 Hello everybody. We are very pleased to welcome you to the energy data workshop for the MENA region organized by the International Energy Agency in collaboration with the United Nations Economic and Social Commission for Western Asia and the Regional Center for Renewable Energy and Energy Efficiency. My name is Roberta Quadrell. I'm working at the Energy Data Center of the International Energy Agency. We do have a couple of logistic explanations for you just before the meeting. This is a virtual meeting only and the training will be recorded but only the part with the presentations of the speakers. This is to allow more users later to to access the material. We do have French and Arabic interpretation during the presentations and you could test already to select the language by clicking on the interpretation tab at the bottom of the zoom window. We would like to encourage you to keep the microphones turned off during the presentations of other speakers. However, feel really free to ask questions either by raising your virtual hand or writing in the special Q&A section you find also at the bottom of the zoom window. Yes, with this I think we can have a brief overview of the agenda. For those who attended our three-day statistic training before, this will be a deepening of the subjects because we have looked already at fundamentals of energy statistics. However, we'll look at a review of the fundamental of energy statistics and other areas as you see in the agenda to touch several topics during this discussion. However, I really wanted to give the floor to our speakers for the opening remarks. On the side of the IEA we have Dr. Nick Johnston, the Chief Statistician of the International Energy Agency followed by a few words from Mr. Nadim Abilama who is working also at the IEA in the Clean Energy Transitions and Global Energy Relations. For Esquia we'll have Dr. Wafa Abulz, Chief of the Economic Statistics section and for Recreate we'll have Mrs. Nadia Shiuq who is International Cooperation and Communication Manager. So thank you very much for joining once again and Nick, the floor is yours for the opening. Well, thank you, thank you very much for Bertha. It's a great honor for me to open this workshop. I know that many of you, as as Roberta mentioned, have participated in the IEA Energy Statistics training week earlier this week and that was our 26th training week but this is our first dedicated training session in the MENA region and it's a great value and importance to us to have had this opportunity for which I would sincerely like to thank both Dr. Abul Huston and Nadia Shiuq for the collaboration and helping us put it together. It's of extraordinary importance to the IEA. I'm also happy to see that we have participation from over 50 different energy users and generators and I think that's quite important. We've got a nice combination, nice diversity both in terms of the countries that are represented, the ministries and the agencies as well as the role that they play in the data cycle because that of course is what we at the IEA focus on, the links between data and good policies. Without good data you cannot have good policies and for us the foundation stone lies with data and statistics and the quality of data and statistics. We work with over 150 countries around the globe but we're particularly keen to work with the MENA region for a number of reasons. First of all it's an extraordinarily important region for both energy consumption and production. It is pivotal in the global energy landscape. Moreover we have the COP28 coming up to be held in UAE so having this workshop just a couple months prior to the COP is of course extremely timely. And also of course we have association countries in the region. By association countries we mean part of the broader IEA family beyond just our our members. Increasingly we are reaching out across the globe to make the IEA the formal IEA family as broad as possible and in the region we of course have Egypt and Morocco as association countries. But we're working with all countries across the region to help further develop our data ensure that it is of high quality, timely and accessible so that as mentioned previously policymakers are in a situation to put in place the most efficient policies as they shift towards the green the clean energy transition. We know that MENA region is facing several important challenges such as increasing demand, environmental concerns and involving market dynamics. It is one of the regions in the world that is most affected by climate change which puts further strain on energy demand by for example boosting the demand for cooling. I make these points because it's important for us to see these exercises as two-way streets. It's not a question of us sharing our knowledge with you. It's a question of us sharing our knowledge with you and learning from you so that together we can improve the quality of the data at the regional level so that globally we have a better system of how a better understanding of how energy systems are changing. So I want to emphasize the fact that for us it is very much seen as a two-way street. Having participated for those of you who participated in the statistics training week and participating in this workshop makes you part of a broader community of energy statisticians across the globe who are helping all governments be in a situation to have the data foundation to design better policies going forward. Final point I would like to reiterate is I would very much like to thank once again the United Nations Economic and Social Commission for Western Asia and the Regional Center for Renewable Energy and Energy Efficiency for collaboration with respect to this. We have partnerships with individual countries, we have contacts in individual countries, but it's also through bodies whether they be thematic or regional such as your own that helps us ensure that our reach is as broad as possible and that we're not duplicating efforts that we're learning together. So I might turn over the floor now to Nadim to say a few words about the structure of the workshop. Of course we hear from our collaborating partners. Thank you very much. Yes, thank you. Am I heard? No? Yes? Yes. So thank you all and thank you Nick and Roberta for these few words and thank you all to all the participants for attending this training. So also in a difficult context for the region as you all know and as was mentioned before, energy is a key element of economic development and statistics is what underpins that. And this workshop is also the opportunity to provide more target to support to the region on energy statistics and it would encourage you to take an active role by asking questions and highlighting how you would like this training to benefit you based on your specific domestic challenges. So in terms of the structure of this workshop, it would be four presentations. They cover common basic principles and statistics both at country and regional levels and they would support national statisticians in enhancing their practice through other countries international experience. So not only this is also as Nick mentioned a two-way street but also between entities and institutions working based on the region. Some of you have already attended the IEA Energy Statistics training earlier this week and you would know what the benefits are for what some people would call South South Corporation but we can call it also Infra-Regional Corporation in exchange of experiences because many of you already faced similar challenges. So without the benefit of time and without delaying the start of the workshop, I'd like to wish you a very fruitful day and again as mentioned before, please do not hesitate to actively practice. Thank you. And you think Dr. Huatha Abul-Hodd can now open for the UNSQA if you can hear me? Okay so we welcome you from our side for this webinar, our team in statistics and technology and the energy team in ASQA. ASQA again is the Regional Economic and Social Commission for Western Asia and Arab countries. We have been working forever with our partners with Grand SB, IEA, AWAPE, QACRI and IMF on joint initiative. We thank IEA for the opportunity to have a dedicated day for the mini-admission. Our region as mentioned by Nick and the team is very important and we love it and this is maybe one of the reasons that this region is at the center of world and conflict unfortunately. I want to just remind maybe our participants who maybe joined us in many trainings, previously we were lucky to have consecutive projects on energy statistics and balance. We had the DA project from 2011 to 2014. We succeeded together to organize regional training for trainers on energy statistics and online. Other regional training and AWAPE hosted by the statistics office there. We did national workshops in Yemen, Iraq, Egypt and new trainings on the joint or data initiative. Also the Islamic Development Bank provided us with a project to target the energy use and the transport sector. It was only for three countries, Jordan, Egypt and Palestine and it was targeted to undertake a field survey to estimate energy use and transport and the project ended with like the results were used in policy in the three countries and we were very happy to see that you know energy policies were taken as per the results that were obtained in the project. Again a third project ADA on SDGs together with UNSD and the regional commissions we were able to provide the national workshop and technical support to Lebanon in 2017. Again during those projects we tried to provide the training material that was developed by IEA and UNSD in Arabic. This is very important for our member countries. The training material of IEA training on energy statistics, the presentations and the exercises were all translated into Arabic and we hosted directly the material for participants to be able to practice on their own in learning course. Other material that we translated are the international energy statistics recommendations, the iris and the energy accounts which is also hosted that can be accessed anytime for our participants who want to join. We also insisted to have both statistical operations and energy during our meetings. It's important to have users and producers and the dialogue between those and for this specific webinar we suggested to our partners to add a session on energy data from trade flows. Our colleague Majd Hamouda who is with us today, the team leader of trade stats will be presenting and we thank him for developing this platform that can inform a lot on energy flows. A lot of time, even like staff in the statistics office with all energy, they don't have access to this detailed trade data and what we're trying here with our team is to really work in the details even like in all products and the demonstration on this. We also suggested to have a presentation on technology applications to assess and estimate solar energy using satellite energy and other geospatial flows. At least Dr. Kohana from our team did the research and will be presenting a news case. So we wish you all the best of luck and we hope we will benefit from this webinar. Thank you. Thank you very much Wafa and I would like to give the floor to Mrs. Nadia Shouk for the opening from the chair. Thank you. Thank you. This is Nadia Shouk, Director of International Cooperation at the Regional Center for Renewable Energy and Energy Efficiency. I'm pleased and happy to be with you today for this workshop on energy data in the minor region. I thank you and I thank our partners, the International Energy Agency, the UNS for this opportunity once again to collaborate together. Of course, as you know, the energy plays a crucial role in driving economic growth. Mr. Johnston has shown the importance of the accurate and reliable energy data in elaborating energy policies. So it's also an important issue for us. The Regional Center for Renewable Energy and Energy Efficiency is the intergovernmental institution that aims to enable and increase the adoption of renewable energy and energy efficiency in the Arab regions. It partners with the regional governments and global organization to initiate and lead clean energy policy dialogue and strategies and technologies and capacity development in our region. And today we are happy to partner with the International Energy Agency and the UNS to deliver this workshop that aims to foster the knowledge into the field of energy data. So please, in this context, I would like to see this opportunity to introduce our recently launched report. So the Arab Future Energy Index affects 2023. So the report that assists and ranks the progress in performance of the Arab countries in the field of renewable energy and energy efficiency. So these affects 2023, conducted by the Regional Center for Renewable Energy and Energy Efficiency in collaboration and partnership with the United Nations Development Program, UNDP, is a comprehensive tool that provides valuable insights into the region's transition towards sustainable energy. For this time, this edition of affects covers the three pillars of sustainable energy, renewable energy, energy efficiency and electricity access. Renewable energy for it will assess the progress in 20 Arab countries under more than 40 indicators focused mainly on policies, strategies, institutional and technical capacities, and also investment environments. For the affects 2023 this year, the affects is becoming an effective tool for the policymakers in the Arab region. And I warmly encourage all the participants in this workshop to use this document as a supporting tool for your works. This is just a small introduction about the affects 2023. It's a good opportunity to introduce it to all the participants. Thank you very much. I encourage all the participants to actively engage in discussions and through the different exercises session. Thank you for being here and I wish you are productive and enriching workshop. Thank you. Thank you very much Nadia and Wafa and Nick. I think the IEA is very pleased with this collaboration with important institutions in the region or anyone who dedicates specific attention to the region. And just before the starting, so I would like to thank the opening speakers once again and just before starting the workshop, we have a couple of questions for our participants. I'm giving the floor to Karen because you wanted to understand a little bit more the background of the audience given that we cannot have you all physically in the same room with us. Karen. Thank you, Roberta. Hello everyone. Good afternoon. We prepared a brief interactive survey on Manti and we will be using this throughout the workshop. So if you could please open a second screen, this could be your cell phone or a new tab on your browser and go to menta.com and enter the code. Or alternatively, you could scan the QR code as well. Give participants a few seconds to join. And once you join, you could see the code on the top of the screen throughout the presentation. We'd just like to get to know the geographic coverage. Today, most of you are joining from the MENA region, but we know we have participants all over the globe. So we'd like to get an idea. You can read the code. So the code, I'll repeat the code. It is 48786728. We have people from the United Arab Emirates, Lebanon, Tunisia. We have UN participants from Oman, Tunisia, Algeria, and people from Paris. Our next question would be about the, as you know, the IA held an energy statistics course between 9 and 11 October. We want to know if the participants here attended the training. We have some people that attended the training for all the three days. So it will be useful to, it will be useful to improve your understanding of fundamental statistics. And this training will be in addition to the training that we already held. So it will be useful. And lastly, we'd like to understand what's your role at your current institution. I know that we have a lot of people who have energy and lists. We have people working on data. We have directors. We have a sustainable engineering term. We have a research associate. We have statisticians. We have people working on energy and environment statistics. So it seems like we have a diverse group of people here. And now I'll give it back to Roberta to introduce the first presentation. Thank you. Thank you very much, Karim. And just a reminder to all participants, this platform that is www.menti.com requires the code that we wrote in the chat. We will use it also across the different presentations. So it may be an opportunity to express some opinions or respond to some quizzes later on. So please try to get familiar if you can by testing the website as it is written in the chat. And with this, thank you, Karim. I like to open the content as part of the workshop with what we consider very important, which is the fundamental of energy statistics and balances. Wafa already introduced the importance of the international recommendations of energy statistics and will review the key concepts that are necessary for us to speak this language of energy data. So I'm inviting our speakers from the International Energy Agency, Nicola Draghi, also with Marc Cardanova, and they will run this session on fundamentals of energy statistics and balances. Thank you very much. Thank you very much, Roberta, for the introduction. I'm showing now the screen, so I hope you can see that correctly, and I'll start the presentation. I hope also that you can hear me well. So again, good afternoon and welcome, everyone. I am Nicola, Nicola Draghi, and I'm an energy data officer within the annual energy statistics team at the IAEA. So together with my colleague Marc Cardanova-Simo, we will first go through this presentation on fundamental of energy statistics and balances, and then there will be an exercise session. So let's start from our reference for energy statistics, which is IRIS. We already mentioned that several times the international recommendation for energy statistics developed by the UN in collaboration with many organizations among which the IAEA. So these guidelines set important information and definition regarding energy statistics, their collection, quality assurance checks, dissemination, and most importantly, they give us an ambiguous definition in order to speak globally the same language as Roberta said before when talking about energy statistics and balances. Now the definition of energy products is based on SIEC, the Standard International Energy Product Classification, and states, as you can read in the slide, that energy products are forms of energy suitable for direct use or for release of energy while undergoing chemical or other processes, chemical transformation and so on. Instead, energy flows are based on the international standard industrial classification, ISIC, and it's interesting to highlight here production, which can be attributed to any economic unit, including households, and energy sector on use, well energy sector as a whole, where we speak about economic units whose main activity is not only energy production but also transformation and distribution. Now, energy statistics are generally collected for one or more energy products pertaining to the same, let's say, group of products, can be oil, can be coal, can be electricity. All of them are put all together, let's say, in the energy balance, which is an accounting framework for compilation of data on all the energy products which enter or exit, and then are also used within the national territory of a country during a reference period, which is usually a calendar year. So, you can see here an example of an energy balance matrix. It is indeed a bidimensional matrix with products in the column dimension, and flows instead in the horizontal dimension in the rows. So, already by looking at this, we can see that every column is a commodity balance in energy units of a given product indeed, whereas in the rows we can already compare the contribution of a different product for the same use or origin of energy but also the interrelationship and conversions from one product to the other. Then, the most important thing about energy balances indeed is the fact that all these products are reported in the same energy unit. There are always the case of energy balances at the IA, and then we have also, because of these comparable energy units, we have the possibility to calculate a total column where we have the sum of all the contribution of all the products. So, in other words, looking at the balance, we have a complete picture of the situation of the energy system of a country for a given year. So, the balance is divided into three blocks. The first one is the supply box that goes from production to stock change, and that it's recapped in the total energy supply row. Then we have the transformation and energy industry on use block