Saharan dust (SD) can be transported over long distances by large-scale atmospheric circulation. SD events (SDE) occur 30 to 150 times each year at the high-altitude station of the Jungfraujoch (JFJ) in the Swiss Alps. The SD detection method, applied since 2001, is based on the inversion of the single scattering albedo wavelength dependence caused by the higher coarse-mode fraction and the chemical composition of dust. Here, the reproducibility of the SD detection by different types of nephelometers and absorption photometers is first investigated and is then compared to detections based on the observed concentration of coarse-mode aerosol, source sensitivities simulated with FLEXPART as well as to the dust index provided by the Copernicus Atmospheric Monitoring Service. The difference in SD detection is stronger for various nephelometer types than for various absorption photometers. Each detection method has advantages and weakness and no one can be considered as reference. The climatology of the 23-year time series of dust hours and dust mass at the JFJ shows that the temporal influence of dust is strongest from February to June, and in October and November, whereas the dust mass is higher in spring than in fall. The SDEs detected by a high coarse-mode particle concentration have different sources and pathways to Europe than the ones detected by the optical method. The inhomogeneity in the SD time series and the high inter-annual variability restrain the evaluation of long-term trends.

Major metropolitan areas are critical carbon emission hotspots, and understanding their carbon dynamics is essential for developing targeted climate mitigation strategies. Remote background stations often capture spatially smoothed anthropogenic signals, failing to resolve distinct urban source-sink processes. Here, we leveraged the unique 632 m Shanghai Tower (121.51 degrees E, 31.23 degrees N) to conduct a nearly 2-year field campaign (April 2021-March 2023), aiming to investigate CO2 and CO dynamic from the top of urban canopy layer (UCL) via stationary, continuous, single-level, high-precision, in situ measurements with a cavity ringdown laser spectrometer. Campaign-averaged mole fractions substantially exceeded global and regional backgrounds, confirming a pronounced urban carbon burden. Through a multi-stage filtering framework targeting nocturnal measurements, we derived robust regional background values. Component analysis of CO2 excess, using CO as a reliable regional combustion tracer, revealed burning of fossil fuels as the dominant contributor (avg. 85 %), alongside biogenic processes that enhanced this atmospheric excess, especially in winter under respiratory predominance, but less so in summer when partially offset by net photosynthetic uptake and cleaner airmass dilution. The 2022 Shanghai lockdown provided a natural experiment that underscored the pronounced sensitivity of UCL-top observations to metropolitan-scale anthropogenic perturbations, as reflected in synchronized decline and rapid rebound of CO2 and CO, along with a marked reversal of their emission ratio compared to 2021. Overall, these findings affirm that UCL-top observations effectively capture integrated metropolitan carbon signals, supporting refined emission tracking and top-down carbon neutrality strategies.

Abstract. Radiocarbon (14C) is a valuable tracer to determine the relative fossil fractions of emitted carbonaceous greenhouse gases, such as CO2 and CH4. While atmospheric Δ14CO2 measurements have been conducted at multiple sites for several decades, Δ14CH4 measurements remain more limited, mainly due to measurement challenges. In addition, 14CH4 emissions from nuclear power plants (NPPs) can complicate data interpretation. In this study, fortnightly Δ14CH4 and Δ14CO2 measurements at the Swiss High-Altitude Research Station Jungfraujoch (JFJ, about 3500 m a.s.l.) between 2019 and 2024 are presented. Over this period, Δ14CH4 values showed an increase from 350 ± 19 ‰ to 381 ± 13 ‰, while Δ14CO2 values decreased from −2.0 ± 3.8 ‰ to −12.7 ± 2.0 ‰, respectively. The former is related to the slight increase of 14CH4 emissions from the nuclear industry over the last years, while the latter is linked to the continued dilution of the 14CO2 signal due to the release of 14C-devoid CO2 from combustion of fossil fuels. Despite its high elevation, JFJ is still influenced by NPPs operating in Europe. To assess the nuclear 14C contribution to our individual measurements, we use a combination of in situ 222Radon measurements and Lagrangian particle dispersion model convolved with bottom-up inventory of 14C emissions from NPPs. Furthermore, our Δ14CH4 measurements reasonably agree with simulated atmospheric values of Δ14CH4 estimated by a global atmospheric one-box model and an estimation of global nuclear 14CH4 emissions.

