This study modified a passive sampling technique similar to the US EPA Method 325 A/B method but extended to include more toxic volatile organic compounds (VOCs) under varied climate conditions to enhance field applicability. A mixing chamber was built to determine uptake rates (Us) for the target compounds. It was found that the Us of 27 air toxics previously reported in the literature agreed reasonably well with our findings within 18%, thus proving the chamber's integrity. To broaden the compound coverage, both Carbopack X and Carboxen 569 were studied for a suite of toxic VOCs to meet stringent quality control (QC) criteria of correlation coefficients (R-square), method detection limits (MDL), back diffusion (BD), storage stability, as well as a wide range of climate conditions in temperature and humidity. After excluding the species that failed to pass any of the QC criteria, Carbopack X was found to fit 50 air toxics, whereas Carboxen 569 held 37. After excluding the overlapped species, 61 toxic VOCs can be determined with robust Us for a broad range of climate conditions when the two sorbents are used in pairs. A one-week field measurement was conducted to compare with the online thermal desorption gas chromatography-mass spectrometry (TD-GC-MS) with hourly data resolution. The field passive sampling showed comparable results to the means of the online hourly measurements, despite the high variability of selected target compounds, such as toluene from 0.3 ppbv as the 5th percentile to the maximum of about 80 ppbv. Passive sampling clearly demonstrated the ability to smooth out concentration variability and thus the time-averaging strength of toxic VOCs, revealing its ideal role as an exposure monitor over time. The passive sampling method can be more desired than active sampling or online methods when the aim is simply the knowledge of prolonged time-averaged concentrations.

Urban Heat Island (UHI) is posing a significant challenge due to growing urbanisations across the world. Green infrastructure (GI) is popularly used for mitigating the impact of UHI, but knowledge on their optimal use is yet evolving. The UHI effect for large cities have received substantial attention previously. However, the corresponding effect is mostly unknown for towns, where appreciable parts of the population live, in Europe and elsewhere. Therefore, we analysed the possible impact of three vegetation types on UHI under numerous scenarios: baseline/current GI cover (BGI); hypothetical scenario without GI cover (HGI-No); three alternative hypothetical scenarios considering maximum green roofs (HGR-Max), grasslands (HG-Max) and trees (HT-Max) using a dispersion model ADMS-Temperature and Humidity model (ADMS-TH), taking a UK town (Guildford) as a case study area. Differences in an ambient temperature between three different landforms (central urban area, an urban park, and suburban residential area) were also explored. Under all scenarios, the night-time (0200 h; local time) showed a higher temperature increase, up to 1.315 °C due to the lowest atmospheric temperature. The highest average temperature perturbation (change in ambient temperature) was 0.563 °C under HGI-No scenario, followed by HG-Max (0.400 °C), BGI (0.343 °C), HGR-Max (0.326 °C) and HT-Max (0.277 °C). Furthermore, the central urban area experienced a 0.371 °C and 0.401 °C higher ambient temperature compared with its nearby suburban residential area and urban park, respectively. The results allow to conclude that temperature perturbations in urban environments are highly dependent on the type of GI, anthropogenic heat sources (buildings and vehicles) and the percentage of land covered by GI. Among all other forms of GI, trees were the best-suited GI which can play a viable role in reducing the UHI. Green roofs can act as an additional mitigation measure for the reduction of UHI at city scale if large areas are covered.

A severe air quality degradation event occurred in the Santiago Metropolitan Area (SMA), Chile, in June 2014. Meteorological and air quality measurements from 11 stations in the area as well as numerical simulations using the Weather and Research Forecasting (WRF) model were used to explain the main reasons for the occurrence of elevated particulate matter (PM) concentrations. The conditions were characterized with formation of a coastal low in central Chile between the southeastern anticyclone and a high-pressure system over Argentina. At a local scale, these conditions generated a depression at the base of the inversion layer, an increase in the vertical thermal stability, lower humidity and low-wind conditions, which were conducive to a decrease in pollutant dispersion and insufficient ventilation of the polluted air. Measurements and simulations using the WRF model revealed a vertical structure of the boundary layer during these stagnant conditions and provided a basis for a trajectory analysis. The back-trajectory calculation showed that the transport of air parcels was contained in the valley during the highest concentrations. The analysis also enabled the definition of the threshold values of a simple indicator of air pollution (ventilation coefficient, VC), which confirmed the evolution of the episode and divided the observed daily concentrations into two groups, with one including values above the limits prescribed by the national air quality standards (NAQS) and the other including values below these limits. For the SMA, the daily PM concentrations above the NASQ limits were associated with an overall mean threshold value of VC below 500 m² s⁻¹ (for PM₂.₅) and 300 m² s⁻¹ (for PM₁₀). To apply the VC analysis to other pollutants and different geographic locations, different threshold values should be evaluated.

