{'fraction_non_alphanumeric': 0.024984384759525295, 'fraction_numerical': 0.012492192379762648, 'mean_word_length': 5.2823529411764705, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Frequency analysis of air quality time series for traffic related pollutants.

In the present work, annual time series of traffic related pollutants (CO and PM(10)) were considered for frequency analysis (Fourier series) with the aim to understand the underlying physical processes and the influence of emission sources on the variability of the air pollutant concentrations. Several urban traffic and suburban background air quality stations located in Porto metropolitan area (Portugal) were analysed. The results obtained for CO and PM(10) reveal the important contributions of short-term fluctuations (12 h and 24 h periods). However, the spectrum signals at low frequencies are significantly different between these pollutants thus stressing that temporal variations of CO and PM(10) are influenced by different processes. Cross-spectrum analysis of the air quality time series against wind measurements and traffic counts allowed us to identify the contribution of long-range transport over a period of about 21 days to the PM(10) fluctuations. Also, a correlation of over 80% between the pollution levels in the vicinity of traffic sources and suburban background levels are found for these harmonic components in the PM(10) spectrum, while correlations for CO is below a significant level. Thus, the spectrum and cross-spectrum analysis performed in this study reveal the distinct influence of local traffic emissions and long-range transport to CO and PM(10) fluctuations in the polluted urban area. The methodology shows to be a powerful tool for the analysis of the causes of air pollution.