and the final consumption block, which are generally referred as the demand. Let's now look at the most important flows of the balance and we start from production. The quantity to be reported in this flow are those that are the remains that are accounted after cleaning and removal of any impurities. So, the quantities that are ready to be sold on the market. This means for oil and natural gas that we do not consider the production directly at the well, and for example, for natural gas, we exclude the gas that is flared, vented, or re-injected for operational purposes, and for oil, we exclude all the impurities that are removed at the at the gate in the center or in any pretreatment of crude oil. However, we include here in production the quantities which are consumed by the producer in the production process in order to keep the equipment on to, for example, for eating or for running all the machines in order to extract these fuels. An important clarification pertaining to production is the distinction between field and plant condensates, where the emphasis is put on the production process. So, crude oil include condensates recovered from associated and not associated gas fields at field separation fertilizers that then are transported together with the crude oil to the next station, let's say, to the refinery and so on. Instead, plant condensate are generally removed from natural gas in more complex natural gas processing plants, and they should be reported together with NGLs. For trade, it's very important to clearly define the boundaries of energy statistics. So, what we consider imports is energy products entering a country for domestic supply, so to be used within the country. Instead, for exports, we should report the amount of products which are domestically produced and then leave the country. So, if we follow this definition, transit trade is excluded, which means, for example, that if a country imports five kilotons of crude oil and then export the same quantity without having touched that crude oil, then this should not be considered for trade for this specific country. Here, we have some scenarios that clarify the situation and are some examples of what could happen. Anyway, we know that in this situation, there can be several particular cases pertaining to one country or another. So, if you are unsure about whether to report or not specific trade, you can always contact us for support. Now, there are two exceptions to the definition above. The first one is for LNG. Now, for LNG, the country of origin, it's not the country where the natural gas was produced and eventually liquefied, but it's the country where the LNG is regasified into natural gas. So, for example, if country A is produced and liquefied natural gas, this is transported via boat to country B, where it's regasified and then exploited to country C via pipelines. Then, for country C, the origin of the gas will be country B. And for country B, obviously, the destination of the exploiter will be country C. Another exception is for electricity and heat, where the trade flows reported are the ones that cross the border and do not follow the origin and destination rule that we described before. And this way, we include also transit trade. And this is because electricity and heat as an energy vector are, let's say, different from coal, oil, and natural gas. So, for example, if a company in France buys some electricity from an electricity producer in Portugal, then despite the initial origin of the electricity, it's Portugal. And the final destination is France. Portugal will report export to Spain. Spain will report import and export to France. And France will report imports from Spain. Moving on to another very important flows, that's international marine and aviation bankers. And in particular, I want to put the emphasis on marine bankers. And this is because marine bankers are very important for the demand of oil in a country, because global trade happens mostly by sea. And it's very important to define whether the consumption happens in domestic or international navigation. Now, the split between the two, domestic and international, should be determined on the basis of the port and airport for aviation of the fighter and arrival. So it has nothing to do with the flag or the ownership of the airline undertaking these voyages. And also, for consumption in fishing, this is covered elsewhere in the balance. In final energy consumption, actually, we have a fishing row, a fishing flow. So it shouldn't be reported the consumption of this vessel into international marine bankers. Moving to the transformation block, I want to show you a very important convention that we have, a sign convention, that it's the fact that inputs of a transformation process are reported with a negative sign. So for example, here, we have the example of an electricity plant whose input is natural gas reported with a negative sign. And the output is electricity reported with a positive sign. Obviously here, you see the total electricity produced by all the inputs, so the value is very high compared to the input of natural gas. And then in the column total, you have in the transformation block generally all negative values, because that's the column that it's the sum of the contribution of the other products before. And you see the energy lost during the transformation as a negative figure. Another important concept and distinction is between gross and net production. So gross production of electricity and heat refers to the total output of a facility before any of it is used. However, we know that not all of the produced quantities are transmitted afterwards, but some of this energy is used to heat or give electricity to all the equipment operating and running in the plants. So that amount consumed to support the plant operation is called on use and will be reported in energy industry on use. The reminder, so what is transmitted to the grid, it's the net production. Spotlight here on transformation efficiency, which are very important and an immediate check that we can calculate from energy balance to verify that the data we collected makes sense. So as you know, the efficiency is output divided by input and it's very important to report them in the same energy units. And obviously in the efficiency calculation, it really depends on the technology used and so on on the age of the plant and many other variables. And obviously, this efficiency has some checks that can be done. For example, it cannot be and has to respect some rules. Obviously, efficiency larger than under percent are not plausible and they depend very much on the technology on the age of the plant. So it's very important to know these variables and also the historical efficiency of a given power plant to know if the data collected for the next year makes sense are consistent or not. And here you simply see an example of a fuel electricity transformation where two types of fuels. I use AMB or two quantities of the same fuel and see the electricity is the output and how to calculate that. This slide on transformation was to move on then in a very important transformation obviously for many countries which is what happened in refineries where generally primary oil is converted into secondary oil and you can see here a list of the oil products collected in energy statistic. Obviously losses occur in this process and this means that generally the refinery intake should be higher than the refinery gross output. However, here it really depends on the unit we are using for collecting this data. For example, in mass terms which are generally used for energy statistics and in energy terms as in the energy balances refinery gains are not possible. But if we collect the data in volumetric units then gains are actually possible because the products compared in volumetric units the output will be usually lighter than the feedstock. So the refinery yield is again the refinery output divided by the refinery intake and it's an indicator which is really important to be monitored because it's an important quality check indeed. For example, if in one year the refinery yield moves a lot decreases a lot without clear motives then it's likely that the data collection of the output is missing some quantities. That's just an example of how to use the refinery yield as a quality check. Still related to the oil sector we want to highlight another important situation and complicated situation for energy statistics. So on the one end we have crude oil and also some quantities of energy and gels that undergo traditional refinery processes yielding secondary oil products. Now the inputs and the outputs of these processes have to be reported in the oil refineries flow in the transformation block. However, it is possible to have some other quantities of NGLs and plant condensate that can be treated in gas processing, gas separation plants yielding a smaller range of output products which are generally LPG, ethane and NAFTA. Now this is some time let me show you where to report that but this is some time misreported because the gas facility is in the same complex of the refinery but it's really important to distinguish these two different processes and the products participating to this separation to this process should be reported in the transfer row again with the corresponding sign. So in this case you see natural gas liquids with a minus sign and all the secondary output products with a positive sign. Finally some example for you to show the difference between transformation and energy industry on use. We have oil refineries first we already went to the transformation but the energy on use is when some part of these outcome products for example fuel oil or refinery gas are used to support the operation of the pipeline so they're burned to support this operation so they have to be reported as a transformation output and then as a consumption in energy industry on use. A similar thing can happen in co-covens where some output products of co-covens can be again burned to provide energy to this very energy intensive process. Finally some examples sorry finally we arrived to the last block the one on final consumption where we see the sector at demand with the desegregation given provided by Aries so we have many different sectors industry transport residential and so on. Among these we have non-energy use so final consumption indeed include non-energy use of energy products and this is especially important for lower products but also natural gas because they're often used as feedstock in the petrochemical and chemical industry to produce plastic fertilizer and other products so what happens is that some of these products some of these secondary products can be used for energy but some others will be used as feedstock input in chemical and petrochemical plants. The outcomes of this plant will be primary chemicals and they are not energy products so they are not included in the energy balance and sometimes we have also a directly output of the refinery as lubricants paraffin waxes and bitumen and so on which are already products used for non-energy use. Finally a special mention for water desalination which is a process very important in your region so you already know that there are many technologies using either electricity or heat as a source of energy. Now the problem with water desalination is that these plants are often in industrial complexes or within companies that produce also energy together with water so it's challenging to separate the statistics. In case this is possible and this should be water desalination falls in ISIC division 36 which to recap means that it should be reported into commercial and public services so the energy used for water desalination should be reported into commercial and public services in final energy consumption. And finally many ways to collect data from administrative sources which are the data generally gathered for non-statistical purposes from various entities as energy regulator, ministry, transmission of electricity operators and so on. We have surveys that are very important and usually yield very high quality data for example on end use of energy but they are also very costly so it's important to know what should be the frequency in order to have a good trade-off between cost and benefit. Then direct measuring this means for example measure of electricity to conventional smite meters of calorific values and you need to have equipment in place in order to do that and modeling as a complementary to all the other data collection to fill some data gaps but that's the case for modeling you need very robust input data in order to have reliable output. To conclude aggregate overview of the main flows in the energy balance left we have the supply side, right we have the demand side transformation, energy, industrial use and total final consumption and as we saw before there will be different sources and methodologies to collect data both from the left and from the right side and so it's very possible also I would say almost probable to have a mismatch between the two sides and this is called statistical difference and as a general rule of thumb this should be not more than 5% in order to be acceptable to show a good data quality. However I just want to conclude with that it's possible that you see also stock change as both rows up and down next to their box which means they can be positive or negative and it can happen that stock change is used as let's say a residual or a mean to let's say return to equilibrate the supply and the demand side. This shouldn't be done because stock change is a very important indicator for example of how tight is the market and it's a very important metric and indeed it's very important to show statistical difference in order to indeed know the the data quality of your data collection. So thank you very much that was it and feel free to ask questions thanks. Thank you very much Nicola and I like your last slide on the supply and demand maybe you can go back one. Because you gave a lot of information to our participants but this is nicely summarizing the structure of the overall energy balance. It would be also interesting to know if our participants have knowledge of the or are collecting data for an energy balance. In the meantime I also reminded that the international recommendations link on the chat because we can find there also the Arabic translation thanks to the UN and I think it's important to really refer to the fundamentals of this language both in terms of what products we should collect data for and what are the flows that are nicely depicted in this slide that allow us to follow you know what happens to these products across the economy and how we can track then what happens. So I would like to encourage any participants to comment on the energy balance or fundamental of energy statistics including whether they are familiar or not with the main concepts because you may defend on the background there is a Q&A window right. We would like that our participants are not feeling shy to express questions or comments including whether you didn't understand. Yes I was a bit fast in some points so I'm definitely happy to come back. We gave a lot of information but I have a question because you Nicola and Marc you work on the collection of data for many countries across the world as Nic mentioned before so looking at this graph where do you see the major difficulties for countries to collect data for you are experiencing that in your validation work every day so can you. Yes definitely so the flows which were introduced at the during the presentation are also some of the obviously of the most important flows they want to pay more attention to and the one where we we can have more more problems I think on the supply side well transit trade it's it's a really important topic as well to have the correct reporting of production obviously stocks are another very important topic because we know that they are not easy to to collect so I mean it's it's a difficult data to to receive so I invite every time that for example a participant or or a data collector doesn't find this information to try to look in all the possible sources and organization that collect data in order really to to have an idea of of this stock stock change and finally also marine bankers and aviation bankers also flow that generally it's it's not easy to collect on on the country side on the demand side I would say that especially for country in the MENA region obviously a refinery as a process as a transformation we know it's a very complex process with many things happening many many flows and products that enter the refinery many others that are transformed and go out so definitely I would indicate that as the main the main attention and focus point in order to have a high quality statistics really to understand what's going on what are the flows involved what gets out as a marketable product as a finished product and try always to compare what is your input and your output in a given year and also in previous year in order to to keep consistency and have refinery losses in mass or energy terms which are not too high and which are consistent over time you don't want yeah there's a question also in the chat if we cannot separate the from a bill if we cannot separate the energy using the salinated plants it will be included in the own use of the plant do you have any other solution for the salination here we go so thank you Abir very much for this question I mean the salination it's a very difficult topic in order for energy statistics to to be collected the the right energy statistics for for that well the own use of the plant it's indeed what we want to be reported in commercial and public services so in case you have you have it as own use then you can directly move it to commercial and public services I know though that your question is probably relating to power plants that produce both energy and water so in that case obviously it's very difficult to separate what is their own use for the power plant to produce electricity and then what is the electricity out of the gross electricity output of the net electricity output that we saw in previous cases in order to in order to that is then used for for water designation I'm afraid I don't have a specific you know advice or or a data on the the efficiency that should have the power plant so it's it might be related to estimation at that point you might have to resort to estimation but it's very important then to speak with the energy producer with the company operating the power plant in order to understand all the technologies all the characteristics and to make the the most accurate possible estimation of the electricity used for water designation plant and for sure you you will have a better view a better angle to take all this this this problem than than us thank you Nicola and thank you for the question and observations on the Q&A I think you had prepared some all exercises with Mark we are a bit late but I think they were nicely emphasizing some key concepts including trade which was also highlighted as one of the important challenges in terms of data in the region yes hello Roberto and hello everyone I will be going through the energy statistics and balances exercises so this is basically just applying the knowledge and the methodology that Nicola has been sharing during the last few minutes if you can go back to the mentee that was introduced in the beginning and use this code it would be it would be great so that you can reply in all the exercises with the answers that you think are are correct so I think there is also a way for me to share the link so you also have the link in in the chat now so if you click there you should be able to to access okay so let's go to the first exercise so this exercise is about a natural gas site which had an annual offshore production of 400 million cubic meters out of these 450 million cubic meters were flared and 100 million cubic meters were vented how would you report this data so here you will have to remember some of the of the methodology some of the the guidelines that Nicola shared regarding natural gas production options are to report the 400 million cubic meters in production and the sum of vented and flared so 150 million cubic meters as losses second option is to report again all the production 400 but then the 150 million cubic meters in the oil and gas industry third option is to report only the production minus the flared and vented natural gas so only 250 million cubic meters but still the losses we would report them in in the losses part of the balance and finally the last option is to report only the 250 million cubic meters as production so I see we have some different opinions but most of the answers are going to towards only reporting the production of 250 