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Effect of aerosol subgrid variability on aerosol optical depth and cloud condensation nuclei: implications for global aerosol modelling

A fundamental limitation of grid-based models is their inability to resolve variability on scales smaller than a grid box. Past research has shown that significant aerosol variability exists on scales smaller than these grid boxes, which can lead to discrepancies in simulated aerosol climate effects between high- and low-resolution models. This study investigates the impact of neglecting subgrid variability in present-day global microphysical aerosol models on aerosol optical depth (AOD) and cloud condensation nuclei (CCN). We introduce a novel technique to isolate the effect of aerosol variability from other sources of model variability by varying the resolution of aerosol and trace gas fields while maintaining a constant resolution in the rest of the model. We compare WRF-Chem (Weather and Research Forecast model) runs in which aerosol and gases are simulated at 80 km and again at 10 km resolutions; in both simulations the other model components, such as meteorology and dynamics, are kept at the 10 km baseline resolution. We find that AOD is underestimated by 13 % and CCN is overestimated by 27 % when aerosol and gases are simulated at 80 km resolution compared to 10 km. The processes most affected by neglecting aerosol subgrid variability are gas-phase chemistry and aerosol uptake of water through aerosol–gas equilibrium reactions. The inherent non-linearities in these processes result in large changes in aerosol properties when aerosol and gaseous species are artificially mixed over large spatial scales. These changes in aerosol and gas concentrations are exaggerated by convective transport, which transports these altered concentrations to altitudes where their effect is more pronounced. These results demonstrate that aerosol variability can have a large impact on simulating aerosol climate effects, even when meteorology and dynamics are held constant. Future aerosol model development should focus on accounting for the effect of subgrid variability on these processes at global scales in order to improve model predictions of the aerosol effect on climate.
Mercury emissions of a coal-fired power plant in Germany

Hg ∕ SO2, Hg ∕ CO, NOx ∕ SO2 (NOx being the sum of NO and NO2) emission ratios (ERs) in the plume of the coal-fired power plant (CFPP), Lippendorf, near Leipzig, Germany, were determined within the European Tropospheric Mercury Experiment (ETMEP) aircraft campaign in August 2013. The gaseous oxidized mercury (GOM) fraction of mercury emissions was also assessed. Measured Hg ∕ SO2 and Hg ∕ CO ERs were within the measurement uncertainties consistent with the ratios calculated from annual emissions in 2013 reported by the CFPP operator, while the NOx ∕ SO2 ER was somewhat lower. The GOM fraction of total mercury emissions, estimated using three independent methods, was below ∼ 25 %. This result is consistent with other findings and suggests that GOM fractions of ∼ 40 % of CFPP mercury emissions in current emission inventories are overestimated.
Carbon isotopic signature of coal-derived methane emissions to the atmosphere: from coalification to alteration

Currently, the atmospheric methane burden is rising rapidly, but the extent to which shifts in coal production contribute to this rise is not known. Coalbed methane emissions into the atmosphere are poorly characterised, and this study provides representative δ13CCH4 signatures of methane emissions from specific coalfields. Integrated methane emissions from both underground and opencast coal mines in the UK, Australia and Poland were sampled and isotopically characterised. Progression in coal rank and secondary biogenic production of methane due to incursion of water are suggested as the processes affecting the isotopic composition of coal-derived methane. An averaged value of −65 ‰ has been assigned to bituminous coal exploited in open cast mines and of −55 ‰ in deep mines, whereas values of −40 and −30 ‰ can be allocated to anthracite opencast and deep mines respectively. However, the isotopic signatures that are included in global atmospheric modelling of coal emissions should be region- or nation-specific, as greater detail is needed, given the wide global variation in coal type.
Extreme dust storm over the eastern Mediterranean in September 2015: satellite, lidar, and surface observations in the Cyprus region

