With the decreasing footprint and power consumption of contemporary
environmental sensors, they can now typically be integrated into
multiparameter sensor platforms (i.e. sondes) to provide new
opportunities for quantifying an array of carbon cycle processes.
Miniaturisation and lower power requirements have also increased the
portability of environmental sensors for deployment onboard mobile
robots, leading to the emergence of commercially available, remotely
operated and autonomous surface vehicles for environmental monitoring
(Wallingford, no date, YSI, no date). However, probes for measuring
dissolved CO2, CH4, and other proxies
for organic matter (e.g., cDOM, UV254, etc.) remain poorly incorporated
into t carbon cycling estimations. Available sensors either require
further development to improve their resolution and detection of
multiple compounds such as emerging contaminants, or for dissolved gases
atmospheric sensors must be deployed in bespoke water-tight,
gas-permeable sleeves (Aho et al., 2021, Bernal et al., 2022) or direct
measurements require combined chemical and optical measurements(Mendes
et al., 2019). Despite the increasing number of sensors that measure
parameters related to carbon, most river studies estimating whole-stream
metabolism have used dissolved oxygen time series (Hoellein et al.,
2013) but this method cannot resolve the change in respiration between
day and night (Tromboni et al., 2022). Conversion of oxygen data to
CO2 production/uptake then relies on the use of
respiratory quotients, with further work needed using concurrent
O2 and CO2 measurements to understand
sources of uncertainty, including organic matter composition and
biological community influences (Bernal et al., 2022) as well as
processes such as denitrification and sulphate oxidation that produce
CO2 without consuming dissolved oxygen.
Additional uncertainty must be minimised with appropriate corrections
for reaeration of atmospheric-aquatic gas exchanges, using either tracer
injections of inverse model fitting to sensor-derived dissolved gas
time-series (Holtgrieve et al., 2016). Novel biosensors based on
microbial-fuel cells (MFC), such as two-electrode bioelectrochemical
systems that use microbial respiration to convert chemical energy to
electricity (Cui et al., 2019), offer potential solutions to
environmental sensors for aquatic respiration-related parameters. The
MFC voltage or current response to aquatic respiration-related
parameters (including DO, BOD, COD and GHG) has been used as the basis
for developing MFC-based biosensors (Wu et al., 2019), including
commercial devices (e.g. HABS-2000 Online BOD Analyser). MFC-based
sensors have additional benefits including low cost, environmental
sustainability, the possibility of self-powered operation, portability
and reduced response times in the order of minutes.