Variation Of Particle Number Concentration Research Articles

Seasonal variation of particle number concentration in a busy urban street with exposure assessment and deposition in human respiratory tract

Ultrafine particles (UFP) associated with air quality and health impacts are a major concern in growing urban regions. Concentrations of UFP (particles of size between 10 and 100 nm) and accumulation mode (Nacc) (particles of size >100 and up to 1000 nm), are analyzed over a highly polluted megacity, Delhi, in conjunction with vehicular flow density, during peak (morning, and evening) and non-peak hours. UFP contributes ≥60% to total particle concentration during autumn and monsoon. UFP concentrations are about 50,000 particles per cm3 in winter which reduces to about 25,000 particles during monsoon. Nacc are about 20,000 (winter) and 10,000 (monsoon) particles per cm3. UFP concentration and Nacc during peak hours are at least twice higher than those obtained in non-peak hours, confirming the dominant influence of emissions from vehicular exhaust in the study region. Seasonal analysis of UFP size distribution reveals that direct emissions dominate the particle concentrations during winter and autumn, whereas new particle formation mechanism contributes the highest in spring and summer. Assessment of inhalable particle number concentration and particle deposition in the human respiratory tract using Multiple Path Particle Dosimetry (MPPD) model, performed for the first time, shows that the order in which these particles deposit in the human respiratory tract is alveoli > bronchiole > bronchus. The deposition ranges between 10 and 18 million nanoparticles during different hours of the day, whereas the estimated inhalable particle concentration (IPN) varies between 0.5 and 1 billion. Results on the IPN during activities classified from light (walking), medium, heavy, very heavy to severe (long-distance running) provide insights into health effects on vulnerable populations. These quantitative results obtained over a megacity on hourly and seasonal variations of nanoparticles along with IPN and deposition rates for different activities are important, and are invaluable inputs for developing mitigation policies aimed to improve air quality and public health, both of which are major concerns in South Asia.

The relative contributions of traffic and non-traffic sources in ultrafine particle formations in Tehran mega city

Emissions of ultrafine particles (UFPs; diameter < 100 nm) are strongly associated with traffic-related emissions and are a growing global concern in urban environments. The aim of this study was to investigate the variations of particle number concentration (PNC) with a diameter > 10 nm at nine stations and understand the major sources of UFPs (primary vs. secondary) in Tehran megacity. The study was carried out in Tehran in 2020. NOx and PNC were reported from a total of nine urban site locations in Tehran and BC concentrations were examined at two monitoring stations. Data from all stations showed diurnal changes with peak morning and evening rush hours. The hourly PNC was correlated with NOx. PNCs in Tehran were higher compared to those of many cities reported in the literature. The highest concentrations were at District 19 station (traffic) and the lowest was at Punak station (residential) such that the average PNC varied from 8.4 × 103 to 5.7 × 104 cm−3. In Ray and Sharif stations, the average contributions of primary and secondary sources of PNC were 67 and 33%, respectively. Overall, we conclude that a decrease in primary emission leads to a decrease in the total concentration of aerosols, despite an increase in the formation of new particles by photo nucleation.

Land Use Regression Models for Particle Number Concentration and Black Carbon in Lanzhou, Northwest of China

It is necessary to predict the spatial variation in particle number concentration (PNC) and black carbon (BC) because they are considered air pollutants associated with traffic and many diseases. In this study, land use regression (LUR) models for PNC and BC were developed based on a mobile monitoring campaign in January 2020 in Lanzhou, and the performance of models was evaluated with hold-out validation (HV) and leave-one-out cross-validation (LOOCV). The results show that the adjusted R2 of the LUR models for PNC and BC are 0.51 and 0.53, respectively. The R2 of HV and LOOCV are 0.43 and 0.44, respectively, for the PNC model and 0.42 and 0.50, respectively, for the BC model. The performances of the LUR models are of a moderate level. The spatial distribution of the predicted PNC is related to the distance from water bodies. The high PNC is related to industrial pollution. The BC concentration decreases from south to north. High BC concentrations are associated with freight distribution centres and coal-fired power plants. The range of PNC particle sizes in this study is larger than in most studies. As one of few studies in Lanzhou to develop LUR models of air pollutants, it is important to accurately estimate pollutant concentrations to improve air quality and provide health benefits for residents.

