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CO2 and CH4 outliers may have a noticeable impact on the trend of both gases. Nine years of measurements since 2010 recorded at a rural site in northern Spain were used to investigate these outliers. Their influence on the trend was presented and two limits were established. No more than 23.5% of outliers should be excluded from the measurement series in order to obtain representative trends, which were 2.349 ± 0.012 ppm year-1 for CO2 and 0.00879 ± 0.00004 ppm year-1 for CH4. Two types of outliers were distinguished. Those above the trend line and the rest below the trend line. Outliers were described by skewed distributions where the Weibull distribution figures prominently in most cases. A qualitative procedure was presented to exclude the worst fits, although five statistics were considered to select the best fit. In this case, the modified Nash-Sutcliffe efficiency is prominent. Finally, three symmetrical distributions were added to fit the observations when outliers are excluded, with the Gaussian and beta distributions providing the best fits. As a result, certain skewed functions, such as the lognormal distribution, whose use is frequent for air pollutants, could be questioned in certain applications.

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Meteorological variables have a noticeable impact on pollutant concentrations. Among these variables, wind speed is typically measured, although research into how pollutants respond to it can be improved. This study considers nine years of hourly CO2 and CH4 measurements at a rural site, where wind speed values were calculated by the METEX model. Nine wind speed intervals are proposed where concentrations, distribution functions, and daily as well as annual cycles are calculated. Contrasts between local and transported concentrations are around 5 and 0.03 ppm for CO2 and CH4, respectively. Seven skewed distributions are applied, and five efficiency criteria are considered to test the goodness of fit, with the modified Nash-Sutcliffe efficiency proving to be the most sensitive statistic. The Gumbel distribution is seen to be the most suitable for CO2, whereas the Weibull distribution is chosen for CH4, with the exponential function being the worst. Finally, daily and annual cycles are analysed, where a gradual decrease in amplitude is observed, particularly for the daily cycle. Parametric and nonparametric procedures are used to fit both cycles. The latter gave the best fits, with the agreement being higher for the daily cycle, where evolution is smoother than for the annual cycle.

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Pollution control is based on an exhaustive knowledge of concentration distributions. This study analyses a detailed database of NO2, O3, PM10 and PM2.5 in England and Wales over the period 2007-2011. Daily and annual means were considered in a 1-km spatial resolution. Histograms revealed a shape like a sawtooth. The interval was wide for NO2 and O3, although with a gap, whilst the particulate matter range was narrow. Spring provided the peak for the O3 annual cycle, whereas minima for the other pollutants were reached in summer. A trend for the annual medians of particulate matter was observed, with a minimum in the period analysed. However, the pattern was uniform for NO2 and O3. Cities appeared as NO2 hot spots and O3 cold spots. Wales stood out as an NO2 clean country, although with high O3 levels. Sources or sinks of particulate matter were not observed, suggesting that more detailed analysis is required. Two NO2 pollution axes were sometimes seen, one in the south from London to Bristol, and the second in the north, from Liverpool to Kingston Upon Hull. No annual spatial pattern was seen for the remaining pollutants beyond the contrast between cities and country sites for O3. Consequently, spatial analysis allows the real impact of pollutant sources be known, although it must be performed with a detailed temporal resolution in order to investigate the extension, quantity, and length of the concentrations calculated.

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Although emissions have a direct impact on air pollution, meteorological processes may influence inmission concentration, with the only way to control air pollution being through the rates emitted. This paper presents the close relationship between air pollution and meteorology following the scales of atmospheric motion. In macroscale, this review focuses on the synoptic pattern, since certain weather types are related to pollution episodes, with the determination of these weather types being the key point of these studies. The contrasting contribution of cold fronts is also presented, whilst mathematical models are seen to increase the analysis possibilities of pollution transport. In mesoscale, land-sea and mountain-valley breezes may reinforce certain pollution episodes, and recirculation processes are sometimes favoured by orographic features. The urban heat island is also considered, since the formation of mesovortices determines the entry of pollutants into the city. At the microscale, the influence of the boundary layer height and its evolution are evaluated; in particular, the contribution of the low-level jet to pollutant transport and dispersion. Local meteorological variables have a major influence on calculations with the Gaussian plume model, whilst some eddies are features exclusive to urban environments. Finally, the impact of air pollution on meteorology is briefly commented on.

