The Metropolitan Region of Rio de Janeiro (MRRJ) has the second largest concentration of population, vehicles, industries and pollutant emission sources, according to the state government. In an attempt to broaden the understanding regarding the changes that have occurred in the urban climate as well as the role of rain in cleaning the urban atmosphere, this study aims at establishing a correlation between air quality and physical-chemical parameters of rainwater, including hydrogen potential (pH), electrical conductivity (EC) and ion concentration. The primary data obtained for the research are based upon the comparison between two sampling points: one located in an area of residential use (Maracanã neighborhood) and another located in the industrial district of the city of Rio de Janeiro (Campo Grande neighborhood). In this research, the parameters for determining air quality were selected from the database of the Municipal Secretariat of Environment (SME), whereas the collection of wind data on a regional scale was obtained through ERA5. The preliminary results of the research indicated pH values above 6.0, suggesting a neutralization of the acidic character of the rain due to the concentrations of calcium hardness and ammonia. The presence of Cℓ⁻ and CaCO₃ ions was attributed, respectively, to the effect of maritime activity, given the coastal location of the city, and to the proximity of cement industries. Therefore, it is clear that, despite little scientific attention, the analysis of rainwater is essential to understand the processes inherent to the local climate and the exposure of the population to contamination events. In addition, it is also vital to rediscuss the rainwater quality standards which are almost exclusively associated in the literature with the hydrogen potential classified as acidic.

How to cite: Manuel, T. and Oscar Júnior, A.: Revealing new processes of Urban Climate: An integrated analysis of atmospheric emissions, air pollution and rainwater quality in the city of Rio de Janeiro (Brazil)., 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-486, https://doi.org/10.5194/icuc12-486, 2025.

Multi-scale atmospheric modelling allows the integration of drivers and processes that dominate at different spatial and temporal scales. In cities, this approach is needed to capture the effects of micro-scale (building and street) impacts on local (neighborhood) and urban scale atmosphere and vice-versa. This integration is needed to understand and manage urban emissions, which are highly heterogenous over time and space. This work focusses on Carbon emissions which are the subject of urban-scale policies to create low (and even zero) Carbon cities. The research presented here couples the Weather Research Forecasting (WRF) and Model of Urban Network of Intersecting Canyons and Highways (MUNICH) models to simulate Carbon emissions in Dublin (Ireland) with a view to developing neighborhood-scale mitigation policies. Initially, WRF-chem is applied to nested domains to capture regional, national, and urban effects: the island of Ireland is simulated at a 1 km resolution and Dublin city at 250 m resolution. The model setup includes a comprehensive treatment of meteorology, land use (including urban cover using WUDAPT derived Local Climate Zones (LCZs)) and biogenic/anthropogenic emissions and sequestration. Following evaluation, the WRF simulations are used to simulate the mixing of transport-based Carbon emissions using MUNICH, which requires details on the characteristics of the street network (e.g., width and height). The Carbon emissions will be estimated based on modelled traffic flows. The results of the simulations will be compared with street-level measurements of Carbon concentrations. The objective of this work is to create a modelling infrastructure suited to the development of urban policies to mitigate Carbon emissions.

How to cite: Sati, A., Mills, G., Fealy, R., and Pilla, F.: Urban Trasport based Emissions: Multi-scale modelling approach using WRF and MUNICH models in Dublin, Ireland, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-674, https://doi.org/10.5194/icuc12-674, 2025.

Air pollution is a global threat to human health, especially in densely populated areas. Pollutant concentrations in European countries have been decreased due to legislative actions. However, non-exhaust emissions, consisting of tyre, brake and road wear, as well as road dust resuspension, remain and even tend to increase.
This study quantifies tyre and brake wear emissions using a bottom-up model for the city of Hamburg in 2018. The concentrations of these particles are simulated with the urban scale chemistry transport model EPISODE-CityChem. For this purpose, EPISODE-CityChem 1.8 has been extended to include six new particle components representing different size classes for tyre and brake wear.
The size classes are PM_2.5, PM_2.5-10 and PM₁₀₊, particles larger than 10 μm. The emission factors are based on the emission factor from the UK national atmospheric emission inventory for PM₁₀ for tyre and brake wear, respectively. These are combined with the mass size distribution of the total suspended particles according to EMEP to derive the emission factors for the other size classes.
The contribution of PM_2.5 from tyre and brake wear to the total PM_2.5 concentrations varies throughout the months between 9% and 16% at traffic stations and between 2% and 6% at urban background stations.
The particle concentrations from tyre and brake wear show local and seasonal differences, which could be a difficulty in adhering to the recommended guideline values for particle concentrations. 
The results of this study can be transferred to other large European cities with high traffic volumes and can help to understand the problem's scope, as measurements rarely differentiate between particles caused by exhaust vs. non-exhaust emissions.

