Proglacial valleys of western Canada and Alaska demonstrate extensive historical and contemporary records of mineral dust emissions. These contributions remain unresolved by current dust emission modelling and unaccounted for in global emission estimates. We developed and evaluated a sub-km implementation of the Weather Research and Forecasting model with Chemistry (WRF-Chem) capable of simulating dust emissions from proglacial valleys of the St. Elias Mountains, Canada. Modelling these dust sources required precise treatment of surface characteristics and wind dynamics to accurately resolve surface erodibility, emission rates and aerosol dispersion within this mountainous terrain. Land-surface inputs were overhauled, with explicit treatment of glaciofluvial deposit heterogeneity and inundation conditions. Simulations covering 5–19 d periods across 2019–2022 were evaluated against in situ meteorological and dust emission measurements, camera stations and surface-based Doppler LiDAR data. A total emission rate of 1.0×104 kg km−2 d−1 was estimated from erodible deposits across 47 d of simulation, providing a first-order estimate of emissions from these valleys during dusty periods. Seasonal-dependent skill in reproducing surface meteorology and in-valley vertical dispersion is demonstrated, modifying dust dispersion. Emission dynamics from a variety of glaciofluvial deposits were successfully reproduced, however the sensitivity of the emission scheme to soil texture is discussed in light of glaciofluvial deposit heterogeneity and dataset scarcity. The successful model implementation under extreme topographic conditions and arguably the most severely constrained deposits (channel width: 0.1–3 km; sidewalls up to +1.7 km) supports the potential of this approach to simulate dust emissions from currently unaccounted for proglacial valleys across northwest North America and other regions.

We investigated the optical and microphysical characterization of High- and sub-Arctic dust events across the Canadian Arctic Archipelago (CAA). Events from local sources (local dust) were first identified and characterized using a combination of ground-based lidar, two AERONET instruments, and passive (MODIS, Sentinel-2, MISR) imagery in the neighbourhood of the High-Arctic Polar Environment Atmospheric Research Laboratory (PEARL) at Eureka, Nunavut (on Ellesmere Island in the northernmost part of the CAA). The PEARL findings informed the identification and characterization of local dust events over other parts of the CAA using a suite of satellite instruments whose remote sensing (RS) capabilities were complementary to or an extension of the ground- and satellite-based techniques employed at Eureka. The events included plumes emanating from Axel Heiberg Island, just west of Ellesmere Island, Banks Island in the southwest corner of the CAA, Ellef Ringnes Island in the eastern part of the central CAA and Prince of Wales Island/Victoria Island in the central southern CAA. Plume identification, plume source and CM (coarse mode) aerosol optical depth (AOD) retrievals were investigated using a combination of low to high spatial resolution (MODIS to Sentinel-2) color imagery and the MODIS dark target AOD product over water. Plume thickness, height and speed for most of the events were obtained (depending on orbit availability and lack of cloud contamination) from MISR (Multi-angle Imaging Spectro Radiometer) stereoscopic products. These RS results support an argument for the ubiquitous presence of pan-Arctic, low altitude dust that is typically (away from any strong sources such as mountainous drainage basins) at the lower levels of detectability offered by ground- and satellite-based RS techniques. The ability to RS airborne, near-source, local dust events and characterize dust properties and dynamics of important regions such as the CAA is critical to understanding local dust impacts such as early snow/ice melt and the nucleation role of local dust in the formation of low-altitude clouds.

The 'A'ay Ch & ugrave;' Valley in Kluane National Park and Reserve, Yukon, Canada has undergone significant hydrological change in the past decade due to climate-driven glacial recession. This has reverted the 'A'ay Ch & ugrave;' to a major source of sediment-derived mineral dust, representing an environmental change for the region. Mineral dust influences climatic radiative forcing and impacts human health, both of which depend on its concentration, size distribution, and composition. This work discusses results from a field campaign conducted in the 'A'ay Ch & ugrave;' Valley in 2021 aimed at understanding and quantifying these parameters, with comparison to a previous campaign in the same location to evaluate the evolution of the dust emissions between 2018 and 2021. An optical particle counter (OPC) instrument measured a mean volume diameter of airborne dust of 4.43 mu m at 3.3 m above ground, with Coulter Counter measurements being used for comparison and validation. The concentration of many metal(loid)s in the dust were also studied: Al, Ag, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Ni, Pb, Rb, Tl, U, and V. It was found that 24 h ambient air quality criteria for exposure to several metal(loid)s were surpassed. Significant enrichment of several metal(loid)s was observed for both the PM10 and PM2.5 size fractions relative to the Total Suspended Material (TSP) fraction of the mineral dust and the parent soil. This suggests that the mineral dust in the 'A'ay Ch & ugrave;' Valley possesses compounding characteristics that are detrimental to human health due to exposure to potentially toxic metal(loid) concentrations.