Abstract. Atmospheric aerosols in the free troposphere (FT) exert a disproportionate influence on climate forcing yet remain poorly constrained. Here, we present an 11-year (2011–2021) characterization of PM10 chemical composition at the High Altitude Research Station Jungfraujoch (3580 m above sea level), capturing both FT conditions and episodic planetary boundary layer intrusions (PBLi). We integrate long-term measurements of organic aerosol (OA), elemental carbon, sulfate, crustal elements, trace metals, and bulk and molecular-level organic composition with gas-phase observations and proxies for atmospheric transport and oxidative capacity to quantify the drivers of aerosol loading and composition. The concentrations of primary aerosol species, including metals and elemental carbon, are strongly controlled by episodic PBL-to-FT transport (2-3-fold seasonal amplitude, e.g. 0.15 to 0.3 ng m-3 for Pb). Secondary species, including sulfate and OA, also reflect PBLi impact, but their formation requires sustained oxidative processing, for which the atmospheric humidity ratio (ω) acts as a key control. OA exhibits the strongest seasonal amplitude (10-fold, 0.1 to 1 μg m-3), additionally reflecting enhanced biogenic emission intensities in the PBL. This is accompanied by a systematic shift in C9 and C10 compounds, likely related to seasonal maxima in monoterpene emissions. Together, these results demonstrate that FT aerosol is governed by a dynamic interplay between episodic PBL-FT transport, source emission intensities and oxidative processing. This dataset constrains their relative contributions, and provides decade-scale observational benchmarks for improving the representation of transport and aging in atmospheric models, with implications for reducing uncertainties in climate forcing.

Long-term measurements of atmospheric composition are essential for understanding regional and global climate impacts. Although the Global Atmosphere Watch (GAW) programme provides a network of worldwide measurements, continuous atmospheric measurements across Africa remain scarce. This study presents multi-year in-situ measurements of trace gases and black carbon from the Mount Kenya GAW station (MKN) from 2020 to 2024, offering a unique dataset from equatorial Africa. Its location exposes MKN to contrasting air masses from both hemispheres, enabling detection of emissions and providing insights into tropical variability such as seasonal and diurnal cycles. We present carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), ozone (O-3), and black carbon (BC) measurements and describe seasonal and diurnal variability. Atmospheric transport modelling combined with emissions estimates for CO and methane were used to distinguish African and non-African contributions to greenhouse gases and air pollution. CO and BC were mainly linked to household fuel use and industrial energy, with biomass burning contributing during dry seasons. Methane variability was driven by agriculture and seasonal wetlands, but large uncertainties remain in all emission estimates. We further compare the measurements from 2020-2024 with trace-gas data from 2002-2012. More positive trends were observed for CO2 and CH4 in agreement with global patterns, whereas O-3 exhibited non-significant positive trends in the recent period, consistent with findings from previous studies. CO trends were less conclusive due to the influence of sporadic biomass burning events, which complicate long-term trend detection. Comparison of the observations with Copernicus Atmospheric Monitoring Service (CAMS) model products shows CAMS fails to capture O-3 and BC dynamics during rainy seasons. Overall, our results demonstrate the value of MKN observations for evaluating atmospheric models and emission inventories, and underscore the urgent need to expand measurement infrastructure across Africa to improve understanding of atmospheric processes and climate impacts.

