Aerosol-cloud interactions (ACI) are a significant source of uncertainty in climate projections. Nitrogen-dominated aerosol episodes are emerging over the Netherlands, strongly influencing local air quality and climate, but our understanding of aerosol-cloud interactions under these nitrogen-dominated conditions is still not well quantified. Ground-based remote-sensing instruments like cloud radars can provide us high temporal and spatial resolution data for cloud microphysics, like cloud droplet number concentration, and aerosol properties can be obtained using lidar measurements. In this study, we quantify how these aerosol particles in nitrogen-polluted episodes affect low-level clouds by combining remote-sensing observations with aerosol speciation measurements at the Ruisdael Observatory in the Netherlands.

Generally, column aerosol optical depth (AOD) from sun photometers and vertically resolved attenuated backscatter (ATB) from ceilometers are used as aerosol proxies. A key difference is that AOD represents extinction integrated over the full atmospheric column, whereas ATB is a vertically resolved backscatter profile, and ATB must therefore be vertically integrated for a meaningful comparison. However, both respond differently to meteorological parameters, aerosol loadings, and the instrument’s configurations. Therefore, understanding the variation of ATB and AOD in response to meteorology is essential. Overall, our framework will provide consistent conditions under which ceilometer ATB can be used as an aerosol proxy along with the column AOD during nitrogen-dominated episodes.

Here, we use a Mie model framework to investigate how ATB and AOD behave under different aerosol compositions, loadings, and meteorological conditions. Further, using a long-term observation from Cabauw (the Netherlands) as a case site, we focus on periods when nitrate clearly dominates the aerosol composition. Surface data from aerosol mass spectrometry and size-distribution measurements are combined with ceilometer profiles, sun-photometer retrievals, and meteorological data. Together, these measurements allow nitrogen-dominated episodes to be grouped by composition, relative humidity, and boundary-layer conditions, providing a consistent way to quantify aerosol-cloud interactions.

Our initial results indicate that, during nitrate-dominated episodes, hygroscopic aerosol particles build up in the boundary layer and strongly enhance light extinction. Extinction, backscatter, and other related aerosol optical properties respond strongly to RH-driven particle growth, making the growth factor a key control on the observed signals. We will investigate these relationships in more detail using measurements from both the RITA-2021 and the CAINA-2025 campaign datasets. These nitrate-rich aerosols act as cloud condensation nuclei (CCN), and they are expected to increase cloud droplet number concentration with more but smaller cloud droplets, which can be detected by ground-based cloud radar observations.

The resulting framework provides insight into how nitrogen-rich aerosol pollution affects clouds' microphysical properties and strengthens the understanding of aerosol-cloud interactions in nitrate-dominated environments.

Proposed solar radiation modification (SRM) field experiments are receiving growing scientific and policy attention, with several localized experiments having occurred or under development. While they may be critical for improving technical understanding and reducing uncertainties, SRM field experiments remain controversial and inadequately captured under current legal, ethical, and political frameworks, which often rely on binary “small-scale” or “large-scale” distinctions. In practice, SRM field experiments may vary widely in scale, geography, materials, scientific purpose, and environmental impacts, making uniform governance approaches impractical. Here, we develop a typology of plausible, scientifically motivated SRM field experiments across three leading approaches: stratospheric aerosol injection (SAI), marine cloud brightening (MCB), and cirrus and mixed-phase cloud thinning (CCT/MCT). We identify six SAI, five MCB, and three CCT/MCT experiments across a range of scales, assessing their interaction with existing environmental and legal frameworks, particularly within the EU. The study also addresses governance challenges such as scale perception and stakeholder legitimacy, and highlights procedural tools, including exit ramps and transparency requirements. We introduce a phase-based typology of plausible SRM field experiments: near-phase (technically and regulatorily feasible), intermediate-phase (technically feasible but likely to cross regulatory thresholds), and distant-phase (plausible but requiring comprehensive review and new governance mechanisms). The intermediate-phase highlights that SRM research cannot be reduced to a small-/large-scale binary: many plausible experiments occupy a gray zone where scientific value is high, but governance remains underdeveloped. Recognizing this distinction may help prioritize governance, guide proportionate regulation, and ensure field experiments are evaluated by intent and their regulatory implications.

