Improving the current air quality index with new particulate indicators using a robust statistical approach.

To convey the severity of ambient air pollution level to the public, air quality index (AQI) is used as a communication tool to reflect the concentrations of individual pollutants on a common scale. However, due to the enhanced air pollution control in recent years, air quality has improved, and the roles of some air pollutant species included in the existing AQI as urban air pollutants have diminished. In this study, we suggest the current AQI should be revised in a way that new air pollution indicators would be considered so that it would better represent the health effects caused by local combustion processes from traffic and residential burning. Based on the air quality data of 2017-2019 in three different sites in Helsinki metropolitan area, we assumed the statistical distributions of the current indicators (NO2 and PM2.5) and the proposed particulate indicators (BC, LDSA and PNC) were related as they have similar sources in urban regions despite the varying correlations between the current and proposed indicators (NO2: r = 0.5-0.85, PM2.5: r = 0.28-0.72). By fitting the data to an optimal distribution function, together with expert opinions, we improved the current Finnish AQI and determined the AQI breakpoints for the proposed indicators where this robust statistical approach is transferrable to other cities. The addition of the three proposed indicators to the current AQI would decrease the number of good air quality hours in all three environments (largest decrease in urban traffic site, ~22 %). The deterioration of air quality class appeared more severe during peak hours in the urban traffic site due to vehicular emission and evenings in the detached housing site where domestic wood combustion often takes place. The introduction of the AQI breakpoints of the three new indicators serve as a first step of improving the current AQI before further air quality guideline levels are updated.

Technical control of nanoparticle emissions from desktop 3D printing.

Material extrusion (ME) desktop 3D printing is known to strongly emit nanoparticles (NP), and the need for risk management has been recognized widely. Four different engineering control measures were studied in real-life office conditions by means of online NP measurements and indoor aerosol modeling. The studied engineering control measures were general ventilation, local exhaust ventilation (LEV), retrofitted enclosure, and retrofitted enclosure with LEV. Efficiency between different control measures was compared based on particle number and surface area (SA) concentrations from which SA concentration was found to be more reliable. The study found out that for regular or long-time use of ME desktop 3D printers, the general ventilation is not sufficient control measure for NP emissions. Also, the LEV with canopy hood attached above the 3D printer did not control the emission remarkably and successful position of the hood in relation to the nozzle was found challenging. Retrofitted enclosure attached to the LEV reduced the NP emissions 96% based on SA concentration. Retrofitted enclosure is nearly as efficient as enclosure attached to the LEV (reduction of 89% based on SA concentration) but may be considered more practical solution than enclosure with LEV.

Shipping Remains a Globally Significant Source of Anthropogenic PN Emissions Even after 2020 Sulfur Regulation.

Shipping is the main source of anthropogenic particle emissions in large areas of the globe, influencing climate, air quality, and human health in open seas and coast lines. Here, we determined, by laboratory and on-board measurements of ship engine exhaust, fuel-specific particle number (PN) emissions for different fuels and desulfurization applied in shipping. The emission factors were compared to ship exhaust plume observations and, furthermore, exploited in the assessment of global PN emissions from shipping, utilizing the STEAM ship emission model. The results indicate that most particles in the fresh ship engine exhaust are in ultrafine particle size range. Shipping PN emissions are localized, especially close to coastal lines, but significant emissions also exist on open seas and oceans. The global annual PN produced by marine shipping was 1.2 × 1028 (±0.34 × 1028) particles in 2016, thus being of the same magnitude with total anthropogenic PN emissions in continental areas. The reduction potential of PN from shipping strongly depends on the adopted technology mix, and except wide adoption of natural gas or scrubbers, no significant decrease in global PN is expected if heavy fuel oil is mainly replaced by low sulfur residual fuels. The results imply that shipping remains as a significant source of anthropogenic PN emissions that should be considered in future climate and health impact models.

Particulate emissions of a modern diesel passenger car under laboratory and real-world transient driving conditions.

Exhaust emissions from diesel vehicles are significant sources of air pollution. In this study, particle number emissions and size distributions of a modern Euro 5b -compliant diesel passenger car exhaust were measured under the NEDC and US06 standard cycles as well as during different transient driving cycles. The measurements were conducted on a chassis dynamometer; in addition, the transient cycles were repeated on-road by a chase method. Since the diesel particulate filter (DPF) removed practically all particles from the engine exhaust, it was by-passed during most of the measurements in order to determine effects of lubricant on the engine-out exhaust aerosol. Driving conditions and lubricant properties strongly affected exhaust emissions, especially the number emissions and volatility properties of particles. During acceleration and steady speeds particle emissions consisted of non-volatile soot particles mainly larger than ∼50 nm independently of the lubricant used. Instead, during engine motoring particle number size distribution was bimodal with the modes peaking at 10-20 nm and 100 nm. Thermal treatment indicated that the larger mode consisted of non-volatile particles, whereas the nanoparticles had a non-volatile core with volatile material condensed on the surfaces; approximately, 59-64% of the emitted nanoparticles evaporated. Since during engine braking the engine was not fueled, the origin of these particles is lubricant oil. The particle number emission factors over the different cycles varied from 1.0 × 1014 to 1.3 × 1015 #/km, and engine motoring related particle emissions contributed 12-65% of the total particle emissions. The results from the laboratory and on-road transient tests agreed well. According to authors' knowledge, high particle formation during engine braking under real-world driving conditions has not been reported from diesel passenger cars.

Input-Adaptive Proxy for Black Carbon as a Virtual Sensor.

