ALBERT

Description: The spread of the new coronavirus SARS-CoV-2 that causes COVID-19 forced the Spanish Government to implement extensive lockdown measures to reduce the number of hospital admissions, starting on 14 March 2020. Over the following days and weeks, strong reductions in nitrogen dioxide (NO2) pollution were reported in many regions of Spain. A substantial part of these reductions was obviously due to decreased local and regional anthropogenic emissions. Yet, the confounding effect of meteorological variability hinders a reliable quantification of the lockdown's impact upon the observed pollution levels. Our study uses machine-learning (ML) models fed by meteorological data along with other time features to estimate the “business-as-usual” NO2 mixing ratios that would have been observed in the absence of the lockdown. We then quantify the so-called meteorology-normalized NO2 reductions induced by the lockdown measures by comparing the estimated business-as-usual values with the observed NO2 mixing ratios. We applied this analysis for a selection of urban background and traffic stations covering the more than 50 Spanish provinces and islands. The ML predictive models were found to perform remarkably well in most locations, with an overall bias, root mean square error and correlation of +4 %, 29 % and 0.86, respectively. During the period of study, from the enforcement of the state of alarm in Spain on 14 March to 23 April, we found the lockdown measures to be responsible for a 50 % reduction in NO2 levels on average over all provinces and islands. The lockdown in Spain has gone through several phases with different levels of severity with respect to mobility restrictions. As expected, the meteorology-normalized change in NO2 was found to be stronger during phase II (the most stringent phase) and phase III of the lockdown than during phase I. In the largest agglomerations, where both urban background and traffic stations were available, a stronger meteorology-normalized NO2 change is highlighted at traffic stations compared with urban background sites. Our results are consistent with foreseen (although still uncertain) changes in anthropogenic emissions induced by the lockdown. We also show the importance of taking the meteorological variability into account for accurately assessing the impact of the lockdown on NO2 levels, in particular at fine spatial and temporal scales. Meteorology-normalized estimates such as those presented here are crucial to reliably quantify the health implications of the lockdown due to reduced air pollution.

Description: It is well established that in Europe, high O3 concentrations are most pronounced in southern/Mediterranean countries due to the more favourable climatological conditions for its formation. However, the contribution of the different sources of precursors to O3 formation within each country relative to the imported (regional and hemispheric) O3 is poorly quantified. This lack of quantitative knowledge prevents local authorities from effectively designing plans that reduce the exceedances of the O3 target value set by the European air quality directive. O3 source attribution is a challenge because the concentration at each location and time results not only from local biogenic and anthropogenic precursors, but also from the transport of O3 and precursors from neighbouring regions, O3 regional and hemispheric transport and stratospheric O3 injections. The main goal of this study is to provide a first quantitative estimation of the contribution of the main anthropogenic activity sectors to peak O3 events in Spain relative to the contribution of imported (regional and hemispheric) O3. We also assess the potential of our source apportionment method to improve O3 modelling. Our study applies and thoroughly evaluates a countrywide O3 source apportionment method implemented in the CALIOPE air quality forecast system for Spain at high resolution (4 × 4 km2) over a 10-day period characterized by typical summer conditions in the Iberian Peninsula (IP). The method tags both O3 and its gas precursor emissions from source sectors within one simulation, and each tagged species is subject to the typical physico-chemical processes (advection, vertical mixing, deposition, emission and chemistry) as the actual conditions remain unperturbed. We quantify the individual contributions of the largest NOx local sources to high O3 concentrations compared with the contribution of imported O3. We show, for the first time, that imported O3 is the largest input to the ground-level O3 concentration in the IP, accounting for 46 %–68 % of the daily mean O3 concentration during exceedances of the European target value. The hourly imported O3 increases during typical northwestern advections (70 %–90 %, 60–80 µg m−3), and decreases during typical stagnant conditions (30 %–40 %, 30–60 µg m−3) due to the local NO titration. During stagnant conditions, the local anthropogenic precursors control the O3 peaks in areas downwind of the main urban and industrial regions (up to 40 % in hourly peaks). We also show that ground-level O3 concentrations are strongly affected by vertical mixing of O3-rich layers present in the free troposphere, which result from local/regional layering and accumulation, and continental/hemispheric transport. Indeed, vertical mixing largely explains the presence of imported O3 at ground level in the IP. Our results demonstrate the need for detailed quantification of the local and remote contributions to high O3 concentrations for local O3 management, and show O3 source apportionment to be an essential analysis prior to the design of O3 mitigation plans in any non-attainment area. Achieving the European O3 objectives in southern Europe requires not only ad hoc local actions but also decided national and European-wide strategies.