Solar radiation modification (SRM) is increasingly discussed as a potential method to ameliorate some negative effects of climate change. However, unquantified uncertainties in physical and environmental impacts of SRM impede informed debate and decision making. Some uncertainties are due to lack of understanding of processes determining atmospheric effects of SRM and/or a lag in development of their representation in models, meaning even high-quality model intercomparisons will not necessarily reveal or address them. Although climate models at multiple scales are advancing in complexity, there are specific areas of uncertainty where additional model development (often requiring new observations) could significantly advance understanding of SRM's effects, and improve our ability to assess and weigh potential risks against those of choosing to not use SRM. We convene expert panels in the areas of atmospheric science most critical to understanding the three most widely discussed forms of SRM. Each identifies three key modeling gaps relevant to either stratospheric aerosols, cirrus, or low-altitude marine clouds. Within each area, key challenges remain in capturing impacts due to complex interactions in aerosol physics, atmospheric chemistry/dynamics, and aerosol-cloud interactions. Across all three, in addition to arguing for more observations, the panels argue that model development work to either leverage different capabilities of existing models, bridge scales across which relevant processes operate, or address known modeling gaps could advance understanding. By focusing on these knowledge gaps we believe the modeling community could advance understanding of SRM's physical risks and potential benefits, allowing better-informed decision-making about whether and how to use SRM.

There are obstacles in better understanding the climate impacts associated with new materials that could be used for Stratospheric Aerosol Injections (SAI), like the lack of an integrated framework that combines climate modeling across scales, laboratory studies and small-scale field experiments. Vattioni et al. (2023, https://doi.org/10.1029/2023gl105889) explored one aspect of using alternative, non-sulfate materials for SAI. They investigated how uncertain the response of stratospheric ozone would be to alumina injections for SAI. In their study, they quantify chlorine activation rates in the presence of alumina, and then cascade these uncertainties into estimates of ozone depletion, concluding that alumina might have less detrimental impacts on stratospheric chemistry than sulfate, but with large uncertainties. Their results provide a useful basis upon which future research endeavors combining indoor and outdoor experiments and modeling may be structured to produce robust assessments of SAI impacts, benefits and uncertainties, together with clarifying what kind of research needs to be prioritized.

The open-source Video In Situ Snowfall Sensor (VISSS) is introduced as a novel instrument for the characterization of particle shape and size in snowfall. The VISSS consists of two cameras with LED backlights and telecentric lenses that allow accurate sizing and combine a large observation volume with relatively high pixel resolution and a design that limits wind disturbance. VISSS data products include various particle properties such as maximum extent, cross-sectional area, perimeter, complexity, and sedimentation velocity. Initial analysis shows that the VISSS provides robust statistics based on up to 10000 unique particle observations per minute. Comparison of the VISSS with the collocated PIP (Precipitation Imaging Package) and Parsivel instruments at Hyytiälä, Finland, shows excellent agreement with the Parsivel but reveals some differences for the PIP that are likely related to PIP data processing and limitations of the PIP with respect to observing smaller particles. The open-source nature of the VISSS hardware plans, data acquisition software, and data processing libraries invites the community to contribute to the development of the instrument, which has many potential applications in atmospheric science and beyond.

Ice nucleating particles (INPs) are rare particles that initiate primary ice formation, a critical step required for subsequent important cloud microphysical processes that ultimately govern cloud phase and cloud radiative properties. Laboratory studies have found that organic-rich dusts, such as those found in soils, are more efficient INPs compared to mineral dust. However, the atmospheric relevance of these organic-rich dusts are not well understood, particularly in regions with significant agricultural activity. The Agricultural Ice nuclei at the Southern Great Plains field campaign (AGINSGP) was conducted in rural Oklahoma to investigate how soil dusts contribute to INP populations in the Great Plains. We present chemical characterization of ambient and ice crystal residual particles from a single day of sampling, using single particle mass spectrometry (SPMS) and scanning microscopy. Ambient particles were primarily carbonaceous or secondary aerosol, while the fraction of dust particles was higher in the residual particles. We also observed an unusual particle type consisting of a carbonaceous core mixed with dust fragments on the surface, which was found in higher proportion in residuals. Dust particles measured during residual sampling contained greater proportions of phosphate (63PO2 and 79PO3) and lead (206Pb+). Strong sulfate signals were not seen in the residual dust particles measured by the SPMS, while nitrate was slightly depleted relative to ambient dust. This study shows that organic-rich soils may be important contributors to the ambient INP population in agricultural regions.