1 00:00:01,260 --> 00:00:14,640 Good afternoon, I'm Alejandra Cituno Pedraza, and today I'm going to give you a presentation on my project, Pollution in Madrid, a comparison between the data from 2019 and 2020 during the Estado de Alarma period. 2 00:00:15,039 --> 00:00:20,449 To begin with, I'll tell you about the index of this presentation. 3 00:00:21,710 --> 00:00:24,929 Firstly, I'll start talking about the problem I recognized. 4 00:00:25,870 --> 00:00:28,710 Secondly, I will keep on talking about my hypothesis. 5 00:00:28,710 --> 00:00:36,009 Later on, I will talk about my experiment, explaining the tools used, and the methodology. 6 00:00:36,009 --> 00:00:41,369 In fourth place, I'll explain the analysis of the results, showing you the data and graphs 7 00:00:41,369 --> 00:00:43,049 obtained. 8 00:00:43,049 --> 00:00:48,310 After that, I will show you the conclusions obtained, which include comparisons with last 9 00:00:48,310 --> 00:00:52,070 year's values and the reality of the situation. 10 00:00:52,070 --> 00:00:56,789 And finally, I will talk about what should we do from now on, and I'll show you the 11 00:00:56,789 --> 00:01:06,150 bibliography used. Now, I'll start talking about the recognized problem. As it's 12 00:01:06,150 --> 00:01:12,450 widely known, pollution is a huge problem in big cities, like for example, Barcelona 13 00:01:12,450 --> 00:01:19,209 or Madrid. In Spain, there were more than 10,000 deaths every year due to 14 00:01:19,209 --> 00:01:25,049 pollution, and in total, 4.2 million people have died all around the world 15 00:01:25,049 --> 00:01:33,209 due to this problem yearly. There are several pollutants, but the most 16 00:01:33,209 --> 00:01:41,250 dangerous ones are the following. PM2.5 and PM10 particles, whose names 17 00:01:41,250 --> 00:01:48,829 come from their size in microus, cause generalized health problems. Ozone causes 18 00:01:48,829 --> 00:01:56,269 respiratory problems. Nitrogen dioxide increases defects of asthma, and sulfur 19 00:01:56,269 --> 00:02:04,650 dioxide, respiratory and eye problems. As all of us know, the world has been in 20 00:02:04,650 --> 00:02:12,729 trouble since the 17th of November 2019, when the first COVID-19 patient was 21 00:02:12,729 --> 00:02:21,389 diagnosed in China. On the 31st of January 2020, the first COVID-19 patient 22 00:02:21,389 --> 00:02:30,189 was diagnosed in Spain, in La Gomera Island. On the 11th of March 2020, the World Health 23 00:02:30,189 --> 00:02:39,949 Organization declared COVID-19 as a pandemic, and on the 14th of March 2020, we've been in 24 00:02:39,949 --> 00:02:49,469 estado de alarma situation in Spain. COVID-19, a highly infectious disease that has spread all 25 00:02:49,469 --> 00:02:56,509 over the world forced the Spanish government to declare the Estado de Alarma, creating a lockdown 26 00:02:56,509 --> 00:03:05,310 situation all across the country. Everything stopped. Cars, industries reduced their capacities, 27 00:03:06,430 --> 00:03:14,889 commerce and even mobility were reduced, and teleworking was widely implemented. 28 00:03:14,889 --> 00:03:21,770 This has left us with some images like the following ones. Some of them, the black and 29 00:03:21,770 --> 00:03:28,889 white ones, are from a photography collection in Reina Sofia Museum and the others from local 30 00:03:28,889 --> 00:04:14,639 newspapers. So this is where my hypothesis has to be stated. I definitely think that pollution might 31 00:04:14,639 --> 00:04:23,920 have lowered a lot due to the decrease of transit and economic activity now i'll talk about my 32 00:04:23,920 --> 00:04:32,720 experiment the tools i used were several spreadsheet documents and madrid's council 33 00:04:32,720 --> 00:04:42,360 air quality portal and the followed methodology was the following i took day-by-day data from 34 00:04:42,360 --> 00:04:50,759 three stations next to my neighborhood three times a day on rush hours 9 a.m 2 p.m and 9 p.m 35 00:04:52,199 --> 00:04:58,839 then i introduced