Over the years, there has been a gradual increase in the emission of pollutants, and it is imperative to establish mechanisms to monitor air quality. In addition to carbon dioxide (CO₂), particulate matter (PM) is considered one of the main types of air pollution. However, there is a wide variety of pollutants, and high investment is required to carry out detailed air quality monitoring. We present the third version of a previously proposed air quality monitoring platform based on CO₂ concentration measurements. In this new version, a specific sensor for PM measurements and an artificial intelligence algorithm were added. The added algorithm traced associations between measurements of CO₂ and PM concentrations. Thus, the measurement of a pollutant can be used for estimating the concentration of another. This can contribute to the development of a simpler and cheaper monitoring system. The acquisition of CO₂ and PM concentrations was carried out daily over a period of one month. Pollutant measurements were taken in three strategic locations in a Brazilian city. It was possible to determine a correlation between pollutant concentrations for the monitored locations. Thus, it would be possible to efficiently estimate the PM concentration based on the measured CO₂ concentration.

Fugitive emissions are unintentionally produced by pipeline leakage and evaporation in industrial processes and contribute 5% of Global Greenhouse Gas emissions (GHG). Frictional wear and thermal fatigue in vehicle exhaust pipe couplings and joints can cause leaks that are not visible and difficult to quantify. It is therefore essential to trace and document these sources. In this work, an experimental survey was conducted on buses in accordance with Regulation (EC) N° 715/2007 of the European Parliament. Statistical methods by means of a priori analysis aided by G${}^{\ast }$Power 3.1 software was used to define the required sample. Three random sample groups were stratified and fugitive gases were encased and piped into a bronze tube 5 mm in diameter and 500 mm in length. A Horiba PG-300 analyzer was used to analyze the samples using chemiluminescence and infrared methods. The results proved the existence of fugitive emissions in all samples analyzed with variations of (3.000–27.500 ppm) among the samples for $C{O}_2$, (6.0–138.5 ppm) and (2.0–5.0 ppm) for $CO$ and $N{O}_x$, respectively. Statistical analysis showed that engine mileage had no significant influence on $N{O}_x$ emissions, while $CO$ and $C{O}_2$ emissions increased with mileage. Analysis using Response Surface Methodology (RSM) indicated a trend of increasing concentrations of $C{O}_2$ and $CO$ for both explanatory variables, mileage and usage time.