Organic aerosol (OA) is a major component of atmospheric particulate matter (PM), affecting both human health and climate. However, high-resolution estimates of OA exposure needed for exposure analysis remain scarce. Here, we integrate a chemical transport model (CAMx) with a random forest (RF) machine learning approach to bias-correct and downscale daily OA concentrations across Europe. CAMx OA simulations at ∼15 km resolution show moderate agreement with observations (r = 0.55). By combining these outputs with high-resolution land-use data and training the RF model on ∼48,000 daily OA measurements from 137 sites, prediction accuracy improved (r = 0.65), with ∼l5% reduction in root mean square error. The resulting maps provide European daily OA concentrations at ∼250 m resolution for alternate years from 2011 to 2019. The model captures key spatial features, including elevated OA in the Po Valley, Southeastern, and Central Europe, as well as intracity variations due to local hotspots. Seasonal analysis reveals higher concentrations in winter, while long-term trends indicate a general decline in OA levels. Exposure estimates show that half of the European population experiences OA levels above 3 µg/m3, and ∼50 million people are exposed to more than 5 µg/m3, which is the current guideline level recommended by the world health organization for total PM2.5. These high-resolution OA maps offer vital critical support for epidemiological research and air quality policy.

It is important to study aerosols and their origins, as they pose various negative health and environmental impacts. In this study, we combined year-long datasets from 15 different countries with Trajectory Statistical Methods (TSMs) for the first time at this comprehensive scale. We found possible source regions and seasonal variations of various particulate matter (PM) components in Europe, including total organic aerosol (OA), biomass burning OA (BBOA), oxygenated OA (OOA), ammonium (NH4), nitrate (NO3), and sulphate (SO4). We found that for all of the studied components, Eastern Europe was among the highest contributors. For NO3, other important source regions were Northern France and the Benelux, while for SO4 there were significant contributions from the Mediterranean region. We also compared our measurement-based model with simulated concentrations of an atmospheric chemistry transport model (CAMx). We observed a satisfactory agreement in regions where we had sufficient coverage with air pollution monitoring stations. The main deviations for OA were found around the Po Valley, where CAMx consistently estimated higher concentrations, while the TSM analysis did not highlight it as a hotspot because long-term monitoring datasets in this region are lacking. CAMx also underestimated the concentrations around Poland, mainly from residential burning. Our results provide opportunities to refine European emission inventories and deliver valuable information on long-range transported air pollutants. This work suggests that policies mitigating air pollution in Eastern Europe and the Benelux could help improve overall air quality in entire Europe more efficiently.

Fine particulate matter (PM) poses a major threat to public health, with organic aerosol (OA) being a key component. Major OA sources, hydrocarbon-like OA (HOA), biomass burning OA (BBOA), and oxygenated OA (OOA), have distinct health and environmental impacts. However, OA source apportionment via positive matrix factorization (PMF) applied to aerosol mass spectrometry (AMS) or aerosol chemical speciation monitoring (ACSM) data is costly and limited to a few supersites, leaving over 80% of OA data uncategorized in global monitoring networks. To address this gap, we trained machine learning models to predict HOA, BBOA, and OOA using limited OA source apportionment data and widely available organic carbon (OC) measurements across Europe (2010-2019). Our best performing model expanded the OA source data set 4-fold, yielding 85 000 daily apportionment values across 180 sites. Results show that HOA and BBOA peak in winter, particularly in urban areas, while OOA, consistently the dominant fraction, is more regionally distributed with less seasonal variability. This study provides a significantly expanded OA source data set, enabling better identification of pollution hotspots and supporting high-resolution exposure assessments.

Background Lockdown measures during the SARS-CoV-2 pandemic determined radical changes to behavioral and social habits, that were reflected by a reduction in the transmission of respiratory pathogens and in anthropogenic atmospheric emissions. Objective This ecological study aims to provide a descriptive evaluation on how restrictive measures during the SARS-CoV-2 pandemic impacted Pediatric Emergency Department (PED) referrals for asthma exacerbations, and their potentially associated environmental triggers in Bologna, a densely populated urban area in Northern Italy. Methods Files of children evaluated for acute asthma during 2015 to 2020 at the PED of Sant'Orsola University Hospital of Bologna were retrospectively reviewed. Historical daily concentration records of particulate (PM2.5, PM10) and gaseous (NO2, C6H6) air pollutants, and pollen were concurrently evaluated, including specific PM chemical tracers for traffic-related air pollution (TRAP). Results In 2020, asthma-related PED referrals decreased compared to referral rates of the previous 5 years (p < 0.01). This effect was particularly marked during the first lockdown period (March to May), when the drastic drop in PED referrals was associated with a reduction of high-priority cases up to 85% and by 54%, on average. A concomitant reduction in the concentrations of traffic-related air pollutants was observed in the range of 40%-60% (p < 0.01). Conclusions The lower rate of asthma exacerbations in childhood was in this study paralleled with reduced TRAP levels during the pandemic. Synergic interactions of the multiple consequences of lockdowns likely contributed to the reduced exacerbations, including decreased exposure to ambient pollutants and fewer respiratory infections, identified as the most important factor in the literature.

