Remote Sensing Observations for Air Quality Applications

0:01 Speaker 1: I'm an assistant research scientist, also working at the Goddard Space Flight Center and employed by Morgan State University through the cooperative agreement called GESTAR.

0:19 Speaker 2: Dr. Carl Mallings is also a scientist and assistant scientist at the Goddard Center at NASA. and is employed at Morgan State University as a contractor through a company called Guestar.

0:44 Speaker 3: My name is Didier Designeaux, working for Environment and Climate Change Canada, and I also have the role of Health Focal Point for the World Meteorological Organization. And I'm here because during the AMERICEO air quality session, I presented a collection of examples on how bird observation is used for health applications in the federal government of Canada.

1:25 Speaker 2: El próximo panelista es el doctor Didier Davignon. Él trabaja en Canadá en el programa del ambiente y cambios climáticos. Y también es la persona de contacto en el programa mundial con la Organización Mundial de la Salud World Health Organization did you say?

2:06 Speaker 3: Meteorological Organization.

2:09 Speaker 2: I'm sorry. Perdón. Él es el punto de contacto relacionado a la salud con la Organización Meteorológica Mundial, el World Meteorological Organization. Y él presentó durante la semana de Amerigio sobre el uso de datos de modelos y satelitales para ver la calidad del aire en Canadá. Y finalmente, yo soy instructora con, soy científica en el laboratorio de propulsión a chorro de la NASA y también soy instructora con el programa ARSAT. My name is Erika Potest. I am a scientist at NASA's Jet Propulsion Laboratory, and I am also an instructor with the RSAT program.

3:06 Speaker 2: All right.

3:08 Speaker 1: Thank you very much, everyone, and thank you, Erika, for the translations. So we'll now transition to the question and answer session. We've received several questions already. You can see them on the document on the screen now. And we'll go through those questions and read out the answers, first in English, and then Erika will provide the Spanish translation.

3:41 Speaker 2: Okay. Entonces, vamos a comenzar ahora con la sesión. Como ven en pantalla, hemos estado recolectando las preguntas que han estado enviando y lo que vamos a hacer es que cada pregunta la vamos a leer en inglés y responder en inglés y también igual en español. Por favor, si tienen preguntas a medida que avanzamos, por favor escriban las preguntas en el buzón de preguntas y para acceder a ese buzón, Yeah, so, and then.

4:40 Speaker 1: As Erica said, so if you have additional questions that you think of during the session, the best way to get them to us, if you look on your webinar, the WebEx screen in the lower right corner, there's three buttons. If you click on that, it brings up a menu, and the first option of that menu is called Q & A. So that'll open up a Q & A box. You can type your questions there, and we'll add them to this list and we'll go through them in the order they're received. All right, so now we can get started with the questions.

5:17 Speaker 1: I'll hand over to Melanie, who will be reading off the questions to get us started, and I'll be providing the responses.

5:26 Speaker 4: Great. Thank you, Carl. So starting with question one, what is the difference between aerosols and particulate matter? And Erica, do you want to translate the question, or should we just translate everything at the end?

5:42 Speaker 2: Go ahead. How about you go ahead and answer it, and then I'll take it from the top on that question in Spanish.

5:49 Speaker 4: Excellent.

5:52 Speaker 1: Okay, so the difference here is that, or first let's say the similarities between the two, is that they both refer to particles which are suspended in the atmosphere. These could be solid or liquid particles. And air pollution is composed of both these particles, which are referred to as aerosols or particulate matter, and also various trace gases, for example, nitrogen dioxide and ozone. But if we're talking about aerosols and particulate matter, that is one type of air pollution. In terms of the differences, really, the difference is the terminology and who uses these terms.

6:38 Speaker 1: So the term aerosol is more commonly used by researchers in atmospheric science and in climate science, while the term particulate matter, which is commonly abbreviated in English as PM, is typically used by those who work in air quality and in health.

7:06 Speaker 2: Okay, entonces la primera pregunta es,¿ cuál es la diferencia entre aerosoles y materia particulada? En inglés, particulate matter. Comenzamos con las similitudes. Ambas se refieren a partículas suspendidas en atmósfera, ya sea partículas sólidas o líquidas. La contaminación atmosférica se compone de estas partículas y de trazas de gases. Así que las trazas de gases se refieren a gases como el NO2 y el ozono, y estos trazas The term aerosol is used by the community of scientific research and climate studies.