Description: Atmospheric processing of iron in dust and combustion aerosols is simulated using an intermediate-complexity soluble iron mechanism designed for Earth system models. The solubilization mechanism includes both a dependence on aerosol water pH and in-cloud oxalic acid. The simulations of size-resolved total, soluble and fractional iron solubility indicate that this mechanism captures many but not all of the features seen from cruise observations of labile iron. The primary objective was to determine the extent to which our solubility scheme could adequately match observations of fractional iron solubility. We define a semi-quantitative metric as the model mean at points with observations divided by the observational mean (MMO). The model is in reasonable agreement with observations of fractional iron solubility with an MMO of 0.86. Several sensitivity studies are performed to ascertain the degree of complexity needed to match observations; including the oxalic acid enhancement is necessary, while different parameterizations for calculating model oxalate concentrations are less important. The percent change in soluble iron deposition between the reference case (REF) and the simulation with acidic processing alone is 63.8 %, which is consistent with previous studies. Upon deposition to global oceans, global mean combustion iron solubility to total fractional iron solubility is 8.2 %; however, the contribution of fractional iron solubility from combustion sources to ocean basins below 15∘ S is approximately 50 %. We conclude that, in many remote ocean regions, sources of iron from combustion and dust aerosols are equally important. Our estimates of changes in deposition of soluble iron to the ocean since preindustrial climate conditions suggest roughly a doubling due to a combination of higher dust and combustion iron emissions along with more efficient atmospheric processing.

Description: The direct radiative effect (DRE) during 20 intense and widespread dust outbreaks, which affected the broader Mediterranean basin over the period March 2000–February 2013, has been calculated with the NMMB-MONARCH model at regional (Sahara and European continent) and short-term temporal (84 h) scales. According to model simulations, the maximum dust aerosol optical depths (AODs) range from ∼ 2.5 to ∼ 5.5 among the identified cases. At midday, dust outbreaks locally induce a NET (shortwave plus longwave) strong atmospheric warming (DREATM values up to 285 W m−2; Niger–Chad; dust AODs up to ∼ 5.5) and a strong surface cooling (DRENETSURF values down to −337 W m−2), whereas they strongly reduce the downward radiation at the ground level (DRESURF values down to −589 W m−2 over the Eastern Mediterranean, for extremely high dust AODs, 4.5–5). During night-time, reverse effects of smaller magnitude are found. At the top of the atmosphere (TOA), positive (planetary warming) DREs up to 85 W m−2 are found over highly reflective surfaces (Niger–Chad; dust AODs up to ∼ 5.5) while negative (planetary cooling) DREs down to −184 W m−2 (Eastern Mediterranean; dust AODs 4.5–5) are computed over dark surfaces at noon. Dust outbreaks significantly affect the mean regional radiation budget, with NET DREs ranging from −8.5 to 0.5 W m−2, from −31.6 to 2.1 W m−2, from −22.2 to 2.2 W m−2 and from −1.7 to 20.4 W m−2 for TOA, SURF, NETSURF and ATM, respectively. Although the shortwave DREs are larger than the longwave ones, the latter are comparable or even larger at TOA, particularly over the Sahara at midday. As a response to the strong surface day-time cooling, dust outbreaks cause a reduction in the regional sensible and latent heat fluxes by up to 45 and 4 W m−2, respectively, averaged over land areas of the simulation domain. Dust outbreaks reduce the temperature at 2 m by up to 4 K during day-time, whereas a reverse tendency of similar magnitude is found during night-time. Depending on the vertical distribution of dust loads and time, mineral particles heat (cool) the atmosphere by up to 0.9 K (0.8 K) during day-time (night-time) within atmospheric dust layers. Beneath and above the dust clouds, mineral particles cool (warm) the atmosphere by up to 1.3 K (1.2 K) at noon (night-time). On a regional mean basis, negative feedbacks on the total emitted dust (reduced by 19.5 %) and dust AOD (reduced by 6.9 %) are found when dust interacts with the radiation. Through the consideration of dust radiative effects in numerical simulations, the model positive and negative biases for the downward surface SW or LW radiation, respectively, with respect to Baseline Surface Radiation Network (BSRN) measurements, are reduced. In addition, they also reduce the model near-surface (at 2 m) nocturnal cold biases by up to 0.5 K (regional averages), as well as the model warm biases at 950 and 700 hPa, where the dust concentration is maximized, by up to 0.4 K. However, improvements are relatively small and do not happen in all episodes because other model first-order errors may dominate over the expected improvements, and the misrepresentation of the dust plumes' spatiotemporal features and optical properties may even produce a double penalty effect. The enhancement of dust forecasts via data assimilation techniques may significantly improve the results.