The importance of ammonia for springtime atmospheric new particle formation and aerosol number abundance over the United States

New particle formation (NPF) and subsequent growth can contribute upwards of 50 % of the global cloud condensation nuclei (CCN) budget. It is also a significant source of ultrafine aerosols (PM0.1) with health implications. Ammonia (NH3) can play a significant role in enhancing NPF and contributing to the growth of nucleated particles. Understanding these processes are vital for air quality and climate. Here, we examine the role of NH3 in NPF and consequent effects on aerosol number concentrations (including CCN) and size distributions during springtime over the United States (US). We use the GEOS-Chem chemistry transport model coupled with the size-resolved Advanced Particle Microphysics (APM) Model. We also employ measurements of particle number size distributions, CN10 (condensation nuclei > 10 nm), CCN0.4 (CCN at 0.4 % supersaturation), and aerosol composition (SO4, NO3, NH4, Organics) at the Southern Great Plains site (SGP). The impact of NH3 in ion-mediated nucleation is the improved capturing of the occurrence of almost all springtime (March–April) NPF events observed at SGP during 2015–2020. Furthermore, this brings the magnitude and temporal variations of particle number concentrations in stronger agreement with observations; mean fractional bias for modeled CN10(CCN0.4) reducing from −1.26 to −0.27 (−0.75 to −0.54) and overall good-agreement (∣FractionalBias ∣ < 0.6) improving from 8.5 to 54 % (31 to 42 %). The contribution of NH3 in new particle formation is important for springtime abundance of ultrafine aerosols (explaining 63 ± 15 % of CN10) and CCN (16 ± 10 % of CCN0.4) over the US. Our analysis shows that the deviation of CCN0.4 is strongly correlated with PM1-NH4+ deviations, suggesting the importance of improved model representation of ammonium for more accurate quantification of potential cloud forming particles.

Variations in source contributions of particle number concentration under long-term emission control in winter of urban Beijing

Many studies revealed the rapid decline of atmospheric PM2.5 in Beijing due to the emission control measures. The variation of particle number concentration (PN) which has important influences on regional climate and human health, however, was rarely reported. This study measured the particle number size distributions (PNSD) in 3–700 nm in winter of Beijing during 2013–2019. It was found that PN decreased by 58% from 2013 to 2017, but increased by 29% from 2017 to 2019. By Positive matrix factorization (PMF) analysis, five source factors of PNSD were identified as Nucleation, Fresh traffic, Aged traffic + Diesel, Coal + biomass burning and Secondary. Overall, factors associated with primary emissions were found to decrease continuously. Coal + biomass burning dominated the reduction (65%) among the three primary sources during 2013–2017, which resulted from the great efforts on emission control of coal combustion and biomass burning. Fresh traffic and Aged traffic + Diesel decreased by 43% and 66%, respectively, from 2013 to 2019, as a result of the upgrade of the vehicle emission standards in Beijing-Tianjin-Hebei area. On the other hand, the contribution from Nucleation and Secondary decreased with the reduction of gaseous precursors in 2013–2017, but due to the increased intensity of new particle formation (NPF) and secondary oxidation, they increased by 56% and 70%, respectively, from 2017 to 2019, which led to the simultaneously increase of PN and particle volume concentration. This study indicated that NPF may play an important role in urban atmosphere under continuous air quality improvement.