Abstract Accurately separating the contributions of different sources to recent atmospheric methane (CH 4 ) growth is crucial for better quantifying the present and future responses of CH 4 emissions to changing climate and anthropogenic activity. Here, we run atmospheric inversions to assess global and regional CH 4 emissions from microbial, fossil, and pyrogenic sources from 2000 to 2022, using measurements of atmospheric CH 4 and its stable carbon isotope ratio ( 13 C: 12 C, expressed relative to a standard as δ 13 C-CH 4 ). We confirm that global total CH 4 emissions has increased by 15% from 2000 to 2022, with dominated contribution from microbial emissions. Both microbial and fossil emissions increased during 2007–2013 relative to 2000–2006, with the largest contributions from temperate Asia. From 2014–2017, microbial emissions from tropical regions, particularly South America and Africa, were the dominant driver of the overall increase, while fossil emissions remained stable in Europe and North America. Between 2020 and 2022, microbial emissions surged in the African and Asian tropics, whereas fossil emissions declined across most industrial regions. Notably, inversions constrained only by CH 4 observations did not capture the decline in fossil emissions during 2020–2022, a decline potentially related to the COVID-19 pandemic, policy-driven changes, and decreases in CH 4 emissions intensity, highlighting the critical role of isotopic measurements in independently verifying changes in fossil emissions. Further, our inversion with isotopic constraints estimates a more prominent increase in wetland emissions that is 20–30% more strongly correlated with variations in terrestrial water storage during 2003–2022, demonstrating the importance of climate-driven natural sources in explaining long-term CH 4 growth.

To tackle the planetary environmental and climate crisis and meet the United Nations’ Sustainable Development Goals (SDGs), we must fully leverage the potential of Earth observations (EO). This involves integrating globally sourced data on the atmosphere, hydrosphere, cryosphere, lithosphere, along with ecological and socio-economic information. By harmonizing and integrating these diverse data sources, we can more effectively incorporate observational data into multi-scale modeling and artificial intelligence (AI) frameworks. This paper is based on discussions from the “Towards Global Earth Observatory” workshop held from May 8–10, 2023, organized by the World Meteorological Organization (WMO) and the Atmosphere and Climate Competence Center (ACCC), in collaboration with the Institute for Atmospheric and Earth System Research (INAR) at the University of Helsinki. The current state of EO and data repositories is fragmented, highlighting the need for a more integrated approach to establish a new global Ground-Based Earth Observatory (GGBEO). Here, we summarize the current status of selected in-situ and ground-based remote sensing observation systems and outline future actions and recommendations to meet scientific, societal, and economic needs. In addition, we identify key steps to create a coordinated and comprehensive GGBEO system that leverages existing investments, networks, and infrastructures. This system would integrate regional and global ground-based in situ and remote sensing systems, marine, and airborne observational data. An integrated approach should aim for seamless coordination, interoperable and harmonized data repositories, easily searchable and accessible data, and sustainable long-term funding.

The Global Atmosphere Watch (GAW) Programme of the World Meteorological Organization coordinates a worldwide network of hundreds of ground-based in-situ monitoring stations that provide reliable scientific data on the chemical composition of the atmosphere. Within the framework of the GAW Programme, the Quality Assurance/Scientific Activity Centre Switzerland has developed a web app (GAW-QC, available at www.empa.ch/gaw, see also Brugnara et al., 2024) to support station operators in timely detecting issues in their in-situ measurements of various trace gases.GAW-QC consists of a dashboard that highlights anomalous values using a mixture of purely data-driven and hybrid anomaly detection techniques. It exploits historical measurements made at the target station as well as the archive of gridded numerical forecasts by the Copernicus Atmosphere Monitoring Service (CAMS). The accuracy of the latter for the specific site is improved through machine learning using multiple predictors, including meteorological parameters and aerosol concentrations.The app allows station operators to upload their latest measurements, visualize the data with different temporal aggregations, and detect anomalous values using just their internet browser. By combining the information gathered from the dashboard with logbook entries and local expertise, they can effectively flag problematic measurements and even detect instrumental issues that would remain unnoticed otherwise. First case studies indicate that this process can indeed facilitate the detection of malfunctions in the analytical setup and reduce the ingestion of erroneous data into international data repositories. Moreover, it has the potential to shorten data gaps if applied timely.GAW-QC is publicly available and can be used to analyze historical time series of carbon dioxide, carbon monoxide, methane, and ozone made at 98 GAW stations worldwide. The applicability to a given station depends on whether historical data have been submitted to the GAW world data centers by the station operator. Additional gas species may be added in the future depending on user feedback. Brugnara, Y., Steinbacher, M., Baffelli, S., and Emmenegger, L.: Technical note: An interactive dashboard to facilitate quality control of in-situ atmospheric composition measurements, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-3556, 2024.

