 Hello everyone. Good morning, afternoon, and evening to everybody. My name is Nicola and I'm an energy data officer at the IA in charge of call annual statistics for question and countries, among the other things, with my colleagues Marc and Seydoux who you will get to know later because they will present the exercises session. Now it's up to me to guide you through this first of our fuel statistics presentation that is focused on call and call products. And as you have seen before explained by my Galita for question, we will have some time on the end of this presentation. So let's start by looking at some of the latest trends in the call sector. And after that, I will show you all the products flows and definition in our data collection methodology. And finally, we will see also the annual questionnaire and some tables more in details. Here you have two donut charts, the one on the left it's showing, sorry, the word total energy supply and the one on the right, the word electricity generation, both for 2020. Now an important thing here to notice is that call is a major player in both of them. On the word total energy supply, it is the second largest source after oil and just in front of natural gas. Instead, in terms of the electricity mix worldwide call is by far the first source again in front of natural gas. I will show in the following slide some charts that have been extracted by one of our publication called information 2022, which is a yearly publication that reports the latest and historical figures about cold production, consumption and trade. Here you see cold production from 1978 up to projection in 2021. As you can see, the trend has been increasing in the 80s, then flat in the 90s, then a steep increase in the 2000s following the big increase of what became the main producer in the 2000s, which is China. And then again, a bit of a bumpy road in the 2010s going down, then up again, and then we had COVID and the rebound. The biggest producer is China, which amounts for about half of the global production followed by two other developing countries as India and Indonesia, whereas OECD countries as an aggregate are the second biggest producer worldwide and use in Australia. Sorry, I hear my voice. So I kindly ask, thank you very much to close all your microphone. Thank you. So the OECD, I was saying it's the second biggest producer as an aggregate with the USA and Australia being important producer of coal, whether for the EU there is a rather small production. Then we have consumption in this chart, which follows what is production. And we have a similar historical trend with sorry, I again ask all the participants to close the microphone, please. So China, it's this time has more than 50% award total consumption of coal. And together with India, it's about two-thirds of the world demand followed by US and OECD again at the second place with the EU a bit upper in the classification. So also you being an important consumer in this case. As you can see in this graph, let me magnify it here. You see that consumption decreased a little bit in 2020. That's because of the pandemic and it has an increase about 6% overall in 2021. So let's look at this increase more in details. And we notice in grey that China accounted for almost half of the world increase in coal consumption in 2021, followed by India, and then also advanced economies as the United States in light green and the European Union. Now what are the causes of this increase in 2021? Of course it's the rebound from the COVID pandemic, so an increase in economic and industrial activities. But also the fact that coal reaffirmed itself in 2021 as a very cheap and reliable source of electricity, substituting natural gas in some cases, because the price of natural gas in 2021 has been unstable and has risen steeply in some cases. So we see that energy security concerns in this case as an overcome environmental and pollution ones which caused the drop in previous years. Let's move to the trade side and OECD this time is the biggest exporter of coal, thanks to Australia mostly, but also the United States. However, looking at countries singularly, we see that Indonesia is the biggest exporter. They increased the export by far in the 2000s to surpass Australia in 2010 and then a bit of up and down and now again in the first position. And an important takeaway from this graph is that, similar to what we saw for production and consumption, it is an handful of countries which accounts for the vast majority of exports. Finally, looking at the coal sector, we talk about imports and OECD is as an aggregate the main importer, thanks to two important players which are Japan and Korea. However, in terms of single countries, we have again that China and India are the biggest importers. As we saw, they were also the biggest producer but as well the biggest consumer, so they need to import some of the coal to meet their internal demand. Also European Union, it's a significant importer of coal with Germany whose imports increased by 30% in the last year. Now that we finished this introduction about coal trends, let's look at the key concepts in terms of definition and coal balance. First of all, the product classification. So primary coal products can be distinguished and classified by their physical and chemical characteristics, as for example the carbon content, but also the levels of moisture, volatile matter, and so on. And obviously, these characteristics determine the price and the suitabilities for certain uses. On the left, you have a classification based on these physical and chemical characteristics, and it distinguishes between hard coal and brown coal. In hard coal, we have cooking coal, anthracite, and other bituminous coal, where the brown coal comprises sub-bituminous coal and lignite. And the difference between these two, it's often, let's say, recapped by the calorific value, which is higher than 24,000 kilojoule per kilogram for hard coal and below 24,000 for brown coal. However, on the left side, you can see that also the different types of coals can be classified by their use. In particular, cooking coal, it's also called metallurgical coal, because it's mostly used in iron and steel industry, both in the transformation processes in co-covens, but also downstream to power all the final consumption activities of the industry. Then we have