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The impact of heterogeneous uptake of HO2 on aerosol surfaces on radical concentrations and the O3 production regime in Beijing in summertime was investigated. The uptake coefficient of HO2 onto aerosol surfaces, γHO2, was calculated for the AIRPRO campaign in Beijing, in summer 2017, as a function of measured aerosol soluble copper concentration, [Cu2+]eff, aerosol liquid water content, [ALWC], and particulate matter concentration, [PM]. An average γHO2 across the entire campaign of 0.070±0.035 was calculated, with values ranging from 0.002 to 0.15, and found to be significantly lower than the value of γHO2=0.2, commonly used in modelling studies. Using the calculated γHO2 values for the summer AIRPRO campaign, OH, HO2 and RO2 radical concentrations were modelled using a box model incorporating the Master Chemical Mechanism (v3.3.1), with and without the addition of γHO2, and compared to the measured radical concentrations. The rate of destruction analysis showed the dominant HO2 loss pathway to be HO2 + NO for all NO concentrations across the summer Beijing campaign, with HO2 uptake contributing % to the total loss of HO2 on average. This result for Beijing summertime would suggest that under most conditions encountered, HO2 uptake onto aerosol surfaces is not important to consider when investigating increasing O3 production with decreasing [PM] across the North China Plain. At low [NO], however, i.e. ppb, which was often encountered in the afternoons, up to 29 % of modelled HO2 loss was due to HO2 uptake on aerosols when calculated γHO2 was included, even with the much lower γHO2 values compared to γHO2= 0.2, a result which agrees with the aerosol-inhibited O3 regime recently proposed by Ivatt et al. (2022). As such it can be concluded that in cleaner environments, away from polluted urban centres where HO2 loss chemistry is not dominated by NO but where aerosol surface area is high still, changes in PM concentration and hence aerosol surface area could still have a significant effect on both overall HO2 concentration and the O3 production regime. Using modelled radical concentrations, the absolute O3 sensitivity to NOx and volatile organic compounds (VOCs) showed that, on average across the summer AIRPRO campaign, the O3 production regime remained VOC-limited, with the exception of a few days in the afternoon when the NO mixing ratio dropped low enough for the O3 regime to shift towards being NOx-limited. The O3 sensitivity to VOCs, the dominant regime during the summer AIRPRO campaign, was observed to decrease and shift towards a NOx-sensitive regime both when NO mixing ratio decreased and with the addition of aerosol uptake. This suggests that if [NOx] continues to decrease in the future, ozone reduction policies focussing solely on NOx reductions may not be as efficient as expected if [PM] and, hence, HO2 uptake to aerosol surfaces continue to decrease. The addition of aerosol uptake into the model, for both the γHO2 calculated from measured data and when using a fixed value of γHO2=0.2, did not have a significant effect on the overall O3 production regime across the campaign. While not important for this campaign, aerosol uptake could be important for areas of lower NO concentration that are already in a NOx-sensitive regime.

Field observation networks are becoming denser, more diverse, and more mobile, while being required to provide real-time results. The ERC urbisphere program is coordinating multiple field campaigns simultaneously to collect datasets on urban atmospheric and environmental conditions and processes in cities of different sizes. The datasets are used for improving climate and weather models and services, including assessing the impact of cities on the atmosphere (e.g. aerosols, greenhouse gases) as well as the exposure of urban populations in the context of atmospheric extreme events (heat waves, heavy precipitation, air pollution). For model development and evaluation, we are using meshed networks of in-situ observations with ground-based and airborne (remote-)sensing platforms. This contribution describes the urbisphere data management infrastructure and processes required to handle a variety of data streams from primarily novel modular observation systems deployed in complex urban environments.The modular observation systems consist of short-term deployed instrumentation and are separated into three thematic modules. Module A aims at characterizing urban form and function affecting urban climates. Module B quantifies the impact of urban emissions (heat, pollutants, greenhouse gases, etc.) on the urban boundary layer over and downwind of cities. Module C provides data on human exposure at street and indoor-level. The three modules are served with consistent data management, documentation and calibration. Systems deployed in Modules A, B and C include customized automatic weather stations, (Doppler) lidars and ceilometers, scintillometers, balloon radio sounding and spectral camera imaging. Systems are street-light-mounted, located on building roof-tops or indoors as well as on mobile platforms (vehicles, drones). Data ingestion processes are automated, delivering moderate data volumes in real-time to central data infrastructure through mobile phone and IOT connectivity. A meta data system helps keep track of the location and configuration of all deployed components and forms the backbone for conversion of instrument records into location-aware, conventions-aligned and quality-assured F.A.I.R. data products. Furthermore, the data management infrastructure provides services (APIs, Apps, IDEs, etc.) for data inspection and computations by scientists and students involved in the campaigns. Select datasets are integrated in near real-time into other global or local data systems such as, e.g., AERONET, the Phenocam Network, ICOS, or PANAME, for multiple uses.Besides technical aspects and design considerations, we discuss how cooperation and attribution are safeguarded when data are being accessed for immediate academic and citizen data science.