8:06 Speaker 2: So the term PM, particulate matter, is used by the communities of air quality and health. But really,

8:25 Speaker 2: Es lo mismo, simplemente que hay diferentes términos utilizados por diferentes comunidades.

8:33 Speaker 1: Okay, gracias.

8:36 Speaker 4: Okay, question two. How can we compare ground-based PM2. 5 observations with PM2. 5 that has been estimated using satellite observations, using aerosol optical depth, for example?

8:55 Speaker 1: Okay, so the first thing is that these are different quantities. So the PM, and especially PM 2.5, which refers to the specific size, so particles 2.5 micrometers in diameter or smaller. So the PM is a measurement of the concentration of these particles near the Earth's surface where people are breathing them in. The satellite value mentioned here, aerosol optical depth, is a measure of the total amount of particles or aerosols present in the full atmosphere, not just at the ground level. So there are different quantities, as I said.

9:52 Speaker 1: So if we want to compare these, we have to be aware of that and, uh, that into account. So a common method is to what's called do a co-location of the two data sets in space and time. This is basically we take the measurements of PM 2.5 at a location and And we look for the nearest satellite pass in both space and time to that location. And we take those two quantities, the PM 2.5 measured out the ground and the aerosol optical depth from the satellite. And we compare them to each other. And we determine a relationship empirically based upon that comparison.

10:44 Speaker 1: Maybe I'll pause there and let that be translated.

10:53 Speaker 2: Great, thank you. Okay, entonces la pregunta es,¿ cómo podemos comparar los valores in situ de PM2. 5 o PM con los valores de AOD, que es la profundidad óptica de aerosoles basados en satélites? La respuesta es que, lo primero es que se trata de cantidades diferentes, así que PM2. 5 se refiere al tamaño específico de la partícula, 2.5 micrómetros de diámetro o menores. and it is a measure of the concentration of the particle near the surface, where people, this is the area where people breathe, so it really directly affects human quality, human health.

11:41 Speaker 2: The total The aerosol optical depth is the total that is present in the entire atmosphere. So if you want to compare, you have to be aware of it and take this into account. And a common method is what they call the collocation or collocation in the space and time of these measurements. So they take measurements of PM 2.5 in one place and Go ahead, Carl. Okay, one question.

12:40 Speaker 1: Thing I will add. So that is, as I said, the empirical method. An alternative method is to use atmospheric models, which simulate particles in the atmosphere. And those models will simulate both the aerosol optical depth, which is what the satellite would see, as well as the surface level, PM 2.5, which we might measure at the ground. So those models can tell us what the relationship might be, and then we can compare those models to observations to determine whether or not they're accurate and can be trusted for making quantitative relationships between the two quantities.

13:32 Speaker 2: Okay, so Dr. Manning tells us that this empirical relationship It can also be simulated with atmospheric models. It can be determined with atmospheric models that simulate the particles in the atmosphere. So they simulate the AOD and PM2. 5 on the surface, and they can tell us how that relationship is and how precise it is, Okay. Yeah, go ahead.

14:23 Speaker 4: So, question three. What does aerosol optical depth actually measure?

14:32 Speaker 2: Okay.

14:32 Speaker 1: So, that's a good question. So the aerosol optical depth that we talked about in the last question is related to the total amount of aerosols between the Earth's surface and the top of the atmosphere. And the reason it's called optical depth is because it measures the amount of light, either blocked or reflected or scattered light, by those particles in the atmosphere. So basically what the satellite is measuring in the AOD is related to how much light was blocked from reaching the satellite due to the presence of the aerosols.

15:29 Speaker 2: Entonces, nos explica el Dr. Mullins. que la AOD está relacionada con la cantidad de aerosoles entre la superficie de la Tierra y la parte superior de la atmósfera. Entonces, se denomina profundidad óptica porque mide la cantidad de luz bloqueada, reflejada o dispersada por las partículas en la atmósfera. Así que, esencialmente mide la cantidad de luz bloqueada debido a la presencia de aerosoles en la atmósfera.

16:06 Speaker 3: Okay.

16:07 Speaker 2: Question four.

16:08 Speaker 4: Can I use satellite observations to measure surface ozone?

