Investigating the concentration levels, distribution patterns, source identification and health risk assessment of PAHs, n-alkanes, hopanes, and steranes in deposited dust of Mashhad, Iran

Deposited dust (DD) in urban environments contains carcinogenic organic compounds. The Indoor air quality is greatly affected by heating, ventilation, and air conditioning systems (HVAC), and in the Middle East most of the buildings are equipped by HVAC on top of them. It is possible that the DD on the roof near this equipment would be transferred to an indoor area. For these reasons, 40 samples of the over the roof DD were prepared, and organic compounds (16PAH compounds, 20n-alkane homologs, 8hopanes, and 6steranes) of DD were extracted using Soxhlet and analyzed by GC-MS. Source identification of organic compounds conducted by ring classification, diagnostic ratios, and factor analysis (FA). The results showed that the average (±SD) of total PAHs, n-alkanes, hopanes and steranes in DD were 1356.00 (±291.45) ng kg−1dw, 3211.65 (±969.18), 146.37 (±79.45) and 469.76 (±188.25) µg.g_1dw, respectively. The highest concentration of organic compounds was in the city center, where traffic congestion is common. Diagnostic ratios of n-alkanes results showed the dominant source is vehicular emission. FA results indicated vehicular emission and biogenic sources. In agreement, the results of sterane and hopane profiles confirm these results. On the other hand, the PAHs diagnostic ratios results indicated petroleum combustion sources. In this regard, FA findings showed combustion from vehicular emission and natural gas and wood combustion were the main factors. Furthermore, the incremental lifetime cancer risk was calculated as 8.45× 10−12 for children and 9.80 × 10−7 for adults, and the imposed risk was negligible.

Influence of vehicular emissions on metropolitan trees using chlorophyll contents

The study assessed carbon sequestration potential of the identified trees {Gmelina, Mango, Neem, Masquerade, Step and Cassia} along the five selected roadsides in Abeokuta metropolitan. Leaves of the identified trees were plucked, digested in triplicate and analysed for chlorophyll (Ch) A, B and A+B contents using UV-visible spectrophotometer. Obtained data were subjected to descriptive and inferential statistics while correlation analysis for relationship between the analysed leaf Ch contents. Results indicated that leaf chlorophyll contents varied. The ranking of tree to metropolitan vehicular emission along roadsides was Neem < Gmelina < Mango < Masquerade tree. Correlation matrix analysis indicated that production of the Ch contents across the roadsides tree species was not alike and might be due to their specific reactions to vehicular emission. In conclusion, the order of Ch contents might be the tree species potential to withstand vehicular pollutants.

Estimation of Pollutant Emissions in Real Driving Conditions Based on Data from OBD and Machine Learning

This article proposes a methodology for the estimation of emissions in real driving conditions, based on board diagnostics data and machine learning, since it has been detected that there are no models for estimating pollutants without large measurement campaigns. For this purpose, driving data are obtained by means of a data logger and emissions through a portable emissions measurement system in a real driving emissions test. The data obtained are used to train artificial neural networks that estimate emissions, having previously estimated the relative importance of variables through random forest techniques. Then, by the application of the K-means algorithm, labels are obtained to implement a classification tree and thereby determine the selected gear by the driver. These models were loaded with a data set generated covering 1218.19 km of driving. The results generated were compared to the ones obtained by applying the international vehicle emissions model and with the results of the real driving emissions test, showing evidence of similar results. The main contribution of this article is that the generated model is stronger in different traffic conditions and presents good results at the speed interval with small differences at low average driving speeds because more than half of the vehicle’s trip occurs in urban areas, in completely random driving conditions. These results can be useful for the estimation of emission factors with potential application in vehicular homologation processes and the estimation of vehicular emission inventories.