Atmospheric boundary layer (ABL) dynamics severely impact the horizontal transport of pollutants as well as their vertical dilution. Despite this, observations of vertical wind profiles and the ABL height are still rare, particularly in cities. Thanks to recent technological advances compact ground-based remote sensing instruments are now available to monitor the heterogeneous urban atmosphere across dense sensor networks. In urban settings, Doppler wind lidars (DWL) and automatic lidars and ceilometers (ALC) are particularly useful as they operate continuously and automatically with very low maintenance under all weather conditions. Thanks to those novel profiling instruments, high-resolution (time and vertical) wind information as well as aerosol backscatter profiles can be recorded.Based on the RI-URBANS (and ICOS-cities) pilot city of Paris, France, we demonstrate what advanced products can be derived using different detailed algorithms, including vertical profiles of horizontal wind and turbulence, boundary layer heights based on aerosol or turbulence indicators, as well as low-level jet characteristics. In Paris, RI-URBANS is embedded in the PANAME initiative that coordinates the synergy between numerous projects that are investigating the urban atmosphere. Clear measurement standards, careful quality control and advanced processing algorithms are required to ensure harmonised products are obtained from the diverse sensor networks that involve instruments of different models from various manufacturers with respective capabilities and limitations.Using the synergy of the different ABL products obtained in the Paris region, it is investigated how the urban boundary layer interacts with the synoptic scale flow, the underlying topography and the urban surface. A combination of wind direction, atmospheric stability and terrain clearly affect shallow boundary layer heights and the low-level jet characteristics. But also spatial variations across the region are registered during deep convective boundary layer development.

The international ACROSS (Atmospheric ChemistRy Of the Suburban forest) intensive field measurement campaign (supported by the Make Our Planet Great Again initiative) took place from June 13 to July 25 2022 in and around the Ile-de-France during an exceptional hot (more than 3°C above the climatological mean for France) and dry summer season. This work will provide a broad classification of weather conditions that occurred during the campaign, useful for further analysis of observations and simulations. Weather scenarios will be analysed in terms of synoptic weather situations, relating transport patterns (regional advection to the Ile-de-France region, plumes from Paris agglomeration), temperature and relative humidity evolution. During the June-July 2022 period, several distinct weather and pollution patterns occurred, among which: (1) two strong heatwaves, with large photochemical activity promoting secondary pollutants build-up (O3, SOA), (2) advection of relatively clean oceanic air masses, and (3) Saharan dust and intense forest fire events with dust and fire aerosol advection to the Ile-de-France region. The analysis is based on meteorological data from several models (GFS, WRF, ARPEGE, AROME) and observations, pollution forecasts from the French Prev’Air system (http://www2.prevair.org/), and from the AirParif Esmeralda platform (http://www.esmeralda-web.fr/accueil/) that have been used for the airborne campaign support. In addition, dedicated simulations with the CHIMERE model (see companion abstract by Di Antonio et al. for this session), and major pollutant observations by air quality networks, from satellites, or performed within ACROSS will be used to analyse how meteorological conditions and weather patterns impacted the spatial distributions of major primary and secondary chemical species. Especially tracers of anthropogenic and biogenic emissions and photochemical activity (O3, PM2.5, OA, BC, NOx, BVOC) will be analysed. Keywords: Meteorology, pollutant distributions, transport patterns, ACROSS, MOPGA

The urban is at the heart of many disciplinary projects covering very broad scientific areas. Acquired data or simulations are often accessible (when they are) via targeted thematic portals. However, the need for transdisciplinarity has been essential for several years to answer specific scientific questions or societal demands. For this, the crossing of human sciences data, health, air quality, land use, emissions inventories, biodiversity, etc., would allow new innovative studies in connection with the city.PANAME (PAris region urbaN Atmospheric observations and models for Multidisciplinary rEsearch) developed by AERIS was designed as the first brick of a data portal that can promote the discovery, access, cross-referencing and representation of urban data from various sectors with air quality and urban heat islands as a starting point. The portal and future developments will be discussed in this presentation.