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A comparison between monthly CO2 values calculated in the Iberian Peninsula and those measured during six years commencing on October 2010 in the centre of its upper plateau is presented. Gaussian and Epanechnikov kernels are used to calculate CO2 concentration and its growth rate in the study region from values at certain grid points. Slight spatial differences are obtained, revealing that both concentration and growth rate are nearly uniform in the region. However, some intervals were proposed that were represented by bands (strips), distributed meridionally for concentration and zonally for growth rate. Band borders were smoother for the Gaussian kernel than for the Epanechnikov kernel. In addition, the probability distribution function of concentration and growth rate were obtained with both kernels. Temporal analysis is carried out adding a linear evolution for growth rate and a sinusoidal function for the annual cycle. This revealed similar patterns for the region and at the grid point nearest to the measurement site, given by a sinusoidal function with nearly constant amplitude, providing satisfactory agreement. However, measurements showed great dispersion, with the concentration being around 7 ppm higher than for the region. Temporal evolution is characterised by a growth rate of 2.39 ppm yr-1 and a sinusoidal function with an amplitude decrease of 0.25 ppm yr-1.

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This work analyses levels of particles PM10 and PM2.5 recorded at four air-quality monitoring stations located in the urban area of Valladolid (Spain) during 2015-2016. To achieve this, the evolution of particle concentrations at different time scales was determined. Average concentrations ranged from 15.3 to 17.6 µg m-3 for PM10 and between 8.9 and 14.8 µg m-3 for PM2.5. The highest monthly means were recorded in autumn and winter. The difference between mean concentrations at weekends and on weekdays for PM10 was around 3 µg m-3 at most of the measuring stations and was 1 µg m-3 for PM2.5. Two concentration peaks were found during the day, one in the morning and the other in the evening, which evidenced the influence of traffic and other anthropogenic activities on PM concentrations. Their mean values were approximately 21 and 17-21 µg m-3, respectively, for PM10. Mean maximum values for PM2.5 were 12 µg m-3, except at one of the measuring sites, with 17 µg m-3 for the morning maximum and 1 µg m-3 more for the nocturnal peak. In addition, the impact of long-distance transport of air masses in the study area was analysed by applying a HYSPLIT trajectory model, taking into account backward trajectories of European, African, and Atlantic origins as well as local conditions. In particular, high concentration events due to Saharan dust intrusions are presented. Finally, background levels of particle concentrations estimated at most sampling areas were around 15 and 7.7 µg m-3 for the PM10 and PM2.5 particle fractions, respectively.

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The integrated SCOPE (Soil, Canopy Observation, Photochemistry and Energy balance) model, coupling radiative transfer theory and biochemistry, was applied to a biodiesel crop grown in a Spanish agricultural area. Energy fluxes and CO2 exchange were simulated with this model for the period spanning January 2008 to October 2008. Results were compared to experimental measurements performed using eddy covariance and meteorological instrumentation. The reliability of the model was proven by simulating latent (LE) and sensible (H) heat fluxes, soil heat flux (G), and CO2 exchanges (NEE and GPP). LAI data used as input in the model were retrieved from the MODIS and MERIS sensors. SCOPE was able to reproduce similar seasonal trends to those measured for NEE, GPP and LE. When considering H, the modelled values were underestimated for the period covering July 2008 to mid-September 2008. The modelled fluxes reproduced the observed seasonal evolution with determination coefficients of over 0.77 when LE and H were evaluated. The modelled results offered good agreement with observed data for NEE and GPP, regardless of whether LAI data belonged to MODIS or MERIS, showing slopes of 0.87 and 0.91 for NEE-MODIS and NEE-MERIS, and 0.91 and 0.94 for GPP-MODIS and GPP-MERIS, respectively. Moreover, SCOPE was able to reproduce similar seasonal behaviours to those observed for the experimental carbon fluxes, clearly showing the CO2 sink/source behaviour for the whole period studied.

