Abstract
Internationally, severe wildfires are an escalating problem
likely to worsen given projected changes to climate. Hazard reduction burns
(HRBs) are used to suppress wildfire occurrences, but they generate
considerable emissions of atmospheric fine particulate matter, which
depend upon prevailing atmospheric conditions, and can degrade air quality.
Our objectives are to improve understanding of the relationships between
meteorological conditions and air quality during HRBs in Sydney, Australia.
We identify the primary meteorological covariates linked to high PM2.5
pollution (particulates < 2.5 µm in diameter) and quantify
differences in their behaviours between HRB days when PM2.5 remained
low versus HRB days when PM2.5 was high. Generalised additive mixed
models were applied to continuous meteorological and PM2.5 observations
for 2011–2016 at four sites across Sydney. The results show that planetary
boundary layer height (PBLH) and total cloud cover were the most consistent
predictors of elevated PM2.5 during HRBs. During HRB days with low
pollution, the PBLH between 00:00 and 07:00 LT (local time) was 100–200 m
higher than days with high pollution. The PBLH was similar during
10:00–17:00 LT for both low and high pollution days, but higher after
18:00 LT for HRB days with low pollution. Cloud cover, temperature and wind
speed reflected the above pattern, e.g. mean temperatures and wind speeds
were 2 °C cooler and 0.5 m s−1 lower during mornings and
evenings of HRB days when air quality was poor. These cooler, more stable
morning and evening conditions coincide with nocturnal westerly cold air
drainage flows in Sydney, which are associated with reduced mixing height and
vertical dispersion, leading to the build-up of PM2.5. These findings
indicate that air pollution impacts may be reduced by altering the timing of
HRBs by conducting them later in the morning (by a matter of hours). Our
findings support location-specific forecasts of the air quality impacts of
HRBs in Sydney and similar regions elsewhere.
Citation
ID:
137597
Ref Key:
virgilio2018atmosphericmeteorological