EFFECT OF VEHICULAR EMMISSION ON SOME BIOCHEMICAL PARAMETERS AND STOMATA OF SELECTED TREES ALONG ZARIA-KADUNA HIGHWAY

Biochemical and stomatal studies were conducted on selected trees along Zaria-Kaduna highway to determine their pollution tolerance level. The sites were chosen to emphasize exposure to vehicular emission pollution (VEP) and non-exposure to vehicular emission pollutants (NEP). Biochemical parameters analyzed where based on the Air Pollution Tolerance Index (APTI) which prioritizes four biochemical parameters, namely ascorbic acid, total chlorophyll, leaf extract pH and relative water content (RWC), for pollution tolerance. Ascorbic acid and RWC were higher in plants at the polluted site with Mangifera indica showing the highest increase of 1.2mg/g while total chlorophyll decreased most significantly in Ficus polita of about 4.1mg/g. Results from stomata studies reveal a significant difference (P ≤ 0.05) in stomatal size and stomatal index for all the trees at the polluted sites. Stomata was generally found to significantly decrease in size or increase in density for plants at the polluted sites. Results computed for APTI show M. indica (24), Anarcardium occidentale (24.1), Eucalyptus cameldulensis (17.1) and Senna siamea (18.6) having the best APTI which indicate their possible tolerance to air pollution stress while Azadirachta indica (14.4), Ficus polita (13), G. arborea (9.4), T. catapa (15.2), Parkia biglobosa (13.4), and Tamarindus indica (9.9) were found to be sensitive. M. indica and A. occidentale had the best APTI indices which indicate that these plants could serve as sinks in absorbing air pollutants

Multivariate and Confirmatory Factor Analysis of Vehicular Emissions in Some Parts of Benin City, Nigeria

Decline in air quality over the years has been linked to the growing rate of urbanization as well as an increase in the number of vehicles occasioned by the increased purchasing power of the people. Most of the pollutants emitted from vehicular activities have been observed to have adverse effects on individuals as well as the atmosphere. The focus of this study is to employ multivariate and confirmatory factor analysis (CFA) based on maximum likelihood estimation, to study the incidence of vehicular emissions in some parts of Benin city metropolis. Seven (7) georeferenced points (University of Benin main gate, Ekosodin junction, Agen Junction, Super D junction, Nitel junction, Okhunmwun junction and Oluku market junction) were used for data collection. Pollutants from vehicular emission, namely; dinitrogen oxide (NO2), carbon monoxide (CO) including the total radiation were monitored in the morning and evening for a period (7th July to 12th August, 2020) with the aid of portable toxic gas monitors and radiation alert meters. Other measured parameters of interest include maximum temperature and wind speed. To ascertain the quality of the data, selected preliminary analysis, namely; test of normality, test of homogeneity, outlier detection and reliability test were done. With a calculated partial Eta squared based on Pillai’s trace of 0.325, it was concluded that; there exist about 32.50 % variability among the dependent variables. Based on the CFA results, it was concluded that the hypothesis formulated for multivariate analysis of variance fits the sample data. Therefore, the alternate hypothesis was rejected and it was concluded that; the difference in the concentration of vehicular emission was as a result of change in temperature occasioned by time of measurement.

Ambient Air Pollutions along a Major South-Western Nigerian Road

This study investigated the air pollutants in the ambient air of a typical intercity highway in Nigeria. This was to assess the effect of vehicular emission on air quality along the highway. The results showed that NOX concentrations ranged from 9.9±3.2 to 33.8±3.3 µg/m3 during the wet season and 19.0±1.2 to 35.4±2.3 µg/m3 during the dry season. Sulfur dioxide measured along this highway ranged from 49.7±38.1 to 219±18.1 µg/m3 during the wet season while dry season concentration ranged from 89.1±20.9 to 225.4±57.9 µg/m3. The TSP during the wet season ranged from 54.4±25.6 to 126.8±25.6 µg/m3. These values were below the limits of 250 mg/m3 set by FMEnv., and 150-230 mg/m3 by WHO. However, the TSP measured during the dry season ranged from 85.9±44.6 to 277.8±213.5 µg/m3. The average correlations between NOX, SO2, and TSP measured during wet and dry seasons and the traffic density were 0.7, 0.6 and 0.7, respectively. Air pollution along the Nigerian highway is highly linked to vehicular activities.