Munich permanent urban greenhouse gas column observing network

Abstract

Abstract. In order to mitigate climate change, it is crucial to understand the urban greenhouse gas (GHG) emissions precisely as more than two third of the anthropogenic GHG emissions worldwide originate from cities. Nowadays, urban emission estimates are mainly based on bottom-up calculation approaches with high uncertainties. A reliable and long-term top-down measurement approach could reduce the uncertainty of these emission inventories significantly. We present the world’s first urban sensor network that is permanently measuring GHGs based on the principle of differential column measurements (DCM) starting in summer 2019. These column measurements are relatively insensitive to vertical redistribution of tracer masses and surface fluxes upwind of the city. Therefore, they are well-suited to quantify GHG emissions. However, setting up such a stationary sensor network requires an automated measurement principle. We developed our own fully automated enclosure systems for measuring CO2, CH4 and CO column-averaged concentrations with a solar-tracking Fourier Transform spectrometer (EM27/SUN) in a fully automated and long-term manner. This includes also a software that starts and stops the measurements autonomously and can be used independently from the enclosure system. Furthermore, we demonstrate the novel applications of such a sensor network by presenting the measurement results of our five sensor systems that are deployed in and around Munich. These results include the seasonal cycle of CO2 since 2015 as well as concentration gradient measurements upwind and downwind of the city. Thanks to the automation we were also able to continue the measurements during the COVID-19 lockdown in spring 2020. By correlating the CO2 column concentration gradients to the traffic amount, we demonstrate that our network is well capable to detect variations in urban emissions. The measurements from our unique sensor network will be combined with an inverse modeling framework that we are currently developing, in order to monitor urban GHG emissions over years, identify unknown emission sources and assess how effective the current mitigation strategies are. In summary, our achievements in automating column measurements of GHGs will allow researchers all over the world to establish this novel measurement approach as a new standard for determining GHG emissions.

Shipborne measurements of XCO<sub>2</sub>, XCH<sub>4</sub>, and XCO above the Pacific Ocean and comparison to CAMS atmospheric analyses and S5P/TROPOMI

“…CAMS assimilates satellite measurements of atmospheric composition to forecast the global CO 2 , CH 4 , and CO concentrations at high spatial and temporal resolution using the Integrated Forecasting System (IFS). During our campaign in June 2019, CAMS assimilated XCO 2 and XCH 4 measurements from the Greenhouse gases Observing SATellite (GOSAT) (Kuze et al, 2009), CH 4 and CO measurements from the Infrared Atmospheric Sounding Interferometer (IASI) (Crevoisier et al, 2009), and CO measurements from the Measurement of Pollution in the Troposphere (MOPITT) (Drummond and Mand, 1996) instrument. The ultimate goal is to monitor the mitigation of anthropogenic greenhouse gas emissions and air pollution from global to regional scales (Massart et al, 2014(Massart et al, , 2016Inness et al, 2015Inness et al, , 2019Agustí-Panareda et al, 2019;Janssens-Maenhout et al, 2020).…”

What Are the Different Measures of Mobility Telling Us About Surface Transportation CO2 Emissions During the COVID‐19 Pandemic?

“…Specifically, the emergence of COVID-19 led to government restrictions on mobility including shelter-in-place orders and bans on social events (World Health Organisation (WHO), 2020). There has been much interest in understanding and quantifying how these regulations modulated both emissions to the atmosphere and the chemical composition of the atmosphere (e.g., Balamurugan et al, 2021;Dietrich et al, 2020;Tanzer-Gruener et al, 2020;Turner et al, 2020). Recent studies have tried to quantify the impact of the enforced and voluntary restriction of human activities (travel and work related) on global greenhouse gas (GHG) emissions (Forster et al, 2020;Le Quéré et al, 2020;Liu et al, 2020) and air pollution (e.g., Grange et al, 2020;Venter et al, 2020).…”

Comment on acp-2020-1262

“…Hence the EM27/SUN can be deployed and relocated quickly and inexpensively, while still adequately sampling the desired emission sources. Using multiple EM27/SUNs in an upwind-downwind configuration has been proven to be an effective way to measure methane emissions from dairy farms (Chen et al, 2016;Viatte et al, 2017) and coal mining areas (Luther et al, 2019), and some work has explored their usefulness in cities (Hase et al, 2015;Chen et al, 2020;Dietrich et al, 2020). There is also a coordinated effort to build a world wide network of these sensors (Frey et al, 2019).…”

“…These fugitive emissions are a significant source of methane in some cities (Townsend-Small et al, 2012;McKain et al, 2015;Chen et al, 2020), but their detection and quantification is difficult (Phillips et al, 2013;Brandt et al, 2014). Governments have established goals for mitigating these emissions (Rosenzweig et al, 2010), creating a need for long term measurement systems to monitor progress and identify areas where action is needed (Gurney et al, 2015;Dietrich et al, 2020).…”