Mass absorption cross-section and absorption enhancement from long term black and elemental carbon measurements: A rural background station in Central Europe

Black carbon (BC) is a dominant aerosol light absorber, and its brown carbon (BrC) coating can enhance absorption and lead to uncertainties concerning the radiative forcing estimation. This study investigates the mass absorption cross-section of equivalent BC (MAC(eBC)) during a long-term field measurement (2013-2017) at a rural Central European site. The MAC enhancement factor (E-abs) and the contribution of BrC coatings to the absorption coefficient (B-abs) were estimated by combining different approaches. The annual mean B-abs and MAC(eBC) values decreased slightly over the measurement period associated with change in the submicron aerosol size distribution. Regardless of the wavelength, B-abs exhibited clear seasonal and diurnal variations, with higher values in winter when a higher absorption Angstromexponent (1.4) was observed due to the local biomass burning (BB). In contrast, MACeBC did not have a distinct temporal trend at 600 nm (7.84 +/- 2.79 m(2) g(-1)), while it showed a seasonal trend at 370 nm with higher values in winter (15.64 +/- 4.77 m(2) g(-1)). During this season, E-abs_(660) was 1.18 +/- 0.27 and did not exhibit any clear wavelength dependence, despite the influence of BB. During the study period, BrC-attributed absorption was observed in 31% of the samples, with a contribution of up to 40% of total Babs. In summer, the E-abs_(660) increased to 1.59 +/- 0.60, when a larger BC coating could be formed by secondary aerosol fractions. During this season, MAC(eBC)_ (660) and E-abs_(660) showed comparable source profiles that were mainly associated with aged air masses over central Europe, thereby supporting the fact that characteristics of coating materials formed during atmospheric aging are a major factor driving the MAC(eBC)_(660) measured at the regional background site. Further field investigations of the composition of BC coatings would help to better understand and estimate uncertainties related to the radiative effect of aerosols

Estimating Hourly Concentrations of PM2.5 across a Metropolitan Area Using Low-Cost Particle Monitors

There is concern regarding the heterogeneity of exposure to airborne particulate matter (PM) across urban areas leading to negatively biased health effects models. New, low-cost sensors now permit continuous and simultaneous measurements to be made in multiple locations. Measurements of ambient PM were made from October to April 2015–2016 and 2016–2017 to assess the spatial and temporal variability in PM and the relative importance of traffic and wood smoke to outdoor PM concentrations in Rochester, NY, USA. In general, there was moderate spatial inhomogeneity, as indicated by multiple pairwise measures including coefficient of divergence and signed rank tests of the value distributions. Pearson correlation coefficients were often moderate (~50% of units showed correlations >0.5 during the first season), indicating that there was some coherent variation across the area, likely driven by a combination of meteorological conditions (wind speed, direction, and mixed layer heights) and the concentration of PM2.5 being transported into the region. Although the accuracy of these PM sensors is limited, they are sufficiently precise relative to one another and to research grade instruments that they can be useful is assessing the spatial and temporal variations across an area and provide concentration estimates based on higher-quality central site monitoring data

Intercomparison of 15 aerodynamic particle size spectrometers (APS 3321): uncertainties in particle sizing and number size distribution