Description: This paper presents a comprehensive description and benchmark evaluation of the tropospheric gas-phase chemistry component of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH), formerly known as NMMB/BSC-CTM, that can be run on both regional and global domains. Here, we provide an extensive evaluation of a global annual cycle simulation using a variety of background surface stations (EMEP, WDCGG and CASTNET), ozonesondes (WOUDC, CMD and SHADOZ), aircraft data (MOZAIC and several campaigns), and satellite observations (SCIAMACHY and MOPITT). We also include an extensive discussion of our results in comparison to other state-of-the-art models. We note that in this study, we omitted aerosol processes and some natural emissions (lightning and volcano emissions). The model shows a realistic oxidative capacity across the globe. The seasonal cycle for CO is fairly well represented at different locations (correlations around 0.3–0.7 in surface concentrations), although concentrations are underestimated in spring and winter in the Northern Hemisphere, and are overestimated throughout the year at 800 and 500 hPa in the Southern Hemisphere. Nitrogen species are well represented in almost all locations, particularly NO2 in Europe (root mean square error – RMSE – below 5 ppb). The modeled vertical distributions of NOx and HNO3 are in excellent agreement with the observed values and the spatial and seasonal trends of tropospheric NO2 columns correspond well to observations from SCIAMACHY, capturing the highly polluted areas and the biomass burning cycle throughout the year. Over Asia, the model underestimates NOx from March to August, probably due to an underestimation of NOx emissions in the region. Overall, the comparison of the modeled CO and NO2 with MOPITT and SCIAMACHY observations emphasizes the need for more accurate emission rates from anthropogenic and biomass burning sources (i.e., specification of temporal variability). The resulting ozone (O3) burden (348 Tg) lies within the range of other state-of-the-art global atmospheric chemistry models. The model generally captures the spatial and seasonal trends of background surface O3 and its vertical distribution. However, the model tends to overestimate O3 throughout the troposphere in several stations. This may be attributed to an overestimation of CO concentration over the Southern Hemisphere leading to an excessive production of O3 or to the lack of specific chemistry (e.g., halogen chemistry, aerosol chemistry). Overall, O3 correlations range between 0.6 and 0.8 for daily mean values. The overall performance of the NMMB-MONARCH is comparable to that of other state-of-the-art global chemistry models.