Volatile organic compounds (VOCs) are an important factor affecting ambient air quality, and furniture production is one of the important sources of VOC pollution. High VOC concentrations have adverse effects on the environment and worker welfare in furniture factories. In order to control VOC emissions in a furniture workshop, the VOC species and concentration distributions were examined. Qualitative analysis of VOC species was carried out by headspace gas chromatography/mass spectrometry. The results showed that VOCs from a furniture workshop were mainly 12 substances including acetate, toluene, and xylene compounds. The heights and representative positions of VOCs released during the coating process were determined, and the results showed that VOC concentrations depended on environmental and height factors. The concentration of VOCs decreased with increasing altitude and reached a maximum concentration at 0.4 m above the ground. Because the concentration of VOCs varied with temperature, humidity, air pressure, and amount of spray paint, this paper established functional relationships between VOC concentrations and temperature, humidity, air pressure, and amount of spray paint. These results provide a theoretical basis for furniture workshops to automatically monitor and control VOCs.VOCs from the furniture workshop were mainly composed of 10 substances including acetate, toluene, and xylene compounds.

In this study, the effects of descent flight path angle (between 1.25° and 4.25°) on aircraft gaseous emissions (carbon monoxide, total hydrocarbons and nitrogen oxides) are explored using actual flight data from aircraft flight data recording system and emissions indices from the International Civil Aviation Organization. All emissions parameters are corrected to flight conditions using Boeing Fuel Flow Method2, where the ambient air pressure, temperature and humidity data are obtained from long-term radiosonde data measured close to the arrival airport. The main findings highlight that the higher the flight path angle, the higher the emission indices of CO and HC, whereas the lower the emissions index of NOx and fuel consumption. Furthermore, during a descent, a heavier aircraft tends to emit less CO and HC, and more NOx. For a five-tonne aircraft mass increase, the average change in emissions indices are found to be −4.1% and −5.7% (CO), −5.4% and −8.2% (HC), and +1.1% and +1.6% (NOx) for high and low flight path angle groups, respectively. The average emissions indices for CO, HC and NOx during descent are calculated to be 24.5, 1.7 and 5.6 g/kg of fuel, whereas the average emissions for descending from 32,000 ft (9.7 km) and 24,000 ft (7.3 km) are calculated to be 7–8 kg (CO), ∼0.5 kg (HC) and ∼3 kg (NOx).

A national citizen survey quantified the abundance of epiphytic lichens that are known to be either sensitive or tolerant to nitrogen (N) deposition. Records were collected across the UK from over 10,000 individual trees of 22 deciduous species. Mean abundance of tolerant and sensitive lichens was related to mean N deposition rates and climatic variables at a 5 km scale, and the response of lichens was compared on the three most common trees (Quercus, Fraxinus and Acer) and by assigning all 22 tree species to three bark pH groups. The abundance of N-sensitive lichens on trunks decreased with increasing total N deposition, while that of N-tolerant lichens increased. The abundance of N-sensitive lichens on trunks was reduced close to a busy road, while the abundance of N-tolerant lichens increased. The abundance of N-tolerant lichen species on trunks was lower on Quercus and other low bark pH species, but the abundance of N-sensitive lichens was similar on different tree species. Lichen abundance relationships with total N deposition did not differ between tree species or bark pH groups. The response of N-sensitive lichens to reduced nitrogen was greater than to oxidised N, and the response of N-tolerant lichens was greater to oxidised N than to reduced N. There were differences in the response of N-sensitive and N-tolerant lichens to rainfall, humidity and temperature. Relationships with N deposition and climatic variables were similar for lichen presence on twigs as for lichen abundance on trunks, but N-sensitive lichens increased, rather than decreased, on twigs of Quercus/low bark pH species. The results demonstrate the unique power of citizen science to detect and quantify the air pollution impacts over a wide geographical range, and specifically to contribute to understanding of lichen responses to different chemical forms of N deposition, local pollution sources and bark chemistry.