million cubic meters even though the the second most voted option is to report the 400 so the whole thing and then as losses the vented and flared so in this case the correct answer is to report only the production of 250 million cubic meters of natural gas and we do not report the natural gas that is flared or vented so natural gas flared and vented are considered extraction losses so these are losses that take place of course during the extraction of natural gas and these are not included in the marketable production of natural gas which is what we want to report in the in the energy balance so these in addition to gas flared and gas vented it would include also gas reinjected which is natural gas that is injected into an oil reservoir to increase the ideal recovery so I hope this is clear let us know in the chat if or you can take the the floor if you want to ask any questions but remember that natural gas flared and natural gas vented should not be considered natural gas production in the energy balance let's move on to the next question so for this question you will see on your screens an image which is basically an energy balance that I can show also in this image so here we see a few products like primary oil and secondary oil products and we see some flows regarding the supply so production imports exports stock change and oil refineries so here what we want to know is if you see any problems in the reporting of trade for these primary and secondary oil products and if you do see some which problems do you see so let's focus on trade so of course on imports and exports you can go I recommend going product by product so you can first do crude oil so we see in this country we have 10 000 tera gels of crude oil production we see that there are both imports and exports and focusing in the value of exports we see that it's relatively smaller compared to the production so this seems like it could be a good reporting of trade so you can go through these two different products and write any responses if you have them if not I will go myself through the through the issues that they are in this energy balance so there is one issue I can give you this hint on on natural gas liquids because as you see the production is 2000 tera gels and the exports we see they are bigger than the production so there is more there are more natural gas liquids being exported than they are produced in this country so we see of course there are imports in between so most probably what we can guess from this situation is that part of these exports these 2500 tera gels here are actually transit trades so it's amounts of natural gas liquids that have been previously imported that go through the country and that are then directly exported without being used in the country so transit trade as Nicola presented and as is mentioned in the international recommendations for energy statistics should not be reported in the energy balance so imports and exports they comprise all the fuel and other energy products that are entering and leaving the national territory but goods that are simply being transported through a country which are goods in transit and goods temporarily withdrawn are excluded from the energy balance so then we see the same situation for LPG we see that there is no production of LPG which we would see as output of all refineries and we see that there are exports so this is very clear in this case that these exports come from the amounts that have been previously imported so this is again transit trade and finally there is also an issue in this case with NAFTA we see that there is 1500 tera gels that are output from the oil refineries and the value of exports is higher than this so again at least part of these exports are transit trade I see some of you wrote some responses I see I see some of them are matching with what I was explaining so yeah again let us know in the chat if you have any if you need any clarification on this but yeah I see that some of you have seen the issues that I was talking about let's move on to a third exercise so this exercise is about LNG trade and what should each country report so in your screen again you will see some images which I will share here so we have country A which is a producer of natural gas which is liquefying towards LNG these 100 million cubic meters of natural gas these are being transported by an LNG tanker into country B so country B has an LNG regalification plant and then out of these 100 million cubic meters that it has imported it will use 50 million cubic meters for its own consumption and then it is sending 50 million cubic meters also to country C so the question in this case is what should country B and country C report the options are country B should report only the 50 million cubic meters that it is using as imports and country C should also report these 50 million cubic meters that it's using second option is that country B reports all the imports so the 100 million cubic meters and then exports of 50 million cubic meters to country C and from the point of view of country C it would only report the imports of these 50 million cubic meters that it is using finally we have a last option which would be that country B reports everything so the 100 million cubic meters that it has received and country C does not report anything I see again the answers are quite spread through the possible answers but most of you are actually replying to the second option which is the correct one so in this case country B and this was a case that was again explained by Nicola during the presentation country B is the country that has a regasification plant so it is receiving 100 million cubic meters of natural gas in lng form and turning into gas so changing the the physical state of this gas so it will be the country of origin of this regasified gas and it is reporting the the 100 million cubic meters that it has received as imports and 50 million cubic meters as exports to country C then country C is reporting these 50 million cubic meters that it has received from country B as imports again this is according to to the methodology that we use according to iris and according to the to the IEA methodologies as well which are compliant with iris I have a fourth question if there is time so this question is about the correct reporting of fuel oil and diesel for different origins and uses so again there is an image that you see in your mentee which is this one so the situation is a refinery produces 100 terajoules of fuel oil and 200 terajoules of diesel so out of these 10 terajoules of fuel oil are burnt to provide heat for refinery processes and 50 terajoules of diesel are burnt in a thermal power plant outside the complex so the question is how would you report all these values here into the energy balance in this case a very simplified energy balance where we only see fuel oil and diesel and we see some flows which are concerned by the values and the explanations that we have on the left so again if you see any options on how to correctly report these values you can write them in the mentee as your answers so in this case I will I will go through it myself so the production from the refinery will be all refinery output in the energy balance so what we will have here will be positive values of 100 terajoules of fuel oil and 200 terajoules of diesel so this would be reported as the output of all refineries then these 10 terajoules of fuel oil that are burnt to provide heat for refinery processes so this since it's a fuel that is being burnt for refinery processes which is part of the energy industry of course this will be considered energy industry own use so these 10 terajoules would be reported here in fuel oil energy industry own use and then the 50 terajoules of diesel which are burnt in a thermal power plant outside the complex these we can consider since it's outside the complex that it's a main activity electricity plant so these 50 terajoules of diesel would be reported here as an input to main activity producer electricity so very important for these two values they need to be they need to be negative because it's input into the plants so of course this value into the main activity electricity plant and the energy industry on use should be reported as negative values in the energy balance finally I have one last question which is about non-energy use and petrochemical industry so a petrochemical factory used three kilotons of NAFTA as feedstock for the production of plastics and also for this purpose it consumed two kilotons of diesel so how would we report also in the energy balance these different values and different data that we see so how would you report each product in the energy balance one option is to report the use of NAFTA as non-energy use because it's feedstock and the use of diesel as energy use because it is being consumed for its energy content and it is being burned second option is to report the use of NAFTA as a non-energy use and the use of diesel also as a non-energy use because it's in the petrochemical factory third option is only to report the use of diesel as energy use and the final option is to report the use of NAFTA as non-energy use again because it's feedstock the use of diesel as energy use because it is being burned and the production of plastics as non-energy use so please choose one of these options and again I will show the correct answer I see yeah most of you are answering the correct answer which is use of NAFTA because it is being used as a feedstock for the production of plastics and not because of its energy content but because of its physical properties that will allow it to be transformed into primary chemicals that will be then transformed into plastics this is a non-energy use in the balance and then the use of diesel because we are using it to for its processes we are using it as a fuel that will be burned this is an energy use even though it's in a petrochemical plant so in the balance again this needs to appear in the energy use so this will be it from me for the exercises on fundamentals of energy statistics and balances please let us know on the chat if you have any questions and if not I will give back the the floor to the chair to continue with the different presentations thank you Mark thank you Nicola I think you are providing a wealth of information and this topic by itself would deserve a five-day week I think of the explanation in methodologies because we are covering all the fundamentals of energy statistics the energy balances which is also a elaboration of the initial data so it's more to give a sense of the importance of certain methodology to really align data across countries and that's why we also always refer to these international recommendations on energy statistics that have been adopted by the United Nations so they are our common language really I'm saying energy statistics so we hope in the future that we'll get opportunities to discuss more in depth each of the topics introduced in your session because it was very very rich if there is no questions I don't see any questions in the chat or in the Q&A I don't have it yeah the Q&A there was a question from yes I which I can read it to everybody speaking about the Tunisian case Wafa was asking if the balance is disseminated and there is a confirmation of that so it's very nice to know also that the data collection work has a dissemination component which is why we collect the data specifically so thank you for that clarification I didn't read it before so if there is no question I would move to the next session which is about trade because our colleagues especially from a squad they reminded us how important three statistics are in the region and so I would like to invite Mr Majed Hamoud to present on trade data on oil and oil products and the ESCO external trade data platform for the Arab region thank you hello good afternoon colleagues in IEA recovery and from member states good afternoon to you all ladies and gentlemen it is in fact pleasure to me to join you in this session although I after the very informative presentations I felt that I'm really guest to this group of highly specialized and distinguished speakers and attendees it's okay it's okay am I heard okay okay okay so I will just give in a nutshell what we are doing here at Esquah away from the energy and I'm sorry about the a bit of confusion about the presentation the language I prepared the presentation in Arabic for the Arab thought the Arab participants and it would be easier for them to to get it in Arabic but it would be good for the them to see me speaking in English and then they can see the material in Arabic that would also help the translators our colleagues okay okay okay so I'll just go quickly to what we are doing here I heard our colleagues presenters before me emphasizing the fact that getting data and reliable data and good data is imperative for making good decisions and that's true and that's where we endeavored the Esquah to bring detailed database on trade of course trade of everything the energy products and the rest of products everything that is traded internationally and to put it as much in detail as we could and to be in the bilingual in Arabic and English and also to complement it with very useful visualizations that can bring together data to see it on the regional levels of regional levels intra-regional and on groups groups of products you can see it the total trade I mean divided by groups of trade products and also along economic group groupings and regional trading agreements so we did this database to cover a huge gap in the available data in member countries data is not produced usually by many member states on time or with the full detail that is required and in particular for the energy products there's always a huge problem facing users for this type of data to find it in the full detail that they wish so in our database we try to to to bring all these to bridge the gap and bring all these points together and to provide a full consistent time series data and to standardize the classification that these products are classified upon which I will talk in a minute and and this is the shape of the the platform the interface that you can see it's fully Arabized and in English and ready to give the data on the level of the individual country as well as on the the product level this is again the interface in English where you can see the the reporter you can pick the whole region as a region and see it's a trade or you can pick a single Arab country or multiple reporters with the world again the partner country on the right side also you can see the direction of a trade whether it is exports re-exports or imports the year and the economic the trading partners in terms of economic groupings or region trading agreement this is when I said about the groupings we try to group the products in the full trade to be divided like among between 14 trading groups starting because our region is very important in the production and exportation of energy products mainly petroleum gas and their derivatives and that's a group and then there is the the petrochemicals the base metals and so forth you can see it and then you can see if we are talking about the regional level the ranking of countries in that in the product or in the totals which is the most exporting country the second the third and the whole ranking from top to down and then you can see in terms of trading partners if we are picking a product or we are picking the totals of exports and imports you can see the trading partners for example here for the whole Arab region in 2021 the top trading partner or the top export destination for the Arab products is the EU EU countries then the GAFTA the GAFTA which is the great Arab trade agreement which is the intra-regional platform and then the rest NAFTA ACI and Commissar and the rest but you can see this on the level of the product the country or the group of countries then you can trace the total the trade balance also in the total and on every product you can see the trade balance over the period we are bringing providing the data starting from 12 2012 on the right side you can see the top 10 trading partners individual countries so that's in a nutshell what we are trying to do and since last year we launched this database the platform for excel and trade data statistics for the Arab region and now we are just maintaining that and updating that uploading the most recent data that we could in a month time we'll be presenting for the whole region the 22 data now it is 21 when we access anyway and in a second we'll be moving to a live demo from the platform the data platform that we can talk a bit about how to use it and what are the different functionalities in that platform to start with talking about the topic now at hand which is the trade data relevant to energy products here we are talking about the trade statistics for the different energy products whether it is the hydrocarbons the gas and the crude oil or the derivatives or whether it is about the actual products in final use like electricity we have also captured that in this database or if it is related to the trade in renewable energy products which comes in a huge classification because of the diversity of these products which goes from the machinery the equipments and the parts and so forth to generate electricity whether it is generated by wind solar energy hydro laryx by water power water or other means and the the the storage this purpose the every type of thing that could be classified under the or related to the renewable energy products now to use this from the trade point of view because I just listened to the carefully to the presentation before me and it was very informative indeed although some parts big part of it it's not in my area and the calculations of the energy balance and all that from the trade international trade point of view all products whether it is energy or otherwise should be classified should take a code and that coding system is prepared under a convention international convention that is managed by what is called the world customs organization I think they are also in Paris or Madrid and they produce the full classification for every item that goes into international trade exports imports between countries and cross international borders and it is classified in a way to grab the processing and the technology manufacturing stage on every group of products it starts with the the whole classification I mean which is called the harmonized system of coding hs hs for short and a lot of monastic in arabic because we cannot find the short for that so the hs coding starts with the very primitive or primary let me say a processing and we could imagine that the natural the agricultural products fall in the first group of products classified there and then goes to the high in technologies and value added and manufacturing input to the most developed high tech industries and so forth so it is divided on what is called sections it has 21 sections per section is natural agricultural products animal and vegetable and so forth products it goes to section five which is the most important section in our or relevant to our work in energy here which is called mineral products or mineral oils and then in that you find there are many chapters but the most important chapter for us is chapter 27 and chapter 27 of the hs you can see all the mainly the the products the hydrocarbons and their derivatives in crude form or in manufactured or liquefied you can find it there for example the chapter or the hidden 2709 that's for crude oil 2710 is for all the derivatives gasoline diesel oil the jet fuel at every level and then the 2711 which is for classifying natural gas and it's also products and this is on the four digit we call it the hs at the four digit which is at the hidden level and then we go to the classes subclasses inside that should go into a bit of expansion to a six digit and for example this is a snapshot from an arabic for the the platform which shows chapter the section five 27 then is the chapter and then 2709 the hidden and you can see the detail detailing of all the products in there of course we'll be going to a live demo in a few minutes to see in english how that is being done and then we see for example the electricity energy which is finally a product that is passed through electricity grids from a country to a country and there is a huge there is a major project in our region here in the middle east that goes from egypt to jordan passes to syria most probably we'll reach to other countries in the future electricity energy is also classified in this 27 although it does not have anything to do with mineral products but tentatively they put it here for future revisions maybe they will list it in a separate entity not under the mineral products hydrocarbons i mean so it