Skip to content
master
Switch branches/tags
Go to file
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
R
 
 
 
 
 
 
 
 
man
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Mexico City Air Quality Data

Diego Valle-Jones November 06, 2020

R build status AppVeyor build status Coverage Status CRAN_Status_Badge

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"))

About

An R package to download Mexico City air quality data

Resources

License

Packages

No packages published

Languages