A new sensitivity analysis with the Comprehensive Air Quality Model with Extensions (CAMx) using a traditional two-product scheme (SOAP) and the newer Volatility Basis Set (VBS) algorithm for organic aerosol (OA) calculations is presented. The sensitivity simulations include the default versions of the SOAP and VBS schemes, as well as new parametrizations for the VBS scheme to calculate emissions and volatility distributions of semi- and intermediate-volatile organic compounds. The focus of the simulations is the summer season (May to July 2013), in order to quantify the sensitivity of the model in a period with relatively large photochemical activity. In addition to the model sensitivity, we validate the results with ad hoc OA measurements obtained from aerosol mass spectrometers at two monitoring sites. Unlike winter cases previously published, the comparison with experimental data showed limited sensitivity to total OA amount, with an estimated increase in OA concentrations limited to a few tenths of µg m−3, for both the primary and secondary components. We show that the lack of pronounced sensitivity is related to the effect of the new parametrizations on different emissions sectors. Furthermore, the minor sensitivity to the new parametrizations could be related to the greater partitioning of OA towards the gaseous phase in the summer period, thus reducing the organic fraction in the aerosol phase.

A source apportionment study was carried out at four sites in Emilia-Romagna region, southern Po Valley, one of the most critical regions in Europe in terms of atmospheric pollution. PM2.5 daily samples were collected during 4 years from April 2013 to October 2017 at one rural site (San Pietro Capofiume) and three urban background locations in the cities of Bologna, Rimini, Parma which show different features and are located in the central, coastal and inner part of the investigated region. Samples were analyzed to achieve a complete chemical characterization (carbon fractions, ions, and elements). A source apportionment analysis by Positive Matrix Factorization (PMF) was performed and 6 PM2.5 factors were identified at all sites but the rural one (where 5 out of 6 of them were detected); the factors were associated to traffic with dust resuspension, biomass burning, oil combustion/ship emission, mix anthropogenic (not found at the rural site), ammonium nitrate and ammonium sulfate with organics. Chemical profiles of factors were very similar among all the 4 sites, indicating that main pollution sources are basically the same at the 4 sites, while some differences emerged with regard to source contributions. Factors related to secondary components seem to explain almost 50% or even more of PM2.5 mass concentration in all seasons. Traffic and biomass burning are the most relevant contributors to PM2.5 in terms of primary components. A not negligible contribution of biomass burning results in Rimini during the summer, suggesting other possible sources of wood combustion, such as cooking or open burning of agricultural pruning bonfires. Agriculture is not singled out as a PMF factor, but a rough estimate based on ammonium concentrations and ammonia data from emission inventory indicates a contribution from this source of about 10% of PM2.5 mass, thus resulting the single productive activity with the highest impact on PM2.5 at the investigated sites. Back trajectory analysis points out the relevant extra-regional contributions of two factors; indeed, oil combustion/ship emission is related to long-range transport of air masses overpassing the Mediterranean sea and secondary sulfate from Eastern Europe countries occasionally impacts on the Po Valley.

Background: Asthma exacerbations, a common reason for Pediatric Emergency Department (PED) referral, can be triggered by multiple factors, including infections, air pollution and allergens. Lockdown measures and other public health interventions during the SARS-CoV-2 pandemic determined radical changes to behavioral and social habits, that were reflected by a reduction in the transmission of all respiratory pathogens and in the emissions of relevant air pollution anthropogenic sources. Objective: This study aims to describe how restrictions during SARS-CoV-2 pandemic impacted the PED referral for asthma exacerbations and their potentially associated environmental triggers in densely populated urban areas. Methods: PED referrals for acute asthma from 2015 to 2020 were compared to air pollution and pollen data. To this purpose, historical daily concentration records of PM2.5, PM10 (including specific chemical tracers), as well as NO2, C6H6, tree, grass and weed pollen were analyzed. Results: In 2020, asthma-related PED referrals decreased up to 85%, compared to the average referral rate of the previous 5 years (P<0.01). The drastic drop in PED referrals was associated with a reduction of high-priority cases by 50-60%, unlike PED referrals for overall diagnoses, showing a larger contribution for severe outcomes. A concomitant diminished contribution of traffic-related air pollution was shown. Conclusions: The lower rate of asthma exacerbations in childhood can be related to synergic interactions of the multiple effects of lockdown measures which induced lower viral infection rates and decreased exposure to outdoor allergens. The reduction of traffic-related air pollution determined a weakening of inflammatory properties of urban PM.