A record-breaking dust storm originating from desert regions in northern Syria and Iraq occurred over the eastern Mediterranean in September 2015. In this contribution of a series of two articles (part 1, observations; part 2, atmospheric modeling), we provide a comprehensive overview of the aerosol conditions during this extreme dust outbreak in the Cyprus region. These observations are based on satellite observations (MODIS, moderate resolution imaging spectroradiometer) of aerosol optical thickness (AOT) and Ångström exponent, surface particle mass (PM10) concentrations measured at four sites in Cyprus, visibility observations at three airports in southern Cyprus and corresponding conversion products (particle extinction coefficient, dust mass concentrations), EARLINET (European Aerosol Research Lidar Network) lidar observations of dust vertical layering over Limassol, particle optical properties (backscatter, extinction, lidar ratio, linear depolarization ratio), and derived profiles of dust mass concentrations. Maximum 550 nm AOT exceeded values of 5.0, according to MODIS, and the mass loads were correspondingly >  10 g m−2 over Larnaca and Limassol during the passage of an extremely dense dust front on 8 September 2015. Hourly mean PM10 values were close to 8000 µg m−3 and the observed meteorological optical range (visibility) was reduced to 300–750 m at Larnaca and Limassol. The visibility observations suggest peak values of the near-surface total suspended particle (TSP) extinction coefficients of 6000 Mm−1 and thus TSP mass concentrations of 10 000 µg m−3. The Raman polarization lidar observations mainly indicated a double layer structure of the dust plumes (reaching to about 4 km height), pointing to at least two different dust source regions. Dust particle extinction coefficients (532 nm) already exceeded 1000 Mm−1 and the mass concentrations reached 2000 µg m−3 in the elevated dust layers on 7 September, more than 12 h before the peak dust front on 8 September reached the Limassol lidar station around local noon. Typical Middle Eastern dust lidar ratios around 40 sr were observed in the dense dust plumes. The particle depolarization ratio decreased from around 0.3 in the lofted dense dust layers to 0.2 at the end of the dust period (11 September), indicating an increasing impact of anthropogenic haze.
Particle size traces modern Saharan dust transport and deposition across the equatorial North Atlantic

Mineral dust has a large impact on regional and global climate, depending on its particle size. Especially in the Atlantic Ocean downwind of the Sahara, the largest dust source on earth, the effects can be substantial but are poorly understood. This study focuses on seasonal and spatial variations in particle size of Saharan dust deposition across the Atlantic Ocean, using an array of submarine sediment traps moored along a transect at 12° N. We show that the particle size decreases downwind with increased distance from the Saharan source, due to higher gravitational settling velocities of coarse particles in the atmosphere. Modal grain sizes vary between 4 and 32 µm throughout the different seasons and at five locations along the transect. This is much coarser than previously suggested and incorporated into climate models. In addition, seasonal changes are prominent, with coarser dust in summer and finer dust in winter and spring. Such seasonal changes are caused by transport at higher altitudes and at greater wind velocities during summer than in winter. Also, the latitudinal migration of the dust cloud, associated with the Intertropical Convergence Zone, causes seasonal differences in deposition as the summer dust cloud is located more to the north and more directly above the sampled transect. Furthermore, increased precipitation and more frequent dust storms in summer coincide with coarser dust deposition. Our findings contribute to understanding Saharan dust transport and deposition relevant for the interpretation of sedimentary records for climate reconstructions, as well as for global and regional models for improved prediction of future climate.
Evaluation of cloud effects on air temperature estimation using MODIS LST based on ground measurements over the Tibetan Plateau

Moderate Resolution Imaging Spectroradiometer (MODIS) daytime and nighttime land surface temperature (LST) data are often used as proxies for estimating daily maximum (T<mo>max</mo>) and minimum (T<mo>min</mo>) air temperatures, especially for remote mountainous areas due to the sparseness of ground measurements. However, the Tibetan Plateau (TP) has a high daily cloud cover fraction (> 45 %), which may affect the air temperature (Tair) estimation accuracy. This study comprehensively analyzes the effects of clouds on Tair estimation based on MODIS LST using detailed half-hourly ground measurements and daily meteorological station observations collected from the TP. It is shown that erroneous rates of MODIS nighttime cloud detection are obviously higher than those achieved in daytime. Large errors in MODIS nighttime LST data were found to be introduced by undetected clouds and thus reduce the T<mo>min</mo> estimation accuracy. However, for T<mo>max</mo> estimation, clouds are mainly found to reduce the estimation accuracy by affecting the essential relationship between T<mo>max</mo> and daytime LST. The errors of T<mo>max</mo> estimation are obviously larger than those of T<mo>min</mo> and could be attributed to larger MODIS daytime LST errors that result from higher degrees of LST heterogeneity within MODIS pixel compared to those of nighttime LST. Constraining MODIS observations to non-cloudy observations can efficiently screen data samples for accurate T<mo>min</mo> estimation using MODIS nighttime LST. As a result, the present study reveals the effects of clouds on T<mo>max</mo> and T<mo>min</mo> estimation through MODIS daytime and nighttime LST, respectively, so as to help improve the Tair estimation accuracy and alleviate the severe air temperature data sparseness issues over the TP.
Model simulations of cooking organic aerosol (COA) over the UK using estimates of emissions based on measurements at two sites in London

