diegovalle / aire.zmvm

An R package to download Mexico City air quality data

Mexico City Air Quality Data

Diego Valle-Jones February 09, 2024

• What does it do?
• Installation
• Core Functions
• Quick Example

Author:	Diego Valle-Jones
License:	BSD_3
Website:	https://hoyodesmog.diegovalle.net/aire.zmvm/

What does it do?

Tools for downloading airquality data for the Mexico City metro area. This package can download real-time, daily maximum, minimum, or hourly average data for each of the pollution measuring stations or geographical zones in the Zona Metropolitana del Valle de México (greater Mexico City). It also includes the locations of all the measuring stations and a function to perform inverse distance weighting modified to work with wind direction.

Installation

You can always install the development version from GitHub:

if (!require(devtools)) {
    install.packages("devtools")
}
devtools::install_github('diegovalle/aire.zmvm')

To install the most recent package version from CRAN type:

install.packages("aire.zmvm")
library(aire.zmvm)

Note that the version on CRAN might not reflect the most recent changes made to this package.

Core Functions

The package core functions:

• get_station_data and get_station_month_data download pollution, wind and temperature data for each of the measuring stations in the original units (ppb, µg/m³, etc).
• get_station_imeca download pollution values for each station in IMECAs
• get_zone_imeca download pollution data in IMECAs for each of the 5 geographic zones of Mexico City
• get_latest_imeca download the latest pollution hourly maximums for each of the measuring stations.
• idw360 inverse distance weighting modified to work with degrees, useful for wind data

Function	Date range	Units	Wind, Tmp, RH	Earliest Date	Pollutants	Includes All Stations	Criterion
get_station_data	years	Original	Yes	1986	SO2, CO, NO2, O3, PM10, PM25, WSP, WDR, TMP, RH	Yes	hourly, daily maximum, daily minimum
get_station_month_data	1 month	Original	Yes	2005‑01	SO2, CO, NO2, O3, PM10, PM25, WSP, WDR, TMP, RH	Yes	hourly, daily maximum, daily minimum
get_station_imeca	1 day	IMECA	No	2009‑01‑01	SO2, CO, NO2, O3, PM10	No	hourly
get_zone_imeca	1 or more days	IMECA	No	2008‑01‑01	SO2, CO, NO2, O3, PM10	Only zones	hourly, daily maximum
get_latest_imeca	1 hour	IMECA	No	Latest only	Maximum value of SO2, CO, NO2, O3, PM10	No	latest hourly

Quick Example

library("aire.zmvm")
library("dplyr")
library("ggplot2")
library("ggseas")

o3 <- get_station_data(criterion = "MAXIMOS", # Can be one of MAXIMOS (daily maximum), 
                                              # MINIMOS (daily minimum), 
                                              # or HORARIOS (hourly average)
                       pollutant = "O3", # Can be one of "SO2", "CO", "NOX", "NO2", "NO", "O3", 
                                         # "PM10", "PM25", "WSP", "WDR", "TMP", "RH"
                       year = 2009:2018) # A numeric vector, the earliest year allowed is 1986
knitr::kable(head(o3))

date	station_code	pollutant	unit	value
2009-01-01	ACO	O3	ppb	67
2009-01-02	ACO	O3	ppb	71
2009-01-03	ACO	O3	ppb	112
2009-01-04	ACO	O3	ppb	91
2009-01-05	ACO	O3	ppb	70
2009-01-06	ACO	O3	ppb	71

# Daily max among all base stations
o3_max <- o3 %>% 
  group_by(date) %>% 
  summarise(max = ifelse(all(is.na(value)),
                         NA,
                         base::max(value, na.rm = TRUE))) %>%
  na.omit()

# ozone values at which a contingencia ambiental was declared
# and the dates during which they were valid
# source: http://www.aire.cdmx.gob.mx/descargas/ultima-hora/calidad-aire/pcaa/pcaa-modificaciones.pdf
contingencia <- data.frame(ppb = c(216, 210, 205, 199, 185, 155, 155),
  start = c(2009, 2009.4973, 2010.4973, 2011.5795, 
            2012.6052, 2016.291, 2016.4986),
  end = c(2009.4973, 2010.4945, 2011.4945, 
          2012.6025, 2016.2883, 2016.4959, Inf))
max_daily_df <- tsdf(ts(o3_max$max, start = c(2009,1), frequency = 365.25))
ggplot(max_daily_df,
       aes(x = x, y = y)) + 
  geom_line(colour = "grey75", alpha = .5) +
  stat_rollapplyr(width = 30, align = "right", color = "#01C5D2") +
  #geom_vline(xintercept = 2015 + 183/365) +
  geom_segment(data = contingencia, 
               aes(x=start, y=ppb, xend=end, yend=ppb), color="darkred", 
               linetype = 2)  +
  xlab("date") +
  ylab("parts per billion") +
  scale_x_continuous(breaks = c(2010, 2012, 2014, 2016, 2018)) +
  ggtitle("Maximum daily ozone concentration and 30 day rolling average", 
          subtitle = paste0("Red lines indicate the values necessary to ",
                            "activate a phase I smog alert.",
                            "\nData source: SEDEMA"))