16:16 Speaker 1: Okay. So the general answer is no. And the reason is because most of the ozone in the atmosphere is not actually near the surface. It's higher up in the atmosphere. you may have heard of the ozone layer around the Earth. This is higher up in the atmosphere. And when the satellite is looking down, most of the signal due to ozone is coming from that high concentration in the upper atmosphere, which blocks or overwhelms the smaller signal due to the ozone near the Earth's surface. So this is the reason why Again, in general, satellite observations are not useful for looking at ozone near the Earth's surface.

17:21 Speaker 2: Okay, the next question. Can I use satellite observations to measure ozone? And the answer is In general, no. And the reason for that is that most of the ozone in the atmosphere is not close to the surface. It is above, in the upper part of the atmosphere. And everyone has heard of the ozone layer that surrounds the Earth. So this is above in the atmosphere. So when the satellite does that measurement, that is, it is looking from space to the surface, it is really detecting this ozone that is in the upper part Okay, question five.

18:07 Speaker 2: Can we compare ground-based.

18:36 Speaker 4: NO2 data, nitrogen dioxide, which are in ppm or parts per million, and satellite data from OMI or TEMPO, which is in units of molecules per centimeter squared for the troposphere column. How can we compare them?

18:55 Speaker 2: All right.

18:56 Speaker 1: So similar to the discussion I had earlier with comparing the PM 2.5 at the ground to the aerosol optical depth, It's a similar principle for this question, which is that we need information on the vertical distribution of these pollutants in the atmosphere to relate or convert one quantity into the other. In the last question for ozone, I mentioned that's very difficult because of the high concentrations of ozone higher in the atmosphere. But for nitrogen dioxide, this is actually– easier because most of the nitrogen dioxide is concentrated near the surface.

19:43 Speaker 1: So what the satellite is seeing is mostly coming from near the surface. so this is easier to do. But it is, you know, it is still, as was noted in the question, it is still important to know that these are not directly the same quantities, but similar to how we I explained for PM, if we do these collocations between the two datasets, we can develop a relationship between the two, or using an atmospheric model which simulates the nitrogen dioxide, we can determine a relationship between the two.

20:26 Speaker 2: Okay. La siguiente pregunta. Podemos comparar los datos in situ de NO2 que están en partes por millón con los datos de satélite de OMI o TEMPO que están en moléculas por centímetros cuadrados para la columna atmosférica. Y el Dr. Malin nos indica que esto es similar a lo que se explicó anteriormente en la comparación entre el PM2. 5 en la superficie con el AOD. Así que es un principio similar a esta pregunta. Necesitamos información sobre la distribución vertical de estos contaminantes para relacionarlos.

21:23 Speaker 2: Ahora, en el caso de NO2, es más fácil porque la mayor parte del NO2 se concentra cerca de la superficie, por lo que entonces el satélite what the satellite sees proceeds or the source of what the satellite sees is mainly on the surface. But it is still important to know that it is not directly the same quantities. However, then you have to do the collocations and you can develop an empirical relationship haciendo el collocation o usando un modelo atmosférico para determinar esta relación.

22:17 Speaker 4: Okay, question six. I have been using tempo data to monitor air pollutants in major towns in the state of Jalisco, Mexico. I would like to know if there is a numerical model that I can use to generate forecasts. Perhaps something to WARF, which is the Weather Research and Forecasting Model, with which I am familiar.

22:43 Speaker 1: Okay, so I'll provide a brief or two brief answers here, and then maybe I'll ask Didier if he knows of other resources. But the two resources I'll indicate here, the first is called WARF-Chem, W-R-F-Chem. This is a version of the WARF model which you're using, which incorporates chemical simulations.

23:19 Speaker 1: The second resource I'll indicate is called GEOS-CF.

23:25 Speaker 2: G-E-O-S-CF.

23:34 Speaker 1: GOCF is a NASA global atmospheric model which runs forecasts.

23:47 Speaker 1: And in this doc, I'll go through this, we'll go through this document after the training and I'll add links to the GOCF webpage so you can see where to access it. and also there are papers describing the model, which you can read, which I'll also link here. But those are two resources, which I'll point you to from the NASA end. I don't know, well, maybe I'll pause and let Erica translate, and then Didier, if you have anything to add from the Canadian end.

