 Okay. I'm going to close the waiting room and admit all. You are online. Hello. Hello everyone. It was nice to have you back after the lunch and let's wait a little bit for the... I mean, hopefully some people will join and then we will start. I didn't get lunch, not yet. Well, I say that welcome back after the lunch break because having people after lunch is difficult sometimes. So welcome back and yeah, and so let's wait a little bit so we get some more people and then we will start with a scientific presentation. Amna, do you hear what I say? Maybe the signal was not good, so please repeat. I say I didn't get lunch. Oh, you didn't get your lunch. Okay. It will be after. Okay, so let me share with you the screen. You all have. Okay, I guess we can start right now. So for the afternoon session is going to be starting right now from 2 to 430, which is divided into two parts. The first part is going to be a scientific presentation. So we have a three speakers and then after that we have a breakout rooms where it's about one hour and it's going to be divided into four groups, which will going to be divided automatically. So you will be automatically being moved to one of the group where they are going to discuss about the African physical society future and also about the different activities that we can have. I mean virtual meetings and so on. So for now we're going to start with the first speaker which I'll sign. And so please, the floor is yours. Hello, do you hear me? Yes. So you can go ahead and share your screen. So remember you have a 20 minutes for the presentation and five minutes for question and answer. Yes. Thank you very much. I'm not. Thank you very much. Good afternoon, everybody. I'm very pleased to be here with all these scientific people. My name is Alison Traore. And I'm based at the university here in Dakar and I'm a lecturer at the physics department. So I'm very glad to have a chance to share my work in Dakar and with this very nice audience. So my talk will be based on source apportionment and air quality assessment of particulate matter regarding aerodynamic diameter of 2.5 and 10 in a two different sites in urban background area here in Dakar. So we know from the researchers that relate to ambient, it's remained very relative today due to the adverse effect of PM. Please share your screen. Your slides. You have to share your screen. Maybe, maybe I think I'm not have to give me the screen. No, I already switched it off. So you just have to share it as you will did it before. Do you see it now? Yeah, it is starting. Yeah. Okay. Okay. Let me just check. Okay. I was saying at the beginning that my talk will be based on of PM 10 and PM 2.5. And this work was based on the was based on two sites in urban background area here in Dakar. So we know from the from this research related to ambient air. Okay, this research related to ambient air is very, very, very, very scarce. There is no more. There is no lot of articles based on results got here in Africa. So I will be talk on air pollution monitoring regarding the chemical composition from many different emission and the contribution. So this type of work was done here in Dakar has already taught and we will see for a couple of minutes how we perform the work and what was as an assessment. So based on the report from the World Health Organization, we can say that each year we were about 6,800 new case of cancer. And for this 6006,800, we can say almost 5000 days are record and this 5000 days, we can say long cancer and Lawrence cancer are occupying more than 200 days per year. So I think it is more, it's very urgent to see how we some idea, clear idea about the origin of this cancer based on what they record in in the last report. So to do so, we have first full to see, sorry, to see how many sources we have found here in in Senegal because most of the time people they say we have one sources in Senegal based on the Saradas and based on this research we will see how many sources we can find in Senegal in front of that how many contribution it will make to affect this kind of environmental risk or environmental health. So as you can see here, we can find heavy oil combustion like like a source. Vehicle none exist and exist and biomass burning or for each of these sources, we have to see what is the contribution of elemental composition or carbonic composition organic carbonic composition on filter which will be collected during the whole year between 2018 and 2019. Depending of the geographical localization and location and the characteristic of any area, many anthropogenic and the natural source may contribute to 2pm concentration. So we will see in the next slide how we can make a choice about the site and try to overcome this problem in Dakar. So we have choice two different site mostly they are urban urban site. The first one is your view of is a site which is so close to the sea to the Atlantic sea. And there is another site which is called Ashlam and Ashlam is so close to an industrial zone and very crowd people. So we make this choice to be able to check carefully how this density is correlated to the activity of people and how it can affect nearby the habitat. So to do so we have used different type of sampler. The one we have used is what we call Ghent sampler. It is a dichotomous sampler which is able to collect a particular matter. In top of that we collect also what we call black carbon and all these three components are collected within a nuclear carbonate filter and we use two different type of activity related to the days. For example for one week we use one day one working day and one day from weekend and we do the same for the both site and at the end of the year 2009 we were able to collect more than 216 samples related to the year because we know for each year we have 52 weeks and by 52 weeks by four we can get 216 samples per year. Here we can see how many filter we collect for the whole year and based on this data we are able now to see how we can reduce the particulate matter level in the country. So we know so far that PMR identify has a real and serious concern as I already told and the impact of this particulate matter environment and health is in concern. So it is very necessary to identify PM 10 and PM 2.5 and try to estimate their influence on ambient air. To do so we need to do only one thing we need to achieve by performing what we call social apportionment to identify PM sources. So to identify PM sources we need to have some tools and based on that tools we can be able to PM 10, PM 2.5 and black carbon on filter. So how we are going to make it we need to collect this air particulate matter on filter and to wait this sample before and after the collect and to try to see the mass of deposits particulate matter. So after this deposition we use what we call different type of method for source apportionment and based on this study we use two different type we use what we call transport models and receptor models. So based on these two source apportionment methods, we were able to know and to quantify the contribution of each polytank source. We also use techniques we call x-ray techniques x-ray fluorescence techniques and this x-ray techniques allow us to know the composition in terms of elements and to know also the quantitative let's say the quantitative amount of elements which are in each source. So after analyzing this filter we are able to see how this source correlate with PM 10 and PM 2.5 can show the contribution