PM2.5 concentrations in a typical residential apartment in Beijing and immediately outside of the building were measured simultaneously during heating and non-heating periods. The objective was to quantitatively explore the relationship between indoor and outdoor PM2.5 concentrations. A statistical method for predicting indoor PM2.5 concentrations was proposed. Ambient PM2.5 concentrations were strongly affected by meteorological conditions, especially wind directions. A bimodal distribution was identified during the heating season due to the frequent and rapid transition between severe pollution events and clean days. Indoor PM2.5 concentrations were significantly correlated with outdoor PM2.5 concentrations but with 1–2 h delay, and the differences can be explained by ambient meteorological features, such as temperature, humidity, and wind direction. These results indicate the potential to incorporate indoor exposure features to the regional air quality model framework and to more accurately estimate the epidemiological relationship between human mortality and air pollution exposure.

The effects of experimentally elevated O3 on soil respiration rates, standing fine-root biomass, fine-root production and δ13C signature of newly produced fine roots were investigated in an adult European beech/Norway spruce forest in Germany during two subsequent years with contrasting rainfall patterns. During humid 2002, soil respiration rate was enhanced under elevated O3 under beech and spruce, and was related to O3-stimulated fine-root production only in beech. During dry 2003, the stimulating effect of O3 on soil respiration rate vanished under spruce, which was correlated with decreased fine-root production in spruce under drought, irrespective of the O3 regime. δ13C signature of newly formed fine-roots was consistent with the differing gs of beech and spruce, and indicated stomatal limitation by O3 in beech and by drought in spruce. Our study showed that drought can override the stimulating O3 effects on fine-root dynamics and soil respiration in mature beech and spruce forests. Drought has the capacity to override the stimulating ozone effect on soil respiration in adult European beech/Norway spruce forest.

This research study uses Artificial Neural Networks (ANNs) to predict occupational accidents in Sivakasi firework industries. Atmospheric temperature, pressure and humidity are the causes of explosion during chemical mixing, drying, and pellet making. The Proposed ANN model predicts the accidents and the session of accidents (FN/AN) based on atmospheric conditions. This prediction takes values from historical accident data due to the atmospheric conditions of Sivakasi (2009–2021). In the development of ANN model, the Feed-Forward Back Propagation (FFBP) with the Levenberg-Marquardt function has been employed with hidden layers of 5 and 10 to train the network. The performance accuracy of both the hidden layers is evaluated and compared with other models like Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbor (K-NN). The accuracy of the proposed model for accident classification is 82.7% and 67.8% for hidden layers 5 and 10, respectively. Also, the model predicts the session of accident with the accuracy of 72% and 54%, specificity of 77.7% and 60.1%, sensitivity of 69% and 52.92% for hidden layers 5 and 10, respectively. It is found that hidden layer 5 gives higher accuracy than hidden layer 10. The proposed ANN model gives the highest accuracy when compared to other models. This study is helpful in the firework industry management, and workers improve safety precautions and avoid explosions due to atmospheric conditions.

Whatever the exposure route, chemical, physical and biological pollutants modify the whole organism response, leading to nerve, cardiac, respiratory, reproductive, and skin system pathologies. Skin acts as a barrier for preventing pollutant modifications. This review aims to present the available scientific models, which help investigate the impact of pollution on the skin. The research question was “Which experimental models illustrate the impact of pollution on the skin in humans?” The review covered a period of 10 years following a PECO statement on in vitro, ex vivo, in vivo and in silico models. Of 582 retrieved articles, 118 articles were eligible. In oral and inhalation routes, dermal exposure had an important impact at both local and systemic levels. Healthy skin models included primary cells, cell lines, co-cultures, reconstructed human epidermis, and skin explants. In silico models estimated skin exposure and permeability. All pollutants affected the skin by altering elasticity, thickness, the structure of epidermal barrier strength, and dermal extracellular integrity. Some specific models concerned wound healing or the skin aging process. Underlying mechanisms were an exacerbated inflammatory skin reaction with the modulation of several cytokines and oxidative stress responses, ending with apoptosis. Pathological skin models revealed the consequences of environmental pollutants on psoriasis, atopic dermatitis, and tumour development. Finally, scientific models were used for evaluating the safety and efficacy of potential skin formulations in preventing the skin aging process or skin irritation after repeated contact. The review gives an overview of scientific skin models used to assess the effects of pollutants. Chemical and physical pollutants were mainly represented while biological contaminants were little studied. In future developments, cell hypoxia and microbiota models may be considered as more representative of clinical situations. Models considering humidity and temperature variations may reflect the impact of these changes.