As a consequence of the COVID-19 pandemic caused by the SARS-CoV-2 virus, the widespread daily use of face masks is promoted worldwide. Particle-size dependent filtration efficiencies (FE; d p ¼ 30 nm-10 mm), applying a particle counting approach, and additionally pressure drops (Dp) were determined for 44 samples of household materials and several medical masks. Huge FE differences were found between sample materials and for different particle sizes, spanning from <10% up to almost 100%. Minimum FE were determined for d p ¼ 50-500 nm particles with significantly larger values for d p ¼ 30 nm particles and especially for those with d p > 2.5 mm. Measurements at different numbers of layers showed that stacks of textiles can be treated as separate filters and total FE and Dp can readily be estimated from the features of the individual layers, leaving laborious measurements of individual combinations obsolete. For many materials, electrostatic attraction contributes strongly to overall FE for particles up to 100 nm diameter. Measurements with defined leaks showed that already a small fractional leak area of 1-2% can strongly deteriorate total FE. This is especially the case for particles smaller than 5 mm diameter, where FE dropped by 50% or even two thirds. Our measurements show that by stacking an adequate number of layers of many fabrics, decent filtration efficiencies can be reached for homemade face masks over large particle size ranges with acceptable pressure drop across the material. Very important, however, is good fit of the masks to minimize leak flows and selection of non-hazardous mask material.

For a common household wood stove and a pellet stove we investigated the dependence of emission factors for various gaseous and particulate pollutants on burning phase, burning condition, and fuel. Ideal and non-ideal burning conditions (dried wood, under- and overload, small logs, logs with bark, excess air) were used. We tested 11 hardwood species (apple, ash, bangkirai, birch, beech, cherry, hickory, oak, olive, plum, sugar maple), 4 softwood species (Douglas fir, pine, spruce, spruce/fir), treated softwood, beech and oak wood briquettes, paper briquettes, brown coal, wood chips, and herbaceous species (miscanthus, Chinese silver grass) as fuel. Particle composition (black carbon, non-refractory, and some semi-refractory species) was measured continuously. Repeatability was shown to be better for the pellet stove than for the wood stove. It was shown that the user has a strong influence on wood stove emission behavior both by selection of the fuel and of the burning conditions: Combustion efficiency was found to be low at both very low and very high burn rates, and influenced particle properties such as particle number, mass, and organic content in a complex way. No marked differences were found for the emissions from different wood species. For non-woody fuels, much higher emission factors could be observed (up to five-fold increase). Strongest enhancement of emission factors was found for burning of small or dried logs (up to six-fold), and usage of excess air (two- to three-fold). Real world pellet stove emissions can be expected to be much closer to laboratory-derived emission factors than wood stove emissions, due to lower dependence on user operation

Investigations on atmospheric aerosols and their sources were carried out in October/November 2013 and May/June 2014 consecutively in a suburban area of Rome (Tor Vergata) and in central Rome (near St Peter's Basilica). During both years a Saharan dust advection event temporarily increased PM10 concentrations at ground level by about 12-17 mu g m(-3). Generally, in October/November the ambient aerosol was more strongly influenced by primary emissions, whereas higher relative contributions of secondary particles (sulfate, aged organic aerosol) were found in May/June. Absolute concentrations of anthropogenic emission tracers (e.g. NOx, CO2, particulate polycyclic aromatic hydrocarbons, traffic-related organic aerosol) were generally higher at the urban location. Positive matrix factorization was applied to the PM1 organic aerosol (OA) fraction of aerosol mass spectrometer (HR-ToF-AMS) data to identify different sources of primary OA (POA): traffic, cooking, biomass burning and (local) cigarette smoking. While biomass burning OA was only found at the suburban site, where it accounted for the major fraction of POA (18-24% of total OA), traffic and cooking were more dominant sources at the urban site. A particle type associated with cigarette smoke emissions, which is associated with a potential characteristic marker peak (m/z 84, C5H10N+, a nicotine fragment) in the mass spectrum, was only found in central Rome, where it was emitted in close vicinity to the measurement location. Regarding secondary OA, in October/November, only a very aged, regionally advected oxygenated OA was found, which contributed 42-53% to the total OA. In May/June total oxygenated OA accounted for 56-76% of the OA. Here a fraction (18-26% of total OA) of a fresher, less oxygenated OA of more local origin was also observed. New particle formation events were identified from measured particle number concentrations and size distributions in May/June 2014 at both sites. While they were observed every day at the urban location, at the suburban location they were only found under favourable meteorological conditions, but were independent of advection of the Rome emission plume. Particles from sources in the metropolitan area of Rome and particles advected from outside Rome contributed 42-70 and 30-58% to the total measured PM1, respectively. Apart from the general aerosol characteristics, in this study the properties (e.g. emission strength) and dynamics (e.g. temporal behaviour) of each identified aerosol type is investigated in detail to provide a better understanding of the observed seasonal and spatial differences

Abstract. A total of 252 emission plumes of ships operating in the Mediterranean Sea and around the Arabian Peninsula were investigated using a comprehensive dataset of gas- and submicron-particle-phase properties measured during the 2-month shipborne AQABA (Air Quality and Climate Change in the Arabian Basin) field campaign in summer 2017. The post-measurement identification of the corresponding ship emission events in the measured data included the determination of the plume sources (up to 38 km away) as well as the plume ages (up to 115 min) and was based on commercially available historical records of the Automatic Identification System. The dispersion lifetime of chemically inert CO2 in the ship emission plumes was determined as 70±15 min, resulting in levels indistinguishable from the marine background after 260±60 min. Emission factors (EFs) as quantities that are independent of plume dilution were calculated and used for the investigation of influences on ship emission plumes caused by ship characteristics and the combustion process as well as by atmospheric processes during the early stage of exhaust release and during plume ageing. Combustion efficiency and therefore emission factors of black carbon and NOx were identified to depend mostly on the vessel speed and gross tonnage. Moreover, larger ships, associated with higher engine power, were found to use fuel with higher sulfur content and have higher gas-phase SO2, particulate sulfate, particulate organics, and particulate matter EFs. Despite the independence of EFs of dilution, a significant influence of the ambient wind speed on the particle number and mass EFs was observed that can be traced back to enhanced particle coagulation in the case of slower dilution and suppressed vapour condensation on particles in the case of faster dilution of the emission plume. Atmospheric reactions and processes in ship emission plumes were investigated that include NOx and O3 chemistry, gas-to-particle conversion of NOx and SO2, and the neutralisation of acids in the particle phase through the uptake of ambient gas-phase ammonia, the latter two of which cause the inorganic particulate content to increase and the organic fraction to decrease with increasing plume age. The results allow for us to describe the influences on (or processes in) ship emission plumes quantitatively by parameterisations, which could be used for further refinement of atmospheric models, and to identify which of these processes are the most important ones.