Attempting to detect air pollution following SpaceX explosion

SpaceX.R

library(dplyr)
library(ggplot2)
library(ggmap)
library(ropenaq)
library(gridExtra)

# Get pollution data
df <-
  aq_measurements(
    country = "US",
    city = "Deltona-Daytona+Beach-Ormond+Beach",
    parameter = "pm25",
    limit = 200
  )

p_pollution <- ggplot(df$results, aes(x = dateLocal, y = value)) +
  geom_line() +
  geom_point(alpha = 0.25, size = 1) +
  geom_hline(
    yintercept = mean(df$results$value),
    linetype = "dashed",
    size = 0.01,
    color = "blue"
  ) +
  geom_vline(xintercept = as.numeric(as.POSIXct("2016-09-01 09:00:00", "UTC")),
             color = "red") +
  scale_x_datetime(breaks = date_breaks("1 day"), labels = date_format("%m/%d")) +
  theme_light() +
  theme(
    panel.grid.minor = element_blank(),
    axis.title = element_text(size = 8),
    axis.text = element_text(size = 7),
    plot.caption = element_text(size = 8)
  ) +
  labs(
    x = "",
    y = "Particulate matter 2.5 (μg/m3)\n",
    title = "Air pollution following SpaceX explosion",
    subtitle = "As measured in Daytona Beach",
    caption = "Note: Dashed horizontal line shows sample mean.
    Vertical red line shows approximate time of explosion (09:00 local time)."
  )

# Get geo data
box_coords <- c(-80.7729003, 28.7798137)
map <- get_map(box_coords, zoom = 9, maptype = "satellite")

coords <- ggmap::geocode("Cape Canaveral Air Force Station")
coords <- coords %>%
  add_row(lon = unique(df$results$longitude),
          lat = unique(df$results$latitude)) %>%
  mutate(location = c("Explosion\nlocation", "Measuring\nlocation"))

p_map <- ggmap(map) +
  geom_point(
    aes(x = lon, y = lat),
    data = coords,
    color = "red",
    size = 3,
    alpha = 0.4
  ) +
  geom_text(
    aes(x = lon, y = lat, label = location),
    data = coords,
    color = "red",
    hjust = 0,
    fontface = "bold",
    nudge_x = 0.1,
    size = 3
  ) +
  theme_void()

grid.arrange(p_pollution, p_map, nrow = 1, widths = 2:1)

@expersso even at KXMR with riem::riem_measures(station = "XMR", date_start = "2016-08-29", date_end = "2016-09-03") there was nothing interesting. Somehow I'd have expected to see a spike or drop of a weather related paremeter but I know nothing about weather and maybe another airport would be more appropriate?