24:29 Speaker 2: Okay, la siguiente pregunta dice, he está usando datos de tiempo para monitorear contaminantes atmosféricos en las principales poblaciones del estado de Jalisco, México, y quisiera saber si existe algún modelo numérico que pueda usar para generar prognósticos, tal vez algo parecido a WARF, estado del tiempo con el cual estoy familiarizado.

25:02 Speaker 3: So I don't think I would recommend any additional model. I would strongly recommend actually going for WRF-CAM if you are already familiar with WRF because you would be able to see that the mechanics of the model are relatively similar. So you would save a lot of effort trying to use WORFCAM.

25:37 Speaker 2: Okay, so we have two parts to the answer to this question. The first one from Dr. Malin says that the two resources he recommends are WORFCAM, and this is a version of the WORF model that incorporates chemical simulations. And the second resource is called GEOS-CF, which is a global atmospheric model of NASA. que realiza prognósticos. Y este documento de preguntas y respuestas lo vamos a actualizar con enlaces a la página web y también con publicaciones. Así que esos son los dos recursos de la NASA.

26:17 Speaker 2: Y el doctor Davignon añadió que recomienda WORFCAM si es que ya están familiarizados con WORF. y verán que la mecánica del modelo es similar y les ahorrará mucho esfuerzo y tiempo utilizando WARFCAM.

26:48 Speaker 4: Okay, question seven. Which is the best method to compare the results of measurements? Maybe the question, unless other panelists would like to take an attempt, I would ask the question asker to maybe, can you be a little bit more specific? What kinds of measurements? Does that sound okay? And we'll move on to question eight.

27:15 Speaker 1: Yeah, I agree with that. We can, again, when we, maybe I'll state now. So we'll post a version of this document, which you're seeing on your screen now, to our website after the training is And before we do that, we'll go through and add resources. So this is a question, an example of a question where we might point to some general resources about statistical methods to do this, but it's, I think, too detailed to discuss here. So I agree, we can go to the next question.

27:49 Speaker 4: And I'll pause to let Erika.

27:50 Speaker 2: So the next question, what is the best method to compare the results of the measurements? Esta un poquito vaga esta pregunta porque los panelistas quisieran saber exactamente a qué se refiere, un poquito más detalle. Le hemos pedido a la persona que escribió la pregunta que por favor si puede elaborar un poquito más. Y también les recordamos que este documento lo vamos a editar, a pulir y lo vamos a poner en línea con enlaces de referencias y publicaciones para que puedan entonces, los que quieran, indagar más profundamente en estos temas.

28:39 Speaker 4: Thank you. Okay, question eight. Which sensor or satellite is recommended for performing a regional analysis of greenhouse gases and black carbons?

28:56 Speaker 1: Okay, so these are– so first, greenhouse gases are gases. So we need a satellite which can measure these. I

29:14 Speaker 1: would recommend to first look at a satellite called– an instrument called TROPOMI, T-R-O-M-I. T-O-M-I, which measures carbon species like methane, which are greenhouse gases. There are other resources, but I think that's a good place to start. And for black carbon, this is actually a type of aerosol, which we've discussed before. And so instruments which measure aerosols and, in particular, measure the absorption properties of aerosols are useful for this. And I'll mention maybe the VIIRS instrument for that.

30:29 Speaker 1: And I'll pause, but I see there's also a link, some links being put in as well, which others can speak to.

30:42 Speaker 4: Yes, I was adding we have a series of trainings focusing on remote sensing of carbon dioxide and their application in support of climate-related studies. There are two trainings bilingual. You'll recognize Erica's.

30:58 Speaker 2: Voice in those.

31:00 Speaker 4: Those will focus on CO2, and we have an upcoming training specifically focused on methane or emission detection using the EMIT sensor.

31:19 Speaker 2: Okay, and the next question is,¿ Qué sensor o satélite se recomienda para realizar un análisis de gases de efecto invernadero y carbono negro a nivel global? Así que esta es la pregunta número ocho. Doctor Martin nos indica que los gases de efecto invernadero son gases. Necesitamos un satélite que pueda medirlos. Así que él recomienda primero explorar los datos del instrumento llamado Tropomi. And this measures carbon species, such as methane, which is a greenhouse gas, and there are other resources, but this would be a good place to start.

