Hi everyone. I will indeed present you an ongoing study on the use of hydrogen mobility. I will first give you an overview of the goal and scope of our study, then present you the first results and the literature results that we have observed, and finally broaden the scope of the reflection by giving some ideas on how prospective scenarios could be used in RCA to improve this method.

So first, this study is being done for the French and local agencies, ADEM, by Frontis and Enya Consulting, experts in energy.

There is a steering committee of 20 persons, including industrials, researchers, persons from ministers, that are in input to this study, and there is a critical review panel since the results are expected to be released public. While they are in the interest of hydrogen mobility, there are some advantages that are similar to electrical mobility.

There are no fumes at the use-space, and no mass motor means driving, but also specific advantages linked to hydrogen, like the long-running, long autonomy of around 600 km, there is high-speed recharging, and no electricity storage related to security issues.

ADEM, the French and local agencies, is doing this study first to build life-cycle seeking awareness in the hydrogen sector, but also to contribute to guide scientific decisions related to the use of hydrogen in mobility.

The objectives are to identify the most impacting life-cycle stages of the use of hydrogen in mobility, but also to compare different options. As an additional objective, we will also compare the results obtained for hydrogen with other non-hydrogen mobility options,

thermal, enzyme vehicle, and electrical vehicle. In the functional units, there are two. The first is 1 kilogram transport data being drew, so it's a passenger car vehicle type called V4 and a transport cycle index. And the second one is 1 kilogram of hydrogen at the gate of the factory, 30 cars.

What is the system boundary of the study? Here we have the production part of the hydrogen that can come from satanic chlorine,

both from bad gas, from waste, but also natural gas. There is the co-product of chlorine and electrolysis coming from different mix, the French mix, the French mix, the perspective approach from 2013, and the use of 100% main carbs.

Then this hydrogen has to be stored at the factory. It can be stored in either a gaseous form, 200 bars, or a solid form. It has then to be transported until the station. So we have three options considered. Either it's a centralized production with 500 kilometers transport by truck from the factory to the station.

Either it can be local with 30 kilometers, or on-site, and so the car just goes where the hydrogen is produced. Then we have compression at the distribution part here,

and then we include also the use phase, so the production of the vehicle at the end of life, including the fuel cell, and it's recycling. The road infrastructure is also included in the results that I showed. So we have a lot of different possibilities here. In the SCA we will focus on four scenarios,

but we will also provide the next level calculator, providing the results for the different combinations that appear. The four scenarios are the following. So we have the production of hydrogen from biogas, with a local distribution of 30 kilometers.

The scenario two is central production of hydrogen from natural gas to form. Then we have central production also from electrolysis, the average catch mix. And finally, electrolysis, but with a prospective electric mix, with an on-site.

So the indicators that will be assessed are the following, the 16 indicators from the ICD method. The main data sources are, so first of the electricity mix from 30,

it's based on the IBM reports. We have only on-site the different factions of the electricity production sources, but we're not doing it on the background multiplications. For the hydrogen production, it's based on the third thesis.

It is also in vitro and fuel cell inventories, and adaptation of equipment 22. And the other data and background data is from the equipment database. Those data are being progressively modified by the inputs from the tech industrials, and we'll reach the final results with those inputs.

So now the results. I will present climate change impacts only for now. We are here presenting the global life cycle impacts, so in gram of CO2 equivalent per kilometer of transport. We have the different scenarios presented,

and the life cycle stages are the hydrogen production, the storage of hydrogen in transport, and the distribution, so the compression at the station, and the infrastructure with the vehicle, and the world infrastructure.

So we can see that we have the natural gas performing options that have the highest impacts, followed by the bio gas performing, and electrolysis mix, but first the actual mix, and then the best option is the one for 2030. We can also observe that the storage of the hydrogen in transport

and the distribution has really low impacts regarding to the hydrogen production and the infrastructure. Now, if we focus on the hydrogen production, so with the product to gate approach, and the results are presented,

so in kilograms CO2 equivalent per kilogram of hydrogen, we have here the same mapping of the different options, but the impacts are coming from different stages. For the bio gas performing, main impacts are coming from the methane production for hydrogen,

impacts coming from the waste facility. We have for natural gas performing, the main impacts are coming from direct emissions at the hydrogen factory, so mainly CO2.

And for electrolysis, it is not the infrastructure, but the electricity consumed that is the methane. So here is the graphic presenting our results, so for electrolysis in light blue on the left, but compared to other results that we have found in literature,

you can see that for electrolysis, we have the right range of different values depending on the electric mix considered. The ranking is, the differences are more broad for natural gas performing, except for the carbon in capture storage,

which is at 3.3 kilogram of CO2 per kilogram of hydrogen. And we have our study presented here in yellow, and the one with the bio gas performing in green. The main differences, there is also some possibility of differences in the scope of the study,

since infrastructure might not be accounted the same way in all studies, or the coefficient factors also might differ. But it's interesting to know that in the study we have identified, our specificity is to include some prospective electricity mix scenarios,

and bio gas performing. So when we come back to the mobile life cycle, so here we have again the result presented for one kilometer of car transport. We have on the left the difference hydrogen scenario that we have studied,

compared to thermal enzyme vehicle, and an electric vehicle based on the equivalent data. We have the different life cycle stages, so the upstream, in blue, fuel storage, transport and distribution. The use file is direct emission,

they are only occurring for the diesel vehicle. And the infrastructure, with the vehicle production and on-app life amendments, and the rural infrastructure. What we can see that we have some interest of the, sorry, for the hydrogen options, compared to the diesel vehicle.

