Design, operation, and insights from Zurich’s mid- and low-cost ICOS Cities CO2 sensor network

Zurich aims for net-zero direct greenhouse gas emissions by 2040, a target supported by 75 % of voters. Progress is tracked through a detailed CO₂ inventory covering energy, transport, industry, and waste. Under the European ICOS Cities project, a monitoring program was launched using two approaches: (i) a network of mid- and low-cost CO₂ sensors combined with atmospheric inverse modeling, and (ii) CO₂ flux measurements from an eddy-covariance system on a city-center high-rise building, paired with footprint modeling.

Here, we focus on the mid-cost (ZiCOS-M) and low-cost (ZiCOS-L) NDIR (nondispersive infrared) CO₂ networks, which were both operational for at least 3 years since 2022.

ZiCOS-M consists of 26 monitoring sites, 21 in the city and 5 outside the urban area. Daily calibrations using two reference gas cylinders, and corrections of the sensors’ spectroscopic response to water vapour were performed. The hourly mean root mean squared error (RMSE) was 0.98 ppm (0.46 - 1.5 ppm) and the mean bias ranged between 0.72 and 0.66 ppm compared to parallel measurements with a high-precision reference gas analyser for a period of 2 weeks or more. CO₂ concentrations in the city were highly variable with site means ranging from 434 to 460 ppm, and Zurich’s mean urban CO₂ increment was 15.4 ppm above the regional background.

ZiCOS-L consists of 56 sites with paired sensors. The sensors require in-field training for model calibration before deployment and further post-processing steps to account for drift and outliers. After data processing, the hourly RMSE was 13.6±1.4 ppm, and the mean bias 0.75±1.67 ppm when validated against parallel reference measurements from ZiCOS-M. CO₂ concentrations were highly variable with site means in Zurich ranging from 438 to 465 ppm, reflecting mainly the influence of sources in the nearby surroundings. Vegetation (mainly grassland) amplified the morning concentration on average in summer by up to 20 ppm due to ecosystem respiration, while heavy traffic increased the morning rush hour concentration by 15 ppm. Despite its lower measurement accuracy, the ZiCOS-L network enables the study of concentration dynamics at a spatial and temporal scale that is not accessible by any other means.

The ZiCOS-M data was extensively used to derive top-down CO₂ emissions. Similar modelling activities are currently ongoing with the ZiCOS-L data, and both are compared to emissions derived from the eddy covariance system and to the city's emission inventory.

 

Grange SK, … Emmenegger L, The ZiCOS-M CO₂ sensor network: measurement performance and CO₂ variability across Zurich. https://doi.org/10.5194/acp-25-2781-2025.

Creman L, … Bernet L, The Zurich Low-cost CO₂ sensor network (ZiCOS-L): data processing, performance assessment and analysis of spatial and temporal CO₂ dynamics. https://doi.org/10.5194/egusphere-2025-3425

Brunner D, … Emmenegger L, Building-resolving simulations of anthropogenic and biospheric CO₂ in the city of Zurich with GRAMM/GRAL. https://doi.org/10.5194/acp-25-14279-2025.

Hilland R, … Christen A, Sectoral attribution of greenhouse gas and pollutant emissions using multi-species eddy covariance on a tall tower in Zurich, Switzerland. https://doi.org/10.5194/acp-25-14279-2025.

Ponomarev N, … Brunner D, Estimation of CO₂ fluxes in the cities of Zurich and Paris using the ICON-ART CTDAS inverse modelling framework. https://doi.org/10.5194/egusphere-2025-3668.