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Abstract. More than 300 non-dispersive infrared (NDIR) CO2 low-cost sensors labelled as LP8 were integrated into sensor units and evaluated for the purpose of long-term operation in the Carbosense CO2 sensor network in Switzerland. Prior to deployment, all sensors were calibrated in a pressure and climate chamber and in ambient conditions co-located with a reference instrument. To investigate their long-term performance and to test different data processing strategies, 18 sensors were deployed at five locations equipped with a reference instrument after calibration. Their accuracy during 19 to 25 months deployment was between 8 and 12 ppm. This level of accuracy requires careful sensor calibration prior to deployment, continuous monitoring of the sensors, efficient data filtering, and a procedure to correct drifts and jumps in the sensor signal during operation. High relative humidity (> ∼85 %) impairs the LP8 measurements, and corresponding data filtering results in a significant loss during humid conditions. The LP8 sensors are not suitable for the detection of small regional gradients and long-term trends. However, with careful data processing, the sensors are able to resolve CO2 changes and differences with a magnitude larger than about 30 ppm. Thereby, the sensor can resolve the site-specific CO2 signal at most locations in Switzerland. A low-power network (LPN) using LoRaWAN allowed for reliable data transmission with low energy consumption and proved to be a key element of the Carbosense low-cost sensor network.

Abstract. We collected 1 year of aerosol chemical speciation monitor (ACSM) data in Magadino, a village located in the south of the Swiss Alpine region, one of Switzerland's most polluted areas. We analysed the mass spectra of organic aerosol (OA) by positive matrix factorisation (PMF) using Source Finder Professional (SoFi Pro) to retrieve the origins of OA. Therein, we deployed a rolling algorithm, which is closer to the measurement, to account for the temporal changes in the source profiles. As the first-ever application of rolling PMF with multilinear engine (ME-2) analysis on a yearlong dataset that was collected from a rural site, we resolved two primary OA factors (traffic-related hydrocarbon-like OA (HOA) and biomass burning OA (BBOA)), one mass-to-charge ratio (m/z) 58-related OA (58-OA) factor, a less oxidised oxygenated OA (LO-OOA) factor, and a more oxidised oxygenated OA (MO-OOA) factor. HOA showed stable contributions to the total OA through the whole year ranging from 8.1 % to 10.1 %, while the contribution of BBOA showed an apparent seasonal variation with a range of 8.3 %–27.4 % (highest during winter, lowest during summer) and a yearly average of 17.1 %. OOA (sum of LO-OOA and MO-OOA) contributed 71.6 % of the OA mass, varying from 62.5 % (in winter) to 78 % (in spring and summer). The 58-OA factor mainly contained nitrogen-related variables which appeared to be pronounced only after the filament switched. However, since the contribution of this factor was insignificant (2.1 %), we did not attempt to interpolate its potential source in this work. The uncertainties (σ) for the modelled OA factors (i.e. rotational uncertainty and statistical variability in the sources) varied from ±4 % (58-OA) to a maximum of ±40 % (LO-OOA). Considering that BBOA and LO-OOA (showing influences of biomass burning in winter) had significant contributions to the total OA mass, we suggest reducing and controlling biomass-burning-related residential heating as a mitigation strategy for better air quality and lower PM levels in this region or similar locations. In Appendix A, we conduct a head-to-head comparison between the conventional seasonal PMF analysis and the rolling mechanism. We find similar or slightly improved results in terms of mass concentrations, correlations with external tracers, and factor profiles of the constrained POA factors. The rolling results show smaller scaled residuals and enhanced correlations between OOA factors and corresponding inorganic salts compared to those of the seasonal solutions, which was most likely because the rolling PMF analysis can capture the temporal variations in the oxidation processes for OOA components. Specifically, the time-dependent factor profiles of MO-OOA and LO-OOA can well explain the temporal viabilities of two main ions for OOA factors, m/z 44 (CO2+) and m/z 43 (mostly C2H3O+). Therefore, this rolling PMF analysis provides a more realistic source apportionment (SA) solution with time-dependent OA sources. The rolling results also show good agreement with offline Aerodyne aerosol mass spectrometer (AMS) SA results from filter samples, except for in winter. The latter discrepancy is likely because the online measurement can capture the fast oxidation processes of biomass burning sources, in contrast to the 24 h filter samples. This study demonstrates the strengths of the rolling mechanism, provides a comprehensive criterion list for ACSM users to obtain reproducible SA results, and is a role model for similar analyses of such worldwide available data.

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Background: The ability to track fish in the vicinity of dams and detect the presence of fish in fishways (also referred to as fish ladders) is critical to understanding the migration biology of upstream migrating fish and their passage success. Acoustic telemetry provides a valuable method within the telemetry toolbox, but has rarely been used in noisy, constrained, swift-flowing, and air-entrained environments such as fishways because of the perceived limitations of acoustic telemetry in such environments relative to other techniques such as radio telemetry. However, there have been no published studies that represent systematic evaluations of both detection efficiency based on number of transmitted signals and detection probabilities based on number of fish detected in fishways for acoustic telemetry. As such, the efficacy of acoustic telemetry in a fishway was evaluated using both controlled field experiments and movements of live fish at the Wanapum Dam fishway on the Columbia River in Washington State. In this study, the Juvenile Salmon Acoustic Telemetry System (JSATS) was selected because of its high carrier frequency (416.7 kHz) and short signal duration yielding good system resilience in shallow, noisy, and constrained environments.