This study provides the first comprehensive characterisation of the chemical and mineralogical composition of mineral dust from Southern Africa, a major global dust source with significant impacts on regional climate and marine ecosystems. Laboratory-generated dust aerosol samples were produced using soils collected from key natural and emerging anthropogenic dust sources in Southern Africa. The chemical properties of mineral dust across Southern Africa were characterised using the elemental ratios Si/Al, (Ca+Mg)/Al, and K/Al, together with clay content. These indicators distinguish dust aerosols originating from arid western coastal areas from those originating from more humid eastern inland regions. They also provide information about the source-area environments and sediment weathering regimes, which are influenced by current and past temperature and precipitation patterns. The results of this study indicate that Southern African dust contains essential micronutrients such as iron (Fe), phosphorus (P) and manganese (Mn), which can become soluble and bioaccessible during atmospheric transport. In particular, emerging anthropogenic dust can be distinguished by its high content of certain nutrients. This affects the biogeochemistry of nearby and remote marine ecosystems, including the Southern Ocean. Southern African dust also contains higher levels of carbonates than Northern African dust sources, which can promote heterogeneous reactions and particle ageing, and contribute to cloud condensation nuclei in the extensive stratocumulus deck over the northern Benguela Upwelling System. Our findings also suggest that Southern African dust contains higher levels of K-feldspar than Northern African dust, and could therefore be an important source of ice-nucleating particles for low mixed-phase clouds over the Southern Ocean.

Proglacial valleys are important historical and contemporary sources of mineral dust emissions. These dust sources are situated within a complex mountainous terrain, which induce a series of superimposed meteorological phenomena. This paper assesses the forcing mechanisms of high wind speed (HWS) events in the dust storm-prone A'ay Chu (Slims River) valley in southwest Yukon, Canada (60.96 degrees N, 138.60 degrees W). The period of 7 July 2021-30 September 2022 ('15 months) is examined using surface meteorological stations distributed within and near the valley. A hierarchical indexing approach is applied, supported by high-resolution Weather Research and Forecasting (WRF) simulations, to identify dominant meteorological forcing mechanisms of strong wind events. Half (50.0%) of HWS events in the valley occur under high abovevalley wind speeds. Little evidence was found that off-glacier winds drive HWS, despite frequent attribution of these winds to local dust emissions in the literature. A summertime valley wind system is likely responsible for persistent nocturnal HWS near the valley delta (61.00 degrees N, 138.52 degrees W), contributing to the 28% of summer HWS under distinctly calm aloft conditions. Efforts to constrain HWS characteristics from ambient conditions were not successful, partly confounded by adjacent valley wind systems. Ascertaining the configuration of phenomena responsible for high surface winds in these locations is key to yielding the predictive capacity of dust emissions from these rapidly deglaciating landscapes.

Mineral dust dispersion plays a significant role in a variety of natural Earth system processes. This chapter focuses on the identification of major dust sources worldwide. Over the last 20 years a variety of Earth observation sensors have been utilized to identify sources of dust, chiefly by detecting atmospheric aerosols and individual plumes from the TOMS (Total Ozone Mapping Spectrometer), SEVIRI (Spinning Enhanced Visible and InfraRed Imager), MODIS (MODerate resolution Imaging Spectroradiometer) as well as Landsat records. The ability to map aerosols and source points is constrained by several limitations, but overall, has enabled the detection of major dust hotspots around the globe. Many of these have been subject to ground-based inquiries. While we focus on Southern Africa results, much of the world's dust originates from the Sahara and other arid regions. Emissions from high-latitude glacial outwash valleys and anthropogenic activities, such as mining are also noted. The chapter then summarizes the prevailing geomorphological conditions and processes which contribute to dust emissions for a variety of landscape settings and associated landforms. Field equipment and instrumentation used to characterize the nature of dust emissions are briefly introduced. These quantify aerosols in the atmospheric column, determine air quality and allow sampling for physical and geochemical particle analyses. Collectively these techniques provide some insight into the impact of dust. Our full understanding of the extent, nature and controls of mineral dust as well as its impacts at the global scale remain incipient. Results of global dust attribution and modelling efforts are still accompanied by uncertainties. Challenges are numerous and are hindered by the wide range of scales associated with dust research, which include coarse resolution Earth observation data, variable emission at the landform scale, as well as the heterogeneity of particles to name a few.