takes the hidden 2716 electricity energy for the rest of the trading products and data for products of renewable energy that we just talked about they are in diversity and they fall within different sections but mostly we could trace them falling in two chapters 85 and 84 that are allocated to the machinery and the electrical equipment and of course in chapter 87 like vehicles when you talk about electrical vehicles and their spare parts and batteries and so forth so i i prefer to go directly to a live demo to talk to save time i hope my screen looks a bit small i hope it's uh readable uh by uh all so um this is the whole platform which i said arabic english and uh full uh fully interactive and uh where um so i will just talk directly about to save the time i know the time is not that much in my favor i'll go directly and see okay this is the landing page it gives you for the whole arab region the whole arab region the 22 countries from morocco to oman and their trade with the world exports and re exports for the year 21 for the whole we said partners so it will not appear any economic grouping it gives here the total of exports and imports you can see it on the right side the figure which is 1.606 trillion us dollars and then in terms of sections when we said we have 21 sections the top section we could see immediately it's the mineral products which provides the data on the oil in particular crude oil the derivatives and the natural gas exports from this region which is close to 60 percent 631 billion dollar out of 1.06 trillion dollar about 60 and we can see it immediately in the in this graph the grouping graph where you can see the first the top product category it's the petroleum and gas products in terms of exports of this region the least is the furniture for example in comparison the top exporter in our region comes here is the united arab emirates followed by south arabia and qatar the emirates because we are calculating here the exports and re exports and they have a huge amount of re exports because it's a trading hub with a huge amount of re exporting activities and and the rest of the emirates and then you can see the top groups economic groupings importing from our region the balance as it and the top trading partners that importing partners from this region where you could see where you could see china 15 percent of the region's exports are designed to china followed by india japan and korea and let's see let's see dig more now into the mineral products and let's see if you wish on the level of a country we can just pick for example qatar or south arabia or any any country okay the exports of qatar are amounted to 87 us billion dollars 74 billion dollars are the mineral products we know that they are the major exporter of gas natural gas okay we could see the 73 billion is yes right in the chapter 27 here chapter 27 the mineral fuels and then if we dig more in detail to go to the heading level we could see that 53 billions are in the petroleum gases in the 2711 that we talked about in this category less in the crude oil which is 2709 like 12 billion us dollars and then the derivatives gasoline and the stuff 7.8 billion dollars rest is zero this is the now if we want to see and dig more into qatar petroleum gases exports we could see we just up into the very detailed level that we have which you can see here on the six digits on the six digits we could see qatar is in the 2711 12 petroleum gases and other gases had liquid the liquefied liquefied and proven 53 billion us dollars okay if we click on this one to see who are importing the lng from Qatar it's in the sark the the the the agreement in in in asia the top importer here is korea 17 percent or 18 percent almost rounding figure of katar imports are import exports are imported by korea india is the second 16 and then china the issue here what is the input of escrow here is that those products and these data on this level of detail are not available usually maybe they are produced by the countries some countries but they are not published if you go now and search for these at this level of detail per country destination you won't find it so here is the great effort that we did at escrow in in and in doing a different activities to bring this detail to the platform we reviewed and review every time multiple sources to to get the data including the com trade partner data trade epic and the different countries i mean not the national statistical offices but the the energy companies the ministry of energies or natural resources so we pay a lot of effort to bring this detail to the table to this platform to be there and that's i think one of the major contributions that this platform provides for its users and of course on the import side let's say let's say we want to to see for katar not katar but let's let's see one important country for for example the renewable energy products let's see jordan for example okay deselect katar and select jordan and let's deselect exports and select imports for the year 22 from the world let's see what is the code of for example the solar panels which is 85 for 140 if we put this and immediately the platform will grab for us the imports of jordan in the year 2021 from all countries all the sources which is amounted to 98 million us dollars you can see immediately that jordan is importing this top 95 the panels the solar panels from china followed by thailand and 95 from china actually so and we can repeat this process for the any product that we wish to see you do need even to go to the sometimes to some of the presentation the visualizations if you are getting just one product because it will give you just this product this okay if you want to see which is the most country arab country for example in our region interested in developing their solar energy facilities and so you just deselect deselect here the region will go to the arab region and we will say imports the same stay and then we just click again on the hs code and we go and highlight this we find the whole imports of solar panels to the arab region in 2021 amounted to 1.12 billion us dollars and the top importing country is united arab emirates followed by katar and then egypt and jordan lebanon and the rest why the emirates because arab emirates also import not only for the needs of the emirati market but the re-exports as we said in the beginning they are a re-export hub for the region so if you see for example here re-exports you can highlight here the re-exports and i have a comment on this yes we see in terms of re-exports again arab united arab country is is is exporting a lot of of solar panels this is in a nutshell in a hurry how do we reach to the data of energy products the different categories using our platform and the advantages it provides if i go back to my this is this is the electronic website for our platform at escoil.org and this is my email you can please go through and if you have any questions you can write or call to us or any of my colleagues we can pass it and happily answer any question thank you so much we have already one or two questions i wanted really to take the small amount of time to to to read because this is extremely rich database that we are showing and you talk about the classification it's very interesting from the point of view of data collection i see that one question for example from abir is how do you collect the data that then feed the database and what is the difference with the com trade so how do you collect this data that they are so nicely displayed and congratulations for the platform because it's impressive okay thank you so much for this feedback and thanks abir for this question actually this is the part that takes most of our work and effort firstly we try to get as much as we can the the raw data from the national statistics offices but unfortunately they produce them either on the four digit level which is not the detail one the six level that i just showed you um you can see that in in in many cases um and um what what what we can do at that point is for these countries we do multiple effort as follow in com trade you cannot see this detail for example for the gcc countries all of them that producing um and exporting the oil and the gas and the derivatives you cannot see them at all if you go open for example katar saudi arabia kuaet you not you will find a total a total or you will find a total in the four digit uh so you you don't know how much is of every product that is going or the destination you you cannot know that what you can see is if you go to the partner uh data you can see for example the korea south korea imports from every type of every product individually from saudi from kuaet from katar as we saw they are the top importer of katar uh gas products so we try to combine all these resources together because one thing is the data on com trade taken from the mirror data is exaggerated by a margin the margin that is paid for shipping and for insurance and for profits and for you know all this uh sales uh uh circle reaching from katar from the top price to until it reaches to korea it could be 20 or 30 percent higher than the actual price that is paid in katar so we do a lot of effort of bringing these these figures in line with the national figures on the four digits to compare and see the gap the extra gap to bring the actual or something next to the very close to the actual figures comparing them also with the production levels of of epic data to to make it so much close together before we reflect them in our database so it's not an easy process and i would advise to have a look into the database our database and see what i'm talking about when you compare the individual exporting countries uh data with the data that we have there thank you thank you very much and i mean there are other questions but i suggest that also you can answer bilaterally especially on vehicle consumption i don't think this is the appropriate database but um yeah but i think it's very important to put some light on the trade um and it would be very interesting to compare actually monetary values with physical values that we are type we are collecting energy statistics and that there is a classification also um issue in some cases so it's certainly very uh interesting to dig more in depth in the in this area because of the importance of trading the region so thank you very much for your contribution we are rather late but um we are today the objective is really to give the flavor on different topics that could be dealt with in in more time if we had more time so it's not about really teaching all the details but it's it's good to know that the squad has developed such a tool that is available for you so i would like to invite our next speaker from recre if you could also try to be uh compact to the key messages on the renewable development in manna um i have um i don't know if it is nadia or if it is eman adel probably nadia but um please go ahead if hello everyone this is eman adel from wiki and actually i'm going to give you um small introduction about our reports a fixed report where you can find some statistics and indicators about the renewable energy sector in the minna region first of all if you don't know um if not all of you know about recre so recre is a regional intergovernmental organization covering 17 member states we have operated since 2008 with seven member states and our headquarter was in Egypt Cairo then we grow up till we reach 17 member states where we have specific strategic aspects regarding renewable energy energy efficiency and overall the climate change in the minna region um during the the recre work we have a regular flagship report which is the arab future energy index affects one for renewable energy and another one for energy efficiency and for the service time and in line with the long lasting partnership with the un organization the addition of the affects covers the three pillars of sustainable energy for all renewable energy energy efficiency and electricity access assessing the progress in the 20 arab countries under more than 40 indicator focusing mainly on their policies and strategies um it's also covers the institutional and technical capacities and investment environment affects is becoming one of the effective tools for the policy maker and uh uh in the arab region and the evaluation and comparing the progress of their countries with the other countries in the region to make necessary reform to progress and achieve their national targets in cooperation with a strategic partner and in light with the exchanging of the best practices among the countries i would love also to highlight that uh we have launched the first uh this this uh version of the affects today at the minna climate week uh in the kingdom of syria ebio my colleagues dr meget mahmood and engineer akram muhamad have launched it uh today in the early morning so this is uh one of our hot publications now um i would love also to mention that during the affects we have three sections renewable energy energy efficiency and energy access where we cover the install the capacities among the region the renewable energy and energy efficiency projects barriers and the challenges we also uh highlight some of the success stories and we uh mentioned uh the grid access the applicability of the smart grid and the the innovation ideas in the renewable energy sector and makes uh in light with the we the v2x and the green hydrogen innovations uh those days in this slide i would love to mention that 463 million inhabitants which is around 5.6 percent of the world population growing from uh 222 million in 1999 which means that today the Arab population represents 5.6 percent of the world population with 80 percent of the region's population and being concentrated in eight countries which are Egypt, Algeria, Sudan, Iraq, Morocco and Saudi Arabia in addition to Yemen and Syria. The population in the Arab countries or in the Arab region is relatively young with uh adolescent and youth aged from 10 to 24 years representing quarter of the total population and within that access to electricity in the Arab region was almost 91 percent in 2021 with many countries have reached the universal electricity access conflict and political instability and utility sector mismanagement nevertheless leave nearly 42 million people without electricity access uh of course this is due to the instability the political instability and of course also the COVID-19 uh pandemic. The rural areas suffered the largest deficit actually was only 83 percent of the population having electricity access compared to 98 in European areas and the rural European divided uh was most prominent in Arab countries where urban electricity access was 84.5 percent while in rural access was only 52 percent. Around 52 million people in the Arab countries didn't have access to clean cooking with large sub-regional uh uh disparities. Going to the renewable energy I have just to highlight here is that we had five pillars in our analytical uh affects uh we identify uh the market structure through the high level indicators then the policy framework of course we highlighted also the institutional capacity and the overall financial and investment reforms in the Arab region in addition to the final carbon emission and monitoring protocols. In terms of installed capacities the highest are Saudi Arabia targets uh of 58.7 gigawatts by 2030 and Egypt target of 59.7 gigawatts by 2035. These targets represent 30 percent and 42 percent of share of the national installed power generation capacities respectively and during the slides you can figure out that there is announced a target by 2035 among our countries with more than 200 gigawatts which is a huge number and needs to rapid processes and instruction in addition to legal framework to apply this to be applicable I mean. In the slides we have just highlighted the installed capacities in terms of technology so we have 3.9 gigawatts in wind 7.4 gigawatts PV and 0.75 CSP and there is others like hydro and geothermal 0.35 gigawatts excuse me without hydro so the total renewable energy capacity is 12.4 while the hydro is 11.2 and the total capacity's overalls that have been installed till now is 23.6 gigawatts and this slide I just highlighted the renewable energy installed capacities like in terms of technologies but I'm going to excuse me I'm going to share that just one point here that the renewable energy state reduced approximately 7 percent in the installed capacity and the slides I just want to highlight that we have several Arab countries conducted their tariff reform actions and make progress in inducing their energy subsidies in order to promote and catalyze renewable energy and solar energy specifically whereas the region witnessed an unprecedented wave of energy subsidiary forms 16 countries have conducted this in 2020 while 6 countries have started early in 2014 with a total number of 19 countries from the Arab region and this slide I'm just highlighting the development and draft of a new app so there is implemented new app in Palestine in Lebanon and Indonesia while the second phase of the new app was the implementation of the first phase of the new app is conducted in most of our countries the one in the light red here Iraq Saudi Arabia and Sudan Algeria Morocco and Libya Egypt is still under the preparation of new app too and the rest of the countries are still need more ambitious plans to finalize their new apps last but not least just this is just the numbers of after analytical methodology I took during this apex publication to figure out the overall situation of the Arab countries we can say that we have 21 new apps in different strategy stages whether phase one or phase two or even under preparation and as you see it's in Jordan, Bahrain, Algeria, Egypt, Iraq, Lebanon, Libya, Kuwait, Morocco, Djibouti and even Mauritania, Yemen and there is a 14 Arab countries with new app and national targets of the second page we have 17 national assess signs entities for energy efficiency and this is very important because last hope in last hope 27 in China, 27 in China, they have highlighted that the slogan was the energy efficiency comes first should be taking seriously and we have also living countries that use the new app temperature which will lead at the end to monitoring and evaluation of the previous new apps and we will of course consider this in the upcoming new apps at the last slide I'm just sharing with you the QR code of the ethics so you can download it and there is also like small videos that summarize overall ethics which could be benefit and last but not least I just want to thank my colleagues Dr. Mehmet the technical director and my colleague engineer Akram Muhammadi who was on the charge of this ethics report and also in preparing such amazing presentation thank you so much and I hope I wasn't taking too much time no thank you very much Nadia and actually there is so much information in this report that we could spend again longer time and your work was this position really at the center of the priorities for the future because renewable and energy efficiency you know so even the title is very appropriate for the future but and certainly very relevant for this group of participants there is a question from a bill that says why what about nuclear as clean energy of course it's a clean energy but you know that the nuclear is is very pure in the region and actually there is some let's say initial plans for that in the minor region but it's not concrete yet to be considered at the ethics so however we have some data about it and we are trying to figure out in the upcoming ethics if you have concrete information to be included of course it's interesting to know that you are trying to look at that as well yeah yes of course it should be so I would thank you very much Eman thank you thank you so much for having me it was my pleasure and I honor to be part of this training today and I would love to be with you much more longer but I have another commitment I can join you later on thanks a lot thank you very much and I'm very pleased also to move back to the session of the IEA because now we have we are back to a content on energy statistic and estimation of emissions with our expert you are from the our group the International Energy Agency data center so from the balance now we move to the estimation of emissions which is so important especially the thinking of COP and the transitions that we are moving into Yuhar please thank you much Robert so yeah welcome everybody to hear about the greenhouse gas emissions estimates estimations that the IEA does and also we are going to introduce a little bit the methodology that you can use basically first we start with having a short discussion about why it's important to collect emissions data and track the climate targets and then we go into two different