How to cite: Samland, M., Badeke, R., Grawe, D., and Matthias, V.: Modelling the variability of particle concentrations from tyre and brake wear for Hamburg, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-623, https://doi.org/10.5194/icuc12-623, 2025.

Understanding the interplay between urban air quality, traffic emissions, and the impact of future urban transport landscapes on cardiometabolic health outcomes is critical for sustainable urban development. This study employs the high-resolution Parallelized Large-Eddy Simulation Model (PALM) to model air quality in the Augsburg region, focusing on spatial and temporal dynamics of traffic-related pollution. By integrating Agent-Based Modeling (ABM) using MATSim, detailed emission data from vehicle traffic based on mobility is incorporated to quantify its contribution to overall urban air pollution. The PALM configuration includes a fine-grained grid resolution, dynamic representation of urban microclimates and urban topography to realistically simulate pollutant dispersion in complex terrain. Key objectives of this study include estimating individual exposure to health-relevant pollutants like NO2, PM2.5, ultrafine particles (UFP), as well as metal compounds in particulate matter across Augsburg and its neighborhoods, with particular attention to residential areas near traffic hubs. Spatially resolved exposure assessments are refined using population density, mobility data, and activity patterns to evaluate demographic-specific risks, particularly for vulnerable groups such as children and the elderly. Temporal analyses explore diurnal variations in traffic emissions, identifying peak pollution periods during rush hours and seasonal fluctuations. Preliminary results highlight pollution hotspots near major roads and intersections, with expected higher concentrations during peak traffic times. Initial maps reveal significant spatial heterogeneity, indicating heightened exposure levels for populations residing in traffic-dense zones. Anticipated contributions include a robust quantification of traffic's role in air quality deterioration and spatial visualization of pollutant distributions. Future work will focus on developing machine learning-based parameterizations to simplify interactions between traffic emissions and urban background pollution, facilitating scalable predictions for diverse urban settings by further investigating the non-linear health effects of air pollution. This research provides insights for urban planners and policymakers to improve air quality and health in traffic-affected areas.

How to cite: Vaithiyanadhan, S. K. and Knote, C.: Simulating urban air quality in Augsburg, Germany, using the PALM model to understand health impacts of changing traffic emissions in future urban transportation landscapes. , 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-45, https://doi.org/10.5194/icuc12-45, 2025.

Large-eddy simulation (LES) models can evaluate complex flow fields and atmospheric dispersion process in urban areas with higher accuracy than conventional RANS based models. However, simulation in urban areas requires high spatio-temporal resolution, which causes the heavy computational load. In this study, we aim to build an atmospheric dispersion evaluation system which can utilize the LES model in low computational cost. The proposed system consists of pre-calculated LES output database and atmospheric dispersion model. To build the system, we discuss the method to use the LES database efficiently, including the reduced-order modelling based on the mode decomposition method. We also discuss the relationship between large-scale environment (e.g., wind speed, wind direction and atmospheric stability) and flow field in target area simulated by LES. The reduced-order model can simulate the flow field from certain number of dominant modes and large-scale environment, that makes the computational load much lower than full simulation. In addition, we investigate the accuracy of atmospheric dispersion models, Eularian and Lagrangian models, in case of using the LES database as input data. Combining the reduced-order model and atmospheric dispersion model, we propose the atmospheric dispersion evaluation framework which aimed to use widely and easily even in small computational resources.

How to cite: Sato, T. and Nakayama, H.: Development of atmospheric dispersion simulation system based on the efficient use of LES model output, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-164, https://doi.org/10.5194/icuc12-164, 2025.