32:03 Speaker 2: And as for black carbon, this is a type of aerosol, and for this, the instruments that measure aerosols are useful, in particular, the absorption properties of aerosols. And perhaps he recommends the VIRS instrument for this type of measurement. La doctora Foyet-Cook indicó que el programa RSET tiene varias capacitaciones o ha hecho varias capacitaciones sobre CO2, el dióxido de carbono, mediciones de dióxido de carbono desde el espacio utilizando el satélite y el sensor OCO, el Orbiting Carbon Observatory, y estas capacitaciones las pueden encontrar en línea tanto en inglés como en español.

32:51 Speaker 2: También habrá una capacitación que vamos a estar haciendo en el mes de noviembre sobre la detección del metano por medio de satélites. Así que estas son detecciones de grandes emisiones de metano utilizando datos del sensor EMIT, que es un sensor que está en la Estación Espacial Internacional.

33:14 Speaker 4: Okay, question nine. Can you summarize In current times, how far we've reached in the study of aerosols and air quality? What new techniques, data sets, or models are currently being used, and what new research can be done by those who can only use open source data sets?

33:38 Speaker 1: Okay, so this is another very broad question. We'll write a more a little bit more of a complete response to it in the full document. But I will also emphasize that the NASA RSET trainings cover a lot of these techniques and models in more detail. And the RSET trainings also focus on exclusively open source or open access data. So I think In general, the RSET trainings, which will refer to a few introductory trainings in our response when we publish it to the website, can give you a sense of what these resources are and also how to access open source resources.

34:38 Speaker 2: Okay, the next question, which would be question number nine.¿

34:47 Speaker 2: Puede resumir hasta dónde hemos llegado en el estudio de los aerosoles y la calidad del aire?¿ Qué nuevas técnicas, datos o modelos se están utilizando actualmente y qué nuevas investigaciones pueden realizar utilizando datos de código abierto?¿ Qué nuevas investigaciones se pueden realizar para aquellos que utilizan datos de código abierto. Okay. Así que el doctor Malin, pues, indica que la pregunta es un poquito amplia, pero que vamos a añadir más información y enlaces a entrenamientos o capacitaciones de ARCET que se han hecho al respecto.

35:41 Speaker 2: Las vamos a añadir al documento cuando lo ponemos en línea. Pero él enfatizó que las capacitaciones de RSAT cubren muchas de estas técnicas y modelos de los que hemos mencionado, los cubren en detalle y también estas capacitaciones se centran en utilizar datos de código abierto y de libre acceso, no solo datos, pero software. Así que los enlaces que vamos a compartir con ustedes serán de capacitaciones introductorias, para que tengan una idea de cuáles son los recursos y las técnicas que hemos cubierto en estos entrenamientos.

36:33 Speaker 3: Okay.

36:36 Speaker 4: Question 10. How can we measure PM or particulate matter from space? Which data sets are used?

36:47 Speaker 1: Okay, so I covered part of this in the previous question asking about the relationship between AOD and PM2. 5. So if we are able to establish that relationship using the collocation technique or models, as I mentioned, or some combination of both of those techniques, then we have a basis to translate the AOD from the satellite to estimate the PM at the surface. So that is a general approach to it. There are some specific datasets which have been generated using these types of techniques. And again, we'll put links to those specific datasets in the document when we post it.

38:01 Speaker 1: But they do exist, and several of them are available through NASA.

38:12 Speaker 2: Okay, the next question. que vendría siendo la pregunta número 10.¿ Cómo podemos medir PM desde el espacio?¿ Qué conjuntos de datos se utilizan?¿ Qué datos? OK. Doctor Malin dice que cubrió parte de esto en la pregunta anterior, donde se preguntó entre la relación entre AOD y PM 2.5. Now, if we can establish that relationship using the placement technique or models or a combination of both, then we have a basis to translate the satellite AOD to estimate the PM on the surface. And this is a general approach.

39:04 Speaker 2: It is a general way of doing it. There are some specific data that have been generated. han sido generados utilizando este tipo de técnicas. Y incluiremos enlaces a ellos en este documento cuando lo pongamos en línea. Como mencioné, vamos a incluir varios enlaces para que puedan profundizar un poco más.

39:28 Speaker 2: Okay, question 11.

39:28 Speaker 2: For a better analysis with satellite data, is it better to have higher or lower spatial resolution? So this.