Seasonal variations of particle number concentration and its relationship with PM2.5 mass concentration in industrial-residential airshed

The smaller particles that dominate the particle number concentration (PNC) in the ambient air only contribute to a small percentage of particulate matter (PM) mass concentration although present in high particle number concentration. These small particles may be neglected upon assessing the health impacts of the PM. Hence, the knowledge on the particle number concentration size distribution deserves greater attention than the particulate mass concentration. This study investigates the measurement of the particle mass concentrations (PM2.5) and PNC of 0.27μm < Dp < 4.50μm during the southwest (SW), inter-monsoon (IM) and northeast (NE) monsoons in the industrial-residential airshed of Skudai, Johor Bahru, Malaysia. The PM2.5 mass concentrations and PNC were measured using a multi-channel GRIMM Environmental Dust Monitor (GRIMM EDM-SVC 365) equipped with a global positioning system. Diurnal variations, statistical analysis and regression plots were utilised from a six-month hourly data set to examine the patterns of the PNC size distributions and its relationships with the PM2.5 mass concentration. The overall mean PM2.5 mass concentration was 21.85μgm-3, with the 24h mean values of 26.80μgm-3, 26.08μgm-3 and 13.76μgm-3 for the SW, IM and NE monsoons, respectively. It was found that the hourly mean of PNC was recorded at the highest concentration during the SW monsoon (373.20 # cm-3). The particles in the accumulation mode (Dp < 1.0μm) were the prevalent form of the particle number concentration (94-98%). The scatter plots between the PM2.5 mass concentration and particle number size distribution showed that the PNC mode of 0.27 < Dp < 1.0μm has the highest correlation value of r2 = 0.87 due to the emission from the anthropogenic activities. The results of this study highlight the importance of the PNC measurement in the seasonal variations of the PM2.5 pollution, indicating the significance of the regional-scale emission control actions in the local air quality management.

New insights into the spatial distribution of particle number concentrations by applying non-parametric land use regression modelling

Ambient particle number concentration (PNC) varies significantly in time and space within cities, yet complexity and cost prohibit large-scale routine monitoring; as a consequence, there is not enough data for assessment of human exposure to, or risk from the particles. The quality of assessments can be augmented by modelling; however, models are generally less capable of predicting PNC spatial variation than predicting variations in other ambient pollutants. To advance modelling of PNC, we aimed to develop and compare the performance of parametric and non-parametric machine learning land-use regression (LUR) models to predict hourly average PNC. We used data from 25 short-term stationary campaigns and five long-term sites during 2009–2012 in the Brisbane Metropolitan Area, Australia. We analysed three particle size ranges of total PNC (<30 nm, <414 nm and <3000 nm) as response variables, and over 150 independent variables, including land use, roads and traffic, population, distance, elevation, meteorology and time of day as potential predictors of PNC. The LUR models were developed separately for All Days, Nuc Days (when particle nucleation occurred), and No-nuc Days (when no particle nucleation occurred). We selected two algorithms to develop LUR models for PNC: a random forest (RF) model, and a generalised additive model (GAM) based on the least angle regression (LARS). The best LARS model for <30 nm, <414 nm and <3000 nm explained 30%, 31%, and 34%, respectively, whereas the best RF models were significantly better, explaining 73%, 64%, and 88%, respectively. Using this novel approach, we provided new insights into spatial variation in PNC and also demonstrated that the non-parametric RF model is a better choice for developing a LUR model for PNCs because of its robust predictive performance in comparison with the LARS parametric regression model.

Evolution of particle interactions between accidentally released aerosol particles generated from powdered engineered nanomaterials into a simulated workplace atmosphere