Aerodynamic particle size spectrometers are a well-established method to measure number size distributions of coarse mode particles in the atmosphere. Quality assurance is essential for atmospheric observational aerosol networks to obtain comparable results with known uncertainties. In a laboratory study within the framework of ACTRIS (Aerosols, Clouds, and Trace gases Research Infrastructure Network), 15 aerodynamic particle size spectrometers (APS model 3321, TSI Inc., St. Paul, MN, USA) were compared with a focus on flow rates, particle sizing, and the unit-to-unit variability of the particle number size distribution. Flow rate deviations were relatively small (within a few percent), while the sizing accuracy was found to be within 10 % compared to polystyrene latex (PSL) reference particles. The unit-to-unit variability in terms of the particle number size distribution during this study was within 10 % to 20 % for particles in the range of 0.9 up to 3 µm, which is acceptable for atmospheric measurements. For particles smaller than that, the variability increased up to 60 %, probably caused by differences in the counting efficiencies of individual units. Number size distribution data for particles smaller than 0.9 µm in aerodynamic diameter should only be used with caution. For particles larger than 3 µm, the unit-to-unit variability increased as well. A possible reason is an insufficient sizing accuracy in combination with a steeply sloping particle number size distribution and the increasing uncertainty due to decreasing counting. Particularly this uncertainty of the particle number size distribution must be considered if higher moments of the size distribution such as the particle volume or mass are calculated, which require the conversion of the aerodynamic diameter measured to a volume equivalent diameter. In order to perform a quantitative quality assurance, a traceable reference method for the particle number concentration in the size range 0.5–3 µm is needed.JRC.H.2-Air and Climat

Intercomparison of 15 aerodynamic particle size spectrometers (APS 3321) : uncertainties in particle sizing and number size distribution

Aerodynamic particle size spectrometers are a well-established method to measure number size distributions of coarse mode particles in the atmosphere. Quality assurance is essential for atmospheric observational aerosol networks to obtain comparable results with known uncertainties. In a laboratory study within the framework of ACTRIS (Aerosols, Clouds, and Trace gases Research Infrastructure Network), 15 aerodynamic particle size spectrometers (APS model 3321, TSI Inc., St. Paul, MN, USA) were compared with a focus on flow rates, particle sizing, and the unit-tounit variability of the particle number size distribution. Flow rate deviations were relatively small (within a few percent), while the sizing accuracy was found to be within 10% compared to polystyrene latex (PSL) reference particles. The unit-to-unit variability in terms of the particle number size distribution during this study was within 10% to 20% for particles in the range of 0.9 up to 3 mu m, which is acceptable for atmospheric measurements. For particles smaller than that, the variability increased up to 60 %, probably caused by differences in the counting efficiencies of individual units. Number size distribution data for particles smaller than 0.9 mu m in aerodynamic diameter should only be used with caution. For particles larger than 3 mu m, the unit-tounit variability increased as well. A possible reason is an insufficient sizing accuracy in combination with a steeply sloping particle number size distribution and the increasing uncertainty due to decreasing counting. Particularly this uncertainty of the particle number size distribution must be considered if higher moments of the size distribution such as the particle volume or mass are calculated, which require the conversion of the aerodynamic diameter measured to a volume equivalent diameter. In order to perform a quantitative quality assurance, a traceable reference method for the particle number concentration in the size range 0.5-3 mu m is needed.Peer reviewe

New particle formation event detection with convolutional neural networks

New aerosol particle formation (NPF) events play a significant role in altering aerosol concentrations and dispersion within the atmosphere, making them vital for both climate and air quality research. The primary objective of investigating NPF events is to precisely determine their occurrence dates. In this study, we introduced the ConvNeXt model for the first time to identify NPF events, and compared its performance with two other deep learning models, EfficientNet and Swin Transformer. Our main aim was to automate an objective identification and classification of NPF events accurately. All three models employed transfer learning to effectively capture critical features associated with NPF. Our results demonstrated that the ConvNeXt model significantly outperformed the other models, achieving an impressive accuracy rate of 95.3% on event days, surpassing EfficientNet (92.8%) and Swin Transformer (94.9%). Furthermore, we performed tests using different ConvNeXt variants (ConvNeXt-T/S/B/L/XL) and different pre-training weights, revealing that different configurations of ConvNeXt models exhibited improved NPF event recognition capabilities. Finally, we conducted generalizability experiments using the ConvNeXt-XL model, achieving the highest accuracy of 96.4% on event days. This study not only underscores the recognition prowess of ConvNeXt models but also highlights their practical utility in accurately detecting NPF events in real-world scenarios. This contribution aids in advancing our comprehension of aerosol dynamics in atmospheric environments, providing valuable insights for climate and air quality research.This study is supported by the RI-URBANS project (Research Infrastructures Services Reinforcing Air Quality Monitoring Capacities in European Urban & Industrial Areas, European Union's Horizon 2020 research and innovation program, Green Deal, European Commission, contract 101036245). This study is also supported by National Natural Science Foundation of China (42101470, 72242106), and Xinjiang Uygur Autonomous Region (2023D01A57), a grant from State Key Laboratory of Resources and Environmental Information System, in part by the Chunhui Project Foundation of the Education Department of China (HZKY20220053), and by the Hungarian Research, Development and Innovation Office (K132254). M. Savadkoohi would like to thank the Spanish Ministry of Science and Innovation for her FPI grant (PRE-2020-095498) and the support from “Agencia Estatal de Investigaci'on” from the Spanish Ministry of Science and Innovation under the project CAIAC (PID2019-108990RB-I00).Peer reviewe