Elevated concentrations of particulate matter (PM) are associated with poor air quality, and the health effects of PM exposure depend, in part, on its elemental composition. However, techniques to measure the elemental composition of fine and ultrafine PM at the single particle level are limited in terms of their ability to quantitatively detect a wide range of elements in a single particle. In this work, PM2.5 was collected and extracted from polycarbonate filtration membranes using four different methods to optimize recoveries. Based upon gravimetry, the best method tested gave an extraction efficiency of 73 +/- 18%. The elemental compositions of the extracted particles were then determined using single particle inductively coupled plasma time-of-flight mass spectrometry (SP ICP-ToF-MS), which was applied to compare the composition of urban PM (Montreal, Canada) and PM collected from a remote high latitude region impacted by local mineral dust (Dhal T'& agrave;', Canada). With respect to particle number, greater quantities of trace elements associated with anthropogenic sources were observed at the urban site. Specifically, Cr, Pb, Ni, Zn, Ag or Cu were found in 3.8% of the urban particles, often at high mole percentages, but only in 0.7% of the remote particles. Furthermore, the distribution of single particle Fe:Ni and Fe:Cu ratios observed at the urban site was shifted to lower values relative to the remote site. The results demonstrate the value of SP ICP-ToF-MS for analyzing ambient PM, although improved recoveries and sampling methodologies are needed to unlock the full potential of this technique.Copyright (c) 2025 American Association for Aerosol Research

Proglacial valleys of the St. Elias Mountains in western Canada are major sources of historical mineral dust emissions, as evidenced through loess records, yet no estimates of contemporary emissions exist for this region. In these landscapes, dust emissions occur at the interface of glaciofluvial and aeolian processes, not only subject to large seasonal‐annual variability but facing major near‐future changes following rapid deglaciation. We present a camera‐derived observational record of dust emission activity in the A'ą̈y Chù (Yukon, Canada; 60.94°N 138.63°W) and adjacent proglacial valleys between 2016 and 2022, immediately following a major glacial drainage reorganisation. In the A'ą̈y Chù valley, we observe between 57 and 99 days of dust activity per year. Using Landsat 5–8 and MODIS retrievals, long‐term variability in water, snow cover and NDVI was constrained from 1984 to 2023. Across four proglacial valleys, we identify 77.6 km 2 of erodible area (58% of watercourse area), prone to frequent transient meltwater inundation, exposure and potential deflation of glacigenic sediments. Significant variability in seasonal surface erodibility exists between valleys, made notable following the migration of sediment stores into adjacent valleys prone to prolonged snow cover. Ongoing glacier recession and warming climates are anticipated to yield a transient increase in erodible area, and likely dust emissions, in the region over the next several decades. The subsequent decline is anticipated with further deglaciation and the continuing paraglacial transition of proglacial landscapes. A conceptual model is presented to this effect. Understanding contemporary dust emission sources, emission activity and near‐future changes in emission dynamics is critical to establish the role regional mineral dust emissions will occupy in local climatic forcing over the coming decades.

Limited research has been conducted on the role of atmospheric dust as a nutrient source for peatlands, and none has studied the effects of localized and intense road dust on peatland carbon (C) accumulation. To compare the effects of dust deposition from these two sources on peatlands, we examined three ombrotrophic peatlands adjacent to unpaved (gravel) roads in eastern Canada. We find that road dust deposition increases the ash content of peat and decreases its stoichiometric ratios of C, nitrogen (N), and phosphorus (P), with the greatest changes occurring at the site receiving the highest road dust deposition. The dust record since 5,500 cal BP, reconstructed using ICP-MS analysis of lithogenic elements in a peat core, reveals seven dust episodes. The most recent episode, predominantly from road dust, exhibits a flux 19-95 times higher than the background atmospheric dust flux depending on the reference element. In the catotelm layer of the peat core, the atmospheric dust flux exhibits significant positive correlations with C, N, P, and potassium (K) accumulation rates alongside negative correlations with the C:N and C:P ratios. In contrast, the C accumulation rate is lowest closest to the road and increases with distance away from the road as a result of changes in vegetation composition, nutrient availability, and water levels. The different effects of atmospheric dust and road dust suggest that there may be a threshold effect of dust or nutrient inputs, especially P, on peatland C accumulation.