39:49 Speaker 1: Depends on the objective of the analysis. As an example, if we're doing a global study, then a low resolution could be sufficient because we only care about a global average.

40:18 Speaker 1: But if we are studying in a specific city, the air quality, then it would be better to have a higher spatial resolution. And for the global study example I gave,

40:48 Speaker 1: If you used, you could use a high resolution data set, but then you would have a lot more data than you need, and it would be computationally more difficult to do the analysis with the higher resolution data. So that's a reason not to use high resolution data, depending on the objective of your analysis. Great.

41:32 Speaker 2: La siguiente pregunta, la número 11, dice, para un mejor análisis con datos satelitales,¿ es mejor tener una resolución espacial mayor o menor? Y el Dr. Malin indica que esto depende del objetivo del análisis. Así que, por ejemplo, si están haciendo un estudio global, una resolución baja podría ser suficiente porque solo... Estamos interesados en ese caso en, digamos, el promedio global. Pero si están estudiando la calidad del aire, digamos, en una ciudad en específico, entonces tal vez sería mejor tener datos de alta resolución espacial.

42:21 Speaker 2: El ejemplo del estudio global, pueden usar datos de alta resolución, pero tendrán más datos. que probablemente más datos de lo que realmente tal vez necesiten y computacionalmente sería un poco más difícil hacer el análisis. Así que por esa razón, en ese caso sería mejor no usar datos de alta resolución, usar datos de baja resolución. Pero eso depende del objetivo del estudio.

43:03 Speaker 4: Okay, question 12. How often is Tropomy updated?

43:12 Speaker 1: So Tropomy is a satellite which is in a polar orbit. And that means it collects data for the whole world about once per day. So for any given location, we would have about one measurement per day from tropomy. If you're referring to the data produced by tropomy, sorry, the data produced by tropomy is analyzed with what's called retrieval algorithms, which translate what the satellite is actually measuring, which is the spectral radiation coming from the Earth, and they translate it into things like the NO2 concentration, for example.

44:12 Speaker 1: And so those algorithms are updated not on a set schedule, but they are updated as the techniques are refined. So on average, I think maybe an update every year or every two years seems to be what's been happening for Trapomi so far.

44:50 Speaker 2: Bien, la siguiente pregunta... With what frequency is Tropomy updated? Tropomy is a satellite in polar orbit, which means that it makes measurements of the entire planet approximately once a day. So for a certain place, we have approximately one measurement a day. Now, if you refer to data producidos por tropomi con algoritmos de recuperación que traducen esa radiación espectral en, digamos, concentraciones de NO2, por ejemplo, esos algoritmos son actualizados a medida que las técnicas de recuperación son refinadas o mejoradas.

45:54 Speaker 2: Así que, en general, en caso de tropomy, hay actualizaciones cada año o cada dos años.

46:10 Speaker 4: Question 13. What would be the best satellite to obtain data of NOx, SOx, or probably SO2, PM2. 5, and others?

46:25 Speaker 1: So as in my response to a previous question, it really depends on the objective that you're trying to achieve. For example, the previous question asked about the resolution. So the resolution would depend on your.

46:46 Speaker 2: Objective.

46:47 Speaker 1: And similarly, based on what you want to do with the data, you might want a different satellite. I would say, again, TRAPOMI is generally a useful satellite for looking at gases like NO2, SO2. And for PM2. 5, I mentioned previously in.

47:13 Speaker 2: An answer that.

47:22 Speaker 1: We can't measure that directly with a satellite, but we can measure aerosol optical depth and determine PM2. 5 from that.

47:40 Speaker 4: We should probably also mention the tempo in GEMS.

47:46 Speaker 2: Yes, yes.

47:49 Speaker 1: So I mentioned... TRAPOMI, because it has its, as I said in the previous question, its polar orbiting and provides full coverage of the globe. If you were interested in a specific region, there are other useful satellites, as Melanie mentioned. So TEMPO is specifically over North America. And GEMS is specifically over East Asia, covering Japan, Korea, China, and that region, and part of India as well. So for those specific regions, you may have, again, depending on what your objective is, you may be able to obtain more useful information from one of these satellites.

48:47 Speaker 1: But if you're studying the entire globe or region which is not covered by one of those satellites, in those cases, I would recommend tropomy. And again, those are just referring to gases in the atmosphere. If you're interested in aerosols, there would be different instruments we would recommend. And again, different instruments depending on whether you're interested in the global scale or a specific region. So

49:21 Speaker 1: we'll put some links to resources, again, in the document, but it really depends on your objective and what region you're interested in.

