Activation properties of aerosol particles as cloud condensation nuclei at urban and high-altitude remote sites in southern Europe

Determining the impact of new particle formation events on cloud condensation nuclei (CCN) concentrations

Atmospheric aerosol particles act as cloud condensation nuclei (CCN) and play a crucial role in the climate system and hydrological cycle. New particle formation (NPF) events are a significant source of CCN, though their global contribution to the CCN budget remains uncertain. We propose a novel method to estimate the direct contribution of NPF events to CCN concentrations, distinguishing between NPF-generated particles and background or transported aerosols. Previous methods estimated CCN concentration enhancements by comparing CCN concentration at different times periods (during or after NPF events with CCN concentrations prior to the events or with non-event days). Our method overcomes this limitation by focusing on the ceiling size that newly formed particles can reach, the timing of NPF events, and isolating the NPF mode from the overall aerosol size distribution. The method was developed using size-resolved CCN measurements at the Sierra Nevada Station (SNS) in southeastern Spain (2500 m a.s.l.). We demonstrate that the method is also applicable to polydisperse CCN measurements, showing consistency across both variants. Additionally, it has been applied to NPF events at the Izaña Observatory (IZO) in Tenerife (Canary Islands, 2367 m a.s.l.). Both SNS and IZO frequently experience NPF events, though their environmental and aerosol characteristics differ, providing insights into the advantages and limitations of the method. Comparison between the two sites reveals that the mean NPF contribution to CCN is 6.2 ± 4.8 % (IQR = 9 %) at SNS and 24 ± 25 % (IQR = 28 %) at IZO. The higher NPF contribution at IZO is attributed to the ability of newly formed particles to grow to larger sizes and the presence of fewer transported boundary layer particles acting as CCN. Both sites show significant variability in the NPF contribution percentage due to the distinct characteristics of each NPF event.

Under-researched and under-reported new findings in microplastic field

After over 20 years of research on microplastic (MP) pollution, there are important areas of study which are still at the inception. In particular, between 2020 and 2023 new findings on MP have emerged, which open new sub-categories of MP research. These research areas include sea surface MP ejection, direct and indirect MP influence on climate and hydrological cycle, small and nano-sized MP analysis and the relationship between MP size and abundance. Not reported or barely mentioned in previous reviews, these globally-relevant findings are here highlighted and discussed with aim to promote their further research that will potentially result in new evidence of detrimental effects of MP pollution on the biosphere.

Diurnal source apportionment of organic and inorganic atmospheric particulate matter at a high-altitude mountain site under summer conditions (Sierra Nevada; Spain)

High-altitude mountain areas are sentinel ecosystems for global environmental changes such as anthropogenic pollution. In this study, we report a source apportionment of particulate material with an aerodynamic diameter smaller than 10 μm (PM10) in a high-altitude site in southern Europe (Sierra Nevada Station; SNS (2500 m a.s.l.)) during summer 2021. The emission sources and atmospheric secondary processes that determine the composition of aerosol particles in Sierra Nevada National Park (Spain) are identified from the concentrations of organic carbon (OC), elemental carbon (EC), 12 major inorganic compounds, 18 trace elements and 44 organic molecular tracer compounds in PM10 filter samples collected during day- and nighttime. The multivariate analysis of the joint dataset resolved five main PM10 sources: 1) Saharan dust, 2) advection from the urbanized valley, 3) local combustion, 4) smoke from a fire-event, and 5) aerosol from regional recirculation with high contribution of particles from secondary inorganic and organic aerosol formation processes. PM sources were clearly associated with synoptic meteorological conditions, and day- and nighttime circulation patterns typical of mountainous areas. Although a local pollution source was identified, the contribution of this source to PM10, OC and EC was small. Our results evidence the strong influence of middle- and long-range transport of aerosols, mainly from anthropogenic origin, on the aerosol chemical composition at this remote site.