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CO2 and CH4 evolution is usually linked with sources, sinks and their changes. However, this study highlights the role of meteorological variables. It aims to quantify their contribution to the trend of these greenhouse gases and to determine which contribute most. Six years of measurements at a semi-natural site in northern Spain were considered. Three sections are established: the first focuses on monthly deciles, the second explores the relationship between pairs of meteorological variables, and the third investigates the relationship between meteorological variables and changes in CO2 and CH4. In the first section, monthly outliers were more marked for CO2 than for CH4. The evolution of monthly deciles was fitted to three simple expressions, linear, quadratic and exponential. The linear and exponential are similar, whereas the quadratic evolution is the most flexible since it provided a variable rate of concentration change and a better fit. With this last evolution, a decrease in the change rate was observed for low CO2 deciles, whereas an increasing change rate prevailed for the rest and was more accentuated for CH4. In the second section, meteorological variables were provided by a trajectory model. Backward trajectories from 1-day prior to reaching the measurement site were used to calculate distance and direction averages as well as the recirculation factor. Terciles of these variables were determined in order to establish three intervals with low, medium and high values. These intervals were used to classify the variables following their interval widths and skewnesses. The best correlation between pairs of meteorological variables was observed for the average distance, in particular with horizontal wind speed. Sinusoidal relationships with the average direction were obtained for average distance and for vertical wind speed. Finally, in the third section, the quadratic evolution was considered in each interval of all the meteorological variables. As regards the main result, the greatest increases were obtained for high potential temperature for both gases followed by low and medium boundary layer height for CO2 and CH4, respectively. Combining both meteorological variables provided increases of 22 ± 9 and 0.070 ± 0.019 ppm for CO2 and CH4, respectively, although the number of observations affected is small, around 7%.

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The present paper seeks to improve our knowledge concerning the evolution of CO2 and CH4 in terms of monthly trends, growth rate and seasonal variations in the lower atmosphere. Dry continuous measurements of CO2 and the CH4 mixing ratio were carried out over five and a half years (from 15 October 2010 to 29 February 2016) by multi-point sampling at 1.8, 3.7 and 8.3m, using a Picarro analyzer at a rural site in the Low Atmosphere Research Centre (CIBA), on the upper Spanish plateau. Data were divided into diurnal and nocturnal records. The mathematical equation proposed to analyze the overall data was a harmonic one, comprising a polynomial (trend) and a series of harmonics (seasonal cycle). Amplitude was considered as a constant and variable term over time. Quite different behaviour was found between day and night measurements in both climate forcing agents. CO2 showed an accelerating trend in autumn, whereas CH4 trends were higher during the winter. Increasing growth rates were reported for CO2 and CH4 over the whole study period. Nocturnal CO2 amplitudes are higher than diurnal ones except in winter for both gases, and also in the autumn for CH4.

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Continuous methane (CH4) concentrations were measured in Northern Spain over two years (2011-2012) by multi-point sampling at 1.8, 3.7 and 8.3m using a Picarro analyser. The technique is based on cavity ring-down spectroscopy. The contrast in mean concentrations was about 1.2ppb, with 95th percentiles differing by 2.2ppb and mean minimum concentrations proving similar. Temporal variations of CH4 were also analysed, with a similar seasonal variability being found for the three heights. The highest CH4 concentrations were obtained in late autumn and winter and the lowest in summer, yielding a range of 52ppb. This variation may depend on the active photochemical reaction with OH radical during a period of intense solar radiation and changes in soil conditions together with variations in emissions. Peak concentration levels were recorded at night-time, between 5:00-7:00 GMT, with mean values ranging between 1920 and 1923ppb. The lowest value, around 1884ppb, was obtained at 16:00 GMT. This diurnal variation was mainly related to vertical mixing and photochemistry. Therefore, CH4 concentrations were also examined using the bulk Richardson number (RB) as a stability indicator. Four groups were distinguished: unstable cases, situations with pure shear flow, transitional stages and drainage flows. The highest contrast in mean CH4 concentrations between lower and upper heights was obtained for the transition and drainage cases, mainly associated to high concentrations from nearby sources. The impact of long range transport was analysed by means of 3-day isobaric backward air mass trajectories, which were calculated taking into account origins from Europe, Africa, the Atlantic Ocean and Local conditions. Assessment of the results showed the influence of S and SE wind sectors, especially with Local conditions associated with low winds. Finally, an estimation of the background CH4 concentration in the study period provided an average value of about 1892ppb.

