  We demonstrate how a hierarchical network comprising a number of compliant
reference stations and a much larger number of low-cost sensors can deliver
reliable high temporal-resolution ozone data at neighbourhood scales. The
framework, demonstrated originally for a smaller scale regional network
deployed in the Lower Fraser Valley, BC was tested and refined using two much
more extensive networks of gas-sensitive semiconductor-based (GSS) sensors
deployed at neighbourhood scales in Los Angeles: one of ~20 and one of ~45 GSS
ozone sensors. Of these, ten sensors were co-located with different regulatory
measurement stations, allowing a rigorous test of the accuracy of the
algorithms used for off-site calibration and adjustment of low cost sensors.
The method is based on adjusting the gain and offset of the low-cost sensor to
match the first two moments of the probability distribution of the sensor
result to that of a proxy: a calibrated independent measurement (usually
derived from regulatory monitors) whose probability distribution evaluated over
a time that emphasizes diurnal variations is similar to that at the test
location. The regulatory measurement station physically closest to the low-cost
sensor was a good proxy for most sites. The algorithms developed were
successful in detecting and correcting sensor drift, and in identifying
locations where geographical features resulted in significantly different
patterns of ozone variation due to the relative dominance of different
dispersion, emission and chemical processes. The entire network results show
very large variations in ozone concentration that take place on short time- and
distance scales across the Los-Angeles region. Such patterns were not captured
by the more sparsely distributed stations of the existing regulatory network
and demonstrate the need for reliable data from dense networks of monitors.
