A New Algorithm for Simultaneous Retrieval of Aerosols and Marine Parameters

We present an algorithm for simultaneous retrieval of aerosol and marine parameters in coastal waters. The algorithm is based on a radiative transfer forward model for a coupled atmosphere-ocean system, which is used to train a radial basis function neural network (RBF-NN) to obtain a fast and accurate method to compute radiances at the top of the atmosphere (TOA) for given aerosol and marine input parameters. The inverse modelling algorithm employs multidimensional unconstrained non-linear optimization to retrieve three marine parameters (concentrations of chlorophyll and mineral particles, as well as absorption by coloured dissolved organic matter (CDOM)), and two aerosol parameters (aerosol fine-mode fraction and aerosol volume fraction). We validated the retrieval algorithm using synthetic data and found it, for both low and high sun, to predict each of the five parameters accurately, both with and without white noise added to the top of the atmosphere (TOA) radiances. When varying the solar zenith angle (SZA) and retraining the RBF-NN without noise added to the TOA radiance, we found the algorithm to predict the CDOM absorption, chlorophyll concentration, mineral concentration, aerosol fine-mode fraction, and aerosol volume fraction with correlation coefficients greater than 0.72, 0.73, 0.93, 0.67, and 0.87, respectively, for 45∘≤ SZA ≤ 75∘. By adding white Gaussian noise to the TOA radiances with varying values of the signal-to-noise-ratio (SNR), we found the retrieval algorithm to predict CDOM absorption, chlorophyll concentration, mineral concentration, aerosol fine-mode fraction, and aerosol volume fraction well with correlation coefficients greater than 0.77, 0.75, 0.91, 0.81, and 0.86, respectively, for high sun and SNR ≥ 95.

Aerosol microphysics and chemistry reveal the COVID19 lockdown impact on urban air quality

Air quality in urban areas and megacities is dependent on emissions, physicochemical process and atmospheric conditions in a complex manner. The impact on air quality metrics of the COVID-19 lockdown measures was evaluated during two periods in Athens, Greece. The first period involved stoppage of educational and recreational activities and the second severe restrictions to all but necessary transport and workplace activities. Fresh traffic emissions and their aerosol products in terms of ultrafine nuclei particles and nitrates showed the most significant reduction especially during the 2nd period (40–50%). Carbonaceous aerosol both from fossil fuel emissions and biomass burning, as well as aging ultrafine and accumulation mode particles showed an increase of 10–20% of average before showing a decline (5 to 30%). It is found that removal of small nuclei and Aitken modes increased growth rates and migration of condensable species to larger particles maintaining aerosol volume.

Why simple face masks are unexpectedly efficient in reducing viral aerosol transmissions

SummaryDuring the current pandemic and in the past, shortages of high quality respirators have forced people to protect themselves with homemade face masks that filter poorly in comparison to N95 respirators 1–4 and are often designed in ways that makes them susceptible to leaks 5,6. Nevertheless, there is compelling epidemiological 7,8 and laboratory evidence 9–12 that face masks can be effective in impeding the spread of respiratory viruses such as influenza and SARS-CoV-2. Here we show that this apparent inconsistency can be resolved with a simple face mask model that combines our filtration efficiency measurements of various mask materials with existing data on exhaled aerosol characteristics. By reanalyzing these data we are able to reconcile the vastly different aerosol size distributions reported 13–19 and derive representative volume distributions for speech and breath aerosol. Multiplying filtration efficiency by those aerosol volumes, which are proportional to emitted viral load, shows that electrostatically charged materials perform the best but that even most uncharged fabrics remove > 85 % of breath and > 99 % of speech aerosol volume for exhaled particles < 10 µm in diameter. A leak model we develop shows the best uncharged fabric masks are made of highly air-permeable and often thin materials reducing viral load by up to 45 % and 50 % for breath and speech, respectively. Less permeable materials provide reduced protection because unfiltered air is forced through the leak. This can even render some charged materials inferior to uncharged household materials. Our model also shows that thin fabric masks provide protection for the wearer from aerosols expelled by another person reducing inhaled viral load by up to 20 % and 50 % and if leaks are avoided up to 35 % and 90 % for breath and speech, respectively.

A Review: The Prospect of Inhaled Insulin Therapy via Vibrating Mesh Technology to Treat Diabetes

Background: Inhaled insulin has proven to be viable and, in some aspects, a more effective alternative to subcutaneous insulin. Past and present insulin inhaler devices have not found clinical or commercial success. Insulin inhalers create a dry powder or soft mist insulin aerosol, which does not provide the required uniform particle size or aerosol volume for deep lung deposition. Methods: The primary focus of this review is to investigate the potential treatment of diabetes with a wet insulin aerosol. Vibrating mesh nebulisers allow the passive inhalation of a fine wet mist aerosol for the administration of drugs to the pulmonary system in higher volumes than other small-volume nebulisers. Results: At present, there is a significant focus on vibrating mesh nebulisers from the pharmaceutical and biomedical industries for the systemic administration of pharmaceuticals for non-traditional applications such as vaccines or the treatment of diabetes. Systemic drug administration using vibrating mesh nebulisers leads to faster-acting pharmaceuticals with a reduction in drug latency. Conclusions: Systemic conditions such as diabetes, require the innovative development of custom vibrating mesh devices to provide the desired flow rates and droplet size for effective inhaled insulin administration.

