979 resultados para cloud droplet number concentration
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In order to predict the current state and future development of Earth s climate, detailed information on atmospheric aerosols and aerosol-cloud-interactions is required. Furthermore, these interactions need to be expressed in such a way that they can be represented in large-scale climate models. The largest uncertainties in the estimate of radiative forcing on the present day climate are related to the direct and indirect effects of aerosol. In this work aerosol properties were studied at Pallas and Utö in Finland, and at Mount Waliguan in Western China. Approximately two years of data from each site were analyzed. In addition to this, data from two intensive measurement campaigns at Pallas were used. The measurements at Mount Waliguan were the first long term aerosol particle number concentration and size distribution measurements conducted in this region. They revealed that the number concentration of aerosol particles at Mount Waliguan were much higher than those measured at similar altitudes in other parts of the world. The particles were concentrated in the Aitken size range indicating that they were produced within a couple of days prior to reaching the site, rather than being transported over thousands of kilometers. Aerosol partitioning between cloud droplets and cloud interstitial particles was studied at Pallas during the two measurement campaigns, First Pallas Cloud Experiment (First PaCE) and Second Pallas Cloud Experiment (Second PaCE). The method of using two differential mobility particle sizers (DMPS) to calculate the number concentration of activated particles was found to agree well with direct measurements of cloud droplet. Several parameters important in cloud droplet activation were found to depend strongly on the air mass history. The effects of these parameters partially cancelled out each other. Aerosol number-to-volume concentration ratio was studied at all three sites using data sets with long time-series. The ratio was found to vary more than in earlier studies, but less than either aerosol particle number concentration or volume concentration alone. Both air mass dependency and seasonal pattern were found at Pallas and Utö, but only seasonal pattern at Mount Waliguan. The number-to-volume concentration ratio was found to follow the seasonal temperature pattern well at all three sites. A new parameterization for partitioning between cloud droplets and cloud interstitial particles was developed. The parameterization uses aerosol particle number-to-volume concentration ratio and aerosol particle volume concentration as the only information on the aerosol number and size distribution. The new parameterization is computationally more efficient than the more detailed parameterizations currently in use, but the accuracy of the new parameterization was slightly lower. The new parameterization was also compared to directly observed cloud droplet number concentration data, and a good agreement was found.
Spectral dispersion of cloud droplet size distributions and radar threshold reflectivity for drizzle
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In this paper, the main microphysical characteristics of clouds developing in polluted and clean conditions in the biomass-burning season of the Amazon region are examined, with special attention to the spectral dispersion of the cloud droplet size distribution and its potential impact on climate modeling applications. The dispersion effect has been shown to alter the climate cooling predicted by the so-called Twomey effect. In biomass-burning polluted conditions, high concentrations of low dispersed cloud droplets are found. Clean conditions revealed an opposite situation. The liquid water content (0.43 +/- 0.19 g m(-3)) is shown to be uncorrelated with the cloud drop number concentration, while the effective radius is found to be very much correlated with the relative dispersion of the size distribution (R(2) = 0.81). The results suggest that an increase in cloud condensation nuclei concentration from biomass-burning aerosols may lead to an additional effect caused by a decrease in relative dispersion. Since the dry season in the Amazonian region is vapor limiting, the dispersion effect of cloud droplet size distributions could be substantially larger than in other polluted regions.