Climate change is having an accelerating global impact through the increased frequency, magnitude and duration of droughts, fires, floods and other extreme climatic events. The most vulnerable populations bear the greatest brunt of these impacts. The societal solutions to this crisis depend also on how scientific research can address the air quality-climate-health nexus. Observations are needed as a foundation for air quality and climate services to address UN Sustainable Development Goals (SDGs). The atmospheric observing capabilities in most countries in Low- and Middle Income Countries (LMIC) remain often sketchy and heterogeneous, are established based on opportunities, and often not designed for integration into the operational infrastructures of the National Meteorological and Hydrological Services. As a result, operation often lacks sustainability and compatibility, and data are not easily and widely available. This is true for meteorological and climatological observations, but is even more pronounced for the complex instrumentation required to monitor greenhouse gases and short-lived climate pollutants. The development of standardised observations in sustainable research infrastructures (RIs) can overcome some of these issues.The Horizon Europe funded KADI project (Knowledge and climate services from an African observation and Data research Infrastructure) aims to provide the conceptual framework for the future implementation of an All-African RI that delivers the science-based services to fully address the requirements of the Paris agreement and the SDGs.The KADI project works towards the development of a comprehensive design for a pan-African climate observation system and research infrastructure using the climate services identified and required by key stakeholders as a guiding design principle. Knowledge is compiled and gaps identified through the SEACRIFOG collaborative inventory tool, the OSCAR/Surface, OSCAR/Space and OSCAR/Requirements tools, as well as a comprehensive survey and other stakeholder engagement. A pilot project focused on Kenya collects and integrates information on user requirements, existing and past observing capabilities, and services. Based on extensive engagement with stakeholders who use or provide weather, climate and atmospheric composition services, lessons-learnt and best practices for future endeavours will be distilled. The outputs from this will further inform the strategic design of the long-term observational and data infrastructures required.The results so far suggest that services need to cover diverse requirements of a wide range of stakeholders. Sustainable standardized observations are a critical foundation. Sustainability requires long-term commitment of the operating institution at various organizational levels. Information derived from observations is often required with short lead times. Twinning programs and personnel exchange between new and established stations or laboratories can be effective to advance and transition new monitoring capabilities into full operation. The presentation will introduce the approaches and first results.

In-situ measurements of trace gases are crucial for monitoring changes in the atmosphere's composition and understanding the underlying processes that drive them. For over three decades, the Global Atmosphere Watch (GAW) programme of the World Meteorological Organization (WMO) has coordinated a network of surface monitoring stations and facilities with the goal of providing high-quality atmospheric composition measurements worldwide. One of the critical challenges towards this goal is the spatially unbalanced availability of high-quality time series, and the lack of near-realtime quality control (QC) procedures that would allow the prompt detection of unreliable data. Here, we describe an interactive dashboard designed for GAW station operators, but which may be of much wider use, that is able to flag anomalous values in near-realtime or historical data. The dashboard combines three distinct algorithms that identify anomalous measurements: (i) an outlier detection based on the Subsequence Local Outlier Factor (Sub-LOF) method, (ii) a comparison with numerical forecasts coupled with a machine learning model, and (iii) a Seasonal Autoregressive Integrated Moving Average (SARIMA) regression model. The application, called GAW-QC, can process measurements of methane (CH4), carbon monoxide (CO), carbon dioxide (CO2), nitrous oxide (N2O), and ozone (O3) at hourly resolution, offering multiple statistical and visual aids to help users to identify problematic data. By enhancing QC capabilities, GAW-QC contributes to the GAW programme's goal of providing reliable atmospheric measurements worldwide.