of different sources which are responsible of the So we correlate this work with different type of works performed in the same times and using the same methodology. And we are different country which are looking for the same results. Here you can see different country Ghana, Morocco, Tunisia, Cameroon, Kenya, Ivory Coast, DRC, Congo, Algeria, Madagascar, Sudan. So for one year measurement we are able to see what was the amount of mass concentration in terms of PM 2.5 and also in terms of PM PM PM 10 and we can see for 24 hours and for the whole year measurement. Most of the country were verified from the threshold. To measure the amount of black carbon in filter, we have used what we call Mabit instrument. It is a multi wavelength absorption black carbon instrument and this server to be able to know where is where come from the black carbon and also to be able to know what is the amount of black carbon on each filter. I want to remind you that you have five minutes. Okay, black carbon is the term that is used depending of the source of the pollution. For the use of positive matters factorization analysis, we were able to identify and each sources based on the amount of PM 10 PM PM PM 2.5 and also based on the amount of each element related to each source. By doing so, we have an Excel sheet which gather all the in terms of quantification and also to see the contribution of different type of sources based on their amount for each filter. So we were able also to have the contribution in terms of elemental analysis and based on these reasons we are able to know how contribute and how we can define the fingerprinting of this area based on each factor we have found. During this study, we have found four different type of sources based on the results and the four cities were mineral dust sea salt, which is combined with secondary sulfate traffic emission and industry emission. So all these four components were quantified and we were able to do what we call reconstruction from Sahara dust for source contribution. In the next slide, you will see how we perform this source profile and what was the trend of this results based on the black carbon and the elemental composition of each filter during the whole period of the measurement. We also perform what we call trajectory analysis and long range transport to be able to quantify the air mass background, but trajectory arriving to the site we have choice and we were able to see by using two different model open air package and the the National Oceanic and Atmospheric Administration High Split Model 4 to quantify the provenance of PM 10, PM 2.5. Here we can see in HLM, PM 2.5 mostly from and PM 10 are mostly from the Sahara. So from Mauritania and around. So we can see how these results can and how we can do quantification of the impact of these results. We use these results to help our authority here in Dhaka in terms of what we call urban mobility program, which is a kind of promoting air quality to be able to renewable our public transport felt and also we use these results to be able also to help our policymaker for to draw and to implement a new road and infrastructure here in the capital. Do you have one minutes only to wrap up wherever you are. I am. If you are interesting to do. I am almost done. Okay. Okay. Well, we also use this data to to see how we can actually to actually help the government to organize and to to redraw. The results we have carried out on such apportionment. So what it was what I have to present for this afternoon and I'm very glad to be with all this audience. Thank you very much. Thank you for the interesting talk and if someone interesting or have some questions, please go ahead and write it in the chat or raise your hand. No questions. I see some of the participants are interesting to collaborate with you because they work similar to what you are doing. And I have just one question is like, did you also look for the area which is very close to the urban background? I mean, you are looking to the urban background of some area in Senegal. But did you try, for example, to look to the area around because maybe they have some effect from from the other side as well, or you are just focusing in a specific area. The research we have performed is not we have, you have to decide which area you're going to do your, your, your, your measurement, your sampling site. But this, this, this have to be done based on the environmental condition. You have to know the humidity, the, you have to know the wind direction. And if it is on the wind direction like a rose wind, you, you, you will be able to track a potential source, and also to track source from transbandering transportation of air mass. So it was not local one, but it was, it was a big, big area for for sampling. And what is the control experiments that I mean as a samples, because you are making sampling for the, for the urban background area but how about the control to know what you are measuring it is exactly what is going on there. So to do so you have to go to the positive factor mattress by using the EPA for it is a kind of open source. You have to make a choice about which type of source you want to control, and it will give you what we call the factor contribution, and based on the factor contribution you have to assign, you can say this, this area, this area is polluted only for anthropogenic activity, or there is a kind of natural background area, which come from the, the cluster for example. So, for that you have to do what we call speciation by using one formula from coin. Interesting. So we have a time for one quick questions if someone is having something. Okay, we want him. I just want him to say some acknowledgement for this work. Do you hear me? Yeah, I heard very well you, Professor. Hello. Good afternoon from Nigeria, please. I cannot see where to raise my hand that is why I'm asking directly. Can anybody hear me? It's no problem. Yeah, you go ahead. Okay, please. What I'm looking at is I have worked with a particular matter for a region in Abuja, Nigeria, and one of the problems I got or I experienced during that work was how to colorate with different seasons. Like, I don't know which season the presenter worked with, because what I did was during the dry season, I experienced a lot of slow emission of the particulate matter. While at the dry season, the admission was very, very high. So I, I try to see that if such a work is done, then consideration of season could really help to pop solution so that one could be able to know that seasons and different weather conditions could have an influence on PN. So I don't know, please, a presenter, if you can do that. And also, if you can also refer me to a tool that can do an intensive differentiation of the season. Thank you. Maybe you can answer him very quickly or you can just in the background privately discuss it if you think it will take time. No, it will not take time. Okay. Thank you. Thank you very much. Have this data. We have also the we have performed the same thing because we do this sampling over the over the year. So we have tried to categorize the impact of Hello. Hello. It seems that he has some problems. 2.5 and PM 10 is a bit higher than you meet time or a cold time is true. We also perform this kind of Let's say measurement and we have the results. Okay, interesting. So let's thanks again, Alsania, and we move to the second talk and you can share your screen. So the second talk is going to be with the speakers mail