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Aerosol-cloud interactions have the potential to modify many different cloud properties. There is significant uncertainty in the strength of these aerosol-cloud interactions in analyses of observational data, partly due to the difficulty in separating aerosol effects on clouds from correlations generated by local meteorology. The relationship between aerosol and cloud fraction (CF) is particularly important to determine, due to the strong correlation of CF to other cloud properties and its large impact on radiation. It has also been one of the hardest to quantify from satellites due to the strong meteorological covariations involved. This work presents a new method to analyze the relationship between aerosol optical depth (AOD) and CF. By including information about the cloud droplet number concentration (CDNC), the impact of the meteorological covariations is significantly reduced. This method shows that much of the AOD-CF correlation is explained by relationships other than that mediated by CDNC. By accounting for these, the strength of the global mean AOD-CF relationship is reduced by around 80%. This suggests that the majority of the AOD-CF relationship is due to meteorological covariations, especially in the shallow cumulus regime. Requiring CDNC to mediate the AOD-CF relationship implies an effective anthropogenic radiative forcing from an aerosol influence on liquid CF of −0.48 W m−2 (−0.1 to −0.64 W m−2), although some uncertainty remains due to possible biases in the CDNC retrievals in broken cloud scenes.
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This study aims at a comprehensive understanding of the effects of aerosol-cloud interactions and their effects on cloud properties and climate using the chemistry-climate model EMAC. In this study, CCN activation is regarded as the dominant driver in aerosol-cloud feedback loops in warm clouds. The CCN activation is calculated prognostically using two different cloud droplet nucleation parameterizations, the STN and HYB CDN schemes. Both CDN schemes account for size and chemistry effects on the droplet formation based on the same aerosol properties. The calculation of the solute effect (hygroscopicity) is the main difference between the CDN schemes. The kappa-method is for the first time incorporated into Abdul-Razzak and Ghan activation scheme (ARG) to calculate hygroscopicity and critical supersaturation of aerosols (HYB), and the performance of the modied scheme is compared with the osmotic coefficient model (STN), which is the standard in the ARG scheme. Reference simulations (REF) with the prescribed cloud droplet number concentration have also been carried out in order to understand the effects of aerosol-cloud feedbacks. In addition, since the calculated cloud coverage is an important determinant of cloud radiative effects and is influencing the nucleation process two cloud cover parameterizations (i.e., a relative humidity threshold; RH-CLC and a statistical cloud cover scheme; ST-CLC) have been examined together with the CDN schemes, and their effects on the simulated cloud properties and relevant climate parameters have been investigated. The distinct cloud droplet spectra show strong sensitivity to aerosol composition effects on cloud droplet formation in all particle sizes, especially for the Aitken mode. As Aitken particles are the major component of the total aerosol number concentration and CCN, and are most sensitive to aerosol chemical composition effect (solute effect) on droplet formation, the activation of Aitken particles strongly contribute to total cloud droplet formation and thereby providing different cloud droplet spectra. These different spectra influence cloud structure, cloud properties, and climate, and show regionally varying sensitivity to meteorological and geographical condition as well as the spatiotemporal aerosol properties (i.e., particle size, number, and composition). The changes responding to different CDN schemes are more pronounced at lower altitudes than higher altitudes. Among regions, the subarctic regions show the strongest changes, as the lower surface temperature amplifies the effects of the activated aerosols; in contrast, the Sahara desert, where is an extremely dry area, is less influenced by changes in CCN number concentration. The aerosol-cloud coupling effects have been examined by comparing the prognostic CDN simulations (STN, HYB) with the reference simulation (REF). Most pronounced effects are found in the cloud droplet number concentration, cloud water distribution, and cloud radiative effect. The aerosol-cloud coupling generally increases cloud droplet number concentration; this decreases the efficiency of the formation of weak stratiform precipitation, and increases the cloud water loading. These large-scale changes lead to larger cloud cover and longer cloud lifetime, and contribute to high optical thickness and strong cloud cooling effects. This cools the Earth's surface, increases atmospheric stability, and reduces convective activity. These changes corresponding to aerosol-cloud feedbacks are also differently simulated depending on the cloud cover scheme. The ST-CLC scheme is more sensitive to aerosol-cloud coupling, since this scheme uses a tighter linkage of local dynamics and cloud water distributions in cloud formation process than the RH-CLC scheme. For the calculated total cloud cover, the RH-CLC scheme simulates relatively similar pattern to observations than the ST-CLC scheme does, but the overall properties (e.g., total cloud cover, cloud water content) in the RH simulations are overestimated, particularly over ocean. This is mainly originated from the difference in simulated skewness in each scheme: the RH simulations calculate negatively skewed distributions of cloud cover and relevant cloud water, which is similar to that of the observations, while the ST simulations yield positively skewed distributions resulting in lower mean values than the RH-CLC scheme does. The underestimation of total cloud cover over ocean, particularly over the intertropical convergence zone (ITCZ) relates to systematic defficiency of the prognostic calculation of skewness in the current set-ups of the ST-CLC scheme.rnOverall, the current EMAC model set-ups perform better over continents for all combinations of the cloud droplet nucleation and cloud cover schemes. To consider aerosol-cloud feedbacks, the HYB scheme is a better method for predicting cloud and climate parameters for both cloud cover schemes than the STN scheme. The RH-CLC scheme offers a better simulation of total cloud cover and the relevant parameters with the HYB scheme and single-moment microphysics (REF) than the ST-CLC does, but is not very sensitive to aerosol-cloud interactions.
