Routine aerosol measurements have been carried out at INTA–El Arenosillo (Huelva, Spain) since February 2000 with a Cimel sun photometer integrated in the global aerosol monitoring network AERONET. A 5‐year aerosol database allows characterization and classification of aerosol properties, which define the local aerosol climatology. In this work two basic parameters for aerosol characterization, aerosol optical depth (AOD) and Ångström exponent, α, are used for aerosol analysis. The mean AOD is 0.18 ( ± 0.14) and the mean α is 1.05 ( ± 0.43). The AOD presents two peaks during the year, at the end of the winter and during the summer, which are related to the seasonal patterns of the desert dust aerosols which arrive at the south‐western Iberian Peninsula from North Africa. The Ångström exponent presents two frequency modes, related to the two main aerosol types present at El Arenosillo: coastal marine aerosols and desert dust. A main aerosol scenario (66% of data) is defined as coastal marine aerosols, with the influence of local sources of continental and polluted aerosols. Continental aerosols are present in 11% of cases, while the desert dust has a very relevant occurrence in around 20% of the data. Copyright © 2007 Royal Meteorological Society

Knowledge of aerosol size and composition is important for determining radiative forcing effects of aerosols, identifying aerosol sources and improving aerosol satellite retrieval algorithms. The ability to extrapolate aerosol size and composition, or type, from intensive aerosol optical properties can help expand the current knowledge of spatiotemporal variability in aerosol type globally, particularly where chemical composition measurements do not exist concurrently with optical property measurements. This study uses medians of the scattering Ångström exponent (SAE), absorption Ångström exponent (AAE) and single scattering albedo (SSA) from 24 stations within the NOAA/ESRL Federated Aerosol Monitoring Network to infer aerosol type using previously published aerosol classification schemes.Three methods are implemented to obtain a best estimate of dominant aerosol type at each station using aerosol optical properties. The first method plots station medians into an AAE vs. SAE plot space, so that a unique combination of intensive properties corresponds with an aerosol type. The second typing method expands on the first by introducing a multivariate cluster analysis, which aims to group stations with similar optical characteristics and thus similar dominant aerosol type. The third and final classification method pairs 3-day backward air mass trajectories with median aerosol optical properties to explore the relationship between trajectory origin (proxy for likely aerosol type) and aerosol intensive parameters, while allowing for multiple dominant aerosol types at each station.The three aerosol classification methods have some common, and thus robust, results. In general, estimating dominant aerosol type using optical properties is best suited for site locations with a stable and homogenous aerosol population, particularly continental polluted (carbonaceous aerosol), marine polluted (carbonaceous aerosol mixed with sea salt) and continental dust/biomass sites (dust and carbonaceous aerosol); however, current classification schemes perform poorly when predicting dominant aerosol type at remote marine and Arctic sites and at stations with more complex locations and topography where variable aerosol populations are not well represented by median optical properties. Although the aerosol classification methods presented here provide new ways to reduce ambiguity in typing schemes, there is more work needed to find aerosol typing methods that are useful for a larger range of geographic locations and aerosol populations.

Aerosol particles are essential constituents of the Earth's atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence times, resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in situ near-surface segment of the atmospheric observation system. This paper will provide the widest effort so far to document variability of climate-relevant in situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High-quality data from almost 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single-scattering albedo, and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information, including data provision procedures, quality control and analysis, data policy, and usage of the ground-based aerosol measurement network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.