The evaluation of aerosol processes which alter the size distribution of accidentally released nanomaterial particles in an indoor environment can provide size resolved exposure estimations, and subsequently contribute to a more comprehensive risk analysis on engineered nanomaterials (ENMs). In this work processed suspensions of TiO2 and SiO2 nanopowders were introduced into the reservoir of a nebuliser, and injected continuously as nano-aerosols into a room-size dispersion facility for a fixed release time. Following injection, the concentration of the dispersed aerosols was allowed to naturally decay for a prolonged period. Airborne particle number concentration (PNC) and particle size distributions (PSD) were continuously measured at a point within the breathing zone near to the source, while deposited particles were collected for transmission electron microscopy (TEM) analysis. A log10-normal fitting program was used to determine the evolution of the modal groups present within the measured PSDs. A modelling approach that considered the experimentally determined particle decay rate as a sum of the pair to pair coagulation and deposition rates was employed to estimate the relative importance of size-resolved deposition compared to coagulation. Results indicated that the variation of PNC with time was accurately modelled, providing size-dependent insights into the contribution of the two particle removal mechanisms to the change of PNC over time. The deposition patterns obtained from the TEM images qualitatively supported the model results. Since a limited set of input parameters were used, we concluded that the proposed model could be an effective tool for a reasonable quantification of worker's exposure to aerosols originating from the accidental release of diffuse ENM in real workplaces.

Source Apportionment and Size Distribution of Aerosols at Lin'an Atmosphere Regional Background Station During Winter

Using a wide-range particle spectrometer (WPS), an environmental management system (EMS), KC-120H middle volume sampler, a 850 professional ion chromatography analyzer, and heat/light carbon analyzer (DRI2001A), we observed the number concentration of aerosols with sizes ranging from 10 nm to 10 μm, gas concentrations, and concentrations of PM2.5, water-soluble ions, OC, and EC in a Lin'an atmospheric background station from January 9 to 31, 2015. The positive matrix factorization (PMF) model was applied for source apportionment, and the size distribution and diurnal variations of emission sources were analyzed based on the meteorological data. The average aerosol concentration was 5062 cm-3·nm-1 and PM2.5 mass concentration was 123.6 μg·m-3. The average concentrations of NO3-, SO42-, and NH4+, the main water-soluble ions in PM2.5 were 19.2, 15.4, and 10.8 μg·m-3, which accounted for 37.9%, 30.4%, and 21.4% of total water-soluble ions, respectively. Theaverage concentrations of OC and EC were 24.4 μg·m-3 and 6.6 μg·m-3. Secondary aerosol formation, coal combustion, motor vehicle emissions, dust, andbiomass burning were the main sources of PM2.5 in Lin'an during winter with contributions of 42.3%, 21.4%, 17.1%, 8.7%, and 10.6%, respectively. Different sources had different aerosol number concentration distributions. The aerosol number concentration spectra of secondary sources, vehicle emissions, dust, and biomass burning followed unimodal-type distributions with peaks at 120, 50, 100, and 90 nm. Coal particle number concentration was a bimodal distribution which exhibited peak values at 25 nm and 100 nm (19842 cm-3·nm-1 and 18372 cm-3·nm-1, respectively). The spectra of surface concentrations of secondary sources, coal combustion, motor vehicle emissions, dust, and biomass burning followed a three-peak distribution. The peaks were at 650, 210, 160, 180, and 575 nm. The diurnal variations of particle number concentrations influenced by diurnal variations in the boundary layer and human activities were consistent with the variations in surface concentrations, which displayed bimodal-type distribution.

Elemental composition of Arctic soils and aerosols in Ny-Ålesund measured using laser-induced breakdown spectroscopy