The Po Valley (Italy) is a well-known air quality hotspot characterized by particulate matter (PM) levels well above the limit set by the European Air Quality Directive and by the World Health Organization, especially during the colder season. In the framework of Emilia-Romagna regional project “Supersito”, the southern Po Valley submicron aerosol chemical composition was characterized by means of high-resolution aerosol mass spectroscopy (HR-AMS) with the specific aim of organic aerosol (OA) characterization and source apportionment. Eight intensive observation periods (IOPs) were carried out over 4 years (from 2011 to 2014) at two different sites (Bologna, BO, urban background, and San Pietro Capofiume, SPC, rural background), to characterize the spatial variability and seasonality of the OA sources, with a special focus on the cold season. On the multi-year basis of the study, the AMS observations show that OA accounts for averages of 45±8 % (ranging from 33 % to 58 %) and 46±7 % (ranging from 36 % to 50 %) of the total non-refractory submicron particle mass (PM1-NR) at the urban and rural sites, respectively. Primary organic aerosol (POA) comprises biomass burning (23±13 % of OA) and fossil fuel (12±7 %) contributions with a marked seasonality in concentration. As expected, the biomass burning contribution to POA is more significant at the rural site (urban / rural concentration ratio of 0.67), but it is also an important source of POA at the urban site during the cold season, with contributions ranging from 14 % to 38 % of the total OA mass. Secondary organic aerosol (SOA) contributes to OA mass to a much larger extent than POA at both sites throughout the year (69±16 % and 83±16 % at the urban and rural sites, respectively), with important implications for public health. Within the secondary fraction of OA, the measurements highlight the importance of biomass burning aging products during the cold season, even at the urban background site. This biomass burning SOA fraction represents 14 %–44 % of the total OA mass in the cold season, indicating that in this region a major contribution of combustion sources to PM mass is mediated by environmental conditions and atmospheric reactivity. Among the environmental factors controlling the formation of SOA in the Po Valley, the availability of liquid water in the aerosol was shown to play a key role in the cold season. We estimate that the organic fraction originating from aqueous reactions of biomass burning products (“bb-aqSOA”) represents 21 % (14 %–28 %) and 25 % (14 %–35 %) of the total OA mass and 44 % (32 %–56 %) and 61 % (21 %–100 %) of the SOA mass at the urban and rural sites, respectively.

Elemental carbon (EC), a ubiquitous component of fine atmospheric aerosol derived from incomplete combustion, is an important player for both climate change and air quality deterioration. Several policy measures have been implemented over the last decades to reduce EC emissions from anthropogenic sources, but still, long-term EC measurements to verify the efficacy of such measurements are limited. In this study, we analyze the concentration of EC suspended in fog water samples, collected over the period 1997–2016 in a rural background site of the southern Po Valley. The comparison between EC in fog water and EC atmospheric aerosol concentration measured since 2012 allowed us to reconstruct EC atmospheric concentration from fog water chemical composition dating back to 1997. The results agree with the EC atmospheric observations performed at the European Monitoring and Evaluation Program (EMEP) station of Ispra in the northern part of the Po Valley since 2002, and confirm that the Po Valley is a pollution hotspot, not only in urban areas, but also in rural locations. The reconstructed trend over the period 1997–2016 indicates that EC concentration during the winter season has decreased on average by 4% per year, in agreement with the emission reduction rate, confirming the effectiveness of air quality measures implemented during the past 20 years.