this data in the spreadsheet document and i compared this with the one from 36 00:04:58,839 --> 00:05:07,879 last year at this time period and this is the analysis of the results where you can see in 37 00:05:07,879 --> 00:05:14,360 more detail. The data and the graphs much on if you are interested as it is 38 00:05:14,360 --> 00:05:21,259 uploaded on the aula virtual. These graphs are from Parque Enrique Tierno Galvan 39 00:05:21,259 --> 00:05:27,500 which correspond with Mendez Alvaro station in Madrid's council air quality 40 00:05:27,500 --> 00:05:36,860 portal. This is the nitrogen dioxide graph in Enrique Tierno Galvan park and this is the 41 00:05:36,860 --> 00:05:47,120 average comparison of nitrogen dioxide during the years 2019 and 2020, where a decrease 42 00:05:47,120 --> 00:05:51,860 of 44% can be seen. 43 00:05:51,860 --> 00:05:59,040 This is the PM2.5 graph of Enrique Tierno Galván Park. 44 00:05:59,040 --> 00:06:07,779 And here, in this comparison between the years 2019 and 2020, an increase of 12% can be seen 45 00:06:07,779 --> 00:06:11,220 in PM2.5 values. 46 00:06:11,220 --> 00:06:19,199 This might be because in 2019, there were much less measurements due to technical problems. 47 00:06:19,199 --> 00:06:26,379 This one shows the values of PM10 particles in the Wikipedia Level 1 part. 48 00:06:26,379 --> 00:06:41,550 From the 2019 and 2020 average values of PM10 particles, a decrease of 6.6% can be seen. 49 00:06:41,550 --> 00:06:49,790 The following graphs correspond to the data obtained from Barclay, which corresponds to 50 00:06:49,790 --> 00:06:55,009 registration in Madrid's council air quality portal. 51 00:06:55,009 --> 00:07:00,250 This is the nitrogen dioxide comparison graph. 52 00:07:00,250 --> 00:07:08,410 Comparing the averages of both years, we can see that in 2020, there was a 41% less nitrogen 53 00:07:08,410 --> 00:07:12,379 dioxide impact than in 2020. 54 00:07:12,379 --> 00:07:20,379 This is the ozone levels graph, and the averages comparison of both years shows a decrease 55 00:07:20,379 --> 00:07:25,240 of 7% in ozone levels. 56 00:07:25,240 --> 00:07:32,319 And finally, here we have the data from Casa de Campo, which corresponds to Casa de Campo 57 00:07:32,319 --> 00:07:38,310 station in Madrid's air quality portal. 58 00:07:38,310 --> 00:07:42,689 This is the sulfur dioxide graph. 59 00:07:42,689 --> 00:07:52,769 And this is a comparison of the averages of the levels of sulfur dioxide of 2019 and 2020, 60 00:07:52,769 --> 00:07:56,750 where we can see an increase of a 16.6% 61 00:07:56,750 --> 00:08:00,089 in the levels in Casa de Campo. 62 00:08:00,089 --> 00:08:06,170 On this slide, we can see the levels of nitrogen dioxide 63 00:08:06,170 --> 00:08:08,470 in Casa de Campo. 64 00:08:08,470 --> 00:08:17,689 Nitrogen dioxide levels were reduced in 46.5% during 2020. 65 00:08:17,689 --> 00:08:24,149 Here we can see the PM2.5 particles levels. 66 00:08:24,149 --> 00:08:34,629 We can also see here that PM2.5 particles decreased in a 2% during 2020. 67 00:08:34,629 --> 00:08:40,289 This is the graph of PM10 particles. 68 00:08:40,289 --> 00:08:51,090 On this slide, we can see that the levels of PM10 particles decreased by 9% during 2020. 69 00:08:51,090 --> 00:08:56,409 This graph shows the ozone levels in Casa de Campo. 70 00:08:56,409 --> 00:09:03,730 And finally, on this slide, we can see the aritest comparisons of ozone in Casa de Campo. 71 00:09:03,730 --> 00:09:11,149 In 2020, there was a 21.6% less ozone in Casa de Campo. 72 00:09:11,149 --> 00:09:15,129 And now, the conclusions. 73 00:09:15,129 --> 00:09:24,190 I decided to check the average difference of each pollutant between 2019 and 2020. 