Due to urbanization, people’s daily commutes can emit huge amounts of CO2. Therefore, an accurate picture of the number of vehicles moving through a city is necessary for traffic management and effective emissions control. The development of intelligent transportation systems has enabled real-time traffic data collection. For example, Seoul has hourly traffic speed data for almost all of its road network and traffic volume data measured by 139 in-situ sensors. Telecom operators also process cell phone data to provide traffic mobility data. In this study, we developed a graph neural network model to estimate city-wide traffic volumes from traffic speeds, reflecting the actual road network connectivity. Our approach learns the relationship between speed and volume and then extrapolates this relationship for periods when city-wide traffic data did not exist. To train the model, we used hourly full-coverage speed data from the Seoul Traffic Information Center and volume data from a telecom company for a limited period from April to September 2024. We then used the trained model and full-coverage speed data to construct traffic volume for a longer period from January 2018 to December 2023. The model’s estimated traffic volume was evaluated against in-situ traffic volume, achieving an R² of 0.888 and an RMSE of 446.30 vehicles per hour on average over the 6-year period. Next, we calculated road-scale CO2 emissions at an hourly timescale using country-specific emission factors based on the estimated traffic volumes. Our estimates, which show the spatial distribution of large emissions on urban highways and main arterials, can provide more spatio-temproal variability compared to global OC2 emission inventories such as EDGAR and ODIAC, which provide smoother patterns. By constructing reliable city-wide traffic volume data, this study supports more precise CO2 emission assessments and decision-making process for urban transportation management.

How to cite: Lee, Y., Lee, S., Kang, Y., and Im, J.: Graph Neural Networks for Hourly 1 km Urban CO2 Emissions Estimation Using Real-World Data, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-567, https://doi.org/10.5194/icuc12-567, 2025.

This research, carried out within the framework of the PNRR Italian National Centre for Sustainable Mobility CNMS (European Union – Next Generation EU – PNRR – MISSIONE 4 – COMPONENTE 2 – INVESTIMENTO 1.4 – Spoke 7 – Code CN00000023, CUP: F83C22000720001), investigates the impact of vehicular emissions in urban environments, with a particular emphasis on the vicinity of sensitive receptors such as schools and densely populated residential areas. Recent studies suggest that current legislation limits may not adequately safeguard vulnerable populations, particularly children and adolescents.

To address this issue, a network of high-resolution monitoring instruments will be deployed in Lecce and its surrounding areas (Southern Italy). Specifically, measurement campaigns will take place in urban sites and on a bridge outside the urban area. The setup includes AIRQINO air quality and meteorological stations, as well as vehicle-counting cameras. These instruments will continuously collect data on key atmospheric parameters (wind speed and direction, temperature, precipitation, humidity, solar radiation) and traffic patterns (vehicle classification and speed). The collected data will be integrated into the ADMS-Roads dispersion model, simulating pollutant dispersion dynamics, while air quality measurements will validate the model outputs for NOx, PM₁₀, PM_2.5 and O₃ concentrations.

The complementary use of urban and extra-urban sites will provide a more comprehensive characterization of pollution transport mechanisms and their dependence on meteorological and traffic conditions. This approach enhances the accuracy of dispersion modeling and enables a detailed evaluation of emission hotspots.

By combining real-time monitoring with advanced dispersion modeling, this study will develop targeted mitigation strategies to reduce air pollution exposure in high-risk urban areas, providing scientific evidence to support air quality policies and public health protections, particularly for vulnerable populations in sensitive locations.

How to cite: Metrangolo, C., Dinoi, A., Pappaccogli, G., Kumar, P., and Buccolieri, R.: Integrating real-time monitoring and dispersion modelling to evaluate vehicular emission impacts in urban environments: a case study in Southern Italy, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-1006, https://doi.org/10.5194/icuc12-1006, 2025.

A low-cost air quality sensor package to measure particulate matter (PM_2.5), ozone (O₃), carbon monoxide (CO), nitric oxide (NO), and nitrogen dioxide (NO₂) was designed for integration with the New York State Mesonet (NYSM), an advanced weather monitoring network continuously collecting observations since 2015. The low-cost sensors were calibrated using regulatory-grade instruments at the New York State Department of Environmental Conservation Queens College monitoring site in Queens, NY. During spring and summer 2023, sensor packages were deployed at 38 NYSM sites within the New York City Metropolitan Area (NYCMA). From May 2023 through August 2024, air pollutants were measured at 5-s sampling period and collected remotely in real time, with data retention rates exceeding 90% for all pollutants across the network. We will present our Network Calibration Model, which prioritized long-term accuracy and stability of the low-cost sensors. Calibrated and quality-controlled hourly data will be used to demonstrate the capability of the network to characterize temporal pollutant patterns at daily, weekly, and seasonal time scales, to contrast pollutants in urban and rural environments, and to evaluate spatial correlations across the network. The study also highlights the network’s ability to resolve the impacts of episodic pollution events such as the 2023 Quebec, Canada wildfires on air quality across the NYCMA.