Sensor based monitoring systems have been indicated as a promising tool to increase information on spatio-temporal distribution of air pollution but several issues have been raised about the accuracy of such monitors when used in the field. The study aimed at assessing the performance of sensor based systems after multiple relocation in different seasons and sites. The systems included electrochemical sensors to measure NO2 and O-3 concentrations. The approach consisted in two-week field calibration of each device at a reference monitoring station and the test of the calibrated device at different reference station sites. The main specific goal was a comparison of sensor performance considering site-specific (SS) and no site-specific (no SS) calibration, i.e. calibration and testing carried out or not at sites with similar characteristics. Calibration was performed by season using random forest (RF) models. Very good performance was found for calibrated O-3 sensors with R-2 >= 0.82 regardless of seasons and sites. Mean normalized root mean square error (nRMSE) was around 7% and 6% in winter and summer tests, respectively. Very good performance of sensor systems was observed also for NO2 during winter (R-2 >= 0.84) with much better accuracy for SS compared to no SS calibration (nRMSE equal to 6% and 17%, respectively). A marked decrease of performance was observed for NO2 sensors during summer. Our results show a good potential of sensor based systems after SS field calibration in increasing information on the distribution of air pollution at high spatial and temporal resolution.

Background/aim: The aim of the present study was to assess the association between PM2.5, its sources, and preterm birth (PTB), low birth weight (LBW), and small for gestational age (SGA) in a large open residential cohort (Supersito Project in the Emilia-Romagna Region - Northern Italy). Methods: We collected 2012-2014 pregnancy and childbirth data from Birth Assistance Certificates and selected the pregnancies of interest. PTBs (gestational age < 37 weeks), LBW (weight < 2500 g), and SGA (newborns weighing <= 10th age and pregnancy week-specific percentile) were considered. Three-year measurements of daily concentrations and constituents of PM2.5 were available at four sites and were analyzed through a source apportionment approach identifying 6 sources (traffic, biomass burning, oil combustion, anthropogenic mix, and two secondary factors). Exposure to PM2.5 and sources was calculated at address level. Using logistic regression models, associations between exposure and outcomes were derived, applying single-pollutant and two-pollutant models, to verify the independent effect of each source. Results: The study included 23,708 neonates born to 23,415 women, among whom 1,311 PTB, 424 LBW, and 1,354 SGA occurred. PTB was the only outcome associated with PM2.5 mass (OR 1.03, 95% CI 1.002-1.058 per 1 mu g/m(3)). Traffic, oil combustion and secondary sulfates and organics showed independent effects on PTB. Exposure to secondary nitrates was associated with a lower risk of PTB. There was no association between LBW or SGA and source-specific PM2.5 components or the residual PM2.5 related to all other sources. Conclusion: This study found an association between PTB and PM2.5. Traffic, secondary sulfates, and organic and oil combustion were the sources with most consistent association.

This study presents a high-resolution (5 km) set of new simulations performed with CAMx v6.40 over the Po Valley area (Northern Italy), aimed to enhance organic aerosol (OA) levels prediction and to gain insight into the sensitivity of CAMx to different uncertain features of the input setup. In particular, we mainly investigated the role of (i) volatility distributions of organic emissions, (ii) parametrizations of semi- and intermediate-volatile organic compounds (S/IVOC) emissions and (iii) different aging schemes, by exploiting the latest experimental information available in the recent scientific literature. Model results were validated against two OA-specific datasets, available for both an urban site (Bologna, February 2013) and a rural one (Ispra, March 2013). We found out a remarkable performance enhancement of modelled OA levels when applying revisions in S/IVOC emission parametrizations together with the new volatility distributions, at both the validation sites. This performance enhancement is associated with a very significant improvement in secondary organic aerosol (SOA) prediction, mainly due to revised IVOC emissions. At Bologna urban site, mean fractional bias (MFB) of OA ranged from - 80.1% in the worst run to - 10.1% in the best one and index of agreement (IOA) from 0.52 to 0.75. Notable improvements but overall poorer metrics were found for Ispra site, where MFB ranges from - 84.2% to - 35% and IOA from 0.45 to 0.50. These findings indicate that organic matter in the semi- and intermediate-volatile range are most likely underestimated in official emission inventories for each main source category (i.e. biomass burning, diesel and gasoline vehicles exhaust). Finally, model results did not show a very pronounced sensitivity to aging processes, due to the low photochemical activity typically observed during winter-time. However, we give evidence that enabling aging processes for biomass burning related SOA, which is by default disabled in CAMx v6.40, can help in closing the gap between modelled and observed SOA concentrations.