Term birth weight and ambient air pollutant concentrations during pregnancy, among women living in Monroe County, New York

Increased ambient air pollutant concentrations during pregnancy have been associated with reduced birth weight, but the etiologically relevant pregnancy time window(s) is/are unclear. In 76,500 singleton births in Monroe County, NY (2005–2016), who were 37–42 gestational weeks at delivery, we used generalized linear models to regress term birth weight against mean gestational month pollutant concentrations, adjusting for mean temperature, and maternal, infant, and medical service use characteristics. Overall, there were no clear patterns of term birth weight change associated with increased concentrations of any pollutant across gestational months. However, among Hispanic women only, increases in all pollutants, except O3, in multiple gestational months, were associated with decreased term birth weight. Each 3.25 µg/m3 increase in PM2.5 concentration in the 6th gestational month was associated with a −20.4 g (95% CI = −34.0, −6.8) reduction in term birth weight among Hispanic women, but a 4.1 g (95% CI = −2.5, 10.8) increase among non-Hispanic mothers (p for interaction < 0.001). Although ambient air pollutant concentrations during pregnancy were not associated with reduced term birth weight among women of all ethnicities living in Monroe County, this observed association in Hispanic mothers may be a result of less exposure misclassification and bias (due to closer residential proximity to the monitoring site)

Precipitation scavenging of aerosol particles at a rural site in the Czech Republic

The influence of in-cloud and below-cloud scavenging, described by the obscurities (mist, fog and shallow fog) and precipitation, on submicron atmospheric aerosol (AA) particle number size distributions (PNSDs) was studied using 5 years of measurements at the rural background station Kosˇetice. The typical PNSDs during individual meteorological phenomena were compared, and the change in the concentrations before and after the beginning of the phenomenon, the scavenging coefficient ls, and the rate of change of the AA concentrations with time were computed. It was found that both obscurities and precipitation have a strong influence on theAAconcentrations, both on the total number concentrations and on the PNSDs. The presence of phenomena even changes the number of modes on the PNSDs. The PNSD main mode is shifted to the larger particles, and the concentrations of particles smaller than 50 nm in diameter are considerably lower. In nucleation mode, however, wet scavenging does not seem to be the main process influencing the AA concentrations, although its considerable effect on the concentration was proved. During obscurities, there is a typical PNSD to which the PNSDs converge at any mist/fog/shallow fog event. The concentrations of AA particles smaller than 80 nm are lower than they are during periods without any phenomenon recorded, and the concentrations of the strongly prevailing accumulation mode are higher. During liquid precipitation, PNSDs are lower when compared to non-event periods. With larger droplets of the phenomenon, the position of the main mode of the bimodal PNSDs is shifted to the smaller particles. The process of gas-to-particle conversion takes place in the breaks from precipitation during a rain showers period. Precipitation containing frozen hydrometeors behaves differently from liquid precipitation. Concentrations of AA particles larger than 200 nm during precipitation containing solid particles do not differ from non-event cases, suggesting insignificant scavenging