Two laser-induced breakdown spectroscopy (LIBS) systems (soil LIBS and aerosol LIBS) were used to determine the elemental composition of soils and ambient aerosols less than 2.5μm in Ny-Ålesund, Svalbard (the world's most northerly human settlement). For soil LIBS measurements, matrix effects such as moisture content, soil grain size, and surrounding gas on the LIBS response were minimized. When Ar gas was supplied onto the soil sample surfaces, a significant enhancement in LIBS emission lines was observed. Arctic soil samples were collected at 10 locations, and various elements (Al, Ba, C, Ca, Cu, Fe, H, K, Mg, Mn, N, Na, O, Pb, and Si) were detected in soils. The elemental distribution in arctic soils was clearly distinguishable from those in urban and abandoned mining soils in Korea. Moreover, the concentrations of most of anthropogenic metals were fairly low, and localized sources in extremely close proximity affected the elevated level of Cu in the soil samples derived from Ny-Ålesund. The number of elements detected in aerosols (C, Ca, H, K, Mg, Na, and O) was lower than those determined in soils. The elements in aerosols can mainly originate from minerals and sea salts. The elemental distribution in aerosols was also clearly distinguishable from that in soils, suggesting that the resuspension of local soil particles by wind erosion into aerosols was minimal. The daily variation of particle number concentration (RSD=71%) and the elements in aerosols (RSD=25%) varied substantially, possibly due to fluctuating air masses and meteorological conditions.

Ultrafine particles in four European urban environments: Results from a new continuous long-term monitoring network

To gain a better understanding on the spatiotemporal variation of ultrafine particles (UFPs) in urban environments, this study reports on the first results of a long-term UFP monitoring network, set up in Amsterdam (NL), Antwerp (BE), Leicester (UK) and London (UK). Total number concentrations and size distributions were assessed during 1–2 years at four fixed urban background sites, supplemented with mobile trailer measurements for co-location monitoring and additional short-term monitoring sites. Intra- and interurban spatiotemporal UFP variation, associations with commonly-monitored pollutants (PM, NOx and BC) and impacts of wind fields were evaluated. Although comparable size distributions were observed between the four cities, source-related differences were demonstrated within specific particle size classes. Total and size-resolved particle number concentrations showed clear traffic-related temporal variation, confirming road traffic as the major UFP contributor in urban environments. New particle formation events were observed in all cities. Correlations with typical traffic-related pollutants (BC and NOx) were obtained for all monitoring stations, except for Amsterdam, which might be attributable to UFP emissions from Schiphol airport. The temporal variation in particle number concentration correlated fairly weakly between the four cities (rs = 0.28−0.50, COD = 0.28−0.37), yet improved significantly inside individual cities (rs = 0.59−0.77). Nevertheless, considerable differences were still obtained in terms of particle numbers (20–38% for total particle numbers and up to 49% for size-resolved particle numbers), confirming the importance of local source contributions and the need for careful consideration when allocating UFP monitoring stations in heterogeneous urban environments.

Particle Climatology in Central East China Retrieved from Measurements in Planetary Boundary Layer and in Free Troposphere at a 1500-m-High Mountaintop Site

ABSTRACTParticle number size distribution (PNSD) is an important variable for evaluating the effect of aerosols on climate. In this study, the PNSD in the size range of 3 nm–2.5 µm was measured over a 20-month period at Mt. Tai station, located at ~1500 m asl. in central east China (CEC). The mean particle number concentrations in the nucleation (Nnuc, 3–25 nm), Aitken (NAit, 25–100 nm), accumulation modes (Nacc, 100–1000 nm) and in total measured particle size range were 3200 cm–3, 5200 cm–3, 3400 cm–3, and 11800 cm–3, respectively. New particle formation (NPF) events determined from the PNSD data occurred on 32% of measured days, with particle formation rate and growth rate of 4.0 ± 3.7 cm–3 s–1 and 6.1 ± 2.5 nm h–1, respectively. Time periods of 12:00–17:00 and 23:00–7:00 local time were selected to represent periods when the air mass at the station was dominated by planetary boundary layer (PBL) and free troposphere (FT) air, respectively. The diurnal variation of particle number concentration was influenced mostly by NPF events and evolution of the PBL. When NPF event days were excluded, the particle number concentration also experienced a seasonal variation with maximum in summer and minimum in winter. This seasonality was influenced by seasonal variations in PBL evolution and by air mass advection. The results of this study characterize the regional particle climatology in central east China in terms of particle number and size.