We perform a global inverse modelling analysis to quantify biomass burning emissions of carbon monoxide (CO) from the extreme wildfires in Canada between May and September 2023. Using the GEOS-Chem model, we assimilated observations at 3 d temporal and 2° × 2.5° horizontal resolution from the Tropospheric Monitoring Instrument (TROPOMI) separately and then jointly with Total Carbon Column Observing Network (TCCON) measurements. We also evaluated prior emissions from the Quick Fire Emissions Dataset (QFED), Blended Global Biomass Burning Emissions Product eXtended (GBBEPx), Global Fire Assimilation System (GFAS), and Canadian Forest Fire Emissions Prediction System (CFFEPS). The assimilation of TROPOMI-only measurements estimated posterior North America emissions for QFED, GBBEPx, GFAS, and CFFEPS of 110.4 ± 20, 112.8 ± 20, 127.2 ± 17, and 125.6 ± 18 Tg CO compared to prior estimates of 37.1, 42.7, 91.0, and 90.2 Tg CO, respectively. The joint assimilation of TROPOMI+TCCON reduced the posterior 1σ uncertainty on the North American emission estimates by up to about 30 %, while showing only a modest impact (<5 %) on the mean estimate of the inferred emissions. An evaluation against independent measurements reveals that adding TCCON data increases the correlations and slightly lowers the biases and standard deviations. Additionally, including an experimental TCCON product at East Trout Lake with higher surface sensitivity, we find better agreement of the assimilation results with nearby in situ tall tower and aircraft measurements. This highlights the potential importance of vertical sensitivity in these experimental data for constraining local surface emissions. Our results demonstrate the complementarity of the greater temporal coverage provided by TCCON with the spatial coverage of TROPOMI when these data are jointly assimilated.

The global annual mean atmospheric CO2 growth rate in 2023 was one of the highest since records began in 1958, comparable to values recorded during previous major El Niño events. We do not fully understand this anomalous growth rate, although a recent study highlighted the role of boreal North American forest fires. We use a Bayesian inverse method to interpret global-scale atmospheric CO2 data from NASA's Orbiting Carbon Observatory (OCO-2). The resulting a posteriori CO2 flux estimates reveal that from 2022 to 2023, the biggest changes in CO2 fluxes of net biosphere exchange (NBE) – for which positive values denote a flux to the atmosphere – were over the land tropics. We find that the largest NBE increase is over eastern Brazil, with small increases over southern Africa and Southeast Asia. We also find significant increases over southeastern Australia, Alaska, and western Russia. A large NBE increase over boreal North America, due to fires, is driven by our a priori inventory, informed by independent data. The largest NBE reductions are over western Europe, the USA, and central Canada. Our NBE estimates are consistent with gross primary production estimates inferred from satellite observations of solar-induced fluorescence and from satellite observations of vegetation greenness. We find that warmer temperatures in 2023 explain most of the NBE change over eastern Brazil, with hydrological changes more important elsewhere across the tropics. Our results suggest that the ongoing environmental degradation of the Amazon is now playing a substantial role in increasing the global atmospheric CO2 growth rate.

In recent years, the field of laser spectroscopy has witnessed significant progress, leading to major advancements in the detection of atmospheric trace gases. This technological evolution is reflected in a growing number of commercial implementations, especially for prevalent atmospheric gases, such as carbon dioxide (CO2) and methane (CH4). The spectrum of detectable trace gases continues to expand, and manufacturers offer instruments with increasing performance in term of selectivity, sensitivity, power consumption, compactness and cost-effectiveness. In this presentation, we focus on recent instruments for the observation of atmospheric nitrous oxide (N2O). N2O is a major long-lived greenhouse gas which plays an important role in stratospheric ozone depletion, but still suffers from inadequate global data coverage. Therefore, the advent of more economical yet resilient instruments, demanding less space and power compared to conventional models, presents a welcome opportunity to broaden the N2O monitoring network. We provide an overview of laboratory tests carried out at Empa on a variety of commercial models. The evaluated techniques include (i) Mid-IR Tunable Diode Laser Spectrometry (TDLAS) with Interband Cascade Lasers (ICLs) and Quantum Cascade Lasers (QCL), (ii) Optical Feedback – Cavity Enhanced Absorption Spectroscopy (OF-CEAS), (iii) Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS), and (iv) Cavity Ringdown Spectroscopy (CRDS). The tests assessed the suitability of the instruments for precise atmospheric N2O monitoring and provide insights into the operation, data handling and quality assurance / quality control procedures required for long-term operation. Particular attention was paid to the evaluation of the short-term precision and stability of the instrument response and the repeatability within days to weeks. Overall, the instrument performance is still superior for the most-established CRDS and OA-ICOS analyzers, which are widely used in the Global Atmosphere Watch (GAW) programme and the European Integrated Carbon Observation System Research Infrastructure (ICOS-RI). Nevertheless, the latest generation of TDLS and OF-CEAS instruments are cost-efficient alternatives, which may be suited for more extensive networks, such as the ones to be designed under the umbrella of World Meteorological Organization's new Global Greenhouse Gas Watch (G3W) programme. However, great care needs to be taken in terms of quality assurance and quality control (QA/QC) to ensure long-term accuracy and traceability. The most cost-efficient instrumental components still need to be identified as a function of the scientific targets and the related network design.