anthracite, other bituminous coal, and sub-bituminous coal, which are called steam coal, because they use its prevalence for electricity and heat generation, especially other bituminous coal. And finally, we have lignite, that is the one with the lowest calorific value, also the cheapest of these coals, and as well it's often used for electricity and heat generation. Until now, I talked only about coal, but actually in this presentation and also in our questionnaire, we collect data on the broader concept of solid fossil fuels and manufacture gases. So here you have a more comprehensive list of all the products we consider, and on the left side, we have the five types of coal we saw before, and also other two energy products, which are oil shell and pit. Oil shell is a sedimentary rock from which you can extract oil, whether a pit is a sort of brown deposit, which resembles soil, and it's formed by the decomposition and accumulation of vegetable or organic matter. Now all these products on the left, so in blue, in the blue box, are primary products because they can be ionized from the biosphere, from the nature, let's say, whereas on the right side, in the light green and in the darker green boxes, you have the right secondary products and manufacture gases, which have to be indeed manufactured or transformed from primary products. Here a very comprehensive slide with the sum of the definition of these products, you have also this definition in the documentation of our database product online on our website of World Energy Statistics and World Energy Balances. I will not go through all of this, you can read them at home, obviously, but I want to highlight here what are the intake connections that we can see between coal products. So let me take again the laser pointer, you see that in the first column you have the seven products that we saw before, and then again secondary products here and manufacture gases here. So let's try to follow what is the evolution of cooking coal used and in which secondary products it can be transformed. So we have cooking coal, which is used in cocoa vents in the iron and steel industry and its transformation as outcome as cocoa and coke, coal tar and cocoa and gas. Cocoa and coke then again can be used in blast furnaces to produce pig iron, which is not an energy product, but as a byproduct of this process we have blast furnace gas. So it's very important to know also this intake connection also to check the quality of our data. For example, if we know that cooking coal input to cocoa vents is as decreased in some year, we would expect also that the outcomes, so cocoa and coke production, coal tar production and cocoa and gas production as decreased by a similar rate. Now let's look at the coal balance and what activities it includes. These are simplified flowchart and you start reading it from the left where you have the supply side and then we go on the demand one. First of all you have production which comes from mines or derived coal products from transformation processes of primary products and then you have also production from other sources which is some very specific case where coal can be derived some types of coal from waste piles but also from other products. So other questionnaires, there are some particular cases. After production we have trade, we have seen that and then stock building and stock drawing and then we go on the demand side where you have transformation of primary products into secondary coal products. You have energy industry on use that it's when some coal products is used within an energy industry process to supply the energy needs for this process. Then total final consumption in energy, so in industry transport and other sectors and also non-energy use so use of coal as feedstock and finally distribution losses which are more common for manufactured gases. So let's move to the first item of the supply side and which is production which can happen from underground, from surface mines which are most common and as we said before from other sources but that's very peculiar and a few cases. Now the important thing here to highlight is that the quantity reported in production has to be the one that it's already cleaned and already a marketable product. So after all the operation of removal for example of inert matter and any other type of small things. Another thing to remember is that in production we include also the quantity consumed by the producer in the production process which means for example to power the equipment in mines and this is because this amount will be then reported on the demand side in energy industry on use in coal mines so we have also to report them on the supply in order to balance them out. Moving to trade coal is indeed a very tradable products because it's easily transported over long distances either by ships and by trains and it's important to set the boundaries in terms of energy statistics for imports and exports so imports are the quantity of coal which entered the country for domestic use whether export is the coal which is domestically produced and then leave the countries and should be reported by the country that is using it internally. This means that transit trade is excluded. You have here below three scenarios that try to simplify or just to show some of the possibilities which are okay or not so okay let's say. A and B are a situation where we are fine in particular for country B if production is big in the export then it's likely that the export will come from production. For country C we have some problems because we don't have any production but we have imports and export so it is likely to be transit trade however there are exceptions that we consider and it involves stock change in previous years that then are depleted in later years for export or quantities of imported coal so which undergoes some treatments so in general what is our recommendation is to collect all the information possible not only quantitatively but also qualitatively on the provenance and the usage of this coal and then also with our help or with following the recommendations you can decide whether include or exclude these questionable amounts. Moving to the demand side there is a wide variety of transformation plans and processes so first one very known one transforms coal into electricity and heat and it's the use of coal into power plants