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Diesel engines contribute significantly to deteriorating air quality. Tightening legislation has led to various technological advances, but developments differ between countries. In India, air quality has not improved and fine particle (PM2.5) related premature deaths are predicted to increase. In this study, we characterized the particle emissions of an Indian-manufactured BS IV (Bharat Stage, comparable to Euro emission standards) heavy-duty diesel vehicle and studied the effects of different fuels, fuel blends and lubricating oils. The main aims of the study were to investigate the particle emission dependency on fuel types and fuel blends used in India and to produce useful data for further use (e.g. legislative parties and modeling): emission factors (PN, PM, BC, other chemical compounds), size distributions and volatility of particles. Additionally, the sensitivity of the emissions to the lubricating oil choice was studied. Two lubricating oils, two fossil fuels conforming to BS IV and BS VI emission standards and two biofuel – BS IV fossil fuel blends were tested, one containing Renewable Paraffinic Diesel (RPD) and the other renewable Fatty Acid Methyl Ester (r-FAME). The tests were conducted on a chassis dynamometer (Delhi Bus Driving Cycle, DBDC). Our results show that the emitted particles were in ultrafine particle size range, and both the soot mode particles and smaller nanoparticles were affected by fuels and lubricating oils. The transition from BS IV grade diesel to BSVI was shown to have potential in reducing particle emissions (PN and eBC) of heavy-duty diesel vehicles in India. Blending fossil fuel with biofuel strongly affected particle number emissions, chemical composition, and eBC emissions and the emissions were highly sensitive to biofuel type. Changing the lubricating oil had a comparable magnitude of effect as changing the fuel and the results indicate that in order to reduce particle emissions, a combination of fuel and lubricating oil should be chosen, instead of choosing them separately.

Background: Suspected aerosol-generating dental instruments may cause risks for operators by transmitting pathogens, such as the SARS-CoV-2 virus. The aim of our study was to measure aerosol generation in various dental procedures in clinical settings. Methods: The study population comprised of 84 patients who underwent 253 different dental procedures measured with Optical Particle Sizer in a dental office setting. Aerosol particles from 0.3 to 10 μm in diameter were measured. Dental procedures included oral examinations (N = 52), restorative procedures with air turbine handpiece (N = 8), high-speed (N = 6) and low-speed (N = 30) handpieces, ultrasonic scaling (N = 31), periodontal treatment using hand instruments (N = 60), endodontic treatment (N = 12), intraoral radiographs (N = 24), and dental local anesthesia (N = 31). Results: Air turbine handpieces significantly elevated 5 μm median (p = 0.023), maximum (p = 0.013) particle number concentrations,> 5 μm particle mass concentrations (p = 0.021) and maximum total particle mass concentrations (p = 0.022). High-speed dental handpieces elevated aerosol concentration levels compared to the levels produced during oral examination. Conclusions: Air turbine handpieces produced the highest levels of

Objectives To explore the opinions, the usage and the patient education given on nasal saline irrigation by physicians and pharmaceutical personnel working in Finland. Design An internet-based survey with predetermined, multiple-choice answers. Setting Primary care centres, occupational health centres and private care centres in Eastern Finland as well as pharmacies in Finland. Main outcome measures Healthcare professionals views, practice and general knowledge of nasal irrigation for sinonasal symptoms and conditions. Results We received 595 completed surveys (110 physicians, 485 pharmacists). The majority of the respondents recommended nasal saline irrigation for their patients either as a symptomatic treatment (98.0%) or to treat a specific condition (97.5%) such as acute rhinosinusitis, chronic rhinosinusitis and allergic rhinitis. Nasal saline irrigation was also often recommended as a prophylaxis for airway-infections (71.9%) and to enhance the health of the nasal mucosa (58.2%). In general, the possible adverse effects were recognised poorly by both professions. There was a clear difference between the two professions, as physicians were more conservative in recommending nasal saline irrigation and recognised possible adverse effects, such as epistaxis, pain, and dryness of the nose, better (75% vs. 59%, p = 0.002). Conclusions Nasal saline irrigation seems to be a popular treatment recommended by many health care professionals in Finland. Physicians and pharmaceutical personnel had variable opinions on the indications, utility and risks of nasal saline irrigation. There are also clear differences between physicians and pharmaceutical personnel’s practices. There is a need to better educate professionals about nasal saline irrigation and to further study whether nasal saline irrigation is efficient and safe option for the different common sinonasal conditions.KEY POINTS Little information is available on how physicians and pharmacists recommend nasal saline irrigation as a symptomatic treatment. Physicians and pharmacists seem to have variable opinions about the indications, utility and safety of nasal saline irrigation. The patient education given is in general very heterogenous. Both professions require more education to ensure that the usage remains as safe as possible for the patient.