Impact of urban aerosols on the cloud condensation activity using a clustering model

The indirect effect of aerosols on climate through aerosol-cloud-interactions is still highly uncertain and limits our ability to assess anthropogenic climate change. The foundation of this uncertainty is in the number of cloud condensation nuclei (CCN), which itself mainly stems from uncertainty in aerosol sources and how particles evolve to become effective CCN. We analyze particle number size distribution (PNSD) and CCN measurements from an urban site in a two-step method: (1) we use an unsupervised clustering model to classify the main aerosol categories and processes occurring in the urban atmosphere and (2) we explore the influence of the identified aerosol populations on the CCN properties. According to the physical properties of each cluster, its diurnal timing, and additional air quality parameters, the clusters are grouped into five main aerosol categories: nucleation, growth, traffic, aged traffic, and urban background. The results show that, despite aged traffic and urban background categories are those with lower total particle number concentrations (N_tot) these categories are the most efficient sources in terms of contribution to the overall CCN budget with activation fractions (AF) around 0.5 at 0.75 % supersaturation (SS). By contrast, road traffic is an important aerosol source with the highest frequency of occurrence (32 %) and relatively high N_tot, however, its impact in the CCN activity is very limited likely due to lower particle mean diameter and hydrophobic chemical composition. Similarly, nucleation and growth categories, associated to new particle formation (NPF) events, present large N_tot with large frequency of occurrence (22 % and 28 %, respectively) but the CCN concentration for these categories is about half of the CCN concentration observed for the aged traffic category, which is associated with their small size. Overall, our results show that direct influence of traffic emissions on the CCN budget is limited, however, when these particles undergo ageing processes, they have a significant influence on the CCN concentrations and may be an important CCN source. Thus, aged traffic particles could be transported to other environments where clouds form, triggering a plausible indirect effect of traffic emissions on aerosol-cloud interactions and consequently contributing to climate change.

Lidar and Radar Signal Simulation: Stability Assessment of the Aerosol–Cloud Interaction Index

Aerosol–cloud interactions (ACI) are in the spotlight of atmospheric science since the limited knowledge about these processes produces large uncertainties in climate predictions. These interactions can be quantified by the aerosol–cloud interaction index (ACI index), which establishes a relationship between aerosol and cloud microphysics. The experimental determination of the ACI index through a synergistic combination of lidar and cloud radar is still quite challenging due to the difficulties in disentangling the aerosol influence on cloud formation from other processes and in retrieving aerosol-particle and cloud microphysics from remote sensing measurements. For a better understanding of the ACI and to evaluate the optimal experimental conditions for the measurement of these processes, a Lidar and Radar Signal Simulator (LARSS) is presented. LARSS simulate vertically-resolved lidar and cloud-radar signals during the formation process of a convective cloud, from the aerosol hygroscopic enhancement to the condensation droplet growth. Through LARSS simulations, it is observed a dependence of the ACI index with height, associated with the increase in number (ACINd) and effective radius (ACIreff) of the droplets with altitude. Furthermore, ACINd and ACIreff for several aerosol types (such as ammonium sulfate, biomass burning, and dust) are estimated using LARSS, presenting different values as a function of the aerosol model. Minimum ACINd values are obtained when the activation of new droplets stops, while ACIreff reaches its maximum values several meters above. These simulations are carried out considering standard atmospheric conditions, with a relative humidity of 30% at the surface, reaching the supersaturation of the air mass at 3500 m. To assess the stability of the ACI index, a sensitivity study using LARSS is performed. It is obtained that the dry modal aerosol radius presents a strong influence on the ACI index fluctuations of 18% cause an ACI variability of 30% while the updraft velocity within the cloud and the wet modal aerosol radius have a weaker impact. LARSS ACI index uncertainty is obtained through the Monte Carlo technique, obtaining ACIreff uncertainty below 16% for the uncertainty of all LARSS input parameters of 10%. Finally, a new ACI index is introduced in this study, called the remote-sensing ACI index (ACIRs), to simplify the quantification of the ACI processes with remote sensors. This new index presents a linear relationship with the ACIreff, which depends on the Angstrom exponent. The use of ACIRs to derive ACIreff presents the advantage that it is possible to quantify the aerosol–cloud interaction without the need to perform microphysical inversion retrievals, thus reducing the uncertainty sources.