Characterization of Non-methane Hydrocarbons Fingerprint Prevalence in Urban Areas Using eNose Sensor Technology; Quantifying Correlation of Its Concentration with Windspeed for Identification of the Emission Sources

Volatile organic compounds (VOC) are the common term for hydrocarbon emissions, measured as non-methane hydrocarbons (NMHC). NMHC are an important class of VOC that affect atmospheric chemistry and contribute to the formation of secondary organic aerosols and tropospheric ozone (O3). Ozone at ground level is a primary focus of air quality regulations due to its impact on air quality, human health, and climate. There is a plethora of pyrogenic, anthropogenic and biogenic sources of the production of NMHC. In urban areas, vehicle emissions, industrial emissions, and fugitive solvent evaporation are the primary sources of anthropogenic emissions (Kumar et al., 2020). An estimated 169 megatonne of NMHC are released into the atmosphere annually as a result of anthropogenic activities (Bourtsoukidis et al., 2020). Additionally, marine transportation is a potential source of NMHC because it results in more emissions per ton-kilometre travelled than land-based modes of transportation. Evaporation during tanker loading operations accounts for fifty percent of all NMHC emissions produced by shipping. NMHC can trigger respiratory tract allergies, especially the eyes, nose, and throat. Short-term effects include irritability and restlessness, while long-term effects include damage to the liver and other organs (Boon, 2007).

Toxic chemical contamination in the environment has become a major concern for both developed and developing countries in the modern world. Rapid advancements in IoT and sensor technology, including electronic nose, have sparked a renewed interest in air quality monitoring. Many electronic systems have been developed for the detection and identification of odours, flavours, and the analysis of volatile organic compounds; these systems are commonly referred to as "eNose" systems. These systems use an array of chemical gas sensors and pattern recognition to mimic the human sense of smell (Figure 1) (Bambang Dwi Kuncoro et al., 2012). eNoses can be used to detect the presence of reactive trace gases in industrial gas emissions. Since the released trace gases may have some odorous content, the eNose can detect the presence of industrial odours in the atmosphere (Bootsma et al., 2014).Through a wireless data communications link, the eNoses are connected to a remote computer system, where special software can interpret the signals in real time.

This study focused on assessing the prevalence of NMHC signatures in metropolitan areas and evaluating the association of windspeed with the concentration of these pollutants. eNose sensors and air quality management stations offer the data necessary to identify the origin of the pollutants that are being emitted.

point 1 AQMS has the highest average of NMHC concentration in 2021 that equals to 0.424 ppm compared to Point 2 AQMS measurement which is 0.256 ppm. The direction and velocity of the wind, as well as the proximity of the emissions sources, could be the contributing factors. point 1 is located more closely to the sources that generate NMHC, such as ship loading activities. Given its proximity to point 1 AQMS, the eNose site location was selected. The wind can transport air pollution away from its source and disperse it in other areas (Bishop, 2021). Highest NMHC concentrations in 2021 has been observed in May, when the wind was gusting from the southeast at a level of 21.22 parts per billion (ppb). Additionally, the emission could potentially be caused by traffic. Comparing sensor total eNose and point 1 AQMS measurements, the results indicate that both share the same pattern on certain dates, with maxima occurring virtually at the end of each month. To get better results, the S2 sensor of the eNose could be compared to the NMHC concentration of point 1 AQMS rather that the total eNose sensor values since S2 is less sensitive compared to the other three sensors so there is no huge changes in the pattern and could give more accurate results when it comes to NMHC. Higher wind speeds lead to a greater dispersion of the pollution, which decreases its concentrations. The study demonstrates the correlation between wind speed and point 1 AQMS data and the eNose sensor confirming that higher concentrations of pollutants will be present at lower wind speeds. The concentration is highest at night, when the wind is calmest, and lowest during the day, when the wind is at its strongest; this pattern holds true for both the eNose and the point 1 measurements.

Rapid advances in IoT and sensor technologies, including electronic nose have revived air quality monitoring. This study examined NMHC signatures in urban regions and the relationship between windspeed and pollution concentrations. Interestingly, the study reveals the association between wind speed, wind direction, point 1 AQMS data, and the eNose sensor, demonstrating that there would be higher amounts of pollutants at lower wind speeds. Moreover, traffic can be a major contributor to pollution levels. However, in order to make firm findings and provide workable solutions, more study based on a larger dataset is required.