Cooking organic aerosol (COA) is currently not included in European emission inventories. However, recent positive matrix factorization (PMF) analyses of aerosol mass spectrometer (AMS) measurements have suggested important contributions of COA in several European cities. In this study, emissions of COA were estimated for the UK, based on hourly AMS measurements of COA made at two sites in London (a kerbside site in central London and an urban background site in a residential area close to central London) for the full calendar year of 2012 during the Clean Air for London (ClearfLo) campaign. Iteration of COA emissions estimates and subsequent evaluation and sensitivity experiments were conducted with the EMEP4UK atmospheric chemistry transport modelling system with a horizontal resolution of 5 km  ×  5 km. The spatial distribution of these emissions was based on workday population density derived from the 2011 census data. The estimated UK annual COA emission was 7.4 Gg per year, which is an almost 10 % addition to the officially reported UK national total anthropogenic emissions of PM2.5 (82 Gg in 2012), corresponding to 320 mg person−1 day−1 on average. Weekday and weekend diurnal variation in COA emissions were also based on the AMS measurements. Modelled concentrations of COA were then independently evaluated against AMS-derived COA measurements from another city and time period (Manchester, January–February 2007), as well as with COA estimated by a chemical mass balance model of measurements for a 2-week period at the Harwell rural site (∼ 80 km west of central London). The modelled annual average contribution of COA to ambient particulate matter (PM) in central London was between 1 and 2 µg m−3 (∼ 20 % of total measured OA1) and between 0.5 and 0.7 µg m−3 in other major cities in England (Manchester, Birmingham, Leeds). It was also shown that cities smaller than London can have a central hotspot of population density of smaller area than the computational grid cell, in which case higher localized COA concentrations than modelled here may be expected. Modelled COA concentrations dropped rapidly outside of major urban areas (annual average of 0.12 µg m−3 for the Harwell location), indicating that although COA can be a notable component in urban air, it does not have a significant effect on PM concentrations on rural areas. The possibility that the AMS-PMF apportionment measurements overestimate COA concentrations by up to a factor of 2 is discussed. Since COA is a primary emission, any downward adjustments in COA emissions would lead to a proportional linear downward scaling in the absolute magnitudes of COA concentrations simulated in the model.
Parameterization of oceanic whitecap fraction based on satellite observations

In this study, the utility of satellite-based whitecap fraction (W) data for the prediction of sea spray aerosol (SSA) emission rates is explored. More specifically, the study aims at evaluating how an account for natural variability of whitecaps in the W parameterization would affect SSA mass flux predictions when using a sea spray source function (SSSF) based on the discrete whitecap method. The starting point is a data set containing W data for 2006 together with matching wind speed U10 and sea surface temperature (SST) T. Whitecap fraction W was estimated from observations of the ocean surface brightness temperature TB by satellite-borne radiometers at two frequencies (10 and 37 GHz). A global-scale assessment of the data set yielded approximately quadratic correlation between W and U10. A new global W(U10) parameterization was developed and used to evaluate an intrinsic correlation between W and U10 that could have been introduced while estimating W from TB. A regional-scale analysis over different seasons indicated significant differences of the coefficients of regional W(U10) relationships. The effect of SST on W is explicitly accounted for in a new W(U10, T) parameterization. The analysis of W values obtained with the new W(U10) and W(U10, T) parameterizations indicates that the influence of secondary factors on W is for the largest part embedded in the exponent of the wind speed dependence. In addition, the W(U10, T) parameterization is able to partially model the spread (or variability) of the satellite-based W data. The satellite-based parameterization W(U10, T) was applied in an SSSF to estimate the global SSA emission rate. The thus obtained SSA production rate for 2006 of 4.4  ×  1012 kg year−1 is within previously reported estimates, however with distinctly different spatial distribution.
Estimating contributions from biomass burning, fossil fuel combustion, and biogenic carbon to carbonaceous aerosols in the Valley of Chamonix: a dual approach based on radiocarbon and levoglucosan