In this study, we performed, for the first time, a detailed analysis of cloudiness in Qu & eacute;bec using station based observations and evaluated the trustworthiness of various satellite and reanalysis based cloud cover products. We found only 12 stations with observational time series long enough for providing robust analysis due to various issues related to observing methods and recording of information during the 1990s. Our results showed that Qu & eacute;bec can be fairly cloudy throughout the year with annual mean cloud cover fraction ranging between 0.5 and 0.7 with autumn being the cloudiest season at most station locations. We also found a significantly increasing trend in cloudiness in the winter season over Qu & eacute;bec during 1982-2012 (similar to 2-6% per decade depending on the location). Among the cloudiness products evaluated in this study, a satellite based cloudiness product (i.e. based on AVHRR) performed best in representing the observed cloudiness over Qu & eacute;bec including the wintertime increasing trend. Two reanalysis based cloudiness products (i.e. ERA5 and NARR) also performed well in representing the observed cloudiness indicated by high correlations, relatively lower mean biases and smaller root mean square errors. However, the reanalysis products did not capture well the observed seasonal trends. All products showed relatively larger biases in the winter season except JRA-25 reanalysis product. During the warmer months, however, JRA-25 showed largest biases followed by MERRA-2 reanalysis product. JRA-25 and MERRA-2 also had lower correlation for annual and winter means and highest root mean square errors for all seasons. Furthermore, based on two skill scores, we found that the ERA5, AVHRR and NARR performed relatively better than JRA-25 and MERRA-2. Based on these results we conclude that the satellite product and the two reanalysis products can be useful resources (as observational proxies) along with station based observations for understanding long term changes in cloudiness of this region and also potentially evaluating regional climate model simulations. [Traduit par la r & eacute;daction] Dans cette & eacute;tude, nous avons r & eacute;alis & eacute;, pour la premi & egrave;re fois, une analyse d & eacute;taill & eacute;e de la n & eacute;bulosit & eacute; au Qu & eacute;bec & agrave; partir d'observations en station et & eacute;valu & eacute; la fiabilit & eacute; de divers produits de couverture nuageuse bas & eacute;s sur des satellites et des r & eacute;analyses. Nous n'avons trouv & eacute; que 12 stations dont les s & eacute;ries temporelles d'observation & eacute;taient suffisamment longues pour permettre une analyse solide, en raison de divers probl & egrave;mes li & eacute;s aux m & eacute;thodes d'observation et & agrave; l'enregistrement des donn & eacute;es au cours des ann & eacute;es 1990. Nos r & eacute;sultats ont r & eacute;v & eacute;l & eacute; que le Qu & eacute;bec peut & ecirc;tre assez nuageux tout au long de l'ann & eacute;e avec une moyenne annuelle de la fraction de couverture nuageuse variant entre 0,5 et 0,7, l'automne & eacute;tant la saison la plus nuageuse dans la plupart des stations. Nous avons & eacute;galement constat & eacute; une tendance & agrave; une hausse significative de la n & eacute;bulosit & eacute; en hiver au Qu & eacute;bec entre 1982 et 2012 (similar to 2-6% par d & eacute;cennie selon l'emplacement). Parmi les produits de n & eacute;bulosit & eacute; & eacute;valu & eacute;s dans cette & eacute;tude, un produit de n & eacute;bulosit & eacute; satellitaire (c.-& agrave;-d. bas & eacute; sur l'AVHRR) a le mieux r & eacute;ussi & agrave; repr & eacute;senter la n & eacute;bulosit & eacute; observ & eacute;e au-dessus du Qu & eacute;bec, y compris la tendance & agrave; la hausse en hiver. Deux produits de n & eacute;bulosit & eacute; provenant de r & eacute;analyses (ERA5 et NARR) ont & eacute;galement bien repr & eacute;sent & eacute; la n & eacute;bulosit & eacute; observ & eacute;e, comme en t & eacute;moignent les corr & eacute;lations & eacute;lev & eacute;es, les biais moyens relativement plus faibles et les erreurs quadratiques moyennes plus faibles. Cependant, les produits de r & eacute;analyse ne reproduisent pas bien les tendances saisonni & egrave;res observ & eacute;es. Tous les produits ont montr & eacute; des biais relativement plus importants en hiver, & agrave; l'exception du produit de r & eacute;analyse JRA-25. Pendant les mois les plus chauds, cependant, JRA-25 a montr & eacute; les biais les plus importants, suivi par le produit de r & eacute;analyse MERRA-2. JRA-25 et MERRA-2 pr & eacute;sentaient & eacute;galement une corr & eacute;lation plus faible pour les moyennes annuelles et hivernales et les erreurs quadratiques moyennes les plus & eacute;lev & eacute;es pour toutes les saisons. En outre, sur la base de deux indices de comparaison, nous avons constat & eacute; que l'ERA5, l'AVHRR et le NARR ont obtenu des r & eacute;sultats relativement meilleurs que le JRA-25 et le MERRA-2. Sur la base de ces r & eacute;sultats, nous concluons que le produit satellite et les deux produits de r & eacute;analyse peuvent & ecirc;tre des ressources utiles (en tant qu'approximations d'observation) avec les observations bas & eacute;es sur les stations pour comprendre les changements & agrave; long terme de la n & eacute;bulosit & eacute; dans cette r & eacute;gion et aussi potentiellement & eacute;valuer les simulations de mod & egrave;les climatiques r & eacute;gionaux.