However, the electric vehicle is closer to the least impacting option for hydrogen. So, in terms of the conclusions, we have main impacting stages for climate change, that are coming from hydrogen production,

but also from infrastructure, especially vehicle production and on-app life, and the rural construction. The lowest climate change impact scenario, is the one from electrolysis with the mix of 2013. However, you should note that those results might evolve,

and the final results will be released in August 2013. And the sites that presented all the risks for climate change, and the ranking for other indicators might differ. So, we will continue to refine the data on this model, especially on the infrastructure, so for the vehicle production and natural composition of the fuel cells,

but also on the hydrogen production, especially from biogas and forming, as we have noticed this morning, that updated inventories might lower the impact. So, those data are being collected there from manufacturers.

So, this illustration of how SAE can be used in developing technologies using prospective scenarios, might be unsatisfying for several reasons. We have not modified systematically the inventories using prospective data,

but also we are focusing on an available efficiency of presenting the results per kilometer of transport. Those limitations might be overcome by increasing new concepts in SAE. This is a first art of food for thought,

to present what could be the conceptual framework of transitional SAE, as life cycle assessment coupled with prospective scenarios. It illustrates, in fact, an equation that you might know, at the IPAT equation.

So, we have the global impacts, that are equal to the population multiplied by the sum of impacts per services. This sum is, in fact, a factor of the use intensity of the service, multiplied by the impact per functional unit.

For example, here we have this term N, which is the use intensity service per person, that would be the average car transportation distance, whereas the impact per functional unit, the impacts per kilometer of transport.

So, basically, this standard attributional ACA, we are focusing on this term here, impacts per functional unit. The transition SAE would broaden the scope, by including this use intensity service per person,

as an output of prospective scenarios, that are given this term, based on global impact objectives, that could be, for instance, a one-hand personal renewable energy prediction, limiting CO2 in the atmosphere to 350 PPM,

based on a per capita quota, sustainable land use, all those aspects could be some inputs, some inputs of the prospective scenario, also with the population evolution. And the outputs are this use intensity service per person. So, integrating this aspect,

it allows not only to speak about environmental efficiency, but also about environmental sobriety, and also equity and human rights, related to this use intensity service per person. So, I would be pleased to discuss a bit more of those concepts with you. Thank you for your attention.

Also practice your transition management as the transition SAE essay. Are there any discussion points, or any questions? Okay, let's start over there. We have two questions from followers of the livestream.

The first is, which electricity mix do you use for the electric car? And the second one is, if you could explain what you mean with allocation during impact assessment. He or she understands that the allocation is only used during the inventory.

For the first question, we have used for electricity vehicle, the French average mix. In fact, we have different mix that are considered, the French mix, actual, and the one in 2030. We will also assess, as a sensitivity,

consider the average European mix, as it might also differ as for the impact. For the allocation, I'm not sure I understand the question. Could you rephrase the question on allocation?

I think there was one for the previous suggestion. It's an idea hard for me to answer. Because I didn't know the answer in my speech. Could you mention what the electricity mix from 2013 is composed?

I don't have a slide here, but basically you have lower share of nuclear power, and you have no more electricity produced from petrol and coal, and an increase of renewable energy as wind farms, solar panels, and so on.

How large is the share of fossil fuels in the current gas? It's not so big, since in France you have a larger share that is coming from nuclear power, around 80%, if I'm not wrong. You have around 15% of hydro-electricity,

so the share for fossil fuels is quite limited, I would say between 0.5% and 1.5%. In fact, the increase of the impact for electricity is mainly coming from the suppression of the little share of fossil fuel.

Just out of curiosity, did you check also the biogas, CNG, or without the detour over the fuel cell just to calibrate your results?

It's a very good question. It was not in the scope of the study. I'm just out of curiosity. You should be curious. I was definitely doing it for myself. It's not among the comparisons that I investigated.

It is in fact one of the possibilities. When we look at the content of the prospective scenarios in transportation, we have a group of electric vehicles, but in some of the scenarios, and most of them, you have a quite large share of increased use

of deadly methane in the matter of the vehicles. I will check. I have a very quick question. I'm from the media. Are you going to make a sensitivity on the future helix helix?

We are not sure. It might be a good idea to check the whole possibilities. It's one option. We will definitely do some sensitivity analysis on the electricity mix.

We have chosen the ADEM one because the study is for ADEM. We have, of course, different mixes that are existing for 2030 horizon. So we might also consider a different...

Your gold diesel has such a high amount of grams per kilometer. Could you explain that? A high amount of? It was 24035 grams per kilometer, which seems... This one? Well, basically, those are data that they are taking from eco-invents.

What you have is that you have the direct emissions here. I don't know the size, but they should be around 200 grams, which is quite high. I mean, it's got some kind of average value,

probably, for the present car, overall cars that we have. And then you have also the infrastructure, so the construction of the vehicle, but also the road maintenance. And then there you have the fuel. It's quite high, and it's higher than the one that has been presented.

Probably, the scope is not exactly the same. We are integrating, for instance, the index related to the road construction and so on. Which is a small part, but still.

Okay, thank you very much once again for your presentation.