How to cite: Hojeily, E., Miller, S., Covert, J., Lu, C.-H., Bari, Md. A., Schwab, M., Moore, I., and Brooking, M.: Network-calibrated low-cost air quality sensors integrated with the New York State Mesonet for continuous fine-scale monitoring in New York City, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-806, https://doi.org/10.5194/icuc12-806, 2025.

In France, fine particulate matter (PM) pollution is estimated to be responsible for 40,000 premature deaths per year. If PM₁₀ (d < 10 µm) and PM_2.5 (d < 2.5 µm) size fractions are regulated at the European level, this is not the case for the carbonaceous particle pollution, namely Black Carbon (BC). However, according to the WHO, BC is highly toxic for human health. Moreover, BC can be considered as a good proxy for resident exposure in urban environment as this pollution originates from traffic, residential heating or industrial activities. This study focuses on the BC diagnosis at a district scale, upstream of its sustainable development in Dijon Metropolis, Eastern France. Mobile BC measurement campaigns were carried out between February and mid-April 2024 during days and hours representative of typical urban pollution conditions, using the MA-200 mini-aethalometer. The results show that BC levels are typically urban (1-3.2 µg/m³), and are higher than background levels in Dijon metropolis (annual averages of 0.7-0.8 µg/m³). The studied area is characterized at 75% by pollution linked to the fossil fuel combustion (BC_ff), mainly related to road traffic. The contribution from the wood burning component (BC_wb) is relatively marked in winter (34% of total BC, compared to 18% in spring) due to the effect of residential heating. Finally, the spatio-temporal variability of BC is induced by land use at the fine scale (street, neighborhood) and wind speed at the city scale. These results highlight the original insights of BC mobile measurements to characterize the particulate pollution in an urban context. Even though the BC concentration levels are very low compared to PM_2.5, their strong spatio-temporal variability at micro-scale makes it possible to identify pollution “hot-spots” and their origin. Thus, the BC evaluation at fine scales may help in the planning of sustainable urban development strategies.

How to cite: Martiny, N. and Massoud, R.: Urban environment diagnosis upstream a district development in a medium-sized European city: Analysis of carbonaceous particle pollution captured by mobile measurements , 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-896, https://doi.org/10.5194/icuc12-896, 2025.

Air pollution levels vary significantly within urban environments due to the high density of local emission sources and limited ventilation. Over the past 30 years, the Dutch annual emission inventory has recorded a remarkable decline in road traffic-related PM2.5 emissions (including both tailpipe and wear particles), with a 13-fold reduction driven by stricter regulations.

However, this progress has not extended to woodstove emissions. Despite various initiatives—such as subsidies for high-efficiency woodstoves and woodstove operation courses—emission reductions remain negligible. Since 2020, PM2.5 emissions from woodstoves have been three times higher than those from road traffic and show no signs of decline. This trend is partly due to the shift away from natural gas heating, driven by rising gas prices and the initial promotion of woodstoves as a carbon-neutral alternative. As a result, woodstove usage has surged, making it a primary heating source.

These developments pose a significant challenge to meeting EU air quality targets in cities by 2030. To assess the spatial distribution of PM2.5 pollution, measurements were conducted using novel instruments within the Netherlands' most densely populated citizen science monitoring network. A novel analytical method was applied to quantify spatial variations, revealing a distinctive emission signature associated with woodstove usage.  . .

How to cite: Heusinkveld, B.: Woodstoves, the smoking gun of Dutch urban air pollution, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-1062, https://doi.org/10.5194/icuc12-1062, 2025.

Ozone formation is driven by complex photochemical reactions, with inter-provincial transport exacerbating air quality in downwind region of South Korea. To identify transport pathways of ozone and its precursors and develop effective mitigation strategies, the WRF (v4.3) and CMAQ (v5.3.2) models were employed and integrated with the Process Analysis - Integrated Process Rates (PA-IPR) tool. Anthropogenic air pollutant emissions were based on the up-to-date national emission inventory (CAPSS 2021) in South Korea.