methodologies that are usable sectoral and reference approach and then we have short conclusions and basically out of the source categories in the 2006 IPCC guidelines for emissions estimates we define energy as so so that we have few combustion activities then we have futures of emissions and then we have also carbon dioxide transport and storage so basically the category 1c here can also include negative effect on emissions so some carbon can be captured and there are some projects actually in the main region in Saudi Arabia and Qatar and the UAE on this also and as you can see here the source category of energy is around three quarters of the total greenhouse gas emissions globally so it's quite important and very important part when we look at the total climate effects also of emissions so that's why energy is such a big focus on the climate discussion and one important thing when we talk about global climate targets and measuring emissions globally is to have a harmonized set of requirements basically everything is based on the international recommendations on energy statistics which as you learned is the basis for the energy balances and from those data the energy statistics data we then calculate the emissions inventories using the 2006 IPCC guidelines for national greenhouse gas inventories and it's very important that these metallurys are used because they align with each other so they work together and that ensures that we will have a coherent set of national energy data and that also needs institutional collaboration at the country level basically the agencies or departments producing the energy data will need to make sure that the same data is used also in the climate side of the government I will not go to Menti for these questions necessarily to save some time but basically one question to start with is what is the highest emitter in the main region which sector and could be transport could be power generation energy industry could be industry could be buildings but the correct answer depends actually a bit on the country for many countries it's the power sector and the energy industries but also for countries where fossil fuels production is not as big part of the economy actually transport and buildings also become very important and something that we can also see here is that in countries where fossil fuel sector is large also the transport sector is usually the second largest and that's due to for example the fact that the production of fuels needs needs also transportation of those fuels to different markets so transportation of fuels is a big part also in these countries another indicator that tells a bit about the economic structure of the country is the carbon intensity of an economy basically means the emissions divided by the purchase power parity GDP of the country and this gives an indicator of the reliance on fossil fuels of the economy and here we can see there is some it seems to coincide with countries where fossil fuel production is is large but also there's some variance here also and now to continue to how do we estimate the emissions basically there's two approaches we can approach the emissions from the supply side or we can approach them from the demand side and the 2006 IPCC guidelines give us two approaches for estimating fuel combustion emissions which are basically the sectoral approach which is a bottom-up approach so basically from economic activity so demand to emissions and we have basically we have different sectors and we have different products and the transformation and final consumption for each of those and from that we can estimate emissions for all greenhouse gases and then we have reference approach which is top-down so from the energy supply side and of course this is less granular approach and it can only account for CO2 emissions from fuel combustion when we go to when we start looking into fuel combustion more we can see that it's actually divided can be divided in the subcategories let's say energy industries manufacturing transport and all of these as you see can be split even to smaller categories which is important in the sectoral approach to have that granularity of different consumption and then we'll see and see it through to the emissions side and carbon capture side there's also some split in the different categories when going to the separate sectoral approach the main idea here is that when you have a fossil fuel here a simple example of methane which contains one carbon atom when you combust that you add oxygen to it and basically you get the result where the carbon is conserved so here you can see one molecule of CO2 and then two molecules of water and based on the these because we know the chemical principles we can estimate when you know when we know the mass of carbon contained in the in the fuel and we know know that the carbon will be preserved in the reaction and we also know the mass of greenhouse gases that's produced in the combustion and this basically gives us the emission factor and which tells us like how much greenhouse gases are released per a unit of fuel combusted and traditionally usually in the sectoral approach instead of mass of fuel we use the energy contained in the fuel so that's how we derive the emission factor and how we use that in the sectoral approach in the tier one methodology is that basically we have a sum of all of the fuels and for each fuel we have the emission factor of the fuel times the consumption of the fuel times the net calorific value of the fuel and this gives us the emissions from that fuel and basically as it is a bottom-up approach we include total final consumption so combustion happening in the industry, residential etc but also the impact in the electricity and heat production and the own use because of course the energy industry also uses fuels to power their own processes so that needs to be accounted to for and the net calorific value here basically means the practical amount of energy received when the fuel is combusted or the usable amount of energy received this question we were going to be I'll quickly run you through it but we don't go to Menti here so if you have a car that combusts five kilogram of motor gasoline for 100 kilometer how many tons of CO2 will be emitted in a 1000 kilometer trip so basically we here know that in 1000 kilometer trip we will have 10 times the amount of fuel so 50 kilograms and then we could multiply that with the net calorific value for megajoules and then again multiply that with the CO2 emission factor of motor gasoline and we will get to the first answer of 220 tons of CO2 so that's basically a simple example of how to estimate emissions using the sectoral approach then going to next topic fugitive emissions these don't come from fuel combustion but these are actually leaks of gases and vapors and mostly unintentional or at least irregular so these happen can happen during the extraction and exploration of fuels the transmission and distribution can be flaring and venting can be happening in the refining and processing and so on and how to be how can we estimate these well that becomes a bit trickier because there's different kinds of activities can be volume of flaring can be number of abandoned mines where gases are leaked can be we can try to have a factor for refinery throughput we can have pipeline capacity and all of these will be specific also to the category of fugitive emissions so solid fuels liquid liquid fuels etc and so basically the lowest tier methodology here will be to have activity data so let's say a number of abandoned mines and then a factor for if you have x number of abandoned mines how many how much is the leakage from one mine for example on average and then you could arrive to a estimate of the total emissions and with the tier two tier three you would be able to use country specific data and then also direct measurements in the in the most exact approach for the reference approach so this is the supply side approach where we previously for the sexual approach had the idea of carbon conservation here we are using the idea of mass conservation basically all carbon that's input into the national economy either by production or imports is 100% considered to be released into atmosphere or diverted so starting the products in fuel stocks and basically here we think that like 100% will be combusted so that's not as accurate as the sexual approach but it's it can be used for a benchmark to verify the results of the sexual approach because even though we would expect these approaches to produce slightly different results we wouldn't expect them to be crazy much apart from each other and this the thing with reference approach is because we only assume all carbon to be combustion and turned in the co2 we only get co2 emissions from this approach and one thing to remember for countries where biomass use is is is large is to remember that the co2 emissions from biomass combustion they are not included in the energy sector or energy category emissions but instead they go to agricultural forestry and land use sector but the sea like the methane and nitrous oxide emissions should in turn be estimated into the emissions emissions category because those are not estimated in the agriculture and forestry and land use sector getting some answers here so basically the question was which of the following are true for the the sexual approach but which was just explained and whether it's based on energy supply data whether it's more granular than the reference approach whether it accounts only for co2 emissions and whether if it's affected by uncertainties in the net calorific values and we can go to the answer please so we see that it's not based on supply data because the idea of the sexual approach is that it is based on the demo inside data and it's therefore more granular and the sexual approach the reference approach is based on the supply data so therefore number three is correct and the sexual approach does account for other ghd emissions too it's not only for co2 and it is affected however heavily by the net calorific values because as you remember when you calculate the emissions for each fuel you use the net calorific value of that fuel in that calculation okay we can go to the next question thank you so here we have the apparent consumption of and the idea of apparent consumption I don't know if you can see the formula on the left hand side here basically this apparent consumption is used in the reference approach to estimate the consumption from the supply side so basically it includes the production and imports of a fuel minus the export minus fuels going to international bankers so the stocks of international aviation and marine transportation and and stock chains is so fuel that goes in the storage and basically from you can also answer here but basically when you calculate this is from for Australia in 2021 for crude oil and basically if you go to the answer next slide thank you the last one is the correct one and I think we can do maybe one or two more mentis so here we can see the share of future on total energy emissions in the manner region as we know fugitive emissions as they come from from the different phases of fossil fuel like the cycle of fossil fuels from well to tank we can see that the emissions of fugitive emissions are higher in countries with fossil fuel production and if you go to the next slide can you name some sources of fugitive emissions so now you can feel free to write if you know of sources where where there might be leaks or involuntary or irregular emissions during either the transmission distribution or production of fossil fuels yes all all all true well agriculture the emissions for agriculture go to their own category but basically if it's if it's a leak of so basically for example a truck the full combat fuel combustion of a truck is not considered fugitive but if there is let's say if the container on the truck is is somehow open and leaking oil or gas that will that will be fugitive emission and same for agriculture if it's this kind of of leak it could be there okay pipelines pipelines that are are important part in here possible leaks of pipelines okay yeah i think we can move move forward yeah okay just a second i will here again so now to conclude the key key takeaways of this emissions session is that the sectoral approach is the most granular approach available and by using that and then checking it with the reference approach there's a good chance that if there are some problems with the data for example the difference is in those approaches could point to this and those challenges in the data could have could be identified some causes for this could be differences in in the activated data versus the supply data so basically what Nikola mentioned earlier the statistical difference and then an inaccurate net calorific values carbon content of different fuels and maybe there is some some in the reference approach side maybe some carbon is included that should not be included so that is not compressed composted etc and and the important thing is to make sure that the national energy data is is very good quality which requires well resource and will design data collection in the national level and also the institutional arrangement so making sure that the people working on generating the energy statistics also work with the people working on climate targets and climate data so that the natural gas inventories are calculated based on the same energy data produced in the in the energy energy side of the government and that is basically it that's my part for this one thank you very much or any questions thank you very much yuha i think it was very very clear and you are highlighting here very important points in particular thinking that many countries now all the countries that signed the paris agreement will be invited to regularly report all the greenhouse gas inventories and this is a sort of very important effort and it strongly relies on good energy statistics as you're pointing out maybe some in the some experts in the audience can let us know whether they are aware of national greenhouse gas measurements or inventories in the country and whether the energy side is involved because this is what yuha told us this arrangement is really important if there are national experiences you'll be happy to hear in the meantime maybe you mentioned also the difference between carbon and other gases maybe you can give us one minute explanation on estimation for example for methane that is so important and not so easy as easy as the carbon yeah thanks Loberta sure basically as we saw before when we calculate the fuel combustion emissions we use and we for CO2 we assume everything is oxidized so all of the carbon going into the fuel combustion is is becoming CO2 and and we have emissions factors based on that but for and and CO2 emissions are usually depend not not depending on the technology or the process they're usually consistent in this way but for methane or other greenhouse gases there is a great variance between the emissions factors depending on the technology used in the fuel combustion so that's one one key different difference to be remembered when estimating emissions for other other gases that some things that are possible for CO2 there needs to be more maybe dedicated approach with the other gases and need to take into account that if you want to be have an accurate estimate you would also need to change the emissions factors based on the technology you're using and for methane that's also a big from the fugitive side and it depends a little bit on what are the resources available for the country or for the entity making the estimates but basically you could either use emissions factors that are estimated for another country and then use those with with maybe some factors in between to estimate your own when you know the activity data let's say pipeline pipeline leaks you know the type of pipelines and length of the pipeline network you could maybe and the gas going going inside you could estimate the leaks based on emissions factor from similar systems from other countries but if you have the opportunity of course let's say satellite measurements or also like direct measurements on on the on site based on the technology used that can help to make the data more accurate but a simple estimate can be also made using factors calculated for for another country where these measurements have already been made thank you thank you very much you have I think there is a lot of work possible around the fugitive emissions and methane I also highlighted in the chat for those who are interested that some recent work of the international energy agency on trucking methane which is also equally important in the future but thank you very much you have this is an extremely important topic and we wanted really to include it looking ahead of course becoming in the region I propose that we skip the break for the sake of time as we are late and I am very happy to give the floor to the other and she can lead the second part of the workshop thank you very much Roberta so hi everyone so we have seen earlier in the first presentation of the IE how energy balances can be used to get an overview of the country's consumption as they're available in almost every country however the the level of disaggregation of such energy data is not enough to monitor energy efficiency as we don't have enough detailed information on for example end users in the residential sector so we need more detailed demand data and they are still globally poor so I now invite Domenico Latanzio from the IE to talk more about end-use data and energy efficiency indicators Domenico the floor is yours very much I'm sharing my screen do you see it correctly and can you hear me yes okay thank you very much good morning I'm Domenico Latanzio and I'm statistics manager at the international energy agency leading the team responsible for the data collection on energy end-uses and efficiency data and today with this presentation I'm going to present what Zacchia just mentioned so you're going to work on a fish of the efficiency team on disaggregated energy end-use end-uses and efficiency indicators this is very important to understand better what's happening in our countries first of all what is energy efficiency well the simple definition of energy efficiency is that energy efficiency is using less energy to provide the same service this sentence will be our light throughout the presentation why energy efficiency is so important well we here at the IEA we estimate that 40 percent of the reduction of the energy related greenhouse gases emissions will come from efficiency 40 percent so it is both creating some metrics to track it but energy efficiency means also much more we have different benefits from improving our energy efficiency it has different implications in our society and our economy it increases for instance energy security having less need of imports i'm less dependent on the important countries in general it affects also prices if we have less demand of a specific energy commodity with the same offer the price decrease and then it increases industrial productivity industries that invest in reducing their energy input are more resilient and competitive in the market it increases also the employment most of the time improving efficiency means employing more people let's think about all the renovation of the housing ongoing in different parts of the world it brings home energy efficiency and it requires employees in the construction sectors and much more there are no silver bullets in the energy world but energy efficiency is what gets closer to be the silver bullet why then disaggregated data are key well because you get what you measure as you have seen presentation of balances and all the presentations throughout the day balances are full of very interesting information and input to policies the balance gives me the overall energy behavior of the country but we need to further disaggregate the data to draft tailored policies for instance if you realize that the energy consumption for the residential sector represents a big share of the energy consumption in the country i need to assess who is driving this consumption to be able to tackle it and reuse it is it cool king is it watery heating or is it cooling i need disaggregated data and indicators to set the starting line and to assess and verify the the final result of all my policy how to build energy efficiency indicators what we can learn from them so as we have seen we once we have disaggregated energy consumption by end use we need to create our indicator we use to define the indicators as energy consumption by induced divided by the relevant activity so for instance we can have an energy use for heating divided by space floor or we can have some indicators based