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The European Centre for Medium-range Weather Forecast (ECMWF) provides an aerosol re-analysis starting from year 2003 for the Monitoring Atmospheric Composition and Climate (MACC) project. The re-analysis assimilates total aerosol optical depth retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS) to correct for model departures from observed aerosols. The reanalysis therefore combines satellite retrievals with the full spatial coverage of a numerical model. Re-analysed products are used here to estimate the shortwave direct and first indirect radiative forcing of anthropogenic aerosols over the period 2003–2010, using methods previously applied to satellite retrievals of aerosols and clouds. The best estimate of globally-averaged, all-sky direct radiative forcing is −0.7±0.3Wm−2. The standard deviation is obtained by a Monte-Carlo analysis of uncertainties, which accounts for uncertainties in the aerosol anthropogenic fraction, aerosol absorption, and cloudy-sky effects. Further accounting for differences between the present-day natural and pre-industrial aerosols provides a direct radiative forcing estimate of −0.4±0.3Wm−2. The best estimate of globally-averaged, all-sky first indirect radiative forcing is −0.6±0.4Wm−2. Its standard deviation accounts for uncertainties in the aerosol anthropogenic fraction, and in cloud albedo and cloud droplet number concentration susceptibilities to aerosol changes. The distribution of first indirect radiative forcing is asymmetric and is bounded by −0.1 and −2.0Wm−2. In order to decrease uncertainty ranges, better observational constraints on aerosol absorption and sensitivity of cloud droplet number concentrations to aerosol changes are required.
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Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (τa) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd ) compares relatively well to the satellite data at least over the ocean. The relationship between �a and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and �a as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld–�a relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between �a and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - �a relationship show a strong positive correlation between �a and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of �a, and parameterisation assumptions such as a lower bound on Nd . Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5Wm−2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clearand cloudy-sky forcings with estimates of anthropogenic �a and satellite-retrieved Nd–�a regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2Wm−2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5Wm−2, with a total estimate of −1.2±0.4Wm−2.
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In their contribution to PNAS, Penner et al. (1) used a climate model to estimate the radiative forcing by the aerosol first indirect effect (cloud albedo effect) in two different ways: first, by deriving a statistical relationship between the logarithm of cloud droplet number concentration, ln Nc, and the logarithm of aerosol optical depth, ln AOD (or the logarithm of the aerosol index, ln AI) for present-day and preindustrial aerosol fields, a method that was applied earlier to satellite data (2), and, second, by computing the radiative flux perturbation between two simulations with and without anthropogenic aerosol sources. They find a radiative forcing that is a factor of 3 lower in the former approach than in the latter [as Penner et al. (1) correctly noted, only their “inline” results are useful for the comparison]. This study is a very interesting contribution, but we believe it deserves several clarifications.