Dust is a mineral aerosol of the atmosphere that often contains trace elements such as As, Cd, and Pb. Lhù’ààn Mân’ (Kluane Lake), located in southwestern Yukon, is a region of frequent dust activity. In 2016, the lake level fell due to a dramatic decrease in inflow from glacier meltwater, and the delta of the lake became an important source of dust to surrounding ecosystems. To determine the impacts of dust deposition on vegetation and soil trace element concentrations and characteristics, we sampled the lichen Peltigera canina and soil layers at 57 sites along a deposition gradient located 1.4–33.6 km downwind from the principal dust source. Arsenic, Cd, Cu, Ni and Pb in lichens were negatively correlated with the distance away from the dust source, with the highest correlations in Ni and Pb (r2 = 0.50 and 0.48, respectively). Lichen and tree abundances were negatively impacted by dust deposition, suggesting that dust can affect ecosystem vegetation composition. Starting 8 km away from the dust source, the concentrations of As, Ni, and Pb decreased by more than 50% per km, while Cd and Cu concentrations decreased by more than 40% per km. Overall, within the sampled ecosystems, soil pH is 1.4 times higher in the first 8 km from the dust source while carbon content and nutrients are lower, which implies changes in nutrient availability and cycling in dust‐affected ecosystems.

Dust deposition can fertilize nutrient-limited peatlands and affect their plant assemblages and ecosystem functions, but the effects of local road dust on peatlands have seldom been studied. Here, we investigate the responses of vegetation composition and surface chemistry (vegetation, surface peat, and groundwater chemistry) at three ombrotrophic peatlands: Rivière-au-Tonnerre (RT), Chemin de l'Anse-de-la-Grande-Pointe (GP), and Kegaska (KEG) in eastern Québec, Canada, to varying levels of road dust deposition with differential chemical composition. At each site, a transect aligned with the dominant wind direction, starting at and perpendicular to the roadside, was sampled at increasing intervals up to 250 m away from the gravel (unpaved) road. We find that the ash content of surface peat is highest closest to the roads at all three sites and decreases exponentially with increasing distance up to 200 m away from the roads. At KEG, with the highest amount of, and the most phosphorus (P) rich, road dust deposition, the ash content is highest among the three sites, decreasing most rapidly with distance away from the road. The stoichiometric mass ratios of carbon (C), nitrogen (N) and P, i.e., C:N, C:P, and N:P, in foliar tissues and surface peat increase significantly with distance away from the road at KEG, and mosses are found to be more responsive in terms of foliar chemistry than shrubs to the road dust deposition. A higher concentration of total dissolved phosphorus at KEG is found closer to the road. At GP, having a moderate amount of road dust deposition, significant increases in C:N, C:P, and N:P ratios with distance are found only in surface peat but not in foliar tissues. Due to the presence of carbonate minerals in the road dust of GP, the calcium (Ca) concentration and pH value of groundwater closer to the road are higher, leading to an obvious loss of vegetation coverage, especially mosses, and a consequent increase in NO3− leaching. In contrast, at RT, having the lowest amount of road dust deposition, only a few clear variation patterns in surface chemistry are found along the sampling transect. Overall, our results suggest that dust from gravel roads can be an important localized source of nutrients for adjacent peatlands and influence their vegetation composition and surface chemistry, depending on the amount of road dust and its chemical composition, especially its contents in Ca and P.

