Urban air pollution is one of the most important environmental problems nowadays. Understanding urban pollution is rather challenging due to different factors that produce a strongly heterogeneous pollutant distribution within streets. Observed concentrations depend on processes occurring at a wide range of spatial and temporal scales, complex wind flow and turbulence patterns induced by urban obstacles and irregular traffic emissions. The main objective of this paper is to model particulate matter dispersion at microscale while considering the effects of mesoscale processes. Computational Fluid Dynamic (CFD) PM10 simulations were performed taking into account high spatial resolution traffic emissions from a microscale traffic model and inlet vertical profiles of meteorological variables from Weather Research and Forecasting (WRF) model. This modelling system is evaluated by using meteorological and PM10 concentration data from intensive experimental campaigns carried out on 25th February and 6th July, 2015 in a real urban traffic hot-spot in Madrid. The effect of uncertainties in the inlet profiles from mesoscale input data on microscale results is assessed. Additionally, the importance of the sensible surface heat fluxes (SHF) provided by WRF and the selection of an appropriate turbulent Schmidt number in the dispersion equation are investigated. The main conclusion is that the modelling system accurately reproduces PM10 dispersion imposing appropriate inputs (meteorological variables and SHF) and a suitable turbulent Schmidt number. Better agreement is found for simulation with a low turbulent Schmidt number. This approach improves the standard microscale modelling alone because more realistic boundary conditions and mesoscale processes are considered.

PM₁₀ samples were collected at eight monitoring (urban, industrial and regional background) stations during 2011 in SW Poland (Voivodeship of Lower Silesia) with the objectives of identifying their potential sources, as well as of quantitatively estimating the anthropogenic impact on their carbon content by coupling carbon stable isotope compositions of the total carbon (TC) with organic (OC) and elemental carbon (EC) concentrations. Results showed that (i) the highest OC and EC concentrations measured at the five urban background stations were 11.9 and 1.9 μg m⁻³, respectively, with an average δ¹³CTC of −26.5 ± 1.13‰. Annual average concentrations measured (ii) at the industrial and (iii) the two regional stations were similar for OC (6.9 and 6.4 μg m⁻³, respectively) and EC (0.9 and 0.8 μg m⁻³, respectively) with average δ¹³CTC of −27.4 ± 0.81 and −27.6 ± 0.99‰, respectively. This indicates that similar contamination sources explain the PM₁₀ levels at stations (ii) and (iii), however significantly different from the source(s) influencing station (i). Moreover, using an isotope mass balance that incorporates δ¹³CTC and OC and EC concentrations, we show that while during the heating season coal is the dominant source of aerosol contamination (with contributions ranging from 5.1 to 73.8 μg m⁻³), during the vegetative season road traffic is the dominant one (with contributions ranging from 2.2 to 20.2 μg m⁻³). These large ranges confirm the spatiotemporal heterogeneity of air contamination, even within such a small monitoring area, and should be taken into consideration for future implementation of air quality management measures at larger, e.g. national and international, scales.

The comparison of two methods in calculating transboundary concentrations of NO₂ and PM₁₀ using CMAQ chemical transport model is presented. The total mean annual concentrations for the pollutants were computed from the hourly outputs of the CMAQ model. The first method for calculating the transboundary concentrations is based on switching off the emissions from the studied country, while the remaining emissions are the same as in the full model run. The second method is based on running the model with the emissions from the studied country only. The resulting concentrations are then subtracted from the full model run concentrations. The result of this subtraction represents the transboundary air pollution together with pollution originating from the interaction of national and foreign sources. The pollution which cannot be attributed unambiguously to national or foreign sources is caused by the non-linear processes included in the model. It is evaluated as the difference between the two methods. It is shown that the non-linearity effect is more expressed for PM₁₀ than for NO₂ annual mean concentrations. It is estimated that the non-linearity effect for PM₁₀ can reach values up to 2.7 μg/m3 in absolute value, or up to 16% of the total annual mean concentrations and up to 25% of the total estimated transboundary concentrations in the studied area. It is also demonstrated that this non-linearity effect is more important for both pollutants during some episodes than in the annual mean. The method of removing the bias from the calculated transboundary concentrations is presented, together with the proposed method of evaluation of the uncertainties of the transboundary concentration calculations. The estimated transboundary contribution is evaluated at the locations of Slovak air-quality monitoring stations. The impact of several emission reduction levels on the estimation of the transboundary contribution is also presented. The simulations are performed for the reference year of 2015 for Slovakia, but the proposed methods can by applied universally.