Existing CO2 emissions reported by city inventories usually lag real-time by a year or more and are prone to large uncertainties. This study responds to the growing need for timely and precise estimation of urban CO2 emissions to support the present and future mitigation measures and policies. We focus on the Paris metropolitan area, the largest urban region in the European Union and the city with the densest atmospheric CO2 observation network in Europe. We performed long-term atmospheric inversions to quantify the citywide CO2 emissions, both fossil fuel and biogenic sources and sinks, over six years (2016–2021) using a Bayesian inverse modeling system. Our inversion framework benefits from a novel near-real-time hourly fossil fuel CO2 emission inventory (Origins.earth) at 1 km spatial resolution. In addition to the mid-afternoon observations, we attempt to assimilate morning CO2 concentrations based on the ability of the WRF-Chem transport model to simulate atmospheric boundary layer dynamics constrained by observed layer heights. Our results show a long-term decreasing trend by around 2 % per year in annual CO2 emissions over the Paris region. The impact of COVID-19 pandemic led to a 13 %±1 % reduction in annual fossil fuel CO2 emissions in 2020 with respect to 2019. Then, annual emissions increased by 5.2 % from 32.6±2.2 MtCO2 in 2020 to 34.3±2.3 MtCO2 in 2021. Based on a combination of up-to-date inventories, high-resolution atmospheric modeling, and high-precision observations, our current capacity could deliver near real-time CO2 emission estimates at city scale in less than a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.

The atmospheric boundary layer (ABL) defines the volume of air adjacent to the Earth’s surface for the dilution of heat, moisture, and trace substances. Quantitative knowledge on the temporal and spatial variations in the heights of the ABL and its sub-layers is still scarce, despite their importance for a series of applications (including, for example, air quality, numerical weather prediction, greenhouse gas assessment, and renewable energy production). Thanks to recent advances in ground-based remote-sensing measurement technology and algorithm development, continuous profiling of the entire ABL vertical extent at high temporal and vertical resolution is increasingly possible. Dense measurement networks of autonomous ground-based remote-sensing instruments, such as microwave radiometers, radar wind profilers, Doppler wind lidars or automatic lidars and ceilometers are hence emerging across Europe and other parts of the world. This review summarises the capabilities and limitations of various instrument types for ABL monitoring and provides an overview on the vast number of retrieval methods developed for the detection of ABL sublayer heights from different atmospheric quantities (temperature, humidity, wind, turbulence, aerosol). It is outlined how the diurnal evolution of the ABL can be monitored effectively with a combination of methods, pointing out where instrumental or methodological synergy are considered particularly promising. The review highlights the fact that harmonised data acquisition across carefully designed sensor networks as well as tailored data processing are key to obtaining high-quality products that are again essential to capture the spatial and temporal complexity of the lowest part of the atmosphere in which we live and breathe., European Cooperation in Science and Technology (COST) PTDC/CTAMET/29678/2017 European Commission, French National Research Agency (ANR) Region Ile-de-France, Spanish Government, Junta de Andalucia, University of Granada, Programa Operativo FEDER Andalucia 2014-2020, Earth System Excellence Units Program, Marie Sklodowska-Curie Action Cofund 2016 EU project - Athenea3i national Portuguese funds through FCT - Fundacao para a Ciencia e Tecnologia, I.P. CA18235 871115 101036245 ANR-20-CE22-0013 PID2020-120015RB-I00 PID2020.117825GB.C21 P18-RT-3820 P20-00136 A-RNM-430-UGR20 754446 UIDB/04683/2020