There is growing recognition that high-latitude dust (HLD), originating from local drainage-basin flows, is the dominant source for certain important phenomena such as particle deposition on snow/ice. The analysis of such local plumes (including a better exploitation of remote sensing data) has been targeted as a key aerosol issue by the HLD community. The sub-Arctic Lhu'aan Man' (Kluane Lake) region in the Canadian Yukon is subject to regular drainage-basin, wind-induced dust plumes. This dust emission site is one of many current and potential proglacial dust sources in the Canadian north. In situ ground-based measurements are, due to constraints in accessing these types of regions, rare. Ground- and satellite-based remote sensing accordingly play an important role in helping to characterize local dust sources in the Arctic and sub-Arctic.We compared ground-based passive and active remote sensing springtime (May 2019) retrievals with microphysical surface-based measurements in the Lhu'aan Man' region in order to better understand the potential for ground- and satellite-based remote sensing of HLD plumes. This included correlation analyses between ground-based coarse mode (CM) aerosol optical depth (AOD) retrievals from AERONET AOD spectra, CM AODs derived from co-located Doppler lidar profiles, and OPS (optical particle sizer) surface measurements of CM particle-volume concentration (vc(0)). An automated dust classification scheme was developed to objectively identify local dust events. The classification process helped distinguish lidar-derived CM AODs which covaried with vdust(0) (during recognized dust events) and those that varied at the same columnar scale as AERONET-derived CM AOD (and thus could be remotely sensed). False positive cloud events for dust-induced, high-frequency variations in lidar-derived CM AODs in cloudless atmospheres indicated that the AERONET cloud-screening process was rejecting CM dust AODs. The persistence of a positive lidar ratio bias in comparing the CIMEL/lidar-derived value with a prescribed value obtained from OPS-derived particle sizes coupled with dust-speciation-derived refractive indices led to the suggestion that the prescribed value could be increased to optically derived values of 20 sr by the presence of optically significant dust particles at an effective radius of 11-12 mu m. Bimodal CM PSDs (see Appendix B for a glossary) from full-fledged AERONET inversions (the combination of AOD spectra and almucantar radiances) also showed CM peaks at similar to 1.3 and 5-6.6 mu m radius: this, we argue, was associated with springtime Asian dust and Lhu'aan Man' dust, respectively. Correlations between the CIMEL-derived fine mode (FM) AOD and FM OPS-derived particle-volume concentrations suggest that remote sensing techniques can be employed to monitor FM dust (which is arguably a better indicator of the long-distance transport of HLD).

Abstract. The observation and quantification of mineral dust fluxes from high-latitude sources remains difficult due to a known paucity of year-round in situ observations and known limitations of satellite remote sensing data (e.g., cloud cover and dust detection). Here we explore the chronology of dust emissions at a known and instrumented high latitude dust source: Lhù’ààn Mân (Kluane Lake) in Yukon, Canada. At this location we combine ground instrumentation, space-based remote sensing platforms, ground-based AERONET data, and oblique camera images to (i) investigate the daily to annual chronology of dust emissions recorded by these instrumental and remote sensing methods (at timescales ranging from minutes to years), and (ii) use data intercomparisons to comment on the principal factors that control the detection of dust in each case. Dust emissions were observed using oblique time-lapse (RC) cameras installed at Lhù’ààn Mân for up to 23 hours a day. These were used as a baseline for analysis of aerosol retrievals from in situ metrological data, AERONET, and co-incident MODIS MAIAC. Use of high-cadence remote camera (RC) data collected during dust events allowed us to optimise the use of combination of date quality (DQ) 1 (aerosol optical depth - AOD) and DQ2 (single scattering albedo and Angstöm exponent) to best represent AOD dust retrievals from AERONET. Nevertheless, when compared with time series of RC data, optimised AERONET data only manage an overall 26 % detection rate for events (sub day) but 100 % detection rate for dust event days (DED) when dust was within the field of view. Here, in this instance, RC and remote sensing data were able to suggest that the low event detection rate was attributed to fundamental variations in dust advection trajectory, dust plume height, and inherent restrictions in sun angle at high latitudes. Working with a time series of optimised AOD data (covering 2018/2019), we were able to investigate the gross impacts of DQ choice on DED detection at the month/year scale. Relative to ground observations, AERONET’s DQ2.0 cloud screening algorithm may remove as much as 97 % of known dust events (3 % detection). Finally, when undertaking an AOD comparison for DED and non-DED retrievals, we find that cloud screening of MODIS/AERONET lead to a combined low sample of co-incident dust events, and weak correlations between retrievals. Our results quantify and explain the extent of under-representation of dust in both ground and space remote sensing method; a factor which impacts on the effective calibration and validation of global climate and dust models.