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The activation of aerosols to form cloud droplets is dependent upon vertical velocities whose local variability is not typically resolved at the GCM grid scale. Consequently, it is necessary to represent the subgrid-scale variability of vertical velocity in the calculation of cloud droplet number concentration. This study uses the UK Chemistry and Aerosols community model (UKCA) within the Hadley Centre Global Environmental Model (HadGEM3), coupled for the first time to an explicit aerosol activation parameterisation, and hence known as UKCA-Activate. We explore the range of uncertainty in estimates of the indirect aerosol effects attributable to the choice of parameterisation of the subgrid-scale variability of vertical velocity in HadGEM-UKCA. Results of simulations demonstrate that the use of a characteristic vertical velocity cannot replicate results derived with a distribution of vertical velocities, and is to be discouraged in GCMs. This study focuses on the effect of the variance (σw2) of a Gaussian pdf (probability density function) of vertical velocity. Fixed values of σw (spanning the range measured in situ by nine flight campaigns found in the literature) and a configuration in which σw depends on turbulent kinetic energy are tested. Results from the mid-range fixed σw and TKE-based configurations both compare well with observed vertical velocity distributions and cloud droplet number concentrations. The radiative flux perturbation due to the total effects of anthropogenic aerosol is estimated at −1.9 W m−2 with σw = 0.1 m s−1, −2.1 W m−2 with σw derived from TKE, −2.25 W m−2 with σw = 0.4 m s−1, and −2.3 W m−2 with σw = 0.7 m s−1. The breadth of this range is 0.4 W m−2, which is comparable to a substantial fraction of the total diversity of current aerosol forcing estimates. Reducing the uncertainty in the parameterisation of σw would therefore be an important step towards reducing the uncertainty in estimates of the indirect aerosol effects. Detailed examination of regional radiative flux perturbations reveals that aerosol microphysics can be responsible for some climate-relevant radiative effects, highlighting the importance of including microphysical aerosol processes in GCMs.
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Hochreichende Konvektion über Waldbränden ist eine der intensivsten Formen von atmosphärischer Konvektion. Die extreme Wolkendynamik mit hohen vertikalen Windgeschwindigkeiten (bis 20 m/s) bereits an der Wolkenbasis, hohen Wasserdampfübersättigungen (bis 1%) und die durch das Feuer hohen Anzahlkonzentration von Aerosolpartikeln (bis 100000 cm^-3) bilden einen besonderen Rahmen für Aerosol-Wolken Wechselwirkungen.Ein entscheidender Schritt in der mikrophysikalischen Entwicklung einer konvektiven Wolke ist die Aktivierung von Aerosolpartikeln zu Wolkentropfen. Dieser Aktivierungsprozess bestimmt die anfängliche Anzahl und Größe der Wolkentropfen und kann daher die Entwicklung einer konvektiven Wolke und deren Niederschlagsbildung beeinflussen. Die wichtigsten Faktoren, welche die anfängliche Anzahl und Größe der Wolkentropfen bestimmen, sind die Größe und Hygroskopizität der an der Wolkenbasis verfügbaren Aerosolpartikel sowie die vertikale Windgeschwindigkeit. Um den Einfluss dieser Faktoren unter pyro-konvektiven Bedingungen zu untersuchen, wurden numerische Simulationen mit Hilfe eines Wolkenpaketmodells mit detaillierter spektraler Beschreibung der Wolkenmikrophysik