Abstract. Atmospheric particulate matter smaller than 2.5 µm in diameter
(PM2.5) has a negative impact on public health, the environment, and
Earth's climate. Consequently, a need exists for accurate, distributed
measurements of surface-level PM2.5 concentrations at a global scale.
Existing PM2.5 measurement infrastructure provides broad PM2.5
sampling coverage but does not adequately characterize community-level air
pollution at high temporal resolution. This motivates the development of
low-cost sensors which can be more practically deployed in spatial and
temporal configurations currently lacking proper characterization. Wendt et al. (2019) described the development and validation of a
first-generation device for low-cost measurement of AOD and PM2.5: the
Aerosol Mass and Optical Depth (AMODv1) sampler. Ford et al. (2019)
describe a citizen-science field deployment of the AMODv1 device. In
this paper, we present an updated version of the AMOD, known as AMODv2,
featuring design improvements and extended validation to address the
limitations of the AMODv1 work. The AMODv2 measures AOD and PM2.5 at
20 min time intervals. The sampler includes a motorized Sun tracking
system alongside a set of four optically filtered photodiodes for
semicontinuous, multiwavelength (current version at 440, 500, 675, and 870 nm) AOD sampling. Also included are a Plantower PMS5003 sensor for
time-resolved optical PM2.5 measurements and a pump/cyclone system for
time-integrated gravimetric filter measurements of particle mass and
composition. AMODv2 samples are configured using a smartphone application,
and sample data are made available via data streaming to a companion website
(https://csu-ceams.com/, last access: 16 July 2021). We present the results of a 9 d AOD validation
campaign where AMODv2 units were co-located with an AERONET (Aerosol
Robotics Network) instrument as the reference method at AOD levels ranging
from 0.02 ± 0.01 to 1.59 ± 0.01. We observed close agreement
between AMODv2s and the reference instrument with mean absolute errors of
0.04, 0.06, 0.03, and 0.03 AOD units at 440, 500, 675, and 870 nm,
respectively. We derived empirical relationships relating the reference AOD
level to AMODv2 instrument error and found that the mean absolute error in the AMODv2 deviated by less than 0.01 AOD units between clear days and
elevated-AOD days and across all wavelengths. We identified bias from
individual units, particularly due to calibration drift, as the primary
source of error between AMODv2s and reference units. In a test of 15-month
calibration stability performed on 16 AMOD units, we observed median changes to calibration constant values of −7.14 %, −9.64 %, −0.75 %, and −2.80 % at 440, 500, 675, and 870 nm, respectively. We propose annual recalibration to mitigate potential errors from calibration drift. We conducted a trial deployment to assess the reliability and mechanical robustness of AMODv2 units. We found that 75 % of attempted samples were
successfully completed in rooftop laboratory testing. We identify several
failure modes in the laboratory testing and describe design changes that we have
since implemented to reduce failures. We demonstrate that the AMODv2 is an
accurate, stable, and low-cost platform for air pollution measurement. We
describe how the AMODv2 can be implemented in spatial citizen-science
networks where reference-grade sensors are economically impractical and
low-cost sensors lack accuracy and stability.
Particulate Matter in an Urban–Industrial Environment: Comparing Data of Dispersion Modeling with Tree Leaves Deposition
