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.