The concentration of pollutants in the atmosphere is affected by some meteorological variables such as relative humidity, temperature, atmospheric pressure, among others. On the other hand, the dispersion of these pollutants is influenced by the stability that predominates in the atmosphere. At the regional level, attention has been paid to the problem of atmospheric pollution, mainly due to the oil activities carried out in the southwest of Mexico. Through an automated monitoring network known as the Southern Region Automated System (SAMARS) of PEMEX, the main atmospheric pollutants (except ozone) and meteorological variables are monitored. This network has operated since 1999 and has six monitoring stations located on the peripheries of the oil facilities (Batteries and Compressors). The information collected to date has been used mainly in the evaluation of air quality in the periphery of these facilities, in the calibration of pollutant dispersion models, and in the spatial distribution of these. The pollutants whose concentrations were studied are SO2 (sulfur dioxide), NO2 (nitrogen dioxide), and H2S (hydrogen sulfide); In this activity we will focus only on sulfur dioxide and its relationship with some meteorological variables. This information was obtained at a monitoring station in northern Chiapas. 1) The following average concentrations per year of SO2 in ppb (parts per billion) were obtained: Year PPB 2015 2016 12.1 8.7 2017 8.3 2018 5.8 2019 6.1 a) Construct a scatter plot diagram b) What is the interpretation of b1? c) Assuming that the data maintain a similar behavior in the coming years, use a simple linear regression model to estimate the average SO2 concentration in the year 2021. d) Obtain the Pearson correlation coefficient between both variables and make an interpretation of it. Is it consistent with what was obtained in a)? Explain. e) What proportion of the observed variation y is explained by the simple linear regression model?

Applications and Investigations in Earth Science (9th Edition)
9th Edition
ISBN:9780134746241
Author:Edward J. Tarbuck, Frederick K. Lutgens, Dennis G. Tasa
Publisher:Edward J. Tarbuck, Frederick K. Lutgens, Dennis G. Tasa
Chapter1: The Study Of Minerals
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The concentration of pollutants in the atmosphere is affected by some meteorological
variables such as relative humidity, temperature, atmospheric pressure, among
others. On the other hand, the dispersion of these pollutants is influenced by the
stability that predominates in the atmosphere. At the regional level, attention has
been paid to the problem of atmospheric pollution, mainly due to the oil activities
carried out in the southwest of Mexico. Through an automated monitoring network
known as the Southern Region Automated System (SAMARS) of PEMEX, the main
atmospheric pollutants (except ozone) and meteorological variables are monitored.
This network has operated since 1999 and has six monitoring stations located on the
peripheries of the oil facilities (Batteries and Compressors). The information collected
to date has been used mainly in the evaluation of air quality in the periphery of these
facilities, in the calibration of pollutant dispersion models, and in the spatial
distribution of these. The pollutants whose concentrations were studied are SO2
(sulfur dioxide), NO2 (nitrogen dioxide), and H2S (hydrogen sulfide); In this activity we
will focus only on sulfur dioxide and its relationship with some meteorological
variables. This information was obtained at a monitoring station in northern Chiapas.
1) The following average concentrations per year of SO2 in ppb (parts per billion) were
obtained:
Year
PPB
2015
2016
12.1
8.7
2017
8.3
2018
5.8
2019
6.1
a) Construct a scatter plot diagram
b) What is the interpretation of b1?
c) Assuming that the data maintain a similar behavior in the coming years, use a
simple linear regression model to estimate the average SO2 concentration in the year
2021.
d) Obtain the Pearson correlation coefficient between both variables and make an
interpretation of it. Is it consistent with what was obtained in a)? Explain.
e) What proportion of the observed variation y is explained by the simple linear
regression model?
Transcribed Image Text:The concentration of pollutants in the atmosphere is affected by some meteorological variables such as relative humidity, temperature, atmospheric pressure, among others. On the other hand, the dispersion of these pollutants is influenced by the stability that predominates in the atmosphere. At the regional level, attention has been paid to the problem of atmospheric pollution, mainly due to the oil activities carried out in the southwest of Mexico. Through an automated monitoring network known as the Southern Region Automated System (SAMARS) of PEMEX, the main atmospheric pollutants (except ozone) and meteorological variables are monitored. This network has operated since 1999 and has six monitoring stations located on the peripheries of the oil facilities (Batteries and Compressors). The information collected to date has been used mainly in the evaluation of air quality in the periphery of these facilities, in the calibration of pollutant dispersion models, and in the spatial distribution of these. The pollutants whose concentrations were studied are SO2 (sulfur dioxide), NO2 (nitrogen dioxide), and H2S (hydrogen sulfide); In this activity we will focus only on sulfur dioxide and its relationship with some meteorological variables. This information was obtained at a monitoring station in northern Chiapas. 1) The following average concentrations per year of SO2 in ppb (parts per billion) were obtained: Year PPB 2015 2016 12.1 8.7 2017 8.3 2018 5.8 2019 6.1 a) Construct a scatter plot diagram b) What is the interpretation of b1? c) Assuming that the data maintain a similar behavior in the coming years, use a simple linear regression model to estimate the average SO2 concentration in the year 2021. d) Obtain the Pearson correlation coefficient between both variables and make an interpretation of it. Is it consistent with what was obtained in a)? Explain. e) What proportion of the observed variation y is explained by the simple linear regression model?
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