Black carbon (BC), organic carbon (OC), and total carbon (TC) in snow are important for their climatic and cryospheric effects. They are also part of the global carbon cycle. Atmospheric black and organic carbon (including brown carbon) may deposit and darken snow surfaces. Currently, there are no standardized methods for sampling, filtering, and analysis protocols to detect carbon in snow. Here, we describe our current methods and protocols to detect carbon in seasonal snow using the OCEC thermal optical method, a European standard for atmospheric elemental carbon (EC). We analyzed snow collected within and around the urban background SMEARIII (Station for Measuring Ecosystem-Atmosphere Relations) at Kumpula (60° N) and the Arctic GAW (Global Atmospheric Watch) station at Sodankylä (67° N). The median BC, OC, and TC in snow samples (ntot = 30) in Kumpula were 1118, 5279, and 6396 ppb, and in Sodankylä, they were 19, 1751, and 629 ppb. Laboratory experiments showed that error due to carbon attached to a sampling bag (n = 11) was

An air pollutant proxy is a mathematical model that estimates an unobserved air pollutant using other measured variables. The proxy is advantageous to fill missing data in a research campaign or to substitute a real measurement for minimising the cost as well as the operators involved (i.e., virtual sensor). In this paper, we present a generic concept of pollutant proxy development based on an optimised data-driven approach. We propose a mutual information concept to determine the interdependence of different variables and thus select the most correlated inputs. The most relevant variables are selected to be the best proxy inputs, where several metrics and data loss are also involved for guidance. The input selection method determines the used data for training pollutant proxies based on a probabilistic machine learning method. In particular, we use a Bayesian neural network that naturally prevents overfitting and provides confidence intervals around its output prediction. In this way, the prediction uncertainty could be assessed and evaluated. In order to demonstrate the effectiveness of our approach, we test it on an extensive air pollution database to estimate ozone concentration.

Long-term measurements of black carbon (BC) are warranted for investigating changes in its emission, transport, and deposition. However, depending on instrumentation, parameters related to BC such as aerosol absorption coefficient (babs) have been measured instead. Most ground-based measurements of babs in the Arctic have been made by filter-based absorption photometers, including multi-angle absorption photometers (MAAP), particle soot absorption photometers (PSAP), continuous light absorption photometer (CLAP), and Aethalometers. The measured babs can be converted to atmospheric mass concentrations of BC (MBC) by assuming the value of the mass absorption cross section (MAC = babs/MBC). However, the accuracy of conversion of babs to MBC has not been adequately assessed. Here, we introduce a systematic method for deriving MAC values from babs measured by these instruments and independently measured MBC. In this method, MBC was measured with a filter-based absorption photometer with a heated inlet (COSMOS). COSMOS- derived MBC (MBC (COSMOS)) is traceable to a rigorously calibrated single particle soot photometer (SP2) and the absolute accuracy of MBC (COSMOS) has been demonstrated previously to be about 15 % in Asia and the Arctic. The necessary conditions for application of this method are a high correlation of the measured babs with independently measured MBC, and long-term stability of the correlation slope, which represents the MAC. In general, babs - MBC (COSMOS) correlations were high (r² = 0.84-0.96 for hourly data) at Fukue in Japan, Barrow in Alaska, Ny-Ålesund in Svalbard, Pallastunturi in Finland, and Alert in Canada, and stable up to for 10 years. We successfully estimated MAC values (11.0-15.2 m² g-1 at a wavelength of 550 nm) for these instruments and these MAC values can be used to obtain error-constrained estimates of MBC from babs measured at these sites even in the past, when COSMOS measurements were not made. Because the absolute values of MBC in these Arctic sites estimated by this method are consistent with each other, they are applicable to study spatial and temporal variation of MBC and to evaluate performance of numerical model calculations. [ABSTRACT FROM AUTHOR]