on the production the industrial production of a specific industry here it's what we identify as the pyramid of our energy efficiency indicators and from the top to the bottom you have different levels of energy indicators with the very top one which is a very first proxy of the energy efficiency indicators so this is the final consumption divided by GDP this is not an energy efficiency indicator per se but is the best proxy that we have whenever we don't have further disaggregation here the energy data center of the IEA we have this data collection on indicators and we collect the different end use data to be able to create those indicators at at level of the energy intensity so let's have a look what why this is important so here is the index of the total residential consumption for a specific country the blue line is at the top represents the total residential consumption it seems that across the years it increases by one percent but let's dig down and understand through the indicators if this is the reality if we dig a bit down and then we create the first indicator we can we can have the dark blue line which is a total residential per capita and we can already see that actually the consumption tracked by this indicator decreased so the consumption by population decreased if we further dig down in creating more accurate indicators and we get to the yellow line which is the the last one we can see that residential space heating per floor area which is the best indicator we can have for space heating actually decreased by 25 percent so the first light blue line and the yellow line are telling two different stories with the yellow line we have a clearer understanding of what's happening in the country and we have more elements to say that energy efficiency actually increased in in the IEA during this period we have then disentangled activity and structure and all the drivers that that influences the total final consumption so let's see how we identify the different drivers of different activities and the different end uses across the four sub sectors that we we track so for industry we have a number of industries that we we track come spanning from iron and steel to textile and going through automotive and patent paper those divisions are more than the ones that are included in their normal balances and therefore to create the indicator that we have mentioned before we need activity data that we identify as value-added or physical production for industries such as the cement the cement or the steel industry here some examples of the possible indicators that we can create with the with the data that we collect on the left hand side we have the energy intensity per ton of cement for the cement industry and on the right hand side we have the energy intensity per value added for the same industry those two indicators are complementary and they can show they can show two different information and give us more information on the sector going to residential for the residential we distinguish end uses as we have mentioned before we can identify space heating space cooling water heating lighting cooking and appliances the activity for this sector is namely residential floor area occupied dwellings or population and for some end uses appliances stock we need to pay particular attention to this sector because when we then identify we create an indicator we need also to select the right activity data for this sector what we want to to have is the occupied dwellings dwellings because we don't want to overestimate the energy consumption of the average dwelling dividing by a larger number which are unoccupied dwellings and vacation homes so we need really to identify who is the driver for this sector is the occupied dwelling and here are some examples of the the energy efficiency indicators for all those end uses then transport we distinguish transport segments and transport modes so we have distinguished between passenger and freight which is a difference that we cannot do with the balances and then transport modes road air rail and water and then we use the activity data that namely is the passenger kilometer data and the tom kilometer data so this is a measure of how much the people have moved during the year in the country or how much the load how much the the tons have moved in have moved in the country this is how we calculate the passenger kilometer and the ton kilometers and basically we have the vehicle stock we multiply by the average distance traveled and then we multiply this amount by the occupancy rate in the case of passenger kilometers so we have the number of kilometers done by by the passengers and or the load factor for having the indicator the activity data that is the denominator of the energy efficiency indicator for for freight and again here an example of the of what we can produce out of it for services we can have two approaches one is based on the end uses so space heating space cooling and the other one by subsectors so we identify the subsectors in services and we report the energy consumption for it and the activity data for these sectors are again the usual suspects value added or service floor area with the addition of some other activities such as the number of employees and this is again another example of indicators that we can create out of it all of those data once we have the good representation of the the situation on the country we can also create what we call the the composition analysis we have all the drivers to disentangle the effect of the structure and the activity and isolate isolate the energy effect here an example for freight and passenger transport in the blue line is the energy consumption for the subsector if we look at the passenger transport on the right we can see that the energy consumption stayed in in the US more or less stable with some ups and downs and plummeting in 2020 because of covid if we disentangle the effect of the different factors we can see that activity kept increasing across years while the total the final consumption stayed more or less stable and this was the the effect of the efficiency so you can see the green lines that goes down it means that the activity the major activity the major number of people moving was counterbalanced by the more efficiency we publish all of those indicators and those data in a in a publication called energy and uses and efficiency indicators and we have created a data browser for it so I would invite you to navigate our publications I leave you here the links we do know that collecting those data is challenging that's why we have worked and we are working on tools that allow countries to flourish in this space the first tool is the energy efficiency roadmap this is a paper that will help countries to identify gaps and institutional arrangements this roadmap is intended for countries that want to assess and revamp or create from scratch their data governance and when it comes to end uses and activity data most of the most of the time those data sit in different institutions not always the energy means I hear some feedback different institutions not always in the energy and ministry it might be the transporting issue for instance and therefore require a solid and clear data governance arrangement with clear objectives and mandate we have identified key questions and key passages that help countries to evaluate their current data governance and design new ones this roadmap includes also description of the data governance of 11 among our partner countries here at the IA we really think that we can make the difference conveying the experiences of other countries and assisting in restructuring the data governance if you are interested in working with us to revamp your data governance please don't hesitate to reach out to me on the subject the second tool we are working on currently is the what we call the toolkit talking with countries we have realized that most of the time all the ingredients for having an initial desegregation model are there there is a country balance produced in the country and there are some services in place but sometimes countries need and help with putting together those ingredients and create the right model to have desegregated the data therefore we are working on a toolkit that can bridge this gap elevating the level of analysis that can be done in countries and making countries policies better informed by data the toolkit will consist in a in an excel tool and a manual that will guide you in through the modeling and a survey a typical survey that you can have in your country to have the data needed for the toolkit we will implement those models in countries that wish to work with us with a specific projects if you wish to implement those estimation models in your country please don't hesitate to reach out to me and we can understand how to create a doc project for this i personally think those two uh kids are very important and very useful so don't hesitate to reach out to us if needed i will close my presentation here and i will be happy to take any questions you might have thank you thank you very much domenico for this very interesting presentation given how energy efficiency is high on the political agenda of many countries so i think that the work that you will you have just presented can be very useful to countries especially the work that you have done on the on the roadmap to support countries in in developing energy efficiency indicators so if the participants have any questions for domenico please do not hesitate to put it in the q&a box or to take the floor especially we are very interested to hear from countries if you are currently developing um such data on energy efficiency indicators or if you're interested in working on this area and how you can let us know also how we can support you if there's any interest on your side to to work with the ia on developing those indicators there's a question again from abir um domenico i don't know if you can see or i can read it loud as well yes i can i can see it from abir so is this co2 kilograms per kilowatt hour could be an efficient indicator in general uh yes it's a great indicator the indicator of the amount of co2 emitted by kilowatt hour because it's it's getting it's the synthesis of what's happening in the electricity sector we always need to be aware that um that indicator also includes some shift in in shares so it's not an energy efficiency indicator per se it's not measuring the increase of the efficiency in the power plants for instance they're using natural gas but is affected by the different in structure so if we had before only coal and just like a little share of renewables and then we will have uh after a while um 50 percent of renewables and 50 percent of coal then we will see this indicator decreasing but you're not measuring the efficiency of the electricity system you're just measuring a change in the structure so we need to also there to decompose and we have some decomposition for that also in our databases what are the effects if it's a shift in the in the structure or it's actually an energy efficiency measure which means that coal power plants for instance got better and got more efficient so we need to pay particular attention to that thank you thank you dominico any other question for dominico i think then uh anyway you can you can contact dominico i think he he can share his email uh through the through the chat uh and now um i propose that we move to urn sqa presentation uh we have seen earlier with the presentation from augury power renewable energy such as solar pv has seen a considerable uptake in the minna region in the past years and uh however it's still very difficult to collect data on their use but there are some new data sources and methodologies that can be used and uh so um if it's still possible i invite mr christof warna from urn sqa to to present um on how to estimate solar energy good afternoon good morning everyone good morning uh my name is christof roshana i'm here today to talk about using new data sources to estimate solar energy data can you hear me yes yes so solar energy is a rapidly growing source of renewable energy and it is important to have accurate and timely data on solar energy potential and generation this data can be used to make informed decision about solar energy deployment grid integration and energy policy uh it's a growing source of renewable energy in the minna region however estimating solar energy can be challenging to due to the lack of traditional data sources uh here i'll explain uh actually i'll give a brief uh on the content of the presentation first i'll tackle the new data sources for solar energy estimation second i'll be talking about the benefits of using new data sources i'll give an example on sgjo ai tool on solar panel detection uh as well i'll give a list of open sources tools for solar panel detection a couple of case studies the challenges and the opportunities for using the new sources of collecting data so uh for the new data sources uh for solar energy estimation let's dive deeper into these data sources that are enhancing our ability to estimate solar energy potential first there is a satellite imagery this is a powerful tool in our arsenal through satellite imagery we can identify where solar panels are being installed around the globe not just that allow us to estimate the potential solar energy of a particular area and keep track of solar growth of solar energy adoption the importance of space giving us insight about our own planet quite fascinating isn't it uh then there is weather data this is crucial solar energy after all is significantly impacted by the weather by analyzing weather patterns and data we can make informed prediction about solar energy generation additionally this data aids us in identifying prime spot that are mostly conductive for solar development there is iot internet of things data in the era of connected devices our very solar our very solar panels are becoming smarter through iot or or internet of things we can meticulously track the change the energy generation and performance metrics of individual solar panels and with machine learning and play we can process vast amount of data from these devices to precisely estimate solar energy potential as well there is social media data now this might come as a surprise to some but social media can be a goldmine of information it can be used to identify areas where there is interest in solar energy as well there is crowd source data last but by no mean least we have the power of the crowd people across the globe are contributing data on solar planet installation and their respective energy outputs there this grassroots level information can provide us with invaluable insights and ground truth each of these data sources on its own is powerful but when combined they present they present us with unprecedented view in the world of energy solar energy sorry moving on to the benefits of these new data sources there are transformational here's why so first there is an increase in accuracy and timeliness with these new sources we're not only getting data we're obtaining precise and timely insight imagining imagine having a an intricate understanding of solar irradiance and related parameters all updated in real time that's the power of these sources upward as well there is reduced cost traditional data collection and processing methods can be expensive and time consuming but now we're stepping into a nearer we're obtaining critical data is not just quicker but also far more cost effective there is as well the granularity in estimation the devil is in the details they say these data sources allow us to dive deep providing us a granular review of solar energy potential down to individual rooftops in some cases as well there is improved understanding finally this new wave of data doesn't just benefit us on the commercial front it helps us grasp the broader implication of solar energy on our on our power grids on our environment and on our communities in essence as we adopt these new data sources we're not just optimizing we're revitalizing our approach to solar energy here i'll give an example of the tool that we use at s1 it's s3ji tool on solar panel detection i'll give a brief detail about this tool s3ji is a suit of cloud-based tools that enable users to perform machine learning and artificial intelligence tasks on geospatial data the solar panel detection tools uses deep learning to automatically identify solar panels and satellite imagery it can be used to create maps of solar panel installation estimate solar energy potentials and track the adoption of solar energy over time how s3ji solar panel tool works the solar panel detection tool uses a deep learning model that has been trained on large data set of satellite images containing solar panels this model is able to identify solar panel in images based on their size shape and spectral spectral signature the outcome of the tool is from using this tool are profound not only does it provide a highly accurate map of solar installation but it also offer offers invaluable insight into the potential of solar energy in different region by analyzing this data you can observe trends identify patterns and make more informed decision in the realm of solar energy the benefits of the solar panel detection tool are various the first one is accurate and efficient detection the tool efficiency is unparalleled it can swiftly and accurately detect solar panels handing vast terrains with ease whether you're looking at a cozy neighborhood or an expensive city s3ji tool doesn't waver in its performance then there is scalability the beauty of this tool lies in its adaptability regardless of the scale of your project it is equipped to manage ensuring no area is too minute or massive for analysis and then you have cloud based and user friendly operating in the cloud it offers the convenience of accessibility its user friendly interface ensures even those with new to gis find it approachable i'll later give you an example on this and there is integration capabilities one of most notable features is its compatibility with other gis softwares enhancing its utility application range then there is data driven planning beyond just detection the data garnered becomes a pivotal resource laying the foundation for energy policies grid planning and infrastructural advancement and then you have the cost effectiveness let's not overlook the financial perspective by minimizing the reliance on manual surveys and on-site data collection significant savings are realized as well there is the benefit for planning and development some of some of the other benefits are solar energy planning and development streamlining projects from inception to execution then research and analysis offering data driven insights for better solar understanding and policy and regulation guiding decision at government level ensuring sustainable and efficient solar practices here's the short and brief guideline on how we used it and anyone can actually apply it so we first you need to have access to our gis pro second a high resolution aerial or satellite image of the area of interest and for the steps that you have to follow in order to process these to detect solar panels using the s3 jo ai tool for solar panel detection you have to first open the s3 jo ai tool for the solar panel detection in agria s pro then you have to select the image that you want to analyze third you have to set out the output feature class where the detector solar panel will be saved first run that's it so the tool will process the image detect any solar panel that are present and the detector solar panel will be saved as a feature class in the map here i'll provide the a brief list of the other open source tools solar uh open source tools for solar panel detection there is sunroof an initiative from google and then you have open solar map uh it's a testament to the power of collective knowledge it's crowd-driven database continuously updated enriched with solar panel installation from around the world then you have solar gis it's a comprehensive platform offers more than just detection it brings a myriad of tools to the table aiding and estimating the potential of solar energy complete with a detector and energy calculator then however the standout in the list is deep solar a product meticulous uh a product of meticulous research by stanford using advanced deep learning methodologies it identifies solar installation with precision from satellite images uh i'm gonna talk as well as i'm on another tool which is amazon aws solar panel detection uh shifting our focus through amazon cloud-based solution the aws solar panel detection service is an epitome of leveraging deep learning it accurately pinpoint solar panels and satellite images uh two instrumental services in this domain are recognition