Particle number concentration, size distribution and chemical composition during haze and photochemical smog episodes in Shanghai

The aerosol number concentration and size distribution as well as size-resolved particle chemical composition were measured during haze and photochemical smog episodes in Shanghai in 2009. The number of haze days accounted for 43%, of which 30% was severe (visibility<2km) and moderate (2km≤visibility<3km) haze, mainly distributed in winter and spring. The mean particle number concentration was about 17,000/cm3 in haze, more than 2 times that in clean days. The greatest increase of particle number concentration was in 0.5–1μm and 1–10μm size fractions during haze events, about 17.78 times and 8.78 times those of clean days. The largest increase of particle number concentration was within 50–100nm and 100–200nm fractions during photochemical smog episodes, about 5.89 times and 4.29 times those of clean days. The particle volume concentration and surface concentration in haze, photochemical smog and clean days were 102, 49, 15μm3/cm3 and 949, 649, 206μm2/cm3, respectively. As haze events got more severe, the number concentration of particles smaller than 50nm decreased, but the particles of 50–200nm and 0.5–1μm increased. The diurnal variation of particle number concentration showed a bimodal pattern in haze days. All soluble ions were increased during haze events, of which NH4+, SO42− and NO3− increased greatly, followed by Na+, K+, Ca2+ and Cl−. These ions were very different in size-resolved particles during haze and photochemical smog episodes.

Sub-micron particle number size distributions characteristics at an urban location, Kanpur, in the Indo-Gangetic Plain

We present long-term measurements of sub-micron particle number size distributions (PNSDs) conducted at an urban location, Kanpur, in India, from September 2007 to July 2011. The mean Aitken mode (NAIT), accumulation mode (NACCU), the total particle (NTOT), and black carbon (BC) mass concentrations were 12.4×103cm−3, 18.9×103cm−3, 31.9×103cm−3, and 7.96μgm−3, respectively, within the observed range at other urban locations worldwide, but much higher than those reported at urban sites in the developed nations. The total particle volume concentration appears to be dominated mainly by the accumulation mode particles, except during the monsoon months, perhaps due to efficient wet deposition of accumulation mode particles by precipitation. At Kanpur, the diurnal variation of particle number concentrations was very distinct, with highest during morning and late evening hours, and lowest during the afternoon hours. This behavior could be attributed to the large primary emissions of aerosol particles and temporal evolution of the planetary boundary layer. A distinct seasonal variation in the total particle number and BC mass concentrations was observed, with the maximum in winter and minimum during the rainy season, however, the Aitken mode particles did not show a clear seasonal fluctuation. The ratio of Aitken to accumulation mode particles, NAIT/NACCU, was varied from 0.1 to 14.2, with maximum during April to September months, probably suggesting the importance of new particle formation processes and subsequent particle growth. This finding suggests that dedicated long-term measurements of PNSDs (from a few nanometer to one micron) are required to systematically characterize new particle formation over the Indian subcontinent that has been largely unstudied so far. Contrarily, the low NAIT/NACCU during post-monsoon and winter indicated the dominance of biomass/biofuel burning aerosol emissions at this site.

Spatial–temporal variations of particle number concentrations between a busy street and the urban background

To estimate spatial–temporal variations of ultrafine particles (UFP) in Helsinki, we measured particle total number concentrations (PNC) continuously in a busy street and an urban background site for six months, using condensation particle counters (CPC). We also evaluated the effects of temperature, wind speed and wind direction on PNC, as well as the correlation between PNC and PM2.5, PM10 and black carbon (BC) at the street. We found that on weekdays, hourly median PNC were highly correlated with BC (r = 0.88), moderately correlated with PM2.5 (r = 0.59) and weakly correlated with PM10 (r = 0.22). Number concentrations at the street were inversely proportional to temperature and wind speed, and highly dependent on wind direction. The highest PNC occurred during northeastern winds while the lowest occurred during southwestern winds. As these wind directions are nearly perpendicular to the street axis, the formation of wind vortices may have influenced the dispersion of UFP in the site. Although the temporal correlation for PNC was moderately high between the sites (r = 0.71), the median concentration at the street was 3 times higher than the urban background levels. The results indicate that people living or passing by the busy street are exposed to UFP concentrations well above the urban background levels. Thus, the study suggests that urban microenvironments should be considered in epidemiological studies. In addition the results emphasize that regulations based solely on PM2.5 and PM10 concentrations may be insufficient for preventing the adverse health effects of airborne particles.