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The influence of airflow on CO2 concentrations is considered. Two years of measurements recorded with a Picarro G1301 analyser during the night at a rural site were used. Three concentration groups were formed and were related to wind speed. Yearly, directional, and hourly evolution indicated that the isolated contribution of factors affecting CO2 concentrations proves hard to evaluate. Two approaches to airflow based on average wind and a rotating residual were considered. Around two thirds of observations corresponded to anticyclonic rotations. Firstly, circular hodographs of rotating residuals indicated that wavelengths were in the mesoscale range. The greatest concentrations were linked to the lowest wind speeds and no prevailing directions were revealed by the roundness calculation in a spatial analysis using hexagonal cells. Secondly, composite hodographs for anticyclonic turnings were calculated, the greatest concentrations being associated to hodographs with a pronounced curvature. Moreover, these were successfully parameterised using two models. A harmonic function was first used, which satisfactorily fitted hodographs linked to low and intermediate concentrations. The second model initially described the wind direction of residuals with the error function since its change was slow in early and late night-time. Residuals were later parameterised with a second order logarithmic spiral. This procedure successfully fitted the most curved hodographs of low and high concentrations.

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In rural environments, atmospheric CO2 is mainly controlled by natural processes such as respiration-photosynthesis or low atmosphere evolution. This paper considers atmospheric CO2 measurements obtained at a rural site during 2011 using the wavelength-scanned cavity ringdown spectroscopy technique and presents two clustering methods, the silhouette being calculated to evaluate procedure validity. In the first method, clusters were formed depending on the similarity of wind roses, with satisfactory silhouette values. An anticyclonic rotation of the wind direction was observed during the daily cycle and clusters were formed by consecutive directions following the mixing layer evolution. However, monthly roses revealed four quite different wind directions, mainly oriented in the E-W axis. Although CO2 was not used in this procedure, a successful link between clusters and CO2 was obtained. In the second procedure, clusters were formed by the similarity of CO2 histograms calculated in intervals of one or two ancillary variables, wind direction, time of day, or month. The influence of a nearby city, the daily evolution of the low atmosphere, and the growing season were highlighted. Finally, the usefulness of the method lies in its easy extension to other gases or variables.

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This paper provides evidence that symmetry of CO2 concentration distribution may indicate sources or dispersive processes. Skewness was calculated by different procedures with CO2 measured at a rural site using a Picarro G1301 analyser over a two-year period. The usual skewness coefficient was considered together with fourteen robust estimators. A noticeable contrast was obtained between day and night, and skewness decreased linearly with the logarithm of the height. One coefficient was selected from its satisfactory relationship with the median concentration in daily evolution. Three analyses based on the kernel smoothing method were conducted with this coefficient to investigate its response to yearly and daily evolutions, wind direction, and wind speed. Left-skewed distributions were linked to thermal turbulence during midday, especially in spring-summer, or with high wind speeds. Almost symmetric distributions were associated with sources, such as the Valladolid City plume reinforced with spring emissions and the lack of emissions in summer in the remaining directions. Finally, right-skewed distributions were related to low wind speeds and stable stratification at night, furthered by strong emissions in spring. Skewness intervals were proposed and their average median concentrations were calculated such that the relationship between skewness and concentration depends on the analysis performed. Since some skewness coefficients may also be negative, they provide better information about sources or dispersive processes than concentration.

