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.

This paper analyses surface ozone measurements at five stations in an urban area (Valladolid) in the upper Spanish plateau over the period 2002–2020. Temporal evolutions, the relationship between ozone and other pollutants such as nitrogen oxides, and the assessment of the ozone concentration trend during the study period were analysed. Daily evolution of ozone at all the stations showed mean maximum concentrations in the afternoon, 15:00 GMT, with values ranging between 73.8 and 80.9 µg m⁻³, evidencing the influence of photochemical processes favoured by solar radiation in ozone formation. The lowest levels were recorded at night and in the early morning, 7:00 GMT, and were between 23.4 and 32.3 µg m⁻³, related with the reduction by NO reactions and deposition processes. A broad spring–summer peak between May and July was seen, with the highest values in the latter, with a mean value of up to 73.8 µg m⁻³. The variation in the monthly mean ozone concentrations of the different percentiles was analysed using a harmonic model. The empirical equation described the experimental values satisfactorily, with a confidence level of 95% and coefficients of determination above 80%, confirming the major decreasing trend in the ozone peak values over the study period.

This study focuses on the analysis of the distribution, both spatial and temporal, of the PM₁₀ (particulate matter with a diameter of 10 µm or less) concentrations recorded in nine EMEP (European Monitoring and Evaluation Programme) background stations distributed throughout mainland Spain between 2001 and 2019. A study of hierarchical clusters was used to classify the stations into three main groups with similarities in yearly concentrations: GC (coastal location), GNC (north–central location), and GSE (southeastern location). The highest PM₁₀ concentrations were registered in summer. Annual evolution showed statistically significant decreasing trends in PM₁₀ concentration in all the stations covering a range from −0.21 to −0.50 µg m⁻³/year for Barcarrota and Víznar, respectively. Through the Lamb classification, the weather types were defined during the study period, and those associated with high levels of pollution were identified. Finally, the values exceeding the limits established by the legislation were analyzed for every station assessed in the study.

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.

Outliers are frequent in CO₂ and CH₄ observations at rural sites. The aim of this paper is to establish a procedure based on the lag-1 autocorrelation to form measurement groups, some of which include outliers, and the rest include regular measurements. Once observations are classified, a second objective is to determine the number of harmonics in order to suitably describe the annual evolution of both gases. Monthly CO₂ and CH₄ percentiles were calculated over a six-year period. Linear trends for most of the percentiles were around 2.24 and 0.0097 ppm year⁻¹, and the interquartile ranges of residuals calculated from detrended concentrations were 6 and 0.02 ppm for CO₂ and CH₄, respectively. Five concentration groups were proposed for CO₂ and six were proposed for CH₄ from the lag-1 autocorrelation applied to detrended observations. Monthly medians were calculated in each group, and combinations of harmonics were applied in an effort to fit the annual cycle. Finally, adding annual and semi-annual harmonics successfully described the cycle where one step was observed in the concentration decrease in spring, not only for high CO₂ percentiles but also for low CH₄ percentiles.