then we have also transformation of coal into coal products which happen in co covens in blast furnaces and in gas works plants which produce flammable gas from coal and coal products and then you have also coal liquefaction plants which transform some type of coal into liquid hydrocarbons. Let's look more in details at some of these transformation processes and the first and more common example is the use of coal in electricity and heat plants to produce obviously electricity and heat. The average efficiency is 37% worldwide and it's important to know that because this is a reference for some quality checks that we can do on our data so it's always important to calculate this efficiency obviously as output divided by input in energy unit and see whether we are there obviously there are different ranges whether we are producing only heat or combined heat and power. Another important example is the one in co coven where you have a process of carbonization of cooking coal which is heated at high temperatures in an oxygen free atmosphere so it's transformed the main output is co coven coke but there are also some byproducts which are co coven gas and coal tar and the efficiency of this process is generally very high between 70 and 90% and again how to check that all the statistics collected are okay are good enough again trying to calculate the efficiency dividing the all the outputs products divided by the input in energy units. Now let's zoom out and have a look at the general picture of the iron and steel sector because this is very relevant in the coal balance it involves several processes on the demand side and it's important to differentiate and classify the use of coal products into these different processes correctly. Transformation inputs are highlighted in the darker blue arrows so we have a cooking coal used in co covens co coven coke used in blast furnaces but also sometimes bituminous coal used in blast furnaces through a method called pulverized coal injection which improves blast furnace performances and reduces also the cost. Then you have some quantities of the derived byproducts for example you see them at the top co coven gas blast furnace gas and oxygen steel furnace gas that I will explain briefly later on but anyway these gases can be obviously collected and then reused in co covens and blast furnaces to provide energy to these processes you see that in light blue their reporting will be in energy to the industry on use and then you have also some processes which happen downstream which involves generally non-energy products and in that case steel they will need the energy to be driven and so also some coal products can be used there to provide energy and that will be final consumption in iron and steel industry. So in the black arrows or from the black arrows you will see energy products some other here and not energy products as iron ore and pig iron and here you have some efficiency that help you in checking the quality of your data and also the classification for iron and steel industry processes according to international standard for industrial classification. Now that we dealt with the coal products classification and the elements of the balance let's see how this knowledge is turned into data statistics at the IA with your collaboration in particular in particular sorry we will have a look at the data collection and validation in the joint IA at Eurostat annual questionnaires. First of all data collection can come from different sources there are surveys given to companies and enterprises which generally will have a precise accounting of the coal that they produce or that they purchase for some of the uses industrial uses for power plants and so on. Then you will have also surveys to households in order to understand more in details what is the final use of coal even though for coal there are not many different choices either there eating and cooking actually as final uses. Then administrative data which are generally collected for non-statistical purposes as for example to check whether the implementation of a certain policies is going into the right direction. An example of this data is trade data that are collected by the customs office. You can have direct measurements you can have data from other sources national international school association and finally in case you are not able to collect some data there is also the possibility to estimate or model them as for example if you are not able to collect the blast furnace gas production you could estimate that following the iron production or the input of cocoa and coke into the blast furnace. You see here many examples that's just to show you that data collection is really a recollection excuse me for the repetition but a recollection of information from several different sources with supply and demand data which rarely come from the same source so this is why it is possible that data do not match on the supply and demand you can have statistical differences. Now look at the IA questioner you have four main tables the flow tables which have singular commodity balances of every product one by one one next to each other and then all the flows in the row dimension we will see that more in details in a moment then you have inputs and export tables and then you have the calorific value table which is very important and it's for every product but the one that are already collected in energy units as it is the case of manufactured gases then we have also additional 17 products tables so one for each product where you have basically all of these four tables that we saw before one after the others and with the time series so very important first of all the flow table as you can see here let me use also the pointer each column is the commodity balance of a product and each row it's a flow so it's an origin or a use of a certain product you see here the supply block so then you have transformation final consumption and so on you see the cells in yellow this is a particular formatting of our questioner and shows all the values that are different than the pre-filled values so that can be either the inputs for the current years which were zero in the pre-filled questioner or the revisions for previous years this is inputs by so it's an export by destination tables and I want to show you just something here in case you don't know what is or