Exposure to airborne particulates is a major occupational hazard especially for outdoor workers who spending time outdoors at ground level getting exposed to traffic fumes and roadside dust. Aim of this study was to assess respiratory health symptoms and determine the change of lung functions of the roadside vendors and its association with traffic-related exposures and their working experience. A cross-sectional study was conducted in key market places of Kolkata – Gariahat (GH), Esplanade-Park Street (EP), Shyambazar-Hatibagan (SH) and Behala (BE). Particulate (PM10 and PM2.5) levels and meteorological parameters (wind speed, temperature and relative humidity) were monitored in the morning, afternoon and night over the period of October 2019 to February 2020. Lung function status (FEV1, FVC, FEV1/FVC ratio and PEF) was measured for 111 purposively selected participants. PM concentration was observed higher in the morning and night peak hours for all sites. At SH area the average occupational exposure level for PM10 and PM2.5 were observed as 1502.22 μg/m3h and 684.01 μg/m3h. Percentage predicted FEV1 (%FEV1) of street vendors was found decreasing with their work experience and the worst-case scenario was observed in the EP area, with the corresponding value being 70.75%, 49.15% and 47.3% for less than 10 years, 10 to 20 years and more than 20 years participation respectively. The higher particulate burden was observed to have declining lung function status of the street vendors. A strong policy framework should be adopted to improve outdoor working environment for outdoor workers.

A simple and rapid method for the highly sensitive determination of polycyclic aromatic hydrocarbons (PAHs) from airborne fine particulate matter (PM2.5) in an urban environment of Delhi was developed. The target compounds were 10 of the 16 United States Environmental Protection Agency (US-EPA) priority PAHs: fluoranthene, pyrene, chrysene, benzo(a)anthracene, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo[a]pyrene, dibenzo(ah)anthracene, benzo(ghi)perylene, indeno(1,2,3-cd)pyrene. For collecting the samples, the following two locations in Delhi (India) were chosen: ITO and Okhla Industrial Area.  Two sets of samples at these locations of were collected for the purpose of investigation. The fine particulate matter samples were collected on glass fiber filter papers for 24h, from which the PAHs were extracted using dichloromethane (DCM) and hexane using ultrasonication method. Comparison of the characteristic emission of spectra of PAHs with standard spectra indicated the degree of condensation of aromatic compounds present in the investigated mixtures. However, this identification could be more effective with the use of the respective values of Δλ parameter for each particular component of the mixture. It has been found that the concentration of the PAHs is maximum during the winter season and minimum during the summer and monsoon seasons at both the locations.

Because of the pinch of air pollution on human health and its environment, it has become necessary to monitor and map out the peaks and lows threat places of air pollution in different land use across a city. In this regard, air pollution exposure mapping of Kano metropolis based on land use classifications namely industrial, residential, commercial and institutional was carried out for interpretive and assessment of health hazard associated with the selected pollutants. The observations for ambient air quality parameters (CO, SO2, H2S, NO2, and PM10) monitored with portable digital air pollution detecting devices for creation of data. Geographic Information Systems (GIS) technique was applied to create spatial distribution maps of urban air quality of the metropolitan area. The results of pollution index map of ArcGIS extrapolation indicated that neighbourhoods in the vicinity of Bompai and Sabon Gari industrial and commercial zones, respectively were found to be highly exposed and liable to ailments associated with air pollution, while places nearby Dorawa and School of Technology were air pollution-ease zones but could experience bioaccumulation over long exposure time. Therefore, the study reveals that variability of air quality was strongly related to predominant land use in particular areas within the metropolis and could help in estimate and valuation of likely health challenges associated with poor air quality due to air pollution. Besides, the observed spatial variation for air quality could serve as hot spot identifier and as an informant for rational decision on air quality control strategies for environmental management.

Urban activities intensify air pollution by increasing the amount of particulate matter (PM). The trees collect PM by adsorption on the leaf surface and simultaneously absorb inorganic components. In this research, we investigated the potential of the black pine as bioindicator of road traffic emissions in Cluj-Napoca (Romania). We defined three sites types with different exposure to the road traffic (streets, outskirts, parks) and a control site far from the city. We quantified 17 inorganic components (Al, B, Ba, Ca, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, Pb, Sr, Zn) by MP-AES (microwave-plasma atomic emission spectroscopy) technique in the one-year-old needles and we identified the best candidates for biomonitoring purposes. The concentration of Ba, Cr, Cu and Fe showed the most sensitive variations with the road traffic intensity. While in the streets the Ba, Cu and Fe increased by 2.8–3.5 times in relation to the control site, the Cr varied in the highest degree exhibiting ratios of 2.2 (parks), 3.3 (outskirts) and 6.3 (streets). The success of these elements lies in several characteristics: they are closely related to non-exhaust emissions, they are readily absorbed through the leaves rather than the roots, and they tend to accumulate in the needles instead of being relocated to other organs. The street maintenance activities caused considerable accumulation of Na in the trees from the roadsides, but had no impact over the trees from the parks. The elements originating mainly in the re-suspended urban dust (Ni, Pb, Sr) equally affected the pines from the streets and parks.

