at NREL. He says, "Thank you for a very interesting presentation, Avantika. Would you say more about the thermochemical propanol-ethanol blend? And where can find more detailed information about its production?"
Avantika Singh: Yeah, that's a good question. Let me go up.
So it's the propanol-ethanol blend, which is thermochemically produced?
Matt Ratcliff: Yes.
Avantika Singh: Yeah, so we are currently putting together a publication that talks about the process for producing this. The [distorted audio] and we have also looked at the greenhouse gas emission reduction for this. Most of these bubbles, as you can see, you'll have more information there on what's their cost of production, or at least their ranges of their production in terms of baseline cost as well as TRL levels. And if we – in this case, we have some expectation on what's the blend level.
So if there are more particular questions, we have a publication coming up that I can point you to, as well as some details I'm happy to follow offline if there are questions I can probably answer, more specific ones.
Matt Ratcliff: Yeah, I'll just follow up with you by e-mail, Avantika. Thank you.
Avantika Singh: OK. Sounds great. Thanks, Matt.
Moderator: OK. The second question was from me. It appears that the adoption rate of your Co-Optima vehicles appears to be insensitive to the choice of specific blendstock. Was that observation correct? And if so, can you comment on why?
Avantika Singh: Yeah, so there are two things that are leading to this. One is we were trying to get to the same octane number, and what was weighing across all of these adoption scenarios was the blend level required for ethanol, furan, and isopropanol. And the reason, like I said, was we were trying to get to RON of 98. And the blend level I'm forgetting exactly, but I think ethanol was around 15 percent blend level and isopropanol was around probably 21 percent level. So different blend levels were combined to get to the same octane number, which would lead to the same engine-efficiency improvement, which is why it probably seems a little similar across those three cases.
Moderator: Great. Thank you.
Third question in the chat is from Ken [distorted audio]. "I don't understand the expected improvement in air quality in PM 2.5. Don't all light-duty vehicles have to meet the same particulate matter emission standards? And also, wouldn't the use of particulate traps from virtually all PM from all vehicles?"
Avantika Singh: Sorry, can you repeat that please?
Moderator: Yes. Unless Ken wants to – if you want to unmute yourself.
Ken: OK, I'm here. Yeah, my question is about the PM emissions and your statement about improvements in air quality. I think all the vehicles – all new vehicles will have to meet the same PM standard regardless of what fuel they're using. And if they have trouble meeting the standard, they're all going to use particulate traps.
Avantika Singh: Right. So we distinguish emissions by two – what you are describing are like vehicle engine-out emissions, whereas these emissions are from production of biofuel itself or displacement of petroleum. So this corresponds to how the biofuels are produced, and therefore compared to what volume of petroleum they're displacing with their origination from the biofuel production sources.
Ken: OK. Thank you. So it's not related to the vehicle tailpipe at all?
Avantika Singh: No.
Ken: Thank you.
Avantika Singh: Thank you for those questions.
Moderator: OK. And we have Jim McMillan. Jim, I can either read it or you can unmute yourself.
Jim McMillan: Sure. Thank you for the interesting webinar. It's great to see all the Co-Optima work. But right now on the light-duty side, we're seeing all the forecasts are, you know, we're going to have no more internal combustion engines, goodbye for liquid biofuels. And to me what we're really missing is the resiliency aspect. And resiliency of – I mean light-duty transport is pretty important, and it seems like keeping a portion of the fleet able to use liquid fuels, maybe in hybrid electric sort of approaches, so its suspicion as it can be, would be, really important from a resiliency standpoint.
And it's a little off topic of the webinar, but I was interested in what the Co-Optima team, you know, their thoughts about this, and are you aware of any discussions. Because the major media and a lot of things are just like "No more liquid fuels in light-duty." And it seems very shortsighted. Thank you.
Avantika Singh: Yeah, I can attempt to answer and I would appreciate if Dan, Bob, and others wanted to chime in. But yeah, I kind of agree; I think biofuels would be helpful in transitioning. Because even if we go – thinking about current battery electric [distorted audio] they comprise, like they're less than five percent of the total vehicle fleet. And if they want to get to zero emissions or at least, yeah, at least not adding – it's going to be a long evolution, or at least over a number of years to switch to all battery electric, especially in light-duty, which is about 45 percent of GHG emissions in the U.S. transportation sector currently. So I definitely agree that biofuels will have a really pivotal role in that transition, especially if you want to accelerate and get there faster with hybridized and power plug-in hybridized drivetrains combined with biofuels.
We are looking at some scenarios, as I sort of had alluded to here, what is the efficiency of those drivetrains, what are the deployment costs, and therefore, what we can expect would be the adoption. Considering aggressive electrification, this analysis is still very much underway.
But yeah, we are going to look at this more closely.
Audience: And, Avantika, maybe I can just add a couple of things. So that's really a policy question, and I would say that that is outside of our purview. I would note that as Avantika said, we are [distorted audio] the efficiency is impacted and what that means for vehicle adoption, etcetera. So if that's a viewpoint you would like to share broadly, I would encourage you to share that with DOE and other folks who make and implement policy. But from our standpoint, we have provided this information to stakeholders so that they can understand what we think can be done in a light-duty fleet with increased biofuel adoption. And we'll tell you later what we're doing in the medium- and heavy-duty fleet as well.
Jim McMillan: All right. Thank you. I guess we hear more and more about the need to design in for resiliency, and I think in a large sense we're not walking or talking in that way in some key respects. But I will definitely – I'm bringing it forward in lots of venues. Thank you.
Avantika Singh: Thank you for the questions.
Moderator: Do we have any more questions out there? Here's one in the chat. This is from Trevor – this is a comment from Trevor Smith at BETO. I'll let folks read that at their leisure. Is there anymore questions for Avantika?
OK. Well, with that I'll let Avantika close out.
Avantika Singh: Yeah, thank you everybody for dialing in. I appreciate your time and happy to follow up later with anyone who wants to. Please do keep an eye out for upcoming webinars. They're going to be interesting conversations as well.
Audience: Great talk, Avantika. Thank you.
Audience: Good job.
Avantika Singh: Thank you.
Audience: Yeah, thank you very much.
Audience: Thank you.
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