durchgeführt. Diese Ergebnisse können in drei unterschiedliche Bereiche abhängig vom Verhältnis zwischen vertikaler Windgeschwindigkeit und Aerosolanzahlkonzentration (w/NCN) eingeteilt werden: (1) ein durch die Aerosolkonzentration limitierter Bereich (hohes w/NCN), (2) ein durch die vertikale Windgeschwindigkeit limitierter Bereich (niedriges w/NCN) und (3) ein Übergangsbereich (mittleres w/NCN). Die Ergebnisse zeigen, dass die Variabilität der anfänglichen Anzahlkonzentration der Wolkentropfen in (pyro-) konvektiven Wolken hauptsächlich durch die Variabilität der vertikalen Windgeschwindigkeit und der Aerosolkonzentration bestimmt wird. rnUm die mikrophysikalischen Prozesse innerhalb der rauchigen Aufwindregion einer pyrokonvektiven Wolke mit einer detaillierten spektralen Mikrophysik zu untersuchen, wurde das Paketmodel entlang einer Trajektorie innerhalb der Aufwindregion initialisiert. Diese Trajektore wurde durch dreidimensionale Simulationen eines pyro-konvektiven Ereignisses durch das Model ATHAM berechnet. Es zeigt sich, dass die Anzahlkonzentration der Wolkentropfen mit steigender Aerosolkonzentration ansteigt. Auf der anderen Seite verringert sich die Größe der Wolkentropfen mit steigender Aerosolkonzentration. Die Reduzierung der Verbreiterung des Tropfenspektrums stimmt mit den Ergebnissen aus Messungen überein und unterstützt das Konzept der Unterdrückung von Niederschlag in stark verschmutzen Wolken.Mit Hilfe des Models ATHAM wurden die dynamischen und mikrophysikalischen Prozesse von pyro-konvektiven Wolken, aufbauend auf einer realistischen Parametrisierung der Aktivierung von Aerosolpartikeln durch die Ergebnisse der Aktivierungsstudie, mit zwei- und dreidimensionalen Simulationen untersucht. Ein modernes zweimomenten mikrophysikalisches Schema wurde in ATHAM implementiert, um den Einfluss der Anzahlkonzentration von Aerosolpartikeln auf die Entwicklung von idealisierten pyro-konvektiven Wolken in US Standardamtosphären für die mittleren Breiten und den Tropen zu untersuchen. Die Ergebnisse zeigen, dass die Anzahlkonzentration der Aerosolpartikel die Bildung von Regen beeinflusst. Für geringe Aerosolkonzentrationen findet die rasche Regenbildung hauptsächlich durch warme mikrophysikalische Prozesse statt. Für höhere Aerosolkonzentrationen ist die Eisphase wichtiger für die Bildung von Regen. Dies führt zu einem verspäteten Einsetzen von Niederschlag für verunreinigtere Atmosphären. Außerdem wird gezeigt, dass die Zusammensetzung der Eisnukleationspartikel (IN) einen starken Einfluss auf die dynamische und mikrophysikalische Struktur solcher Wolken hat. Bei sehr effizienten IN bildet sich Regen früher. Die Untersuchung zum Einfluss des atmosphärischen Hintergrundprofils zeigt eine geringe Auswirkung der Meteorologie auf die Sensitivität der pyro-konvektiven Wolken auf diernAerosolkonzentration. Zum Abschluss wird gezeigt, dass die durch das Feuer emittierte Hitze einen deutlichen Einfluss auf die Entwicklung und die Wolkenobergrenze von pyro-konvektive Wolken hat. Zusammenfassend kann gesagt werden, dass in dieser Dissertation die Mikrophysik von pyrokonvektiven Wolken mit Hilfe von idealisierten Simulation eines Wolkenpaketmodell mit detaillierte spektraler Mikrophysik und eines 3D Modells mit einem zweimomenten Schema im Detail untersucht wurde. Es wird gezeigt, dass die extremen Bedingungen im Bezug auf die vertikale Windgeschwindigkeiten und Aerosolkonzentrationen einen deutlichen Einfluss auf die Entwicklung von pyro-konvektiven Wolken haben.