Ultrafine particles (UFPs; i.e., atmospheric aerosol particles smaller than 100 nm in diameter) are known to be responsible for a series of adverse health effects as they can deposit in humans' bodies. So far, most field campaigns studying the sources of UFPs have focused on urban environments. This study investigates the outdoor sources of UFPs at the atmospheric monitoring station in Payerne, which represents a typical rural location in Switzerland. We aim to quantify the primary and secondary fractions of UFPs based on specific measurements between July 2020 and July 2021 complementing a series of operational meteorological, trace gas and in situ aerosol observations. To distinguish between primary and secondary contributions, we use a method that relies on measuring the fraction of non-volatile particles as a proxy for primary particles. We further compare our measurement results to previously established methods. We find that primary particles resulting from traffic and residential wood burning (direct emissions – mostly non-volatile BC-rich) contribute less than 40 % to the total number of UFPs, mostly in the Aitken mode. On the other hand, we observe local new particle formation (NPF) events (observed from ∼ 1 nm) evident from the increase in cluster ions (1.5–3 nm) and nucleation-mode particle (2.5–25 nm) concentrations, especially in spring and summer. These events, mediated by sulfuric acid, contribute to increasing the UFP number concentration, especially in the nucleation mode. Besides NPF, the chemical processing of particles emitted from multiple sources (including traffic and residential wood burning) contributes substantially to the nucleation-mode particle concentration. Under the present conditions investigated here, we find that secondary processes mediate the increase in UFP concentration to levels equivalent to those in urban locations, affecting both air quality and human health.

Awareness of atmospheric air quality in Switzerland became a concern in the 1960s, as a result of which the Swiss National Air Pollution Monitoring Network (Nationales Beobachtungsnetz für Luftfremdstoffe - NABEL) was created in the 1970s. This paper describes the establishment and evolution of NABEL, emphasizing its important role in monitoring air quality in Switzerland, and its contribution to international observation networks and research. The network’s history, legal framework, and measurement program are described, and exemplary time-series of air quality parameters are given. NABEL is an excellent example for reliable, long-term air quality monitoring and demonstrates the importance of such monitoring for air pollution control at both national and international levels.

The Global Atmosphere Watch (GAW) Programme of the World Meteorological Organization coordinates a worldwide network of hundreds of ground-based in-situ monitoring stations that provide reliable scientific data on the chemical composition of the atmosphere. In the framework of the GAW Programme, the Quality Assurance/Scientific Activity Centre at Empa has developed an interactive dashboard based on data science to support station operators in timely detecting issues in their in-situ measurements of various trace gases.The application (GAW-qc), currently in beta testing, makes use of a mixture of purely data-driven and hybrid anomaly detection techniques. It exploits historical measurements made at the target station as well as the archive of gridded numerical forecasts by the Copernicus Atmosphere Monitoring Service (CAMS). The accuracy of the latter for the specific site is improved through machine learning using various predictors, including meteorological parameters and aerosol concentrations.GAW-qc allows station operators to upload their latest measurements, visualize the data with different temporal aggregations, and easily detect anomalous values using just their internet browser. By combining the information gathered from the dashboard with logbook entries and local expertise, they can effectively flag problematic measurements and even detect instrumental issues that would remain unnoticed otherwise. First case studies indicate that this process can indeed facilitate the detection of malfunctionings in the analytical setup and reduce the ingestion of erroneous data into the international data repositories. Moreover, it has the potential to shorten data gaps if applied timely. Therefore, it may become a game-changer towards reliable, comparable and traceable world-wide datasets in the field of air quality and greenhouse gases. The software is freely available through a GitHub repository and can be adapted to analyze other atmospheric variables.