Discarded micro/nano-plastic inputs into the environment are emerging global concerns. Yet the quantification of micro/nanoplastics in complex environmental matrices is still a major challenge, notably for soluble ones. We herein develop in-laboratory built nanostructures (zinc oxide, titanium oxide and cobalt) coupled to mass spectrometry techniques, for picogram quantification of micro/nanoplastics in water and snow matrices, without sample pre-treatment. In parallel, an ultra-trace quantification method for micro/nanoplastics based on nanostructured laser desorption/ionization time-of-flight mass spectrometry (NALDI-TOF-MS) is developed. The detection limit is ∼5 pg for ambient snow. Soluble polyethylene glycol and insoluble polyethylene fragments were observed and quantified in fresh falling snow in Montreal, Canada. Complementary physicochemical studies of the snow matrices and reference plastics using laser-based particle sizers, inductively coupled plasma tandem mass spectrometry, and high-resolution scanning/transmission electron microscopy, produced consistent results with NALDI, and further provided information on morphology and composition of the micro/nano-plastic particles. This work is promising as it demonstrates that a wide range of recyclable nanostructures, in-laboratory built or commercial, can provide ultra-trace capability for quantification for both soluble polymers and insoluble plastics in air, water and soil. It may thereby produce key missing information to determine the fate of micro/nanoplastics in the environment, and their impacts on human health.

The city of London, UK, has seen in recent years an increase in the number of high-rise/multi-storey buildings (“skyscrapers”) with roof heights reaching 150 m and more, with the Shard being a prime example with a height of ∼310 m. This changing cityscape together with recent plans of local authorities of introducing Combined Heat and Power Plant (CHP) led to a detailed study in which CFD and wind tunnel studies were carried out to assess the effect of such high-rise buildings on the dispersion of air pollution in their vicinity. A new, open-source simulator, FLUIDITY, which incorporates the Large Eddy Simulation (LES) method, was implemented; the simulated results were subsequently validated against experimental measurements from the EnFlo wind tunnel. The novelty of the LES methodology within FLUIDITY is based on the combination of an adaptive, unstructured, mesh with an eddy-viscosity tensor (for the sub-grid scales) that is anisotropic. The simulated normalised mean concentrations results were compared to the corresponding wind tunnel measurements, showing for most detector locations good correlations, with differences ranging from 3% to 37%. The validation procedure was followed by the simulation of two further hypothetical scenarios, in which the heights of buildings surrounding the source building were increased. The results showed clearly how the high-rise buildings affected the surrounding air flows and dispersion patterns, with the generation of “dead-zones” and high-concentration “hotspots” in areas where these did not previously exist. The work clearly showed that complex CFD modelling can provide useful information to urban planners when changes to cityscapes are considered, so that design options can be tested against environmental quality criteria.

In urban areas, the demand for local assessment of air quality is high. The existing monitoring stations cannot fulfill the needs. This study assesses the potential of hyperspectral tree leaf reflectance for monitoring traffic related air pollution. Hereto, 29 Carpinus betulus saplings were exposed to an environment with either high or low traffic intensity. The local air quality was estimated by leaf saturation isothermal remanent magnetization (SIRM). The VIS-NIR leaf reflectance spectrum (350–2500 nm) was measured using a handheld AgriSpec spectroradiometer (ASD Inc.). Secondary, leaf chlorophyll content index (CCI), specific leaf area (SLA) and water content (WC) were determined. To gain insight in the link between leaf reflectance and air quality, the correlation between SIRM and several spectral features was determined. The spectral features that were tested are plain reflectance values, derivative of reflectance, two-band indices using the NDVI formula and PCA components. Spectral reflectance for wavelength bands in the red and short wave IR around the red edge, were correlated to SIRM with Pearson correlations of up to R = −0.85 (R² = 0.72). Based on the spectral features and combinations thereof, binomial logistic regression models were trained to classify trees into high or low traffic pollution exposure, with classification accuracies up to 90%. It can be concluded that hyperspectral reflectance of C. betulus leaves can be used to detect different levels of air pollution within an urban environment.

Passive steady-state chlorophyll fluorescence (Fs) provides a direct diagnosis of the functional status of vegetation photosynthesis. With the prospect of mapping Fs using remote sensing techniques, field measurements are mandatory to understand to which extent Fs allows detecting plant stress in different environments. Trees of four common species in Valencia were classified in either a low or a high local traffic exposure class based on their leaf magnetic value. Upward and downward hyperspectral fluorescence yield (FY) and indices based on the two Fs peaks (at 687 and 741 nm) were calculated. FY indices of P. canariensis and P. x acerifolia were significantly different between the two traffic exposure classes defined, but not for C. australis nor M. alba. While chlorophyll content could not indicate the difference between low and high traffic exposure, the FY(687)/FY(741) peak ratio increased significantly (p < 0.05) for both leaf sides for the higher traffic exposure class.

This review introduces recent advances in an emerging research area that is focussed on studying the effect of exposure to vehicular emissions on cognition, with specific attention to children from urban environments. Today, air pollution is a global environmental issue, especially in urban environments, emitting particulate matter (PM), nitrogen dioxide (NO2), carbon monoxide (CO), volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs) into the surroundings. The association of exposure to urban air pollution and cognitive disorders in children is a major cause of concern. We review recent findings associated with exposure to air pollutants and explained the potential mechanisms driving oxidative stress in living systems. An attempt has been made to investigate the cognitive effects of air pollutants leading to neurodegeneration, neurodysfunction, attention deficit/hypersensitivity deficiencies and autism in children. Accumulating evidence suggests that urban air pollution may have significant impact on central nervous system (CNS) of the developing brain.