an image analysis tool that can discern and categorize objects including solar panels there is stage maker not just a machine learning platform but a complete ecosystem to train and implement models specifically for detecting solar panels as well there is helioscope exploring the world of open source tools helioscope is a gem for those passionate about solar energy beyond merely estimating uh solar radiation or pv production it's a holistic analyzer that empowers users to assess solar energy potential anywhere moreover it doubles as a design and optimization tool ensuring solar systems meet the highest standard notably we collaborated with the ndp on a project to install solar panels at the select hospital and provided the case study for each for each one using helioscope another tool or a new method of collecting data which is web scraping can be used to collect information on solar energy announcement such as new solar project and government incentive this information can be used to improve the accuracy of the solar energy estimates then uh we have to mention as well incorporating a solar aspect in the household survey the integration of solar data and household survey this offers insight on solar panel ownership consumption and attitude such information not only refines solar panel energy estimates and validate machine learning models but also guides both policy with the climate challenge ahead it's vital to understand household interaction with solar energy and identify barriers to adoption uh here i'm gonna be very brief uh there is several case studies i'll show them they are listed here first we have the world bank global solar atlas then there is the national renewable energy laboratory system advisors model sam then you have the solar gis solar atlas which was a cooperation with the world bank then there is the world resource institute uh which is using satellite imagery and machine uh satellite imagery and leveraging machine learning to gauge the global roof of solar potential then you have the national renewable energy laboratory that taps into crowdsourcing to quantify solar panel installed in the dgs innovative methods are driving our understanding of solar adoption and potential uh nothing ground without the challenges so as with any journey the past the solar powered future comes with a set of challenges ensuring the accuracy of our data stays ahead in the technological race and winning the hearts of admins for broader solar adoption are just few of the herders ahead the challenges are quality and consistency of the data maintaining and privacy and security addressing computational demands however with collaboration and innovation and determination the future looked not just bright but solar bright data is not just numbers on sheets it's a bedrock of strategic planning and the energy sector with precise data policymaker can design initiative that resonates with real world challenges and opportunities infrastructure investment can be more targeted ensuring resources are channeled where they can make the most difference and for the end consumer data-driven outreach means programs and incentives that truly cater their needs and aspiration the domino effect of harnessing solar energy powered by these innovative data sources is so profound economically we're talking about job creation local enterprise simulation and more environmentally the transition to solar is monumentally towards reducing our carbon footprint moreover from a geopolitical standpoint the move the move towards solar aids and energy independence reducing our reliance on imported fuels as a conclusion new data sources can be used to improve the accuracy and timeliness of solar energy estimates this can support a variety of application including solar energy planning and development solar energy research and analysis and solar energy policy and regulation in conclusion the journey towards today's discussion underscores one fundamental truth the interplay of data and technology is visualizing our social landscape as we tap into innovative data sources from jail spatial ai to household survey we're not just estimating solar potential we're crafting a brighter sustainable future this transformation isn't the result of solitary endeavors but of a collaborative synergy each one of us whether we're devising policies developing tools conducting research or simply using solar energy in our homes plays a pivotal role solar energy isn't just the promise of cleaner power embodies the vision of a sustainable world robust economies and thriving communities together guided by insight and driven by purpose we can make this vision a reality thank you thank you very much christoph for this very interesting overview of all the different sources that countries can use to estimate solar PV this looks very promising and i i hope that there will be trainings to support countries in using been learning how to use those tools and and to apply them i don't know if you have time to take some questions and yes okay so i see there's a question from avir did you do any verification between the output from the tool and the actual ground data for example mainly for the huge solar plants uh yes so we have so we have data for solar solar farms in the middle east and we did the test in lebanon on what we got so the machine learning model is framed well any other questions okay i'm here i see you i see a raised hand from darlin edeme darlin can you unmute yourself yes can you hear me yes yeah uh so thank you very much for the presentation very very interesting i just had a curiosity with respect to the web scraping uh approach that was presented quickly in a slide i was just curious to understand what's the methodology there first um if you have any specific case study project that you could describe in which you applied this which were the results and particularly i'm interested in knowing if you were just like the web scraping and the satellite image identification are two separated thing or you're also trying to kind of match them so on one side having the satellite finding i don't know information about specific solar facilities and finding information about that specific facility through web scraping right sure so we used web scraping to gather data on solar farms across the arab region which is various then we ran the model first based on uh i think the model that was set for the united states and we got pretty much 90 exactly the same results so it was just a validation tool as well it is a source of new way to collecting data in case we didn't run the the model okay but just to clarify so i'm imagining the the process tell me if i'm wrong or i'm missing some stuff so you look for like on the internet there is the automatic web scraper that identifies a new plant that's been developed you find the coordinates for that and then you look for the satellite imagery and you try to validate the fact that this plant has been installed through satellite imagery processing correct okay perfect just wanted to check thank you very much very interesting thank you very much donan i see there's also another question in the chat um from sedu so the question is since you use the characteristics of the spectrum of the images can the deep learning models you present a differentiate the installed solar modules by type of technology polycrystalline monocrystalline and amorphous unfortunately you know thank you um and there's also another question from avir how do you uh differentiate between the operated and just installed yeah so we do a time series analysis of satellite imagery so uh so if we take the satellite imagery in 2019 we know that these panels are installed in 2019 then we do we do the same model or we run the model in 2020 and we get the output for 2020 thank you Christophe i think on the question side that's it um i don't know wafa if you will be staying uh till later or if not maybe you would like to say a few words we cannot hear you i will i will stay just to be with our participants if there's anything that you know we can help with so i'm i'm on thank you very much thank you um so thank you again christophe for this very uh interesting and innovative presentation and now we will move on to the next presentation um on uh energy prices so as we have seen energy prices have followed significant events since the past years last year itself following the energy crisis we have seen how energy prices have spiked significantly in most countries of the world and at the idea we work very closely with governments in order to collect energy prices across not only member countries but also from non-member countries and uh today I invite Pedro Carvalho from the IEA to talk more about the work that he's he's doing on energy prices and also the methodology of the IEA for prices data over to you Pedro Hi Zaka thank you very much so today i'm going to be talking about energy prices and the work we do here in the IEA and the energy data center so i'm Pedro and this is our agenda for the prices presentation and firstly i will go through some recent trends then i'll talk about the IEA methodology then a little bit about the database and some key points to remember so when you speak about energy prices uh we are talking about uh basically how real events can affect energy products prices so for example in this in this graph that you're seeing the screen uh you can see the the crude oil brand trends over the time and how the the events affected its prices so you had the oversupply and also more recently the covid and also some recent hikes in in europe in general for example so not only that they also affect our daily lives in general as drivers for inflation for example and here we collected a few headlines from inflation and in Saudi Arabia or full prices in Morocco or here in France as well and more recently the global inflation rises so in our database with the data that we collect as Zaka well pointed we have a database that comprises data for all globe so with our database we are able to build the figure that you're looking at so this has gathered prices in US dollars per liter for many countries in the world and when you look at that you can clearly see the different prices in dollars per liter in different regions of the globe and for the mere region for example a consumer is expected to pay an average of 43 cents of dollar per liter whereas a consumer in jordan would pay 1.63 for example and it's very important to point out that they represent a very significant parcel of countries GDP accounting for around an average 8 between 8 and 10 percent so very quickly talking about our methodology here when we talk about energy energy prices we are talking about annuals prices and these prices they are basically made of two main components the x-tax component and the total tax in which the total tax was subdivided into VAT and excise taxes so the excise taxes they are usually results of governments policies and they are usually put in place for specific purposes and they could be environmental taxes CO2 taxes, motor fuel taxes and so on and for example sometimes we have different taxes for different energy products or a single excise tax for most products which is the case in Israel with down exceptional electricity and the main difference between the excise tax and the VAT which you're going to see in the next slide is that the excise taxes are divided on a volume basis whereas the VAT is divided on value basis and it's applied to 174 countries in the globe as of 2022 and it's usually refunded to intermediate customers as industry and for some countries we have another tax that's an equivalency of that but for the sake of our database we include both of them in the same tax component so speaking of our database uh database is basically divided into two main data sets the first one is the energy prices that covers 141 countries in the globe and the second one is the energy prices data set that's focused on OECD countries and has the taxation breakdown so for most countries in the minor region in our database you'll find the total price the end-use price but not necessarily the taxation breakdown which is not something that's not necessarily always available and we also have complementary data sets namely the monthly prices accept and the energy prices taxation information so just to give you an example here you see the data coverage in the database for mid-grid gasoline and electricity in 2022 front map you can clearly see that the coverage changes if you look at different products so also if you change the year it's going to be different and more specifically if you change the time granularity so for example if you stop looking at monthly or weekly prices you're going to have a lower lower coverage than the one you're seeing in the screen for the same products and if you zoom in the minor region you see that we have a relatively good coverage for few countries such as Algeria or Saudi Arabia but we still have many room for improvements and even the ones that we you get the data as I mentioned before we only have the taxation breakdown for OECD countries so we could enhance their database by collecting more taxation data and but where is that data coming from and this is basically coming from official sources so energy ministries national statistical offices central banks and so on or even like direct submissions or we get them from the websites from the ministry's website or statistical offices websites and so on and usually the data for the global database is available for residential industry and transport sectors and here you see some examples of sources so the first one is the statistic Tunisi the second one is Saudi Ramco for Saudi Arabia another one is the Egypt statistical office and finally the ministry of energy and mineral resources of Jordan so just going very quickly through some key points to remember the first one is our concept of annuals price which is the price paid by the annuals customer its base is basically made of two components the x tax price and the total tax and the total tax is made of value added tax VAT or its equivalent and excise tax and when you talk about specifically electricity and natural gas it's extremely important to clarify that the annuals prices that we're talking about is not the same as tariffs so the tariff is usually a fixed rate at which the products are sold and the annual price they represent the average rate per physical unit or energy unit so they include more components than the tariff like taxation and even the subsidies and rebates so a few points that i would like you to keep in mind the first one is that this to set up the data collections might take time the methodology is extremely important so if you look at our website at the data product website you find the energy price documentation which is basically a word document that we describe everything that we do how we collect the data or sources or methodology so this this is very important in terms of transparency and also to give solid ground to our users and the third point here is that the taxation breakdown can help us and the world understand the prices collected so for example if you your government is establishing a new measure a new measurement that's going to cap the prices by reducing one component of taxation the taxation breakdown is going to therefore help you understand how this is being filled by the the unused consumer and another point is that here we deal with multiple prices and taxation frameworks so this is another thing that you can help each other and you can benefit from by bridging this this open channel with us and in the end basically all the main challenges of our data collection they are linked to national capacity and given the relevance of energy prices it's very important to structure data collection and to build up the national capacity so finally i'd like to say that we are more than happy happy to contribute with with you on your national capacity development and would be very happy to hear from you if you have a data collection place for the prices how is it and if you are able to share it with the IA thank you very much thank you very much Pedro for this very useful presentation on energy prices and taxes on taxes your points to remember was very on point I think we are very interested in learning more what the countries in the MENA region are doing in terms of prices data collection do you have a system in place and also if you're interested also in working with us on developing those prices and taxes of data anyone in the countries that are here in the participants would like to share their experience on prices or just tell us if your country is doing any work on prices data collection we would be happy to hear from you any questions for Pedro on on the topic everything was clear maybe one clarification for me Pedro you talk about VAT excise tax excise taxes but can you tell us a bit if subsidies are taken into account in in the prices yeah of course thanks Nakia so the objective of our database is to understand what's the average end-use price paid by the end-use customers so therefore our prices they comprise the subsidies as well and these are included in the excise do this component of a process thank you thank you Pedro for the presentation I see wafa has erased hand please wafa want to add and to to to mention that the inflation the CPI can you hear me yeah yes so I just want to mention that the CPI that's collected by countries is very important and specifically for example maybe our member countries can have more information on the gas and oil in the CPI basket so it's not only the prices and the inflation but also to gather like what Pedro was saying more detailed information maybe as to keep them for their analysis and you know for their for their use and and unfortunately a lot of countries are not publishing the CPI as as it should be but it's a very important I mean indicator and a lot of things are linked to it so just to encourage that more data on prices should be there and what you presented on trade on the values if we don't have the prices we can't get like the quantities and the and the calorific values and that so this is very important to link all this data together thank you dear thank you wafa very much for for this point are there any participants that would like to contribute otherwise Pedro maybe you can run some of the quantities that you had prepared oh I adapted them to the presentation as we were running out of time thank you okay then I think we can move on to the next and last presentation on our side so it's really to continue with the with the innovative data collection strategies so after the presentation from un sqa on solar pv we also would like to present to you geospatial data which can also offer precise location and time data to analyze various sectors and trend and today we have a darling edema africa analyst at the ii who will be able to talk more about the potential of geospatial data good afternoon everyone nice to meet you all my name is darlan i work for i'm african energy analyst so my work is specifically focused on on africa here at the modeling team of the of the ii but also my expertise is specifically on gis data geo information system data and i wanted to take this opportunity during this this workshop to focus a bit on what could be the help of geospatial data in the energy sector with a particular focus of course on the mean region so the okay so first of all the first point is that i'm really glad that i saw in the previous presentations that gis gis data were basically already almost introduced so i think i will do a step back and just talk first on what gis data are and i think the presentation from the colleagues from the united nations on the identification for instance of solar infrastructure already gave me a real life example of what are the applications in which gis and geospatial analysis can be can be applied so first of all what are geospatial data when we talk about geospatial data we're talking about data that have a spatial component which means that these data not only give us specific research information but they also additionally give us an information about where those data refer refer to on the space and in particular on the on the planet in which we are so whether it's like locating a city or a map or plotting the course for instance of migrating species this data brings another dimension to our data set that most of the time can be like latitude and longitude and stuff we are all used to even outside let's say the energy sector what gis does in practice it's it goes really beyond plotting points and lines on a map it's just it's really a critical let's say decision-making tool that is currently used across industries again not only energy of course urban planning health care planning agriculture and of course energy are sectors that