Atmospheric new particle formation (NPF) is a naturally occurring phenomenon, during which high concentrations of sub-10 nm particles are created through gas to particle conversion. The NPF is observed in multiple environments around the world. Although it has observable influence onto annual total and ultrafine particle number concentrations (PNC and UFP, respectively), only limited epidemiological studies have investigated whether these particles are associated with adverse health effects. One plausible reason for this limitation may be related to the absence of NPF identifiers available in UFP and PNC data sets. Until recently, the regional NPF events were usually identified manually from particle number size distribution contour plots. Identification of NPF across multi-annual and multiple station data sets remained a tedious task. In this work, we introduce a regional NPF identifier, created using an automated, machine learning based algorithm. The regional NPF event tag was created for 65 measurement sites globally, covering the period from 1996 to 2023. The discussed data set can be used in future studies related to regional NPF.
- Publikační typ
- časopisecké články MeSH
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. The result showed that the peak concentrations of LDSA at UB and TR sites are commonly observed in the morning (06:00-8:00 UTC) and late evening (19:00-22:00 UTC), coinciding with traffic rush hours, biomass burning, and atmospheric stagnation periods. The only LDSA night-time peaks are observed on weekends. Due to the variability of emission sources and meteorology, the seasonal variability of the LDSA concentration revealed significant differences (p = 0.01) between the four seasons at all monitoring sites. Meanwhile, the correlations of LDSA with other pollutant metrics suggested that Aitken and accumulation mode particles play a significant role in the total LDSA concentration. The results also indicated that the main proportion of total LDSA is attributed to the ALV fraction (50 %), followed by the TB (34 %) and HA (16 %). Overall, this study provides valuable information of LDSA as a predictor in epidemiological studies and for the first time presenting total LDSA in a variety of European urban environments.
- Klíčová slova
- Particle number size distribution, Spatial variability, Total lung deposited surface area, Traffic emissions, Urban environment,
- MeSH
- látky znečišťující vzduch * analýza MeSH
- monitorování životního prostředí metody MeSH
- pevné částice analýza MeSH
- plíce MeSH
- prach MeSH
- velikost částic MeSH
- výfukové emise vozidel analýza MeSH
- znečištění ovzduší * analýza MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Evropa MeSH
- Názvy látek
- látky znečišťující vzduch * MeSH
- pevné částice MeSH
- prach MeSH
- výfukové emise vozidel MeSH
The 2017-2019 hourly particle number size distributions (PNSD) from 26 sites in Europe and 1 in the US were evaluated focusing on 16 urban background (UB) and 6 traffic (TR) sites in the framework of Research Infrastructures services reinforcing air quality monitoring capacities in European URBAN & industrial areaS (RI-URBANS) project. The main objective was to describe the phenomenology of urban ultrafine particles (UFP) in Europe with a significant air quality focus. The varying lower size detection limits made it difficult to compare PN concentrations (PNC), particularly PN10-25, from different cities. PNCs follow a TR > UB > Suburban (SUB) order. PNC and Black Carbon (BC) progressively increase from Northern Europe to Southern Europe and from Western to Eastern Europe. At the UB sites, typical traffic rush hour PNC peaks are evident, many also showing midday-morning PNC peaks anti-correlated with BC. These peaks result from increased PN10-25, suggesting significant PNC contributions from nucleation, fumigation and shipping. Site types to be identified by daily and seasonal PNC and BC patterns are: (i) PNC mainly driven by traffic emissions, with marked correlations with BC on different time scales; (ii) marked midday/morning PNC peaks and a seasonal anti-correlation with PNC/BC; (iii) both traffic peaks and midday peaks without marked seasonal patterns. Groups (ii) and (iii) included cities with high insolation. PNC, especially PN25-800, was positively correlated with BC, NO2, CO and PM for several sites. The variable correlation of PNSD with different urban pollutants demonstrates that these do not reflect the variability of UFP in urban environments. Specific monitoring of PNSD is needed if nanoparticles and their associated health impacts are to be assessed. Implementation of the CEN-ACTRIS recommendations for PNSD measurements would provide comparable measurements, and measurements of <10 nm PNC are needed for full evaluation of the health effects of this size fraction.
- Klíčová slova
- Aerosols, Air quality, Atmospheric particulate matter, Nanoparticles, Particle number concentrations, Urban environment,
- MeSH
- látky znečišťující vzduch * analýza MeSH
- monitorování životního prostředí MeSH
- pevné částice analýza MeSH
- saze MeSH
- velikost částic MeSH
- velkoměsta MeSH
- výfukové emise vozidel analýza MeSH
- znečištění ovzduší * analýza MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Evropa MeSH
- velkoměsta MeSH
- Názvy látek
- látky znečišťující vzduch * MeSH
- pevné částice MeSH
- saze MeSH
- výfukové emise vozidel MeSH