49:41 Speaker 2: Bien, la siguiente pregunta que vendría siendo la pregunta número 13.¿ Cuál sería el mejor satélite para obtener datos de NOx, SOx, PM2. 5 y otros? Entonces, esto va a depender del objetivo que desean alcanzar. Y, por ejemplo, hablamos de la resolución espacial.¿ Cuál es la resolución espacial adecuada? Y eso depende... of the objective of the study, depending on what they want to do. So, depending on the objective, there are different satellites that can be used. Tropomy is usually a useful satellite to analyze gases such as NO2 or SO2.

50:25 Speaker 2: For PM2. 5, we cannot measure it directly with the satellite, but we can measure the AOD and determine PM2. 5 from it. Tropomy is in a polar orbit and has a complete global coverage. So if you are interested in a specific region, there are other satellites. For example, Tempo covers North America and there is another one called GEMS that covers Japan, Korea, China and parts of India. So for those specific regions you can get información digamos más puntual, más útil de uno de estos satélites. Si desean estudiar, hacer estudios a nivel global, entonces Tropomi es tal vez más adecuado.

51:24 Speaker 2: Y estos satélites solo se refieren a los gases en atmósfera. Si están interesados en los aerosoles, hay otros instrumentos que recomendamos. Nuevamente, dependiendo si el interés es a nivel global o por región. Y vamos a incluir enlaces y descripciones de estos instrumentos y enlaces en este documento cuando lo pongamos en línea. OK.

51:51 Speaker 4: I think we have time for probably about one more question. And I'll just remind, we will answer unanswered questions after today's Q & A session and post it on the website.

52:07 Speaker 4: Question 14, is there a training on how to work with both satellite and in-situ sampling?

52:16 Speaker 1: So that's a good question. I think the most relevant training for this is actually our most recent training, which covers NASA's Atmospheric Composition Ground Networks. What these are are ground-based remote sensors, which are on the surface of the Earth, but they look up from there. And so you're getting

52:49 Speaker 1: information both on concentrations in that specific location as well as the atmosphere, and that can help you relate what the satellite is seeing to the in-situ data. which, as I've mentioned in a few previous answers to a few previous questions, is really key to making these relationships. So, as I said, part two of that recent training goes into this in a little bit more detail, so you can see some examples of this.

53:35 Speaker 2: La siguiente pregunta, y a ver, la número 14.¿ Hay alguna capacitación sobre cómo trabajar con el muestreo, tanto de satélites como in situ? Y esta es una muy buena pregunta. La capacitación más relevante para esto es la de ARSAT, la más reciente de ARSAT, que cubrió redes terrestres de composición atmosférica de la NASA. O sea, esta es una red Y se trata de sensores remotos en la superficie de la Tierra que no solo hacen mediciones in situ, pero están mirando hacia arriba. Así que hacen mediciones de la atmósfera, mirando hacia arriba.

54:18 Speaker 2: Y pueden ayudar a mejor hacer esas relaciones entre las concentraciones in situ y la medición por satélite. And this is key to establish that relationship. So the second part of that training is about this topic in more detail. And again, we are going to include that link to that training in this document.

54:58 Speaker 4: Okay, I think that brings us to the end of our time today. I want to thank Dr. Carl Mailings, D.A. de Avignon, and Erika Podest for their amazing help today. And thank you all for attending and for your great questions. And to hear about upcoming trainings, please visit our website and sign up for our listserv. and you will automatically be notified about upcoming trainings.

55:28 Speaker 2: So this concludes this session. First of all, we are grateful to all the participants for their questions. We will answer all the questions that were sent to us in the document. Even though we didn't get to answer them today, we will answer them all in the document. And I would like to thank Dr. Melanie Foyer-Cook, Dr. Mullings, Didier Davignon, los panelistas por su expertise y recordarles que si quieren más información, porque por favor visiten la página de RSET y pueden encontrar información sobre capacitaciones que hemos hecho anteriormente y capacitaciones que vamos a hacer dentro de los próximos meses.

56:21 Speaker 2: Así que con eso, agradecidos y deseándoles a todos un Excelente día.