Description and evaluation of the community aerosol dynamics model MAFOR v2.0

Numerical models are needed for evaluating aerosol processes in the atmosphere in state-of-the-art chemical transport models, urban-scale dispersion models and climatic models. This article describes a publicly available aerosol dynamics model MAFOR (Multicomponent Aerosol FORmation model; version 2.0); we address the main structure of the model, including the types of operation and the treatments of the aerosol processes. The main advantage of MAFOR v2.0 is the consistent treatment of both the mass- and number-based concentrations of particulate matter. An evaluation of the model is also presented, against a high-resolution observational dataset in a street canyon located in the centre of Helsinki (Finland) during an afternoon traffic rush hour on 13 December 2010. The experimental data included measurements at different locations in the street canyon of ultrafine particles, black carbon, and fine particulate mass PM1. This evaluation has also included an intercomparison with the corresponding predictions of two other prominent aerosol dynamics models, AEROFOR and SALSA. All three models fairly well simulated the decrease of the measured total particle number concentrations with increasing distance from the vehicular emission source. The MAFOR model reproduced the evolution of the observed particle number size distributions more accurately than the other two models. The MAFOR model also predicted the variation of the concentration of PM1 better than the SALSA model. We also analysed the relative importance of various aerosol processes based on the predictions of the three models. As expected, atmospheric dilution dominated over other processes; dry deposition was the second most significant process. Numerical sensitivity tests with the MAFOR model revealed that the uncertainties associated with the properties of the condensing organic vapours affected only the size range of particles smaller than 10 nm in diameter. These uncertainties do not therefore affect significantly the predictions of the whole of the number size distribution and the total number concentration. The MAFOR model version 2 is well documented and versatile to use, providing a range of alternative parametrizations for various aerosol processes. The model includes an efficient numerical integration of particle number and mass concentrations, an operator-splitting of processes, and the use of a fixed sectional method. The model could be used as a module in various atmospheric and climatic models.

A novel approach of creating sustainable urban planning solutions that optimise the local air quality and environmental equity in Helsinki, Finland: The CouSCOUS study protocol

Background Air pollution is one of the major environmental challenges cities worldwide face today. Planning healthy environments for all future populations, whilst considering the ongoing demand for urbanisation and provisions needed to combat climate change, remains a difficult task. Objective To combine artificial intelligence (AI), atmospheric and social sciences to provide urban planning solutions that optimise local air quality by applying novel methods and taking into consideration population structures and traffic flows. Methods We will use high-resolution spatial data and linked electronic population cohort for Helsinki Metropolitan Area (Finland) to model (a) population dynamics and urban inequality related to air pollution; (b) detailed aerosol dynamics, aerosol and gas-phase chemistry together with detailed flow characteristics; (c) high-resolution traffic flow addressing dynamical changes at the city environment, such as accidents, construction work and unexpected congestion. Finally, we will fuse the information resulting from these models into an optimal city planning model balancing air quality, comfort, accessibility and travelling efficiency.

The nano-scanning electrical mobility spectrometer (nSEMS) and its application to size distribution measurements of 1.5–25 nm particles

Particle size measurement in the low nanometer regime is of great importance to the study of cloud condensation nuclei formation and to better understand aerosol–cloud interactions. Here we present the design, modeling, and experimental characterization of the nano-scanning electrical mobility spectrometer (nSEMS), a recently developed instrument that probes particle physical properties in the 1.5–25 nm range. The nSEMS consists of a novel differential mobility analyzer and a two-stage condensation particle counter (CPC). The mobility analyzer, a radial opposed-migration ion and aerosol classifier (ROMIAC), can classify nanometer-sized particles with minimal degradation of its resolution and diffusional losses. The ROMIAC operates on a dual high-voltage supply with fast polarity-switching capability to minimize sensitivity to variations in the chemical nature of the ions used to charge the aerosol. Particles transmitted through the mobility analyzer are measured using a two-stage CPC. They are first activated in a fast-mixing diethylene glycol (DEG) stage before being counted by a second detection stage, an ADI MAGIC™ water-based CPC. The transfer function of the integrated instrument is derived from both finite-element modeling and experimental characterization. The nSEMS performance has been evaluated during measurement of transient nucleation and growth events in the CLOUD atmospheric chamber at CERN. We show that the nSEMS can provide high-time- and size-resolution measurement of nanoparticles and can capture the critical aerosol dynamics of newly formed atmospheric particles. Using a soft x-ray bipolar ion source in a compact housing designed to optimize both nanoparticle charging and transmission efficiency as a charge conditioner, the nSEMS has enabled measurement of the contributions of both neutral and ion-mediated nucleation to new particle formation.