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Continuous methane, CH4, concentrations were measured in a rural area of the upper Spanish plateau from June 2010 to May 2012 by cavity ring-down spectroscopy technique. The results obtained have proven the local impact of anthropogenic nearby sources on CH4 concentrations, and evidence a significant influence on the overall mean, averaged daily and seasonal patterns recorded at the measuring site. The positive anomalies in CH4 concentrations, statistically significant at 95 %, in the southeast sector, defined here as ESE, SE, SSE and S sectors, have been attributed to the contribution of the Valladolid urban plume and the urban landfill. Based on this finding, CH4 background levels were associated to the concentrations recorded in the remaining un-disturbed sectors. CH4 means of the overall data set, the southeast sector and background sectors yielded average means of 1,894.1, 1,927.9 and 1,887.1 ppb, respectively. The diurnal and seasonal patterns of the overall data set and background concentrations have shown that CH4 concentrations are mainly dominated by its reaction with OH radicals. Maximum hourly concentrations were reached during night-time and early morning, 5-7 h, whereas minimum concentrations were recorded at 16 h. Maximum and minimum monthly means were recorded in January and July, respectively. The diurnal and seasonal amplitudes, namely, peak-to-peak means, of background concentrations were 25.1 and 48.1 ppb, respectively. These values were significantly lower than those obtained for the overall data set, 42.9 and 58.1 ppb, revealing the significant role of local influences on CH4 concentrations despite the low frequency of southeast winds recorded at the measuring site, 16.9 %.

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CO2 concentrations recorded for two years using a Picarro G1301 analyser at a rural site were studied applying two procedures. Firstly, the smoothing kernel method, which to date has been used with one linear and another circular variable, was used with pairs of circular variables: wind direction, time of day, and time of year, providing that the daily cycle was the prevailing cyclical evolution and that the highest concentrations were justified by the influence of one nearby city source, which was only revealed by directional analysis. Secondly, histograms were obtained, and these revealed most observations to be located between 380 and 410 ppm, and that there was a sharp contrast during the year. Finally, histograms were fitted to 14 distributions, the best known using analytical procedures, and the remainder using numerical procedures. RMSE was used as the goodness of fit indicator to compare and select distributions. Most functions provided similar RMSE values. However, the best fits were obtained using numerical procedures due to their greater flexibility, the triangular distribution being the simplest function of this kind. This distribution allowed us to identify directions and months of noticeable CO2 input (SSE and April-May, respectively) as well as the daily cycle of the distribution symmetry. Among the functions whose parameters were calculated using an analytical expression, Erlang distributions provided satisfactory fits for monthly analysis, and gamma for the rest. By contrast, the Rayleigh and Weibull distributions gave the worst RMSE values.

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CO(2) transport in the low atmosphere near the surface at night was analysed using spatial procedures applied to back trajectories. Concentration and meteorological data were obtained at a rural site during a seven and a half month campaign. Daily evolution of CO(2) skewness showed positive values during the night and negative values during the day. One concentration and one recirculation factor, an indicator of local recirculation, were associated with each back trajectory calculated during the night to study source and meteorological influences on concentrations recorded. Moreover, four procedures were used to analyse the trajectories, and their strengths and weaknesses were also investigated. (1) The nonparametric trajectory analysis applied with two weight functions successfully marked the most contributing region. (2) Hexagonal cells were used to account for radial distribution of trajectories. The potential source contribution function calculated in these cells highlighted the influence of the source against meteorology, this procedure therefore proving the best to mark the source direction. (3) Trajectory sector analysis revealed the most contributing wind sector and emphasised the role of recirculation in the E-S sectors. (4) Cluster analysis grouped neighbouring trajectories and was the most flexible procedure to classify them, providing a contrast of around 12 ppm between medians obtained in the SE cluster and the least contributing group.

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Directional analysis procedures were extended to study the CO(2) daily cycle in the low atmosphere at a rural site. Weighted average, asymmetric circular functions, and conditional probability curves were applied to concentrations recorded at three levels near surface. Wind speed and potential temperature gradient were the meteorological variables used to establish a link to CO(2). The highest weighted concentration was obtained for wind speed below 4 m s(-1) and for potential temperature gradient above 0.05 °C m(-1). Asymmetric circular functions were fitted to selected percentiles, the generalized von Mises function providing the lowest RMSE. Slight differences among levels were observed in the transition between day and night, and higher gradients were observed during the night. Four intervals were proposed when concentrations were binned by intervals of meteorological variables. Wind speed was only relevant to separate intermediate concentrations. Finally, conditional probability curves provided differences between the highest and lowest levels in up to 20% of cases at 20-22 GMT.