Substantial efforts have been made in recent years to investigate the horizontal variability of air pollutants at regional and urban scales and epidemiological studies have taken advantage of resulting improvements in exposure assessment. On the contrary, only a few studies have investigated the vertical variability and their results are not consistent. In this study, a field experiment has been conducted to evaluate the variation of concentrations of different particle metrics and gaseous pollutants on the basis of floor height at a high rise building. Two 15-day monitoring campaigns were conducted in the urban area of Bologna, Northern Italy, one of the most polluted areas in Europe. Measurements sites were operated simultaneously at 2, 15, 26, 44 and 65 m a.g.l. Several particulate matter metrics including PM2.5 mass and chemical composition, particle number concentration and size distribution were measured. Time integrated measurement of NO2 and BTEX were also included in the monitoring campaigns. Measurements showed relevant vertical gradients for most traffic related pollutants. A monotonic gradient of PM2.5 was found with ground-to-top differences of 4% during the warm period and 11% during the cold period. Larger gradients were found for UFP (similar to 30% during both seasons) with a substantial loss of particles from ground to top in the sub-SO nm size range. The largest drops in concentrations for chemical components were found for Elemental Carbon (-27%), iron (-11%) and tin (-36%) during winter. The ground-to-top decline of concentrations for NO2 and benzene during winter was equal to 74% and 35%, respectively. In conclusion, our findings emphasize the need to include vertical variations of urban air pollutants when evaluating population exposure and associated health effects, especially in relation to some traffic related pollutants and particle metrics. (C) 2017 Elsevier Ltd. All rights reserved.

Estimates of lung dose of submicron particles in the human respiratory system play an essential role in assessing health outcomes of aerosol exposure. The objectives of this study are to calculate the regional lung dose of traffic-generated particles by different metrics from exposure in outdoor and indoor environments and to identify main factors determining the lung dose. Particle number size distributions were collected in both indoor and outdoor environments in two unoccupied apartments from 22nd February to 30th April 2012 in Bologna, Italy. The whole lung doses of outdoor aerosols by number, surface area and mass at a traffic site were 1.0 × 10 10 particles/h, 130 mm 2 /h and 1.9 μg/h, respectively. A majority of particles by number and surface area were found to deposit in the alveolar region (65%). The physical properties of particles such as shape, hygroscopicity and density play an important role in the calculation of surface area and mass dose due to shifting of the lung deposition curve. Particle number can predict well the regional dose by number, while PM 2.5 and PM 10 are good metrics for the prediction of surface area and mass dose. Good correlations between NO x and the surface areas and mass dose ( r 2 ~ 0.8) and number dose ( r 2 ~ 0.7) of submicron aerosols suggest that NO x may be a good indicator for predicting the health outcomes of traffic-generated aerosols. The doses of indoor sub-micrometre aerosols are less than those of outdoor aerosols by factors of 4.1 (for number), 2.7 (for surface area) and 2.1 (for mass). Due to traffic emissions, the lung dose of outdoor aerosols in the traffic area was much higher than that in the residential area by 5 times for number and surface area and 2 times for mass. A different exercise level (standing, walking, running and cycling) has only a slight influence on the whole lung deposition fraction of submicron aerosols but has a large effect on the dose due to differences in ventilation rate.

A large number of studies have shown much higher health effects of particulate matter (PM) during the warm compared to the cold season. In this paper we present the results of an experimental study carried out in an unoccupied test apartment with the aim of understanding the reasons behind the seasonal variations of the health effects due to ambient PM2.5 exposure. Measurements included indoor and outdoor PM2.5 mass and chemical composition as well as particle size distribution of ultrafine particles. Monitoring campaigns were carried out during summer and winter following a ventilation protocol developed to replicate typical occupant behaviour according to a questionnaire-based survey. Our findings showed that seasonal variation of the relationship between ambient and indoor mass concentrations cannot entirely explain the apparent difference in PM toxicity between seasons and size distribution and chemical composition of particles were identified as other possible causes of changes in the apparent PM toxicity. A marked decrease of ultrafine particles (<100 nm) passing from outdoors to indoors was observed during winter; this resulted in higher indoor exposure to nanoparticles (<50 nm) during summer. With regards to the chemical composition, a pooled analysis showed infiltration factors of chemical species similar to that obtained for PM2.5 mass with values increasing from 0.73 during winter to 0.90 during summer and few deviations from the pooled estimates. In particular, significantly lower infiltration factors and sink effect were found for nitrates and ammonium during winter. In addition, a marked increase in the contribution of indoor and outdoor sulfates to the total mass was observed during summer.