<p>The sub-Arctic Lhù’ààn Mân’ (Kluane Lake) region in the Canadian Yukon is subject to regular drainage wind-induced dust plumes emanating from the Slims River basin. This dust emissions site is just one of many current and potential future proglacial dust sources in the Canadian North. We employed ground-based passive and active remote sensing (RS) techniques to analyze the complementarity and redundancy of such RS retrievals relative to springtime (May 2019) Kluane Lake microphysical measurements. This included correlation analyses between ground-based coarse mode (CM) aerosol optical depth (AOD) retrievals from AERONET AOD spectra, CM AODs derived from co-located Doppler lidar profiles and OPS (Optical Particle Sizer) surface measurements of CM particle-volume concentration ( ). An automated dust classification scheme tied to intercorrelations between lidar-derived CM AOD, AERONET-derived CM AODs and  variations was developed to objectively identify local dust events. Lidar ratios derived from a priori refractive indices and OPS-derived effective radius statistics were also validated using AERONET-derived CM AODs. Bi-modal CM PSDs from AERONET inversions showed CM peaks at ~ 1.3 µm and 5 – 6.6 µm radius: we argued that this was associated with springtime Asian dust and Lhù’ààn Mân’ dust, respectively. Correlations between the CIMEL-derived fine-mode (FM) AOD and FM OPS-derived particle-volume concentration suggest that remote sensing techniques can be employed to monitor FM dust (which is arguably a better indicator of the long-distance transport of HLD).</p>

Abstract. The observation and quantification of mineral dust fluxes from high-latitudesources remains difficult due to a known paucity of year-round in situobservations and known limitations of satellite remote sensing data (e.g.cloud cover and dust detection). Here we explore the chronology of dustemissions at a known and instrumented high-latitude dust source:Lhù'ààn Mân (Kluane Lake) in Yukon, Canada. At this locationwe use oblique time-lapse (RC) cameras as a baseline for analysis of aerosolretrievals from in situ metrological data, AERONET, and co-incident MODISMAIAC to (i) investigate the daily to annual chronology of dust emissionsrecorded by these instrumental and remote sensing methods (at timescalesranging from minutes to years) and (ii) use data intercomparisons tocomment on the principal factors that control the detection of dust in eachcase. Lhù'ààn Mân is a prolific mineral dust source; on24 May 2018 the RC captured dust in motion throughout the entire day, withthe longest dust-free period lasting only 30 min. When compared withtime series of RC data, optimized AERONET data only manage an overall 26 % detection rate for events (sub-day) but 100 % detection rate for dustevent days (DEDs) when dust was within the field of view. In thisinstance, RC and remote sensing data were able to suggest that the low eventdetection rate was attributed to fundamental variations in dust advectiontrajectory, dust plume height, and inherent restrictions in sun angle athigh latitudes. Working with a time series of optimized aerosol optical depth (AOD) data (covering2018/2019), we were able to investigate the gross impacts of data quality (DQ) choice onDED detection at the month or year scale. Relative to ground observations,AERONET's DQ2.0 cloud-screening algorithm may remove as much as 97 % ofknown dust events (3 % detection). Finally, when undertaking an AODcomparison for DED and non-DED retrievals, we find that cloud screening ofMODIS/AERONET lead to a combined low sample of co-incident dust events andweak correlations between retrievals. Our results quantify and explain theextent of under-representation of dust in both ground and space remotesensing methods; this is a factor that impacts on the effective calibration andvalidation of global climate and dust models.