Spatial Variation of Particle Number Concentration in School Microscale Environments and Its Impact on Exposure Assessment

It has not yet been established whether the spatial variation of particle number concentration (PNC) within a microscale environment can have an effect on exposure estimation results. In general, the degree of spatial variation within microscale environments remains unclear, since previous studies have only focused on spatial variation within macroscale environments. The aims of this study were to determine the spatial variation of PNC within microscale school environments, in order to assess the importance of the number of monitoring sites on exposure estimation. Furthermore, this paper aims to identify which parameters have the largest influence on spatial variation as well as the relationship between those parameters and spatial variation. Air quality measurements were conducted for two consecutive weeks at each of the 25 schools across Brisbane, Australia. PNC was measured at three sites within the grounds of each school, along with the measurement of meteorological and several other air quality parameters. Traffic density was recorded for the busiest road adjacent to the school. Spatial variation at each school was quantified using coefficient of variation (CV). The portion of CV associated with instrument uncertainty was found to be 0.3, and, therefore, CV was corrected so that only noninstrument uncertainty was analyzed in the data. The median corrected CV (CVc) ranged from 0 to 0.35 across the schools, with 12 schools found to exhibit spatial variation. The study determined the number of required monitoring sites at schools with spatial variability and tested the deviation in exposure estimation arising from using only a single site. Nine schools required two measurement sites and three schools required three sites. Overall, the deviation in exposure estimation from using only one monitoring site was as much as 1 order of magnitude. The study also tested the association of spatial variation with wind speed/direction and traffic density, using partial correlation coefficients to identify sources of variation and nonparametric function estimation to quantify the level of variability. Traffic density and road to school wind direction were found to have a positive effect on CVc and, therefore, also on spatial variation. Wind speed was found to have a decreasing effect on spatial variation when it exceeded a threshold of 1.5 (m/s), while it had no effect below this threshold. Traffic density had a positive effect on spatial variation and its effect increased until it reached a density of 70 vehicles per five minutes, at which point its effect plateaued and did not increase further as a result of increasing traffic density.

Evolution of Aerosol Particles in the Rainfall Process via Method of Moments

The method of moments is employed to predict the evolution of aerosol particles in the rainfall process. To describe the dynamic properties of particle size distribution, the population balance equation is converted to moment equations by the method of moments and the converted equations are solved numerically. The variations of particle number concentration, geometric mean diameter, and geometric standard deviation are given in the cases that the Brownian diffusion and inertial impaction of particles dominate, respectively. The effects of raindrop size distribution on particle size distribution are analyzed in nine cases. The results show that the particle number concentration decreases as time goes by, and particles dominated by Brownian diffusion are removed more significantly. The particle number concentration decreases much more rapidly when particle geometric mean diameter is smaller, and the particle size distribution tends to be monodisperse. For the same water content, the raindrops with small geometric mean diameters can remove particles with much higher efficiency than those with large geometric mean diameters. Particles in the “Greenfield gap” are relatively difficult to scavenge, and a new method is needed to remove it from the air.