Traditional aerosol mechanisms underestimate the observed organic aerosol concentration, especially due to the lack of information on secondary organic aerosol (SOA) formation and processing. In this study we evaluate the chemical and transport model CAMx during a one-month in winter (February 2013) over a 5 km resolution domain, covering the whole Po valley (Northern Italy). This works aims at investigating the effects of chemical and physical atmospheric processing on modelling results and, in particular, to evaluate the CAMx sensitivity to organic aerosol (OA) modelling schemes: we will compare the recent 1.5D-VBS algorithm (CAMx-VBS) with the traditional Odum 2-product model (CAMx-SOAP). Additionally, the thorough diagnostic analysis of the reproduction of meteorology, precursors and aerosol components was intended to point put strength and weaknesses of the modelling system and address its improvement. Firstly, we evaluate model performance for criteria PM concentration. PM10 concentration was underestimated both by CAMx-SOAP and even more by CAMx-VBS, with the latter showing a bias ranging between -4.7 and -7.1 mu g m(-3). PM2.5 model performance was to some extent better than PM10, showing a mean bias ranging between -0.5 mu g m(-3) at rural sites and -5.5 mu g m(-3) at urban and suburban sites. CAMx performance for OA was clearly worse than for the other PM compounds (negative bias ranging between -40% and -75%). The comparisons of model results with OA sources (identified by PMF analysis) shows that the VBS scheme underestimates freshly emitted organic aerosol while SOAP overestimates. The VBS scheme correctly reproduces biomass burning (BBOA) contributions to primary OA concentrations (POA). In contrast VBS slightly underestimates the contribution from fossil-fuel combustion (HOA), indicating that POA emissions related to road transport are either underestimated or associated to higher volatility classes. The VBS scheme under-predictes the SOA too, but to a lesser extent than CAMx-SOAP. SOA underestimation can be related to corresponding underestimation of either aging processes or precursor emissions. This indicates that improvements in the emission inventories for semi and intermediate-volatility organic compounds are needed for further progress in this area. Finally, the comparison between modelled and observed SOA sources points out the urgency to include processing of OA in particle water phase into SOA formation mechanisms, to reconcile model results and observations. (C) 2017 Elsevier Ltd. All rights reserved.

Most conventional aerosol neutralizers are based on radioactive sources, which are controlled by strict regulations restricting their handling, transport, and storage. The TSI 3087 soft X-ray (SXR) neutralizer circumvents these legal restrictions. The aim of the present work is to compare the performance of a standalone SXR aerosol neutralizer with that of conventional radioactive aerosol neutralizers based on Kr-85 (TSI 3077) and Am-241 (Grimm 5522) by performing field tests in a real environmental scenario. The results obtained when the SXR neutralizer was connected to a mobility particle sizer spectrometer (MPS), different from the device suggested by the manufacturer, were comparable with those obtained with the use of radioactive aerosol neutralizers. In changing the neutralizer, the particle number concentrations, measured with the MPS connected to the SXR neutralizer, almost remained within the 10% uncertainty bounds for the particle size interval 10-300 nm, when diffusion losses inside the SXR tube were considered. Based on our comparisons, the SXR neutralizer can be regarded as a standalone instrument that could solve the problems associated with legal restrictions on radioactive neutralizers and fulfil the need for a portable instrument for different field test purposes. (C) 2017 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

We investigate optical–microphysical–chemical properties of brown carbon (BrC) in the urban ambient atmosphere of the Po Valley. In situ ground measurements of aerosol spectral optical properties, PM1 chemical composition (HR-ToF-AMS), and particle size distributions were carried out in Bologna. BrC was identified through its wavelength dependence of light absorption at visible wavelengths, as indicated by the absorption Ångström exponent (AAE). We found that BrC occurs in particles with a narrow monomodal size distribution peaking in the droplet mode, enriched in ammonium nitrate and poor in black carbon (BC), with a strong dependance on OA-to-BC ratios, and SSA530 of 0.98 ± 0.01. We demonstrate that specific complex refractive index values (k530 = 0.017 ± 0.001) are necessary in addition to a proper particle size range to match the large AAEs measured for this BrC (AAE467 − 660 = 3.2 ± 0.9 with values up to 5.3). In terms of consistency of these findings with literature, this study i. provides experimental evidence of the size distribution of BrC associated with the formation of secondary aerosol;ii. shows that in the lower troposphere AAE increases with increasing OA-to-BC ratios rather than with increasing OA – contributing to sky radiometer retrieval techniques (e.g., AERONET);iii. extends the dependence of AAE on BC-to-OA ratios previously observed in chamber experiments to ambient aerosol dominated by wood-burning emissions. These findings are expected to bear important implications for atmospheric modeling studies and remote sensing observations as regards the parametrization and identification of BrC in the atmosphere.