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PURPOSE: A comparison between suburban and rural atmospheric carbon dioxide concentrations in Northern Spain is made. METHOD: Measurements were carried out from April 2006 to November 2007 using MIR 9000 continuous analyzers based on the infrared technique. Two locations were established: a suburban site in Valladolid, a medium-sized city, and a rural location at CIBA, approximately 24 km northwest of Valladolid. RESULTS AND CONCLUSIONS: Mean suburban CO(2) concentrations are 4.5 ppm higher than rural levels. Frequencies of suburban concentrations from 400 to 450 ppm were around twice the rural frequencies. The suburban daily evolution presented two maxima in the predawn hours and at 1900-2000 GMT, mainly associated to anthropogenic emissions which also affected maximum concentrations recorded in autumn-winter and minimum levels in summer. The rural variation with minimum values during the day and high levels at night is mainly related to vegetation activity which also impacts the highest CO(2) concentrations obtained in spring, coinciding with maximum vegetation growth. Boundary layer processes also affected variability of concentrations recorded at both sites. Air quality at the rural site was also influenced by air mass transport from the urban plume (S, SSE, and ESE), which had a mean CO(2) value of 402 ppm. By contrast, concentrations were low when SW-W and NW winds prevailed and brought cleaner air. The relationship between rural CO(2) concentrations and wind speed using a mathematical fit provides a valuable estimation of the background level at the site, 384.8 ppm.

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Conditional probability was used to establish persistence of CO(2) concentrations at a rural site. Measurements extended over three years and were performed with a CO(2) continuous monitor and a sodar. Concentrations in the usual range at this site were proposed as the truncation level to calculate conditional probability, allowing us to determine the extent of CO(2) sequences. Extension of episodes may be inferred from these values. Persistence of wind directions revealed two groups of sectors, one with a persistence of about 16 h and another of about 9 h. Cumulative distribution of CO(2) was calculated in each wind sector and three groups, associated with different concentration origins, were established. One group was linked to transport and local sources, another to the rural environment, and a third to transport of clean air masses. Daily evolution of concentrations revealed major differences during the night and monthly analysis allowed us to associate group 1 with the vegetation cycle and group 3 with wind speed from December to April. Persistence of concentrations was obtained, and group 3 values were lower for concentrations above the truncation level, whereas persistence of groups 1 and 2 was similar. However, group 3 persistence was, in general, between group 1 and 2 persistence for concentrations below the truncation level.

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Integral quantities, wind run, S, and recirculation factor, R, useful for describing air flow, are calculated and combined with CO(2) mixing ratios. Meteorological observations were obtained from a RASS sodar and CO(2) mixing ratios from a continuous analyzer installed at a rural site in the upper Spanish plateau. The measuring campaign spread over 3 years and two approaches were followed. The first approach considered integral quantities on a daily basis and two classifications of air flow, to date scarcely used. The first classification distinguished among stagnation, recirculation, and ventilation, the second considering synoptic, meso-, and local scales. Moreover, 52.94% of daily values handled in this paper corresponded to ventilation and 49.70% to synoptic scale. The main goal of this approach is the subsequent link between the two classifications: the synoptic scale was associated with ventilation, mesoscale with recirculation and local scale partially with recirculation. CO(2) observations were distributed in air flow groups following these classifications and mesoscale processes were satisfactorily described since noticeable evidence of transport from nearby cities was observed. In the second approach, S and R pairs were used and CO(2) mixing ratios were distributed following percent intervals of ventilation, calculated by binning these pairs. The main goal of the second approach is to consider only three groups of mixing ratios. In the first group, with high ventilation, mixing ratios were low. With intermediate ventilation, mixing ratios were medium, and with low ventilation mixing ratios were high. A contrast of 21 ppm between the third and first groups was obtained at the 95th percentile. Finally, the second group provided a contrast of 3 ppm between north and south directions and also between east and west attributed to transport from nearby cities.

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