Ozone Pollution in CDMX and Guadalajara

We can compare ozone pollution trends in two most ozone-polluted cities in Mexico: CDMX and Guadalajara

First, we load the packages needed for the analysis:

## Auto-install required R packages
packs <- c("dplyr", "ggplot2", "lubridate", "sp", "ggmap", "gstat", "zoo",
           "tidyr", "rsinaica")
success <- suppressWarnings(sapply(packs, require, character.only = TRUE))
if (length(names(success)[!success])) {
  install.packages(names(success)[!success])
  sapply(names(success)[!success], require, character.only = TRUE)
}

Download data

## Download a single month of data for all Guadalajara and CDMX stations
get_month <- function(start_date, end_date, net, parameter){
  bind_rows(
    lapply(stations_sinaica$station_id[stations_sinaica$network_name %in% net],
           sinaica_station_data, parameter, start_date, end_date, "Crude")
  )
}
## Download 2018 data, one month at a time
cdmx <- bind_rows(
  mapply(get_month,
         seq(as.Date("2018-01-01"), as.Date("2018-12-01"), by = "month"),
         seq(as.Date("2018-02-01"), as.Date("2019-01-01"), by = "month") - 1,
         "Valle de México",
         "O3",
         SIMPLIFY = FALSE)
  )

guad <- bind_rows(
  mapply(get_month,
         seq(as.Date("2018-01-01"), as.Date("2018-12-01"), by = "month"),
         seq(as.Date("2018-02-01"), as.Date("2019-01-01"), by = "month") - 1,
         "Guadalajara",
         "O3",
         SIMPLIFY = FALSE)
  )

We'll be comparing the maximum daily ozone values among all stations

cdmx <- cdmx %>%
  group_by(date) %>%
  summarise(max = max(value, na.rm = TRUE)) %>%
  mutate(city = "CDMX")
#> `summarise()` ungrouping output (override with `.groups` argument)

guad <- guad %>%
  group_by(date) %>%
  summarise(max = max(value, na.rm = TRUE)) %>%
  mutate(city = "Guadalajara")
#> `summarise()` ungrouping output (override with `.groups` argument)

Plot

and finally we plot the data

ggplot(rbind(cdmx, guad), aes(as.Date(date), max, group = city, color = city)) +
  geom_line(size = .2) +
  geom_smooth(method = 'loess') +
  xlab("date") +
  ylab(expression(paste(O[3], " concentration in ppm"))) +
  ggtitle(expression(paste(O[3], " maximum daily value in Guadalajara and CDMX"))) +
  theme_bw()
#> `geom_smooth()` using formula 'y ~ x'

Diego Valle-Jones

2020-08-08

Download data

Plot