Description: A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter – LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets. The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

Description: Dust emission is initiated when surface wind velocities exceed the threshold of wind erosion. Many dust models used constant threshold values globally. Here we use satellite products to characterize the frequency of dust events and land surface properties. By matching this frequency derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products with surface winds, we are able to retrieve a climatological monthly global distribution of the wind erosion threshold (Vthreshold) over dry and sparsely vegetated surfaces. This monthly two-dimensional threshold velocity is then implemented into the Geophysical Fluid Dynamics Laboratory coupled land–atmosphere model (AM4.0/LM4.0). It is found that the climatology of dust optical depth (DOD) and total aerosol optical depth, surface PM10 dust concentrations, and the seasonal cycle of DOD are better captured over the “dust belt” (i.e., northern Africa and the Middle East) by simulations with the new wind erosion threshold than those using the default globally constant threshold. The most significant improvement is the frequency distribution of dust events, which is generally ignored in model evaluation. By using monthly rather than annual mean Vthreshold, all comparisons with observations are further improved. The monthly global threshold of wind erosion can be retrieved under different spatial resolutions to match the resolution of dust models and thus can help improve the simulations of dust climatology and seasonal cycles as well as dust forecasting.

Description: The direct radiative effect (DRE) of 20 intense and widespread dust outbreaks that affected the broader Mediterranean basin during the period March 2000 – February 2013, has been calculated with the regional NMMB-MONARCH model. The DREs have been calculated based on short-term simulations (84 hours) for a domain covering the Sahara and most part of the European continent. At midday, desert dust outbreaks induce locally a NET (shortwave plus longwave) strong atmospheric warming (DREATM values up to 285 Wm−2), a strong surface cooling (DRENETSURF values down to −337 Wm−2) whereas they strongly reduce the downward radiation at the ground (DRESURF values down to −589 Wm−2). During nighttime, reverse effects of smaller magnitude are found. At the top of the atmosphere (TOA), positive (planetary warming) DREs up to 85 Wm−2 are found over highly reflective surfaces while negative (planetary cooling) DREs down to −184 Wm−2 are computed over dark surfaces at noon. Desert dust outbreaks significantly affect the regional radiation budget, with regional clear-sky NET DRE values ranging from −13.9 to 2.6 Wm−2, from −43.6 to 4 Wm−2, from −26.3 to 3.9 Wm−2 and from −3.7 to 28 Wm−2 for TOA, SURF, NETSURF and ATM, respectively. Although the shortwave (SW) DREs are larger than the longwave (LW) ones, the latter are comparable or even larger at TOA, particularly over the Sahara at midday. As a response to the strong surface cooling during daytime, dust outbreaks cause a reduction of the regional sensible and latent heat fluxes by up to 45 Wm−2 and 4 Wm−2, respectively, averaged over land areas of the simulation domain. Dust outbreaks reduce the temperature at 2 meters by up to 4 K during day, whereas a reverse tendency of similar magnitude is found during night. Depending on the vertical distribution of dust loads and time, mineral particles heat (cool) the atmosphere by up to 0.9 K (0.8 K) during daytime (nighttime) within atmospheric dust layers. Beneath and above the dust clouds, mineral particles cool (warm) the atmosphere by up to 1.3 K (1.2 K) at noon (night). When dust radiative effects are taken into account in numerical simulations, the total emitted dust and dust AOD, computed on a regional mean basis, are decreased (negative feedback) by 19.5 % and 6.9 %. The consideration of dust radiative effects in numerical simulations improves the model predictive skills. More specifically, it reduces the model positive and negative biases for the downward surface SW and LW radiation, respectively, with respect to Baseline Surface Radiation Network (BSRN) measurements. In addition, they also reduce the model near-surface (at 2 meters) nocturnal cold biases by up to 0.5 K (regional averages), as well as the model warm biases at 950 and 700 hPa, where the dust concentration is maximized, by up to 0.4 K.