Missing data has been a challenge in air quality measurement. In this study, we develop an input-adaptive proxy, which selects input variables of other air quality variables based on their correlation coefficients with the output variable. The proxy uses ordinary least squares regression model with robust optimization and limits the input variables to a maximum of three to avoid overfitting. The adaptive proxy learns from the data set and generates the best model evaluated by adjusted coefficient of determination (adjR2). In case of missing data in the input variables, the proposed adaptive proxy then uses the second-best model until all the missing data gaps are filled up. We estimated black carbon (BC) concentration by using the input-adaptive proxy in two sites in Helsinki, which respectively represent street canyon and urban background scenario, as a case study. Accumulation mode, traffic counts, nitrogen dioxide and lung deposited surface area are found as input variables in models with the top rank. In contrast to traditional proxy, which gives 20-80% of data, the input-adaptive proxy manages to give full continuous BC estimation. The newly developed adaptive proxy also gives generally accurate BC (street canyon: adjR2 = 0.86-0.94; urban background: adjR2 = 0.74-0.91) depending on different seasons and day of the week. Due to its flexibility and reliability, the adaptive proxy can be further extend to estimate other air quality parameters. It can also act as an air quality virtual sensor in support with on-site measurements in the future.

Characteristics of particle emissions and their atmospheric dilution during co-combustion of coal and wood pellets in a large combined heat and power plant.

Coal combustion is one of the most significant anthropogenic CO2 and air pollution sources globally. This paper studies the atmospheric emissions of a power plant fuelled with a mixture of industrial pellets (10.5%) and coal (89.5%). Based on the stack measurements, the solid particle number emission, which was dominated by sub-200 nm particles, was 3.4×1011 MJ-1 for the fuel mixture when electrostatic precipitator (ESP) was cleaning the flue gas. The emission factor was 50 mg MJ-1 for particulate mass and 11 740 ng MJ-1 for the black carbon with the ESP. In the normal operation situation of the power plant, i.e., including the flue-gas desulphurisation and fabric filters (FGD and FF), the particle number emission factor was 1.7×108 MJ-1, particulate mass emission factor 2 mg MJ-1 and black carbon emission factor 14 ng MJ-1. Transmission electron microscopy (TEM) analysis supported the particle number size distribution measurement in terms of particle size and the black carbon concentration. The TEM images of the particles showed variability of the particle sizes, morphologies and chemical compositions. The atmospheric measurements, conducted in the flue-gas plume, showed that the flue-gas dilutes closed to background concentrations in 200 sec. However, an increase in particle number concentration was observed when the flue gas aged. This increase in particle number concentration was interpret as formation of new particles in the atmosphere. In general, the study highlights the importance of detailed particle measurements when utilizing new fuels in existing power plants. Implications: CO2 emissions of energy production decrease when substituting coal with biofuels. The effects of fuels changes on particle emission characteristics have not been studied comprehensively. In this study conducted for a real-scale power plant, co-combustion of wood pellets and coal caused elevated black carbon emissions. However, it was beneficial from the total particle number and particulate mass emission point of view. Flue-gas cleaning can significantly decrease the pollutant concentrations but also changes the characteristics of emitted particles. Atmospheric measurements implicated that the new particle formation in the atmospheric flue-gas plume should be taken into account when evaluating all effects of fuel changes." Are implication statements part of the manuscript?

Traffic is a major source of atmospheric nanocluster aerosol.

In densely populated areas, traffic is a significant source of atmospheric aerosol particles. Owing to their small size and complicated chemical and physical characteristics, atmospheric particles resulting from traffic emissions pose a significant risk to human health and also contribute to anthropogenic forcing of climate. Previous research has established that vehicles directly emit primary aerosol particles and also contribute to secondary aerosol particle formation by emitting aerosol precursors. Here, we extend the urban atmospheric aerosol characterization to cover nanocluster aerosol (NCA) particles and show that a major fraction of particles emitted by road transportation are in a previously unmeasured size range of 1.3-3.0 nm. For instance, in a semiurban roadside environment, the NCA represented 20-54% of the total particle concentration in ambient air. The observed NCA concentrations varied significantly depending on the traffic rate and wind direction. The emission factors of NCA for traffic were 2.4·1015 (kgfuel)-1 in a roadside environment, 2.6·1015 (kgfuel)-1 in a street canyon, and 2.9·1015 (kgfuel)-1 in an on-road study throughout Europe. Interestingly, these emissions were not associated with all vehicles. In engine laboratory experiments, the emission factor of exhaust NCA varied from a relatively low value of 1.6·1012 (kgfuel)-1 to a high value of 4.3·1015 (kgfuel)-1 These NCA emissions directly affect particle concentrations and human exposure to nanosized aerosol in urban areas, and potentially may act as nanosized condensation nuclei for the condensation of atmospheric low-volatile organic compounds.

Ion mobility distributions during the initial stages of new particle formation by the ozonolysis of α-pinene.

An ion mobility spectrometer (IMS) was used to study gas phase compounds during nucleation and growth of secondary organic aerosols (SOA). In this study SOA particles were generated by oxidizing α-pinene with O(3) and OH in a 6 m(3) reaction chamber. Positive ion peaks with reduced mobilities of 1.59 cm(2)(Vs)(-1) and 1.05 cm(2)(Vs)(-1) were observed 7 min after α-pinene and ozone were added to the chamber. The detected compounds can be associated with low volatility oxidation products of α-pinene, which have been suggested to participate in new particle formation. This is the first time that IMS has been applied to laboratory studies of SOA formation. IMS was found suitable for continuous online monitoring of the SOA formation process, allowing for highly sensitive detection of gas phase species that are thought to initiate new particle formation.