Atmospheric particulate matter (PM) affects the climate in various ways and has a negative impact on human health. In populated mountain valleys in Alpine regions, emissions from road traffic contribute to carbonaceous aerosols, but residential wood burning can be another source of PM during winter. We determine the contribution of fossil and non-fossil carbon sources by measuring radiocarbon in aerosols using the recently installed AixMICADAS facility. The accelerator mass spectrometer is coupled to an elemental analyzer (EA) by means of a gas interface system directly connected to the gas ion source. This system provides rapid and accurate radiocarbon measurements for small samples (10–100 µgC) with minimal preparation from the aerosol filters. We show how the contamination induced by the EA protocol can be quantified and corrected for. Several standards and synthetic samples are then used to demonstrate the precision and accuracy of aerosol measurements over the full range of expected 14C ∕ 12C ratios, ranging from modern carbon to fossil carbon depleted in 14C. Aerosols sampled in Chamonix and Passy (Arve River valley, French Alps) from November 2013 to August 2014 are analyzed for both radiocarbon (124 analyses in total) and levoglucosan, which is commonly used as a specific tracer for biomass burning. NOx concentration, which is expected to be associated with traffic emissions, is also monitored. Based on 14C measurements, we can show that the relative fraction of non-fossil carbon is significantly higher in winter than in summer. In winter, non-fossil carbon represents about 85 % of total carbon, while in summer this proportion is still 75 % considering all samples. The largest total carbon and levoglucosan concentrations are observed for winter aerosols with values up to 50 and 8 µg m−3, respectively. These levels are higher than those observed in many European cities, but are close to those for other polluted Alpine valleys. The non-fossil carbon concentrations are strongly correlated with the levoglucosan concentrations in winter samples, suggesting that almost all of the non-fossil carbon originates from wood combustion used for heating during winter. For summer samples, the joint use of 14C and levoglucosan measurements leads to a new model to separately quantify the contributions of biomass burning and biogenic emissions in the non-fossil fraction. The comparison of the biogenic fraction with polyols (a proxy for primary soil biogenic emissions) and with the temperature suggests a major influence of the secondary biogenic aerosols. Significant correlations are found between the NOx concentration and the fossil carbon concentration for all seasons and sites, confirming the relation between road traffic emissions and fossil carbon. Overall, this dual approach combining radiocarbon and levoglucosan analyses strengthens the conclusion concerning the impact of biomass burning. Combining these geochemical data serves both to detect and quantify additional carbon sources. The Arve River valley provides the first illustration of aerosols of this model.
The spectral signature of cloud spatial structure in shortwave irradiance

In this paper, we used cloud imagery from a NASA field experiment in conjunction with three-dimensional radiative transfer calculations to show that cloud spatial structure manifests itself as a spectral signature in shortwave irradiance fields – specifically in transmittance and net horizontal photon transport in the visible and near-ultraviolet wavelength range. We found a robust correlation between the magnitude of net horizontal photon transport (H) and its spectral dependence (slope), which is scale-invariant and holds for the entire pixel population of a domain. This was surprising at first given the large degree of spatial inhomogeneity. We prove that the underlying physical mechanism for this phenomenon is molecular scattering in conjunction with cloud spatial structure. On this basis, we developed a simple parameterization through a single parameter ε, which quantifies the characteristic spectral signature of spatial inhomogeneities. In the case we studied, neglecting net horizontal photon transport leads to a local transmittance bias of ±12–19 %, even at the relatively coarse spatial resolution of 20 km. Since three-dimensional effects depend on the spatial context of a given pixel in a nontrivial way, the spectral dimension of this problem may emerge as the starting point for future bias corrections.