Implementation of aerosol data assimilation in WRFDA (V4.0.3) for WRF-Chem (V3.9.1) using the MADE/VBS scheme

The Weather Research and Forecasting model data assimilation (WRFDA) system, initially designed for meteorological data assimilation, is extended for aerosol data assimilation for the WRF model coupled with Chemistry (WRF-Chem). An interface between WRF-Chem and WRFDA is built for the Regional Atmospheric Chemistry Mechanism (RACM) chemistry and the Modal Aerosol Dynamics Model for Europe (MADE) coupled with the Volatility Basis Set (VBS) aerosol schemes. This article describes the implementation of the new interface for assimilating PM2.5, PM10, and four gas species (SO2, NO2, O3, and co) on the ground. And the effects of aerosol data assimilation are briefly examined through a month-long case study during the Korea-United States Air Quality (KORUS-AQ) period. It is demonstrated that the 3DVAR analysis can lead to consistent forecast improvements up to 26 %, diminishing most systematic bias errors for 24 h.

Aerosol transport measurements and assessment of risk from infectious aerosols: a case study of two German cash-and-carry hardware/DIY stores

We report experimental results on aerosol dispersion in two large German cash-and-carry hardware/DIY stores to better understand the factors contributing to disease transmission by infectious human aerosols in large indoor environments. We examined the transport of aerosols similar in size to human respiratory aerosols (0.3μm-10μm) in representative locations, such as high-traffic areas and restrooms. In restrooms, the observed decay of aerosol concentrations was consistent with well-mixed air exchange. In all other locations, fast decay times were measured, which were found to be independent of aerosol size (typically a few minutes). From this, we conclude that in the main retail areas, including at checkouts, rapid turbulent mixing and advection is the dominant feature in aerosol dynamics. With this, the upper bound of risk for airborne disease transmission to a susceptible is determined by direct exposure to the exhalation cloud of an infectious. For the example of the SARS-CoV-2 virus, we find when speaking without a face mask and aerosol sizes up to an exhalation (wet) diameter of 50μm, a distance of 1.5me to be unsafe. However, at the smallest distance between an infectious and a susceptible, while wearing typical surgical masks and for all sizes of exhaled aerosol, the upper bound of infection risk is only ∼ 5% and decreases further by a factor of 100 (∼ 0.05%) for typical FFP2 masks for a duration of 20 min. This upper bound is very conservative and we expect the actual risk for typical encounters to be much lower. The risks found here are comparable to what might be expected in calm outdoor weather.

Silica-encapsulated DNA tracers for measuring aerosol distribution dynamics in real-world settings

Aerosolized particles play a significant role in human health and environmental risk management. The global importance of aerosol-related hazards, such as the circulation of pathogens and high levels of air pollutants, have led to a surging demand for suitable surrogate tracers to investigate the complex dynamics of airborne particles in real-world scenarios. In this study, we propose a novel approach using silica particles with encapsulated DNA (SPED) as a tracing agent for measuring aerosol distribution indoors. In a series of experiments with a portable setup, SPED were successfully aerosolized, re-captured and quantified using quantitative polymerase chain reaction (qPCR). Position-dependency and ventilation effects within a confined space could be shown in a quantitative fashion achieving detection limits below 0.1 ng particles per m3 of sampled air. In conclusion, SPED show promise for a flexible, cost-effective and low-impact characterization of aerosol dynamics in a wide range of settings.