Comparison of particulate number concentrations in three Central European capital cities

Number size distributions of atmospheric aerosol particles in the mobility diameter range from 10 to 1000nm were determined in Budapest, Prague and Vienna for a one-year-long period. Particle number concentrations in various size fractions, their diurnal and seasonal variations, mean size distributions and some properties of new particle formation events were derived and compared. Yearly median particle number concentrations for Budapest, Prague and Vienna were 10.6×103, 7.3×103 and 8.0×103cm−3. Differences were linked to the different pollution levels of the cities, and to diverse measurement environments and local conditions. Mean contributions of ultrafine particles (particles with a mobility diameter <100nm) to the total number concentration were 80%, 84% and 74% for Budapest, Prague and Vienna, thus these particles represent an overwhelming share of all particles in each city. Seasonal variation of particle number concentrations was not obvious. Diurnal variations of particles with a diameter between 100 and 1000nm (N100–1000) exhibited similar shape for the cities, which was related to the time-activity pattern of inhabitants and regional influences. The structure of the diurnal variation for ultrafine particles was also similar. It contained a huge morning peak in each city which was explained by emissions from vehicular traffic. The second peak was shifted from afternoon rush hours to late evenings as a result of the daily cycling in meteorological parameters. The character of the measurement site also influenced the diurnal variation. Diurnal variation of the mean ratio of ultrafine particles to N100–1000 clearly revealed the presence and importance of new particle formation and subsequent growth in urban environments. Nucleation frequencies in Budapest and Prague were 27% and 23%, respectively on a yearly time scale. They showed a minimum in winter for both places, while the largest nucleation activity was observed in spring for Budapest, and in summer for Prague.

Observation of new particle formation in subtropical urban environment

Abstract. The aim of this study was to characterise the new particle formation events in a subtropical urban environment in the Southern Hemisphere. The study measured the number concentration of particles and its size distribution in Brisbane, Australia during 2009. The variation of particle number concentration and nucleation burst events were characterised as well as the particle growth rate which was first reported in urban environment of Australia. The annual average NUFP, NAitken and NNuc were 9.3×103, 3.7×103 and 5.6×103 cm−3, respectively. Weak seasonal variation in number concentration was observed. Local traffic exhaust emissions were a major contributor of the pollution (NUFP) observed in morning which was dominated by the Aitken mode particles, while particles formed by secondary formation processes contributed to the particle number concentration during afternoon. Overall, 65 nucleation burst events were identified during the study period. Nucleation burst events were classified into two groups, with and without particles growth after the burst of nucleation mode particles observed. The average particle growth rate of the nucleation events was 4.6 nm h−1 (ranged from 1.79–7.78 nm h−1). Case studies of the nucleation burst events were characterised including (i) the nucleation burst with particle growth which is associated with the particle precursor emitted from local traffic exhaust emission, (ii) the nucleation burst without particle growth which is due to the transport of industrial emissions from the coast to Brisbane city or other possible sources with unfavourable conditions which suppressed particle growth and (iii) interplay between the above two cases which demonstrated the impact of the vehicle and industrial emissions on the variation of particle number concentration and its size distribution during the same day.

Aerosol size distributions in urban Jinan: Seasonal characteristics and variations between weekdays and weekends in a heavily polluted atmosphere

Aerosol size distributions, trace gas, and PM(2.5) concentrations have been measured in urban Jinan, China, over 6 months in 2007 and 2008, covering spring, summer, fall, and winter time periods. Number concentrations of particles (10-2,500 nm) were 16,200, 13,900, 11,200, and 21,600 cm( -3) in spring, summer, fall, and winter, respectively. Compared with other urban studies, Jinan has higher number concentrations of accumulation-mode particles (100-500 nm) and particles (10-2,500 nm), but lower concentrations of ultrafine particles (10-100 nm). The number, surface and volume concentrations, and size distributions of particles showed obvious seasonal variation and are also influenced by traffic emissions. Through correlation analysis, traffic emissions are proposed to be a more important contributor to Atkien-mode and accumulation-mode particles than coal firing. Around midday, the presence of nanoparticles and new particle formation is limited to pre-existing particles from traffic emissions and the mass transport of particles from suburban and rural areas. Compared with other studies in urban areas of Europe and the USA, the variation of particle number concentration and related gas concentration in Jinan between weekdays and weekends is smaller and the reasons has been deduced.