Residential air quality near noise barriers strongly affected by wind velocity.

Residing within 300-500 m of main roads is linked to specific negative health effects, including reduced lung capacity and increased cardiovascular mortality (Health Effects Institute, 2010). Noise barriers, widely used due to their ability to reduce noise levels, can also have the beneficial side effect of limiting the dispersion of traffic emissions from highways into adjacent areas. We investigated how a high noise barrier influences near-road aerosol concentrations under varying wind conditions.

Plastic and rubber polymers in urban PM by pyrolysis-gas chromatography-mass spectrometry.

Microplastics, including tyre and road wear particles, have been detected in every environmental compartment in both urban and remote areas. However, their contribution to atmospheric particulate matter is still sparsely explored. These airborne micro- and nanosized particles are continuously inhaled and pose risks to the environment and public health.

A European aerosol phenomenology - 9: Light absorption properties of carbonaceous aerosol particles across surface Europe.

Carbonaceous aerosols (CA), composed of black carbon (BC) and organic matter (OM), significantly impact the climate. Light absorption properties of CA, particularly of BC and brown carbon (BrC), are crucial due to their contribution to global and regional warming. We present the absorption properties of BC (b) and BrC (b) inferred using Aethalometer data from 44 European sites covering different environments (traffic (TR), urban (UB), suburban (SUB), regional background (RB) and mountain (M)).

Source apportionment of ultrafine particles in urban Europe.

There is a body of evidence that ultrafine particles (UFP, those with diameters ≤ 100 nm) might have significant impacts on health. Accordingly, identifying sources of UFP is essential to develop abatement policies. This study focuses on urban Europe, and aims at identifying sources and quantifying their contributions to particle number size distribution (PNSD) using receptor modelling (Positive Matrix Factorization, PMF), and evaluating long-term trends of these source contributions using the non-parametric Theil-Sen's method.

Inter-annual trends of ultrafine particles in urban Europe.

Ultrafine particles (UFP, those with diameters ≤ 100 nm), have been reported to potentially penetrate deeply into the respiratory system, translocate through the alveoli, and affect various organs, potentially correlating with increased mortality. The aim of this study is to assess long-term trends (5-11 years) in mostly urban UFP concentrations based on measurements of particle number size distributions (PNSD). Additionally, concentrations of other pollutants and meteorological variables were evaluated to support the interpretations.

Constructing transferable and interpretable machine learning models for black carbon concentrations.

Black carbon (BC) has received increasing attention from researchers due to its adverse health effects. However, in-situ BC measurements are often not included as a regulated variable in air quality monitoring networks. Machine learning (ML) models have been studied extensively to serve as virtual sensors to complement the reference instruments.

Particle lung deposited surface area (LDSA) size distributions in different urban environments and geographical regions: Towards understanding of the PM dose-response.

Recent studies indicate that monitoring only fine particulate matter (PM) may not be enough to understand and tackle the health risk caused by particulate pollution. Health effects per unit PM seem to increase in countries with low PM, but also near local pollution sources (e.g.

Ambient air particulate total lung deposited surface area (LDSA) levels in urban Europe.

This study aims to picture the phenomenology of urban ambient total lung deposited surface area (LDSA) (including head/throat (HA), tracheobronchial (TB), and alveolar (ALV) regions) based on multiple path particle dosimetry (MPPD) model during 2017-2019 period collected from urban background (UB, n = 15), traffic (TR, n = 6), suburban background (SUB, n = 4), and regional background (RB, n = 1) monitoring sites in Europe (25) and USA (1). Briefly, the spatial-temporal distribution characteristics of the deposition of LDSA, including diel, weekly, and seasonal patterns, were analyzed. Then, the relationship between LDSA and other air quality metrics at each monitoring site was investigated.

Sub-23 nm Particles Dominate Non-Volatile Particle Number Emissions of Road Traffic.

Ultrafine particles (<100 nm) in urban air are a serious health hazard not yet fully understood. Therefore, particle number concentration monitoring was recently included in the WHO air quality guidelines. At present, e.

Snapshots of wintertime urban aerosol characteristics: Local sources emphasized in ultrafine particle number and lung deposited surface area.

Urban air fine particles are a major health-relating problem. However, it is not well understood how the health-relevant features of fine particles should be monitored. Limitations of PM (mass concentration of sub 2.

Modeling non-linear changes in an urban setting: From pro-environmental affordances to responses in behavior, emissions and air quality.

Interactions in urban environment were investigated using a multidisciplinary model combination, with focus on traffic, emissions and atmospheric particles. An agent-based model was applied to simulate the evolution of unsustainable human behavior (usage of combustion-based personal vehicles) as a function of pro-environmental affordances (opportunities for sustainable choices). Scenarios regarding changes in multi-pollutant emissions were derived, and the non-linear implications to atmospheric particles were simulated with a box model.

Determinants of spatial variability of air pollutant concentrations in a street canyon network measured using a mobile laboratory and a drone.

Urban air pollutant concentrations are highly variable both in space and time. In order to understand these variabilities high-resolution measurements of air pollutants are needed. Here we present results of a mobile laboratory and a drone measurements made within a street-canyon network in Helsinki, Finland, in summer and winter 2017.

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions.

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM, PM, PMC (coarse fraction of PM), NO, SO, NOx, CO, O and the total gaseous oxidant (OX = NO + O) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020.

Long-term trends in PM mass and particle number concentrations in urban air: The impacts of mitigation measures and extreme events due to changing climates.

Urbanisation and industrialisation led to the increase of ambient particulate matter (PM) concentration. While subsequent regulations may have resulted in the decrease of some PM matrices, the simultaneous changes in climate affecting local meteorological conditions could also have played a role. To gain an insight into this complex matter, this study investigated the long-term trends of two important matrices, the particle mass (PM) and particle number concentrations (PNC), and the factors that influenced the trends.

Input-Adaptive Proxy for Black Carbon as a Virtual Sensor.

Missing data has been a challenge in air quality measurement. In this study, we develop an input-adaptive proxy, which selects input variables of other air quality variables based on their correlation coefficients with the output variable. The proxy uses ordinary least squares regression model with robust optimization and limits the input variables to a maximum of three to avoid overfitting.

Source apportionment of particle number size distribution in urban background and traffic stations in four European cities.

Ultrafine particles (UFP) are suspected of having significant impacts on health. However, there have only been a limited number of studies on sources of UFP compared to larger particles. In this work, we identified and quantified the sources and processes contributing to particle number size distributions (PNSD) using Positive Matrix Factorization (PMF) at six monitoring stations (four urban background and two street canyon) from four European cities: Barcelona, Helsinki, London, and Zurich.

Ultrafine particles and PM in the air of cities around the world: Are they representative of each other?

Can mitigating only particle mass, as the existing air quality measures do, ultimately lead to reduction in ultrafine particles (UFP)? The aim of this study was to provide a broader urban perspective on the relationship between UFP, measured in terms of particle number concentration (PNC) and PM (mass concentration of particles with aerodynamic diameter < 2.5 μm) and factors that influence their concentrations. Hourly average PNC and PM were acquired from 10 cities located in North America, Europe, Asia, and Australia over a 12-month period.