 to show our working on, for example, how estimating special temporal dynamics of solid waste by coupling the material flow analysis into a graphic information system. So again, I'm an assistant professor working with Dr. Wicheng Chen. She's a background in the industry of ecology and actually my background is mostly focus on GIS, remote sensing and urban ecology. So what we do is try to combine special analysis and material flow analysis to estimate not just material, so of course the floors, so the waste generation is belongs to the waste floors. So what we have done is based on this, like urban data, and then we try to build a simulator, so-called, to estimate and simulate material flow and stocks in cities. So in this city simulator, it could be, in your computer, it could be a virtual reality, it could be a three-dimensional cities, and for each building, maybe we know the year of build of that building in that situation, we can simulate or understand urban dynamic, right? So maybe in that step, we try to understand the building's mentality that we can understand the building or city can provide what kind of functions and services for its citizens. So based on this situation, the first case, in Shaman case, we try to understand the construction and material stock in buildings. So based on the material stock analysis, it's normally like this that material stock equals to the total area of each building times the material intensity for that building, and we do that in Shaman cases. It's located in the southeast part of China, and across the sea is Taiwan Island. And for downtown part, Shaman, we have two islands. The bigger one is called Shaman Island, and the smaller one is called Glanzo Island. So based on that material stock analysis, we try to estimate, for example, the total 4.7 million tons of steel and about 25 million tons of breakable storage in Shaman's buildings. It's the whole picture, and let's look more details in that. For example, from high view, it would be standing on the top of Glanzo Island and watch the Zhongshan Road and the downtown part of Shaman Island, you will watch this. So the bottom is the virtual reality city in our computers, and the upper picture is the real snapshot when we're standing on the top of Glanzo Island and watch Shaman Island. You can find the contrast to buildings high, first, probably the image, the flat buildings on Glanzo Island and high buildings that's bigger on Shaman Island. So that's the normal high view part. So if we move our perspective from what we can see to a stock view of EU's building and find the gap between these two islands was wider, because most of the buildings on Shaman Island is belongs to the reinforced concrete structure. So we use huge amounts of steel to build them. But on Glanzo Island, its buildings belongs to the brick concrete structure. So we use huge of the brick to build them. So that gap was filled in these pictures. So that's why from the brick concrete buildings, they usually have not very high end, but the brick intensity is very high. So material intensity is very high. But reinforced concrete buildings usually have very high value in height, but lower value of brick intensity. And in contrast for those EU's steel perspective, brick concrete buildings usually have lower values of height and steel intensity. But reinforced concrete buildings usually have a higher level of high intensity. So that's why the special patent of the EU's steel shows more special to the United than the patent of the brick stock. So beyond the stock part work, we also want to simulate slopes. The output force is like to generate waste, especially. So we do the Dumba case to estimate the E-waste in this part. So again, we use the big data, or the urban quality and the geographic information system try to estimate the E-waste generation in Dumba city. So we also simulate, for example, the EU's stock purchase or the waste generation in Dumba in temporal scale. And of course, we also have the special temporal dynamics of the TV waste generation, for example, from 2020. So that's the E-waste for household. If you have temporary in your home, you may buy a new one, or you may charge it. Maybe that's to generate that special different patent of the US generation. So beyond these two cases, that's our background. So we also want to do a more comprehensive case in for Beijing, for example. So that's why we choose corporate waste poll in this city. So with that part, I can give some first big picture and general information for you. And that's the waste generation in Beijing from 2013 and 2017. So let's see the industrial waste first. It looks good because the industrial waste include in the hazard waste and non-hazard waste decline from 2013 to 2017. And for medical waste, it increase and keep increasing from 2013 to 2017. But the total volume of the medical waste is not too much. So maybe it's a problem, even maybe they have more serious environmental pollution on soil, water, or air. And a rough estimation of the construction waste and agricultural waste generation in Beijing is about 23 million tons in 2017 and about 3.5 million tons in 2017. But it's not from the annual report of the government. It's our rough estimation for Beijing. And a big problem in Beijing is the household waste or domestic waste. You can find this tendency. It's keep increasing from 2013 to 2017. And it seems like it will keep increasing in the future. And the total volume is reach 9 million tons in 2017 to keep increasing. So it's a very big problem. So beyond the total volume numbers of that part of Beijing, so we also want to know what is where to come and where to go through. So for waste drop size, we believe too many in Beijing is rather than in Cape Town. So we do not collect that information. So we just use the Cape Town picture instead of it. But we collected the waste transportation, part of the waste transportation in Beijing. That source is the Beijing Municipal Administration Committee. And we recognize the name of that and recognize on the Bible map and try to find the longitude, latitude, and geo information, so in the map software. Of course, the final destination of the waste is the waste treatment facilities. We also collect that information. There's about more than 20, even 30 treatment facilities located in Beijing. And also this trash was be treated by three main types. So parts of them, about one third by land view, and one sixth by compost, and about another half will be by burn. So it's from this logical, it seems like we try to trace the waste from whole life cycle, especially in space that we are very good at. So from this, we got the information from the generation of the waste, then drop off, then transfer, then treatment. Even in this cycle, parts of waste could be reused or recycled. So that's where we done. But any data in Beijing, if you can share with us, we appreciate it, because not just waste, because waste is just the topic of this conference. And just like Tosan, any environment, social, economic data, even more knowledge from the journal articles reports. And this is, if you can share with us, it's great to appreciate for that. And next, every part of this Beijing data, we have uploaded on the platform for the metabolism of cities. So you can add this, right? So different for Cape Town sectors, we just have the waste part. We invite people to check it out. So for waste sector, just like the Cape Town has done, we also have just like the whole cycle, whole life cycle of the waste, we have the waste generation, waste transfer, and waste treatment, and parts of the policies and regulations for that. And of course, the total volume of waste generation for Beijing has uploaded, just like what I have shown, including the industrial waste, medical waste, construction, agriculture, and household waste. And then we also upload the geo-information about transfer stations and final treatment facilities. Of course, you can check the capacity of these facilities, like it's stream, waste by burn, by compost, or by landfill, and their stable capacity of this capacity also have uploaded, so yeah, thank you.