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We present a novel method for retrieving high-resolution, three-dimensional (3-D) nonprecipitating cloud fields in both overcast and broken-cloud situations. The method uses scanning cloud radar and multiwavelength zenith radiances to obtain gridded 3-D liquid water content (LWC) and effective radius (re) and 2-D column mean droplet number concentration (Nd). By using an adaption of the ensemble Kalman filter, radiances are used to constrain the optical properties of the clouds using a forward model that employs full 3-D radiative transfer while also providing full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from a challenging cumulus cloud field produced by a large-eddy simulation snapshot. Uncertainty due to measurement error in overhead clouds is estimated at 20% in LWC and 6% in re, but the true error can be greater due to uncertainties in the assumed droplet size distribution and radiative transfer. Over the entire domain, LWC and re are retrieved with average error 0.05–0.08 g m-3 and ~2 μm, respectively, depending on the number of radiance channels used. The method is then evaluated using real data from the Atmospheric Radiation Measurement program Mobile Facility at the Azores. Two case studies are considered, one stratocumulus and one cumulus. Where available, the liquid water path retrieved directly above the observation site was found to be in good agreement with independent values obtained from microwave radiometer measurements, with an error of 20 g m-2.
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An elevated particle number concentration (PNC) observed during nucleation events could play a significant contribution to the total particle load and therefore to the air pollution in the urban environments. Therefore, a field measurement study of PNC was commenced to investigate the temporal and spatial variations of PNC within the urban airshed of Brisbane, Australia. PNC was monitored at urban (QUT), roadside (WOO) and semi-urban (ROC) areas around the Brisbane region during 2009. During the morning traffic peak period, the highest relative fraction of PNC reached about 5% at QUT and WOO on weekdays. PNC peaks were observed around noon, which correlated with the highest solar radiation levels at all three stations, thus suggesting that high PNC levels were likely to be associated with new particle formation caused by photochemical reactions. Wind rose plots showed relatively higher PNC for the NE direction, which was associated with industrial pollution, accounting for 12%, 9% and 14% of overall PNC at QUT, WOO and ROC, respectively. Although there was no significant correlation between PNC at each station, the variation of PNC was well correlated among three stations during regional nucleation events. In addition, PNC at ROC was significantly influenced by upwind urban pollution during the nucleation burst events, with the average enrichment factor of 15.4. This study provides an insight into the influence of regional nucleation events on PNC in the Brisbane region and it the first study to quantify the effect of urban pollution on semi-urban PNC through the nucleation events. © 2012 Author(s).
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Quantifying spatial and/or temporal trends in environmental modelling data requires that measurements be taken at multiple sites. The number of sites and duration of measurement at each site must be balanced against costs of equipment and availability of trained staff. The split panel design comprises short measurement campaigns at multiple locations and continuous monitoring at reference sites [2]. Here we present a modelling approach for a spatio-temporal model of ultrafine particle number concentration (PNC) recorded according to a split panel design. The model describes the temporal trends and background levels at each site. The data were measured as part of the “Ultrafine Particles from Transport Emissions and Child Health” (UPTECH) project which aims to link air quality measurements, child health outcomes and a questionnaire on the child’s history and demographics. The UPTECH project involves measuring aerosol and particle counts and local meteorology at each of 25 primary schools for two weeks and at three long term monitoring stations, and health outcomes for a cohort of students at each school [3].
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There is significant toxicological evidence of the effects of ultrafine particles (<100nm) on human health (WHO 2005). Studies show that the number concentration of particles has been associated with adverse human health effects (Englert 2004). This work is part of a major study called ‘Ultrafine Particles form Traffic Emissions and Children’s Health’ (UPTECH), which seeks to determine the effect of the exposure to traffic related ultrafine particles on children’s health in schools (http://www.ilaqh.qut.edu.au/Misc/UPT ECH%20Home.htm). Quantification of spatial variation of particle number concentration (PNC) in a microscale environment and identification of the main affecting parameters and their contribution levels are the main aims of this analysis.
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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 non-instrument uncertainty was analysed 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 one 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 non-parametric 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.