Intercomparison of aerosol volume size distributions derived from AERONET ground-based remote sensing and LARGE in situ aircraft profiles during the 2011–2014 DRAGON and DISCOVER-AQ experiments

Aerosol volume size distribution (VSD) retrievals from the Aerosol Robotic Network (AERONET) aerosol monitoring network were obtained during multiple DRAGON (Distributed Regional Aerosol Gridded Observational Network) campaigns conducted in Maryland, California, Texas and Colorado from 2011 to 2014. These VSD retrievals from the field campaigns were used to make comparisons with near-simultaneous in situ samples from aircraft profiles carried out by the NASA Langley Aerosol Group Experiment (LARGE) team as part of four campaigns comprising the DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) experiments. For coincident (±1 h) measurements there were a total of 91 profile-averaged fine-mode size distributions acquired with the LARGE ultra-high sensitivity aerosol spectrometer (UHSAS) instrument matched to 153 AERONET size distributions retrieved from almucantars at 22 different ground sites. These volume size distributions were characterized by two fine-mode parameters, the radius of peak concentration (rpeak_conc) and the VSD fine-mode width (widthpeak_conc). The AERONET retrievals of these VSD fine-mode parameters, derived from ground-based almucantar sun photometer data, represent ambient humidity values while the LARGE aircraft spiral profile retrievals provide dried aerosol (relative humidity; RH <20 %) values. For the combined multiple campaign dataset, the average difference in rpeak_conc was 0.033±0.035 µm (ambient AERONET values were 15.8 % larger than dried LARGE values), and the average difference in widthpeak_conc was 0.042±0.039 µm (AERONET values were 25.7 % larger). For a subset of aircraft data, the LARGE data were adjusted to account for ambient humidification. For these cases, the AERONET–LARGE average differences were smaller, with rpeak_conc differing by 0.011±0.019 µm (AERONET values were 5.2 % larger) and widthpeak_conc average differences equal to 0.030±0.037 µm (AERONET values were 15.8 % larger).

Retrieval of aerosol properties from ceilometer and photometer measurements: long-term evaluation with in situ data and statistical analysis at Montsec (southern Pyrenees)

Given the need for accurate knowledge of aerosol microphysical and optical properties with height resolution, various algorithms combining vertically resolved and column-integrated aerosol information have been developed in the last years. Here we present new results of vertically resolved extensive aerosol optical properties (backscattering, scattering and extinction) and volume concentrations retrieved with the GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm over a 3-year period. The range-corrected signal (RCS) at 1064 nm measured with a ceilometer and the aerosol optical depth (AOD) and sky radiances from a sun/sky photometer have been used as input for this algorithm. We perform a detailed evaluation of GRASP retrievals with simultaneous in situ measurements performed at the same height, at the Montsec mountaintop observatory (MSA) in the Pre-Pyrenees (northeastern Spain). This is the first long-term evaluation of various outputs of this algorithm; previous evaluations focused only on the study of aerosol volume concentration for short-term periods. In general, our results show good agreement between techniques although GRASP inversions yield higher values than those measured in situ. The statistical analysis of the extinction coefficient vertical profiles shows a clear seasonality as well as significant differences depending on the air mass origin. The observed seasonal cycle is mainly modulated by a higher development of the atmospheric boundary layer (ABL) during warm months, which favors the transport of pollutants to MSA, and higher influence of regional and North African episodes. On the other hand, in winter, MSA is frequently influenced by free-troposphere conditions and venting periods and therefore lower extinction coefficients that markedly decrease with height. This study shows the potentiality of implementing GRASP in ceilometer and lidar networks for obtaining aerosol optical properties and volume concentrations at multiple sites, which will definitely contribute to enhancing the representativeness of the aerosol vertical distribution as well as to providing useful information for satellite and global model evaluation.

Heterogeneous Uptake of N2O5 in Sand Dust and Urban Aerosols Observed during the Dry Season in Beijing

The uptake of dinitrogen pentoxide (N2O5) on aerosols affects the nocturnal removal of NOx and particulate nitrate formation in the atmosphere. This study investigates N2O5 uptake processes using field observations from an urban site in Beijing during April–May 2017, a period characterized by dry weather conditions. For the first time, a very large N2O5 uptake rate (k(N2O5) up to ~0.01 s−1) was observed during a sand storm event, and the uptake coefficient (γ(N2O5)) was estimated to be 0.044. The γ(N2O5) in urban air masses was also determined and exhibited moderate correlation (r = 0.68) with aerosol volume to surface ratio (Va/Sa), but little relation to aerosol water, nitrate, and chloride, a finding that contrasts with previous results. Several commonly used parameterizations of γ(N2O5) underestimated the field-derived γ(N2O5). A new parameterization is suggested for dry conditions, which considers the effect of Va/Sa, temperature, and relative humidity.