Urban pollution impact assessment in six lithuanian cities with a focus on road traffic emissions - integrated framework for environmental health studies.

An integrated framework is introduced and applied to assess the health impact of airborne pollution with greater physiological relevance, moving beyond conventional exposure metrics. Measured particle number size distribution data was integrated with a regional respiratory tract deposition fractions to estimate total and alveolar deposited particle surface area concentrations. Land use regression modeling, combined with randomized commuting patterns, enabled the evaluation of city-specific alveolar surface area deposition doses, providing new insight into localized average exposure and its implications for public health.

Exploration of transfer learning techniques for the prediction of PM.

Modelling of pollutants provides valuable insights into air quality dynamics, aiding exposure assessment where direct measurements are not viable. Machine learning (ML) models can be employed to explore such dynamics, including the prediction of air pollution concentrations, yet demanding extensive training data. To address this, techniques like transfer learning (TL) leverage knowledge from a model trained on a rich dataset to enhance one trained on a sparse dataset, provided there are similarities in data distribution.

Aerosol particle number concentration, ultrafine particle number fraction, and new particle formation measurements near the international airports in Berlin, Germany - First results from the BEAR study.

Studies revealed airports as a prominent source of ultrafine particles (UFP), which can disperse downwind to residential areas, raising health concerns. To expand our understanding of how air traffic-related emissions influence total particle number concentration (PNC) in the airport's surrounding areas, we conduct long-term assessment of airborne particulate exposure before and after relocation of air traffic from "Otto Lilienthal" Airport (TXL) to Berlin Brandenburg Airport "Willy Brandt" (BER) in Berlin, Germany. Here, we provide insights into the spatial-temporal variability of PNC measured in 16 schools recruited for Berlin-Brandenburg Air Study (BEAR).

The Berlin-Brandenburg Air Study-A Methodological Study Paper of a Natural Experiment Investigating Health Effects Related to Changes in Airport-Related Exposures.

This paper presents the study design of the Berlin-Brandenburg Air study (BEAR-study). We measure air quality in Berlin and Brandenburg before and after the relocation of aircraft (AC) traffic from Tegel (TXL) airport to the new Berlin-Brandenburg airport (BER) and investigate the association of AC-related ultrafine particles (UFP) with health outcomes in schoolchildren. The BEAR-study is a natural experiment examining schoolchildren attending schools near TXL and BER airports, and in control areas (CA) away from both airports and associated air corridors.

Rapid growth of Aitken-mode particles during Arctic summer by fog chemical processing and its implication.

In the Arctic, new particle formation (NPF) and subsequent growth processes are the keys to produce Aitken-mode particles, which under certain conditions can act as cloud condensation nuclei (CCNs). The activation of Aitken-mode particles increases the CCN budget of Arctic low-level clouds and, accordingly, affects Arctic climate forcing. However, the growth mechanism of Aitken-mode particles from NPF into CCN range in the summertime Arctic boundary layer remains a subject of current research.

A novel in-situ method to determine the respiratory tract deposition of carbonaceous particles reveals dangers of public commuting in highly polluted megacity.

Background: Exposure to air pollutants is one of the major environmental health risks faced by populations globally. Information about inhaled particle deposition dose is crucial in establishing the dose-response function for assessing health-related effects due to exposure to air pollution.

Objective: This study aims to quantify the respiratory tract deposition (RTD) of equivalent black carbon (BC) particles in healthy young adults during a real-world commuting scenario, analyze factors affecting RTD of BC, and provide key parameters for the assessment of RTD.

Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia.

In this paper, the authors investigated changes in mass concentrations of particulate matter (PM) during the Coronavirus Disease of 2019 (COVID-19) lockdown. Daily samples of PM, PM and PM fractions were measured at an urban background sampling site in Zagreb, Croatia from 2009 to late 2020. For the purpose of meteorological normalization, the mass concentrations were fed alongside meteorological and temporal data to Random Forest (RF) and LightGBM (LGB) models tuned by Bayesian optimization.

A Comprehensive Model Test of the HONO Sources Constrained to Field Measurements at Rural North China Plain.

As nitrous acid (HONO) photolysis is an important source of hydroxyl radical (OH), apportionment of the ambient HONO sources is necessary to better understand atmospheric oxidation. Based on the data HONO-related species and various parameters measured during the one-month campaign at Wangdu (a rural site in North China plain) in summer 2014, a box model was adopted with input of current literature parametrizations for various HONO sources (nitrogen dioxide heterogeneous conversion, photoenhanced conversion, photolysis of adsorbed nitric acid and particulate nitrate, acid displacement, and soil emission) to reveal the relative importance of each source at the rural site. The simulation results reproduced the observed HONO production rates during noontime in general but with large uncertainty from both the production and destruction terms.

A new method to measure real-world respiratory tract deposition of inhaled ambient black carbon.

In this study, we present the development of a mobile system to measure real-world total respiratory tract deposition of inhaled ambient black carbon (BC). Such information can be used to supplement the existing knowledge on air pollution-related health effects, especially in the regions where the use of standard methods and intricate instrumentation is limited. The study is divided in two parts.

Respiratory tract deposition of inhaled roadside ultrafine refractory particles in a polluted megacity of South-East Asia.

Recent studies demonstrate that Black Carbon (BC) pollution in economically developing megacities remain higher than the values, which the World Health Organization considers to be safe. Despite the scientific evidence of the degrees of BC exposure, there is still a lack of understanding on how the severe levels of BC pollution affect human health in these regions. We consider information on the respiratory tract deposition dose (DD) of BC to be essential in understanding the link between personal exposure to air pollutants and corresponding health effects.

First Quantification of Imidazoles in Ambient Aerosol Particles: Potential Photosensitizers, Brown Carbon Constituents, and Hazardous Components.

Imidazoles are widely discussed in recent literature. They have been studied as a secondary product of the reaction of dicarbonyls with nitrogen containing compounds in a number of laboratory studies, potentially acting as photosensitizers triggering secondary organic aerosol growth and are forming constituents of light absorbing brown carbon. Despite the knowledge from laboratory studies, no quantitative information about imidazoles in ambient aerosol particles is available.

Characteristics of black carbon aerosol mass concentration over the East Baltic region from two-year measurements.

Continuous measurements of black carbon (BC) aerosol mass concentration were performed at a background site Preila (55°55'N, 21°00'E, 5 m a.s.l.