The PA-IPR tool was used to assess the ozone budget through the Index of Process Analysis (IPA), a dimensionless metric quantifying the relative contributions of chemical production (CHEM) and transport including advection (ADV) and diffusion (DIF). IPA analysis revealed an average value of 0.58 in Seoul, a major source region, and 1.47 in Gangwon-do, a downwind region from Seoul metropolitan area, highlighting distinct inter-provincial transport patterns. The IPA value increased when inter-regional transport was prominent, enabling case-specific analyses of ozone formation in downwind areas.

To develop effective ozone reduction policies, it is essential to quantify source-receptor relationships by assessing inter-regional contributions. For this purpose, the Integrated Source Apportionment Method (ISAM) was applied to analyze ozone transport from specific regions during April–May 2022. ISAM analysis was further utilized to assess inter-regional contributions during high-ozone episodes in downwind areas.

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (RS-2023-00219830, RS-2024-00356913).

How to cite: Kim, T. and Kwak, K.-H.: Analysis of Formation Mechanisms and Inter-Provincial Transport of Ozone in South Korea, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-581, https://doi.org/10.5194/icuc12-581, 2025.

Achieving carbon neutrality by 2050 announced in Japan is expected to substantially affect air quality. Therefore, the effects of climate change and GHG reduction strategies on the emission of air pollutants are of great interest to environmentalists and policymakers. However, the co-benefits of carbon neutrality on air quality in Asian regions are still discussed.

Here, we projected the future surface ozone (O₃) concentration in 2050 by conducting regional air quality simulations based on a low-carbon emission scenarios for the Asian region considering the newly developed technologies.

First of all, we verified Business as usual (BAU) scenario which considers the low-carbon measures currently envisaged and results in 40% and 45% reduction of O₃ precursors emissions (VOCs and NOx, respectively) from the present (the year 2017) situation. Surface O₃ in the BAU increased ~2.5ppbv compare to that in present in some metropolitan areas which were driven by the reductions of O₃ precursors.

To quantify the impact of further reductions of VOCs and NOx on surface O₃, three additional strict regulation strategies were examined: additional 40% reduction of VOCs emission from the BAU (80redVOCs), additional 45% reduction of NOx emission from the BAU (85redNOx), and the combination of 80redVOCs and 85redNOx (80redVOCs_85redNOx).

The 80redVOCs decreased O₃ concentration by ~1.5 ppbv in metropolitan areas compared to that in the BAU. Otherwise, the 85redNOx and 80redVOCs_85redNOx showed a similar pattern of the change in O₃ concentration compared to the BAU scenarios with larger impacts than that in the 80redVOCs. The largest difference in surface O₃ between these strategies and BAU scenarios occurred in the central part of Japan, where O₃ concentration decreased ~4.5 ppbv, but increased to 3 ppbv in Tokyo metropolitan area. We will present the co-benefit of the Japanese low-carbon strategy on surface O₃ concentration particularly in metropolitan areas by using indexes.

How to cite: Kawano, N., Nagashima, T., Itahashi, S., Ohara, T., Kurokawa, J., Hanaoka, T., and Uno, I.: Co-benefits of low-carbon strategy in Japan on surface ozone concentration in cities, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-971, https://doi.org/10.5194/icuc12-971, 2025.

Globally, air pollution is the leading environmental risk factor for human health. It is especially important in urban areas where multiple sources of air pollution are present, and air quality is typically worse. Air pollution is a known threat to cardiovascular and respiratory disease and ranked as a Group 1 carcinogen. However, emerging evidence provides links between air pollution exposure and human cognitive potential, with both short- and long-term effects. Recent research demonstrates a clear and measurable link between exposure to fine particulate matter air pollution and reduced cognitive function [1], with pronounced implications for educational outcomes and work placed productivity. Longer term cognitive impacts include dementia and Alzheimer’s’ disease.

In this presentation, the role and implications of air pollution impacts upon neurological health will be explored, highlighting the scale of the issue, differences in vulnerability, and whether current air pollution regulation is adequate to protect cognitive health in urban areas. Vulnerability will be investigated through the lenses of exposure, susceptibility and adaptive capacity. The broader societal implications and possible mitigations, with a focus on urban environments, will also be explored.

[1] Faherty et al. (2025) Acute particulate matter exposure diminishes executive cognitive functioning after four hours regardless of inhalation pathway. Nature Communications, 16(1), p.1339. https://doi.org/10.1038/s41467-025-56508-3

How to cite: Pope, F., Faherty, T., Ellis, L.-J., and Harrison, R.: The role of urban air quality on educational outcomes and work placed productivity , 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-1100, https://doi.org/10.5194/icuc12-1100, 2025.