74 00:09:24,190 --> 00:09:34,990 During 2019, the average NO2 values were around a 27.4 micrograms per cubic meter, which is 75 00:09:34,990 --> 00:09:45,629 very low compared to the WHO healthy limit of 40 micrograms per cubic meter each hour. 76 00:09:46,830 --> 00:09:58,429 But on 2020, we had around a 15.48 micrograms per cubic meter, which means a decrease of 43.53% 77 00:09:58,429 --> 00:10:06,049 percent compared to the values of 2019. Something similar happens with ozone 78 00:10:06,049 --> 00:10:13,190 levels in which we could see on 2019 an average of around 66.55 micrograms 79 00:10:13,190 --> 00:10:18,649 per cubic meter which is down below the 100 micrograms per cubic meter per 80 00:10:18,649 --> 00:10:26,190 hours that the WHO sets as its healthy limit. On the other hand, during 2020 81 00:10:26,190 --> 00:10:36,049 there was a decrease of a 14.57%, meaning this a 56.86 micrograms per cubic meters in average. 82 00:10:37,250 --> 00:10:46,389 During the year 2019, sulfur dioxide values remained at around 4.3 micrograms per cubic 83 00:10:46,389 --> 00:10:55,730 meter. During 2020, these values increased, meaning around 5.03 micrograms per cubic meter. 84 00:10:56,190 --> 00:10:58,950 having increased by 16.60%. 85 00:10:58,950 --> 00:11:08,889 Still, this is higher than the 20 micrograms per cubic meter per hour established by the WHO as a help. 86 00:11:08,889 --> 00:11:18,830 During 2019, the average levels of PM2.5 particles were around 6.31 micrograms per cubic meter. 87 00:11:19,529 --> 00:11:28,190 During 2020, this amount raised by 4.87%, meaning a total of 6.62 micrograms per cubic meter. 88 00:11:28,269 --> 00:11:37,669 which is still below the 10 micrograms per cubic meter per hour limit of PM2.5 particles set by the WHO as healthy. 89 00:11:38,830 --> 00:11:52,129 Talking about PM10 particles, we can see that in 2019, there was an average level of these particles at about 11.05 micrograms per cubic meter. 90 00:11:52,129 --> 00:12:02,990 During 2020, these values were decreased by 7.85%, ending up with around 10.18 micrograms 91 00:12:02,990 --> 00:12:04,889 per cubic meter. 92 00:12:04,889 --> 00:12:12,309 These values were both still below the 20 micrograms per cubic meter per hour set by 93 00:12:12,309 --> 00:12:16,200 the home limit. 94 00:12:16,200 --> 00:12:23,299 In order to try to understand how much pollution had decreased during this time period, I decided 95 00:12:23,299 --> 00:12:29,860 to do an average of all the values that I got through this process and I decided to compare 96 00:12:29,860 --> 00:12:37,460 them with the ones from 2019. I got that the average level of pollutants during this last year 97 00:12:37,460 --> 00:12:46,500 was around 23.128 micrograms per cubic meter, while during this same period of 2020 98 00:12:46,500 --> 00:12:52,179 we could find a decrease of an 18.57%, 99 00:12:52,179 --> 00:13:01,909 which left us with an average of 18.834 micrograms per cubic meter. 100 00:13:01,909 --> 00:13:06,070 But in reality, what happens is that the WHO 101 00:13:06,070 --> 00:13:10,710 limits are high above the real values that endanger people's well-being and 102 00:13:10,710 --> 00:13:13,909 health, but it is not possible to reduce them 103 00:13:13,909 --> 00:13:21,110 for now due to country's legislation. So still, these values have to be lowered. 104 00:13:23,029 --> 00:13:32,009 So, what should we do from now on? I personally think that the biggest solution is in improving 105 00:13:32,009 --> 00:13:37,690 R&D, since with that, we could find more efficient methods of transport, 106 00:13:37,690 --> 00:13:45,509 industries and methods of consumption of renewable sources of energy. Examples could be the 107 00:13:45,509 --> 00:13:51,909 development of better and more affordable electric vehicles such as electric cars, 108 00:13:53,669 --> 00:13:58,470 electric motorbikes, and even electric airplanes. 109 00:14:00,549 --> 00:14:19,289 Better and more affordable renewable sources of energy and reducing the consumption of plastics. 110 00:14:19,289 --> 00:14:25,850 In short, change your lives. 111 00:14:25,850 --> 00:14:42,740 And finally, this is the bibliography used. 112 00:14:42,740 --> 00:14:45,320 This is the end of my presentation. 113 00:14:45,320 --> 00:14:46,659 Thank you for your attention.