AIR POLLUTION ANALYSIS USING R SOFTWARE
It is very important to use correct comma separated values (csv) files. Remember to save as csv in LibreOffice Calc or Microsoft Office Excel and to replace all commas to points, then all semicolons to commas and finally all Sense dades to NA. After all that you can use your data in R Studio using the instructions found in the table below.
| Read dataframe | martorell<-read.csv(“E://PollutionData/martorell2015.csv”) |
| Calculate quartiles, median, min, max, outliers | summary (martorell) |
| Create boxplot | boxplot(martorell$NO) |
| Create histogram | hist(martorell$NO, breaks=20, xlab=”NO(micrograms/m3)”, main=”Martorell air pollution”, col= “pink”) |
| Install and load normality test | install.packages(” nortest “)
library(nortest)
|
| Shapiro- Wilk normality test
Anderson-Darling normality test Cramer-von-Mises normality test Kolmogorov-Smirnov normality test Pearson normality test Shapiro-Francia normality test |
shapiro.test(martorell$NO)
ad.test(martorell$NO) cvm.test(martorell$NO) lillie.test(martorell$NO) pearson.test(martorell$NO) sf.test(martorell$NO) |
| library (e1071) | skewness(x), kurtosis(x) |
| skewness (negative:left tail, positive: right tail, normal:0) | skewness(martorell$NO) |
| kurtosis (negative : platycurtic, positive : leptocurtic, normal :0) | kurtosis(martorell$NO) |
| Student t test (compare 2 normal data) | t.test(martorell$NO, santandreu$NO) |
| U Mann Whitney (compare 2 non normal data) | wilcox.test(martorell$NO, santandreu$NO) |
| Compare > 2 normal groups | ANOVA test |
| Compare > 2 non-normal grous | Kruskal-Wallis test |
| Homocedascity (equal variability) | leveneTest(x) in car library |
| View possible correlation | pairs (martorell) |
| Object type : class (x) | numeric, date, time series, dataframe, etc |
| Convert numeric to date | martorell$date<-as.Date(martorell$date) |
| Create time series | martorellNO.ts <- ts(martorell$NO, start=c(2015, 1, 1), end=c(2015, 12,31), frequency=365) |
| Bind column data | NOcompare<-cbind(martorellNO.ts,santandreuNO.ts) |
| Plotting multiple time series | plot(NOcompare, plot.type=”m”,col=c(“blue”, “red”)) |
| Subset time series | mytssummer2015 <- window(myts, start=c(2015, 6,21), end=c(2015, 9,22)) |
| Correlation plot | library (corrplot)
corrplot.mixed (martorell) |
| Linear model | fit<-lm(martorell$NO~martorell$NO2)
summary(fit) |
Regarding NO2 levels found in previous image:
Is Martorell following the NO2 air pollution standards of the EU?
What is the EU decission 3 about NO2 pollution? In Spanish (authentic and valid)
Analyse all EU air standards and compare to WHO air standards
> plot(martorell$date, martorell$NO, type = "l", xlab = "year 2015",ylab = "Nitric oxide (microg/m3)")
Normality tests
install.packages(“nortest”)
> plot(martorell$date, martorell$NO, type = “l”, xlab = “year 2015”,ylab = “Nitric oxide (microg/m3)”, main=”Air pollution in Martorell (8760 observations)”)
> plot(martorell$date[1:168], martorell$NO[1:168], type = “l”, xlab = “year 2015”,ylab = “Nitric oxide (microg/m3)”, main=”Air pollution in Martorell”)
> plot(martorell$date[144:168], martorell$NO[144:168], type = “l”, xlab = “year 2015”,ylab = “Nitric oxide (microg/m3)”, main=”Air pollution in Martorell (7th January)”)
Time series air pollution comparison Martorell vs Sant Andreu de la Barca (2015)
T- test (normal data) or U Mann- Withney (non-normal data)
Air pollutant in Martorell (2015)
One week forecast of air pollution in Martorell