we don't know what is the imports and the exports for some quantities of coal there is a row called not elsewhere specified where we can put the the amount that are left let's say finally very very important the calorific value table where you have different calorific value for each flow let me zoom and show you are there be two means called example which is very interesting because you see that there is a certain calorific value for production and then it's the same calorific value for export so we can already deduce from this table that export come from the production the quantity of coal produced domestically by the country and then you have a different calorific value for imports which is the weighted average of all the imports from the different countries and finite uses will come mostly from these imported quantities here this is one example of a table of a single product and twilight here is that you have the time series in this in this format so you can see the evolution of the data over time finally you have also the remarks page which is very important especially for us because here you can provide additional information about complicated processes or specific situation which apply to your country and finally another small thing to show you is the check data button in the menu worksheet by clicking that and selecting the year you can run some simple but also fundamental arithmetical inconsistency checks within the questionnaire now we saw that consistency is very important in the questionnaire but also with the other questionnaire in general with the reporting of statistics for other fuels so there are many things to check for example the efficiencies in the iron and steel industry transformation processes and some other let's say consistency between table imports and exports in table 23 with table one and also with other questionnaire for example the inputs to electricity and heat power plants this is a quick example let me let me go quickly over this because we are at the end of the presentation but this is an example of how the data between the coal and the electricity questionnaire do not match so let me magnify this the quantity in kilotons so in physical unit matches between the two questionnaires but then the quantity in energy so the fuel input in terra gel will not match if we multiply the physical unit in the coal questionnaire by the calorific value so there is a difference in the fuel input in terra gel between the two questionnaires which will lead also to a difference in the efficiency of this power plant because here we are depicting a process of a main activity producer electricity so when the data do not match then it's important to let's say question a question this data and see how you can make consistency between the two different fuels to conclude if you want to learn more about AI energy statistics we provide the manual for free obviously on our website but there is also you can also find the United Nations international recommendation for energy statistics which is the let's say general which gives the general guidelines for energy statistics reporting and also on our website you can find specific information about the coal questionnaire that I show you with a template of the questionnaire and the reporting instruction and finally an overview of the vast amount of datasets that we produce some for purchase but the vast majority is for free on our website and all the energy statistics that we collect you see that on the right side feed the many the many analysis and reports that the agency makes and that are available for free on the website so thank you very much let me keep this thank you very much for your attention so it's now time for questions thank you very very very much thank you very much for the comprehensive presentation you've just made I'm looking at the chat I don't see any particular questions that have been raised at the moment but I would encourage people to to ask questions either in the chat now or by raising your hand or of course you can send them by email at the end we do have a few minutes for four questions and since I don't see any at the moment maybe I could take the liberty of asking you a question Nicola you have been dealing with cold statistics for quite some time now at the agency what are the key issues you find when receiving questionnaires from colleagues what are some of the typical errors you find and you would like countries to improve on when they are speaking data to us thank you very much Julian indeed there are some some points that we can stress and I think this slide it's interesting but also the slide about for example cocoa beneficency I can show that in a moment so I think that it's important to see the interconnection between primary and secondary products in the cold questionnaire so if you have an input of a primary product in a transformation process then you need also to have an output and this the ratio between output and input test respect more or less a range of efficiency that for example we give as indication in the reporting instruction so I think that's that's something obviously it's sometimes it's difficult to collect some of the the outcome of transformation processes for example in terms of gases but this I think it's it's really important to recognize what are the interconnection because these are very useful to check the quality of of your data for example in cocoa beans very important to know that the efficiency is between 70 and 90 percent and has to be has to be that so when we collect all the statistics on the outcome and we know the input we can we can check or we could estimate either the input or the output if we have certainty about one of the two but we are not able to collect the others and if you let me I think what's another important point it's about trade of coal here it's production and trade so it's really important here to exclude transit trade so really to know what is the destination of the coal which is imported by a country for domestic use or not and well on the exporting side I think it's not always easy to to know whether the coal that you are exporting it's ending in the final decision countries or not but it's important at least for the custom office or for actually the statistician dealing with the statistics from the custom office to know what are the definition in in energy statistics