are leveraging a lot on on gis data right now the so i will go through a bit of the introduction on gis and which kind of data we see in this in this specific category of data and how they can be used in the main region but again the one point one at least application was already introduced so first of all what is gis data i said these are information that have a particular and additional let's say feature which is the location of those data on the planet it's so you can you can really think about basic applications that you are you have in your daily life when you use a gps when you are asked to your phone through either google maps or other map services providers where you are on the planet there are different there are specifically two types of gis data one are called vector data which are then classified in three different types of data some of them are points so you can see here for instance locations of different facilities so police officers pharmacy supermarket a restaurant pretty intuitive we have latitude and longitude we are pretty used to that we have lines so if we superpose let's say to this point an additional type of vector layer it's the these are lines and they can be used for instance for roads of course these are roads in this in this in this image and then the third component the third type of vector data can be polycons and in this case again it's the third layer that i'm adding here and these represent the buildings in an area so this i think these are pretty intuitive data most of the time vector polygons are used to represent discrete information so it's nothing continuous here we only we know the location of those infrastructure like facilities etc but then sometimes there are kind of there are specific type of information that are not discrete and they are they are continuous on the space or on a subset of the space and this for this kind of information gis specialists let's say but in general people working with gis they prefer to use raster data to represent this kind of information what are rasters rasters are really grid based data format in which we have each cell which is also called pixel and that's also like to give you an example of course images are a type of raster data in which we have a continuous information which is represented with a grid based data format so raster data can be used and can be for instance derived also from polygons data so in this case for instance if i start from the previous layer that i showed you which represents the number of polygons for polygons in this case of buildings in an area if i start counting the number of polygons for instance in so in this case of buildings in each of these squares these pixels and i can represent this information through another type of data which are basically raster data so as i anticipated earlier we have a pixel which has a specific resolution that can be meters kilometers and then they have a specific value assigned to that pixel that can represent a continuous information in this case it could be for instance either the population that we estimated living in that pixel that for instance we can derive by the number of buildings multiplying by the average household size in that area but if as you can see through this kind of information we can really display this data in a completely different manner with respect to the vector data and we can for instance this is alge see the difference different density in terms of population in a city so identifying pretty easily and this is basically what we call a spatial analysis so identifying areas in which we have the highest density so in this case this is the neighborhood in which we see the yellow pixels which have which represent places that reach a value which is very high which is 354 for instance people every 100 meter per one every pixel of 100 meters each in terms of resolution so this is for instance where what i was showing you earlier so the question here is how do we create GIS data because i wanted to really have my presentation to show you how you could in case i assume some of you or most of you maybe not familiar with GIS data there are different ways so different ways and different steps in order to produce reliable and consistent GIS data the first part is the data collection so you can do it through different methodologies sometimes there are information that we can go and identify let's say by doing like going let's say on the field so we have what we do like what is done in many sectors which is basically field surveys so going directly on the field with a GPS device for instance and geotag doing what we call geotagging which is basically identifying the latitude and longitude of a specific point in the space we can have user generated data for instance if we have surveys in which people were asked to specifically say for instance an address of for instance a solar power plant we can by finding the where is that specific address on the space geotag that so to say this information refers to this specific address which has this longitude and long and latitude on the space and then the last way which is most of the time used when we are dealing with areas in which it's difficult to go with field surveys or sometimes these areas are very areas are very big so it's difficult and not cost effective to do such large field surveys we know like when we do sensors etc how costly those exercises are so sometimes what we do is identify what we find in this piece of information through analysis of satellite imagery which again was really an application that was very detailed very well detailed in the previous two presentation behind of course once we have collected this kind of data we need to process them so it's not just the imagery which is important but the fact that for instance from an image I can identify solar panels and then I can say okay there is this solar PV plant in this specific location there is a georeferencing and for instance also the digitalization of physical maps is something which is done when for instance in the past when GIS technologies and in general IT and ICT weren't that advanced we have many maps that were done physically what we try to do is to process these these maps which are physical and translate them into digital to a digital format and into files GIS files so geospatial files that we can use for our work and then of course data storage because but again since the focus of this entire workshop is data I'm pretty sure these concepts have been and will be even more detailed in the in the next presentations and next week the next days so please feel free to write in the chat if you have any questions with respect to that what I wanted to show you are specific geospatial data that are used in the energy sector to give you an idea I think some of these might be trivial and you already might guess it but I think also for people that are not familiar with this could be a nice way of seeing which kind of data you could be using your in your daily life so we talked about vectors and rasters so in terms of vectors as I said discrete information we could be talking about locations of power plants substations fuel stations we could have pipelines so not only points but we could also for instance have lines so array routes shipping routes exploration zones so again polygons in this case we could have polygons depicting for instance which areas we think are suitable for instance for either wind power production or geothermal reservoirs we can have of course also regulatory and policy zones which are polygons that represent specific areas that have very specific and dedicated for example regulations and restrictions so for instance an area which is a national parking which is not possible to install and build any power plant for instance or cross with transmission and distribution grids lines this is definitely an information that has to be taken into account while for instance estimating or assessing doing prefusability studies for installation of a power plant and then of course energy consumption points when we do planning and I think if some of you work with some of the utilities of your in your country of course having the precise location and information about industrial zones urban centers is paramount in order to uh correctly plan for instance the extension of the grid or the densification or the scaling up the reinforcement of some of those grids because we know for instance that there are plans for expanding an industrial area building a new mining facilities or oil extraction facility switching on the raster type as I said we try we use them for continuous information representation in this case what we have is for instance terrain analysis so what we you could be using are raster files that says with a specific resolution what's the elevation of each of those points for instance in a country or in a region and then use this information again to plan accordingly infrastructure because of course elevation is an aspect that has to be taken into account same thing for the land cover so you could have different pixels with different categorization saying this pixels pixel is predominantly a forest so it's covered in forest or it's a built area it's a desert so you could use this information to location specific analysis and identify for example areas in which the land cover is suitable for installation of energy facilities thermal imagery is very similar with what was presented earlier which is through satellite imagery identifying areas in which for example the solar potential could be high and could be this could be like an approximate indicator for an area in which of course solar PV exploitation could be could be cost effective and the same for resource distribution so I will skip this just because I will show you an example very soon so just some examples here you can see from open sweet map the open source alternative to google sweet map infrastructure on in this case it's transmission and distribution grids and you can see how by using some very basic let's say data visualization techniques with the color code for the different voltages of the power lines the first symbols for the different types of power plants you can really do even just by looking at the maps and the imagery to have an overview of what's the power system of this area in this case I'm depicting the neighboring area to El Cairo but by applying J.A. specific techniques you could for instance identify those areas in which we expect for instance the demand to grow in the future and accordingly plan a new additional or enforce the existing for instance this distribution grid because we expect the demand in those areas to increase a lot because of new new facilities and new anchor loads going back for instance to the so another example but in this case talking about raster fires here you can see this is it was also mentioned earlier the example with the solar solar potential in this case I'm focusing on the width speed so this is it comes from the same source that was mentioned earlier which is a project from the war bank which tried to assess the wind power potential together with the solar potential in the world and you can see here how this information is in a raster file because basically what we have is that we have a value that is translated in a specific color coding for wind speed at 100 meters and you can see here and the legend that goes from zero to more or less 10 meter per second in terms of wind speed at 100 meters this information is assessed through satellite imagery taking into account like using very complex models that take into account the morphology of the of the land in those areas and studying how wind could develop based on heat which you could put like a wind turbine and the neighboring morphology of the of the territory so very quickly how to implement this in real life I of course in so in such a short presentation I don't want to my plan was not to be exhaustive in understanding how to build up GIS and integrate GIS in your work but here I gave you and of course I think this presentation will be shared you see many resources for different type of applications so you have GIS so proper proper tools that help analyzing most of the type of datasets that I've been mentioning you have options to do remote sensing which is the identification like the usage of satellite commercial or non-commercial satellites to identify specific infrastructure to do spatial analysis spatial analysis of course so dedicated softwares pieces of software that are dedicated to do customized analysis that sometimes maybe with softwares that have a predefined methodology you can't completely customize and automate the work that you would like to do and then other resources for example to create maps and visualizations to obtain that GIS data so here you have a very comprehensive list of resources that you could look at and then other relevant tools for instance to do serve like to create databases and to have servers that have been specifically designed and calibrated to work with GIS data and to GIS data processing quickly challenges and opportunities I think they are more or less the same as when we talk in general about data but some of them are specific to the GIS sector I will go through them very quickly data accuracy and integrity again I'm pretty sure this is something you've been already talking about interoperability this is very critical for GIS because as you've seen GIS data have very different formats because I told you about two but then both of them have very different type of format as sub types let's say we have of course resource limitations because most of the time GIS data are very huge depending on the resolution and processing them can be very time consuming and resource intensive of course data security and privacy and regular regulatory frameworks but there are a lot of opportunities first of all enhanced decision making because with this kind of data you're able really to plan not only take into account the big picture but being as much as possible location specific when doing the type of analysis you want to do and then of course all the rest which is the fact that we really need interdepartmental collaboration between ministries public engagement to use this GIS data also for the general public because they have this advantage of being relatively easily understandable if you do and represent them in a manner that is quite intuitive for non experts capacity building and international partnerships I think through the IEA, UN, ESCWA, RCRE there are a lot of institutions working on this and I think by reaching us we can be able to support you towards the specific applications that you would like to develop I will leave the case studies as an annex as I said we will share the presentation if it wasn't already done but you will see two specific applications that also the IEA has been working on to give you an example of an example of what you can do with GIS thank you I hope I wasn't too long and also I was that I was clear thank you thank you very much Darlene for for this presentation on GIS I'm sure many countries have found it useful and would be trying to to apply some of the tools that you have shared with them I see there's a question in the or two questions in the chat box yes I see let me open them can also stop sharing my screen I think okay so Q&A box in the chat there's one are you planning to disseminate this data okay so which I'm not sure which data you're referring to the GIS data that the IEA has yeah any analysis that the IEA has maybe a little bit more about what the IEA has been doing with GIS data yeah so maybe I can actually quickly use the slide that I put as an annex just because I think they can give an example of some of the applications so for instance one specific analysis we've been doing in the in the recent sorry just too many animations here in the recent the recent period has been the sorry just quickly because we are yeah so just an example of this is the global methane tracker so we have partnered with and NASA and other agencies to basically use their tools to identify leakage from methane extraction and operation in the oil and gas sector in general and through that for instance these data sets are available and we have an alert system that every time that there is a used leak flare flare activity for example informed the key stakeholders about that so definitely I think right now the IEA is one of the go-to places let's say for data and we would like also to strengthen let's say the GIS component of this as I said most of the data are ultimately GIS data because also the prices data that Pedro was showing earlier when you represent them on a map and you say this is the price for this country this other country you can also go sub-country it really gives a completely different level in terms of detail of the information that you can you can provide to users in the sector okay well thank you very much don't we will share the presentation with the with the participants and they can reach out to you as well for more questions and now we are reaching the end of this workshop but if you can see in the chat box we have shared with you an evaluation survey it's a survey monkey's survey that will take you just a few minutes to fill out but which is very important for us because it allows us to improve ourselves for for future workshops also I see that we have our partner from the United Nations statistics division division Leonardo who is the chief statistician I don't know okay I see Leonardo you're here would you like to say a few words yes hi Zaki thank you for the opportunity I'm not the chief statistician I'm the chief of energy statistics in the statistics division but fine I'm Leonardo Souza from the United Nations statistics division it's located in New York we have an energy statistics program and we cooperate with the IEA and ESQUA and that is why I was given the opportunity to introduce myself here to which I am grateful I welcome this energy data workshop of IEA, ESQUA and SCEEE to MANA countries which only helps our own work our mission is to advance energy statistics systems in the countries and we do it through data collection the national coordination and cooperation capacity building and methodological work I hope you had a fruitful workshop today and I look forward to seeing you in the future thank you Leonardo now before I pass over to to Roberta for some concluding remarks I would like to thank to thank all the interpreters who have helped us during this workshop so thank you very much Maya, Elin, Obery, Asma, Musa and Cynthia and now I pass over to Roberta for for some reason battery high no phone is connected thank you Zafia well I think it was a very very nice collaboration especially among all of us around the interest of this region which is so important and we really want as Leonardo said to improve the data that will improve also our global understanding of the energy landscape so primarily I think we would like to thank the UN ESQUA and Recreate to help us in in this collaboration and also UNSD Leonardo because we know that we always work together anyway so I see this more as a sort of pilot project for a future strengthening of the collaboration on data in this region and I hope that this is the same vision from the other partners and also the participants of the workshop I would like to thank the team at the IA there has been a lot of work Audrey, Kerem, Mikey, Zakhia and Nadim and Angelina and other colleagues probably so a lot of the people the speakers from across organizations I cannot name them all and especially thanks to the participants hoping that we'll hear from you also later for a collaboration data work Nadim any conclusion word or Wafa if you want to say one word I won't be long just thank you thank you very much thank you from our side please Wafa go ahead you know just to say thank you also we're very happy for this cooperation we stopped for a few years but it's time that we get back to the countries and see how we can support thank you no thank you very much and I I wanted also to stress on the fact that also beyond statistics you know the Middle East and North Africa program and the IA focused on a range of different topics and activities again all of them are under are they're been by good quality data we've had the chance to work with many of you in the region and we hope to continue to do so and please be assured that statistics will remain a key element of our cooperation and our technical support in the region and thank you all and notably to the participants the colleagues at UNSQA and RECRI and of course the UNSD for the support and we hope to continue working together in the future thank you thank you very much everyone I wish you all a nice afternoon and hoping to to meet you again for future activities and workshops thank you bye