The daily concentrations of 15 polycyclic aromatic hydrocarbons (PAHs) in PM₁ aerosol samples, including 7 carcinogenic PAHs, were determined in six urban/rural areas in the Czech Republic in winter seasons between 2013 and 2017. The PM₁ aerosol was collected on quartz fibre filters using high-volume samplers for 24 h and PAHs were analysed by GC-MS. The highest concentrations of PAHs were found in the industrial city Ostrava (60.8 ng m⁻³), which is one of the most polluted areas in the Czech Republic, while the lowest concentrations were obtained in the small town Čelákovice (11.7 ng m⁻³) and in the background rural area Košetice (12.3 ng m⁻³). Carcinogenic PAHs formed 43.9%–57.8% of total analysed PAHs.The toxic equivalence factors for individual PAHs adopted from literature and two unit risks (Cal-EPA and WHO) were used for the evaluation of carcinogenic risk of PAHs exposure. The inhalation cancer risk models assume a lifetime exposure (70 years), whereas our measurement was realized for a relatively short duration in winters where concentrations of PAHs are usually high. The average of PAHs concentrations will be lower for the whole year resulting in lower lung cancer risk values. The calculated lifetime lung cancer risk of PAHs exposure for the measured winter periods suggested 1545 cases per 1 million people in Ostrava (industrial area), 192–456 cases per 1 million people in other four investigated cities/towns and 182 cases per 1 million people in Košetice (rural area). The calculated lifetime lung cancer risk values are related only to ambient concentrations of PAHs in atmospheric aerosols. Nevertheless, other factors can influence and increase the lung cancer risk, e.g., occupation, smoking, indoor emissions of coal/wood combustion in stoves or genetic factors of individuals. Our results can also be underestimated due to the determination of PAHs only in PM₁ aerosol.

In vitro assays were used to determine the effects of aqueous fine particulate matter (PM₂.₅) extracts on different homogenates of rat organs. The PM₂.₅ collected from two regions (Seropédica and Duque de Caxias) in Rio de Janeiro, Brazil, were used to evaluate different oxidative damages and redox state. Two PM₂.₅ extract concentrations (concentrate and 10x dilution) were evaluated using rat tissue homogenates (heart, lung, liver, and kidney). Measurements of total antioxidant capacity (ACAP), lipid peroxidation levels (LPO), reduced glutathione concentrations (GSH), activity of glutamate cysteine ligase (GCL), activity of glutathione S-transferase (GST) and catalase (CAT) were performed. Most PM₂.₅ aqueous extract concentrations contain numerous metals (e.g. Li, Ti, Fe, Cu, Cd, Sr, among others), which reduced ACAP and generated LPO in most tissue homogenates. Besides this, GST activity decreased in liver and lung, increasing in kidney and heart homogenates. GCL activity increased in lung, liver and kidney and undergo decrease in the heart homogenate. All concentrations of PM₂.₅ evaluated decreased GSH levels. PM₂.₅ concentrations for both sites (regions) raised catalase activity in most tissue homogenates except in the liver. In vitro toxicity of the PM₂.₅ in different tissues, presented an ability to interact with cellular antioxidant defense system, causing depletion of the sulfhydryl stocks, resulting in the damage of biological molecules and inducing oxidative imbalance.

The UK may be required to expand its bioenergy production in order to make a significant contribution towards the delivery of its ‘net zero’ greenhouse gas emissions target by 2050. However, some trees grown for bioenergy are emitters of volatile organic compounds (VOCs), including isoprene and terpenes, precursors in the formation of tropospheric ozone, an atmospheric pollutant, which require assessment to understand any consequent impacts on air quality. In this initial scoping study, VOC emission rates were quantified under UK climate conditions for the first time from four species of eucalypts suitable for growing as short-rotation forest for bioenergy. An additional previously characterised eucalypt species was included for comparison. Measurements were undertaken using a dynamic chamber sampling system on 2-3 year-old trees grown under ambient conditions. Average emission rates for isoprene, normalised to 30 °C and 1000 μmol m⁻² s⁻¹ PAR, ranged between 1.3 μg C gdw⁻¹ h⁻¹ to 10 μg C gdw⁻¹ h⁻¹. All the eucalypt species measured were categorised as ‘medium’ isoprene emitters (1–10 μg C gdw⁻¹ h⁻¹). Total normalised monoterpene emission rates were of similar order of magnitude to isoprene or approximately one order of magnitude lower. The composition of the monoterpene emissions differed between the species and major compounds included eucalyptol, α-pinene, limonene and β-cis-ocimene. The emission rates presented here contribute the first data for further studies to quantify the potential impact on UK atmospheric composition, if there were widespread planting of eucalypts in the UK for bioenergy purposes.