Aerosol particles are a complex component of the atmospheric system which influence climate directly by interacting with solar radiation, and indirectly by contributing to cloud formation. The variety of their sources, as well as the multiple transformations they may undergo during their transport (including wet and dry deposition), result in significant spatial and temporal variability of their properties. Documenting this variability is essential to provide a proper representation of aerosols and cloud condensation nuclei (CCN) in climate models. Using measurements conducted in 2016 or 2017 at 62 ground-based stations around the world, this study provides the most up-to-date picture of the spatial distribution of particle number concentration (N_tot) and number size distribution (PNSD, from 39 sites). A sensitivity study was first performed to assess the impact of data availability on N_tot's annual and seasonal statistics, as well as on the analysis of its diel cycle. Thresholds of 50 % and 60 % were set at the seasonal and annual scale, respectively, for the study of the corresponding statistics, and a slightly higher coverage (75 %) was required to document the diel cycle. Although some observations are common to a majority of sites, the variety of environments characterizing these stations made it possible to highlight contrasting findings, which, among other factors, seem to be significantly related to the level of anthropogenic influence. The concentrations measured at polar sites are the lowest (∼ 10² cm⁻³) and show a clear seasonality, which is also visible in the shape of the PNSD, while diel cycles are in general less evident, due notably to the absence of a regular day–night cycle in some seasons. In contrast, the concentrations characteristic of urban environments are the highest (∼ 10³–10⁴ cm⁻³) and do not show pronounced seasonal variations, whereas diel cycles tend to be very regular over the year at these stations. The remaining sites, including mountain and non-urban continental and coastal stations, do not exhibit as obvious common behaviour as polar and urban sites and display, on average, intermediate N_tot (∼ 10²–10³ cm⁻³). Particle concentrations measured at mountain sites, however, are generally lower compared to nearby lowland sites, and tend to exhibit somewhat more pronounced seasonal variations as a likely result of the strong impact of the atmospheric boundary layer (ABL) influence in connection with the topography of the sites. ABL dynamics also likely contribute to the diel cycle of N_tot observed at these stations. Based on available PNSD measurements, CCN-sized particles (considered here as either >50 nm or >100 nm) can represent from a few percent to almost all of N_tot, corresponding to seasonal medians on the order of ∼ 10 to 1000 cm⁻³, with seasonal patterns and a hierarchy of the site types broadly similar to those observed for N_tot. Overall, this work illustrates the importance of in situ measurements, in particular for the study of aerosol physical properties, and thus strongly supports the development of a broad global network of near surface observatories to increase and homogenize the spatial coverage of the measurements, and guarantee as well data availability and quality. The results of this study also provide a valuable, freely available and easy to use support for model comparison and validation, with the ultimate goal of contributing to improvement of the representation of aerosol–cloud interactions in models, and, therefore, of the evaluation of the impact of aerosol particles on climate.

The Aerosol Robotic Network (AERONET) site “El Arenosillo,” equipped with a Cimel sun photometer, has been in operation since 2000. The data collected there are analyzed to establish an aerosol synoptic climatological description that is representative of the region. Different air masses and aerosol types are present over the site depending on the synoptic conditions. The frequent intrusion of dust from the Sahara Desert at El Arenosillo suggested the use of back trajectories to determine the airmass origins of other types of aerosol observed there. The focus of this study is to classify the air masses arriving at El Arenosillo by means of back-trajectory analyses and to characterize the aerosol within each type by means of the aerosol optical depth (AOD) and its spectral signature, given as the Ångström exponent (AE). The goal is to determine how aerosols observed over the station (receptor site) differ depending on source region and transport pathways. Two classification methods are used, one based on sectors and a second based on cluster analysis. The period analyzed is from 2000 to 2004. Both methods show that maritime air masses are predominant, occurring 70% of the time and having relatively low AOD (≈0.1 at 440 nm) and a wide range of AE (from about 0 to 2.0). Air masses with continental characteristics are moderately turbid and have values of AE that average ≈1.4. Air masses arriving from the south and southwest show the distinct features of the desert dust, having moderate to high values of AOD (0.30–0.35 at 440 nm) and low values of AE.

We present the analysis of the strongest North African desert dust (DD) intrusion that occurred over the Iberian Peninsula (IP) during the last decade, as registered by modern remote sensing techniques like Sun photometry. This event took place from 22 July to 3 August 2004. The most relevant features of this exceptional event, originated over the Saharan desert, were its great intensity and duration. We focus on the columnar aerosol properties measured by the AERONET‐Cimel photometers at El Arenosillo (southwest) and Palencia (north‐center) stations. Aerosol optical depth (AOD) reached a maximum of 2.7 at El Arenosillo during 22 July and 1.3 at Palencia on 23 July, with the Ånsgtröm exponent values near zero during the AOD peaks. In addition, PM10 concentration levels are also reported at various sites of the IP in order to establish the impact of this intrusion, reaching daily values as high as 200 μg/m³ and peaks near 600 μg/m³ in an hourly basis. The interest of this special event is increased because of the mixing with smoke particles from concurrent forest fires in the IP. Features of the columnar volume particle size distribution and derived microphysical parameters, the single scattering albedo, and a reliable estimation of the radiative forcing under these extreme conditions are also reported. Complementary information, as air mass back trajectories, synoptic charts, images, and AOD maps of satellite sensors (SeaWIFS, MODIS) together with NAAPS prognostic model, is used in the analysis in order to draw a detailed scenario of this dust‐smoke event over the IP.