The main research goal of this paper is to identify the most likely source regions of pollution events at Beromünster, Switzerland. Trace gas concentration and flux observations are essential to investigate emission source regions of greenhouse gases (GHGs) and other pollutants. Here we present an analysis of observations taken at an altitude of 212 m above ground at one of the few European tall towers located close to Beromünster, Switzerland (2017–2020). The relatively high observation height — especially for flux measurements — results in a large tower footprint, i.e., area sampled by the tower, predestined for a source analysis on a large scale. We identify high observations and analyze subsets of the concentrations and fluxes by atmospheric stability conditions (local vertical temperature gradient and atmospheric boundary layer height) to distinguish shorter from longer transport distances. And we split the data by prevailing wind direction as an additional separation of potential source regions. Furthermore, we perform inter-species correlation analyses and a parameterized Flux Footprint (FFP) estimation for the tower. We find that pollution events at Beromünster tower are not associated with local emission sources, but are transported from further away — most prominently from the Northeast (NE) and Southeast (SE), where Zurich and Luzern are located, respectively. All species concentrations are highly correlated during winter, while in summer only a limited inter-species correlation exists. The parameterized annual mean FFP shows an extent of roughly 50-x-25 km along and perpendicular to the main wind axis, respectively.

A total of 20 urban neighbourhood-scale eddy covariance flux tower datasets are made openly available after being harmonized to create a 50 site–year collection with broad diversity in climate and urban surface characteristics. Variables needed as inputs for land surface models (incoming radiation, temperature, humidity, air pressure, wind and precipitation) are quality controlled, gap-filled and prepended with 10 years of reanalysis-derived local data, enabling an extended spin up to equilibrate models with local climate conditions. For both gap filling and spin up, ERA5 reanalysis meteorological data are bias corrected using tower-based observations, accounting for diurnal, seasonal and local urban effects not modelled in ERA5. The bias correction methods developed perform well compared to methods used in other datasets (e.g. WFDE5 or FLUXNET2015). Other variables (turbulent and upwelling radiation fluxes) are harmonized and quality controlled without gap filling. Site description metadata include local land cover fractions (buildings, roads, trees, grass etc.), building height and morphology, aerodynamic roughness estimates, population density and satellite imagery. This open collection can help extend our understanding of urban environmental processes through observational synthesis studies or in the evaluation of land surface environmental models in a wide range of urban settings. These data can be accessed from https://doi.org/10.5281/zenodo.7104984 (Lipson et al., 2022).

Air quality and meteorology in urban environments are strongly affected by dynamical and turbulent processes occurring in the atmospheric boundary layer. These are largely driven by the interaction between the surface and the atmosphere, including the exchange of momentum, heat, moisture, and various gases and aerosols. Vertical ventilation, horizontal advection, and atmospheric stratification are key processes.To improve the understanding of the exchange processes in the urban atmosphere and to assess the implications of spatial variations in surface roughness, spatially resolved vertical profiles of the horizontal wind are required. In this work, we are implementing a novel “volume wind processing” approach to retrieve horizontal wind information on a 3D spatial grid from observations of a scanning Doppler wind lidar (Vaisala Windcube 400s). Deployed on the rooftop of a tall building in downtown Paris, France, the Doppler lidar is operated with a series of scan strategies to monitor the vertical and horizontal variations of the mean wind field across the city center.In order to quantify the performance of the volume wind processing, an evaluation measurement campaign was performed combining measurements at the Vaisala measurement site and the SIRTA atmospheric observatory (Paris-Saclay) located 3.5 km from each other. The Windcube 400s, located on the Vaisala site, gathered measurements based on different scan patterns (full or sector (>30°) Plan-position Indicator (PPI)), from which wind profiles were retrieved using the volume wind processing. These retrievals were then compared to vertical wind profiles obtained from a previously validated and calibrated Doppler lidar (WLS70) running in a vertical profiling mode located at SIRTA. The comparison is performed over a 30-days period. We found a mean difference (Volume Wind – Vertical Stare) of -0.69 m/s and a standard deviation of 1.32 m/s for 10-min averaged profiles.The ongoing work consists of identifying the sources of uncertainty in the volume wind processing and improving the quality of the retrievals by improving quality control procedures. High-quality wind profile products will then be available for research on the spatial variability of the wind speed profiles, in order to determine the influence of the surface roughness on exchange processes in the Paris urban atmosphere.