This study investigates the contents, distribution patterns, and sources of lanthanoid elements (La to Lu) in aerosols with an aerodynamic diameter ≤10 μm (PM₁₀) in a coastal Caribbean region in order to better constrain the origin of the atmospheric PM contamination. We sampled and analysed PM₁₀ aerosols during 2015 simultaneously at a rural and an urban site in Cienfuegos (Cuba) as well as particles samples from regional contamination sources. Results showed that the sum of the studied lanthanoids concentrations ranged from 0.03 to 13.42 ng m⁻³ and from 0.51 to 18.75 ng m⁻³ at the rural and the urban site, respectively. Time variations for the lanthanoid concentrations displayed similar trends and showed that the highest concentrations corresponded to the influence of the African dust for both sites, but presented distinct variability and lower concentrations when dust intrusions were less frequent. The lanthanoid distribution patterns in the rural and urban sites were significantly different, due to the impact of different local combustion sources. Our results were comforted by comparing the degree of fractionation of the lighter and heavier lanthanoids and the δEu and δCe anomalies between our PM₁₀ samples and those of the local sources of contamination. Ultimately, we highlight the added value of lanthanoid elements as reliable indicators for discriminating emission sources and for tracking the origin of atmospheric particulate matter.

This article presents the results of a study on the chemical composition of rainwater as an environmental pollution factor in the surroundings of the Puchuncaví - Ventanas industrial complex (V Region, Chile), with the main objectives of assessing acidification and neutralisation factors, measuring elemental pollutant levels including calculation of enrichment factors and pollution sources assignment, and assessing the risk derived from elemental pollutant loads in rainwater, both for human use and natural ecosystems. Forty-seven weekly rainwater samples were collected during the winter (May–August) 2010 (24 samples) and 2011 (23 samples) at three sampling location with different degree of impact from the main emission sources. The pH, conductivity and major ions were analyzed by ion chromatography, as well as 18 traces and main elements by ICP-MS. Most rainwater samples had pH below 5.6, indicating the risk of acidification, but neutralisation factors, mainly by Na⁺ and NH⁴⁺ were also noticed. The elements emitted by anthropogenic activities had significant enrichment values in the rainwater of the area studied, and the principal component analysis (PCA) identified four sources related to the metallurgical industry – crustal material, marine material, traffic -industry and industrial activities. The risk assessment showed that As content in rainwater is above the WHO guideline value for drinking water at some points in the study area. The contribution of Pb and Cd in rainwater to the soil critical loads turned out to be relatively low, with a maximum of 22.1% for Pb in the vicinity of the industrial complex.

Local regressions have been widely employed for decomposing atmospheric data series. However, the use of local quadratic regressions is less extended. The current paper is grounded on the hypothesis that local linear regressions are able to capture CO2 and CH4 temporal evolution equally as well as quadratic linear regressions. Thus, the current paper pursues the following goals: (1) to quantify the temporal variability of both gases by using the local linear and local quadratic regression method; (2) to analyse the main statistics of the detrended series over time; (3) to compare results between the local linear and local quadratic regression method. Minimum mixing ratios in late summer and maximum in winter were detected for both gases. Atmospheric increases of an average of 1.98 ppm year−1 for CO2 and 11 ppb year−1 for CH4 were found when applying the local linear regression method. Alternatively, an increase of 2.24 ppm year−1 for CO2 and around 10.34 ppb year−1 for CH4 was obtained when the local quadratic regression method was applied. The Pearson correlation coefficients (0.21–0.40) showed acceptable values due to the large amount of available data. Statistically significant differences for the initial and the smoothed trend, as well as statistically significant differences for the seasonal component, were reported when comparing the local linear with the local quadratic method. Overall, both methods proved easy to apply and both provided acceptable data accuracy.

Open landfilling is a common practice of waste dumping in developing countries, generating a range of environmental and public health hazards. In this study, we determined the distribution, composition and exposure risk of the size-segregated fungal and bacterial bioaerosols in an open landfill site in Dehradun, India. Bioaerosol and particulate matter (PM) measurements were carried out using a six-stage viable Andersen Cascade Impactor and a Wide Range Aerosol Spectrometer, respectively. Pearson correlation analysis was used to determine the relation of bioaerosol concentration with meteorological parameters and PM. The mean concentration of fungal and bacterial aerosols was observed to be 4582.75 ± 1358.25 CFU/m3 and 3609.53 ± 1000.28 CFU/m3, respectively. The bioaerosol composition showed the predominance of potential pathogens including Aspergillus (25.42%), Penicillium (20.34%), Cladosporium (15.25%), Alternaria (13.56%); and gram-negative Bacillus (21.15%), Streptobacillus (17.31%), Coccus (13.46%). Also, an inhalation risk assessment was conducted for the age-specific predictions of bioaerosol and PM deposition in human airways using a multiple path particle dosimetry model. For bioaerosols, maximum submicron depositions in the pulmonary region were observed in adults, while for PM, in children and infants. Finally, to identify the bioaerosol exposure caused respiratory disorders, a questionnaire-based health survey was conducted among the exposed population around the landfill site. The chi-square test showed significantly higher respiratory complaints in females for cold, cough, chest pain and chest tightness than in males. This work highlights the role of bioaerosols and PM in human health disorders in occupational environments associated with waste management.