This paper presents model results for the dispersion of radionuclides released into the atmosphere by intense forest fires in the Chernobyl Exclusion Zone in April 2020. The ¹³⁷Cs activity concentration in the surface air is calculated on a regional scale (in Ukraine) and a local scale (within the Chernobyl Exclusion Zone). The ¹³⁷Cs activity in the surface air of Kyiv was found to have reached 2–4 mBq m⁻³ during the period April 4–20. The results presented in this paper are generally consistent with measured data pertaining to radioactive contamination in Kyiv and areas around several nuclear power plants in Ukraine. The total effective dose to the population of Kyiv during the fire period was estimated to be 5.7 nSv from external exposure and the inhalation of ¹³⁷Cs and ⁹⁰Sr, rising to 30 nSv by the end of 2020. This is about 0.003% of the annual permissible level of exposure of the population. A committed effective dose of about 16 nSv was estimated for the personnel of the Chernobyl nuclear power plant from the inhalation of ¹³⁷Cs and ⁹⁰Sr during the 2020 forest fires. A method for estimating the radionuclide activity emissions during wildland fires in radioactively contaminated areas is proposed. This method is based on satellite measurement data of the fire radiative power, the radionuclide inventory in the fire area, and an emission factor for radioactive particles.

The concentration of ions, metals, and metalloids in hailstone samples was evaluated for the first time in South America. The samples were previously cleaned with ultrapure water to eliminate potential contaminants. The ions concentrations in the samples showed a general pattern according to the following sequence: Ca²⁺ >NO3-> K⁺ > CHOO⁻ > Mg²⁺ > Cl⁻ >SO 42_> Na⁺ >NH4+ > F⁻. Regarding the metals and metalloids concentrations, the order was of Zn > Al > Fe > Mn > Sr > Ba > Cu > Ni > Cr > Pb > Co > V. Ca²⁺ was the most abundant and agricultural activity, one of the sources due to long-distance transport. Concentrations of K⁺ and Cl⁻ may originate from fires that occur every year in the North and Center-West regions of Brazil. Local sources also contributed to the chemical composition, such as soil resuspension contributing mainly to the species and elements Al, Fe, Na⁺, K⁺, SO 42_, and F⁻. Besides that, the region is an agricultural area with unpaved roads and use of fertilizer; therefore, the species and elements NH4+, Mg²⁺, K⁺, Cl⁻, Cu, and Zn, were also associated with local sources, including emissions from vegetation. A possible vehicular contribution was also observed. Among the few existing studies, this is the first to evaluate the hailstones cleaning procedure's efficiency. The findings also support the previous studies' conclusion that the concentration of chemical species varies considerably according to the region of study's characteristics. This work contributes to improve the understanding of local and remote natural and anthropic emissions in this complex atmospheric phenomenon.

A source apportionment study was carried out at four sites in Emilia-Romagna region, southern Po Valley, one of the most critical regions in Europe in terms of atmospheric pollution. PM₂.₅ daily samples were collected during 4 years from April 2013 to October 2017 at one rural site (San Pietro Capofiume) and three urban background locations in the cities of Bologna, Rimini, Parma which show different features and are located in the central, coastal and inner part of the investigated region. Samples were analyzed to achieve a complete chemical characterization (carbon fractions, ions, and elements). A source apportionment analysis by Positive Matrix Factorization (PMF) was performed and 6 PM₂.₅ factors were identified at all sites but the rural one (where 5 out of 6 of them were detected); the factors were associated to traffic with dust resuspension, biomass burning, oil combustion/ship emission, mix anthropogenic (not found at the rural site), ammonium nitrate and ammonium sulfate with organics. Chemical profiles of factors were very similar among all the 4 sites, indicating that main pollution sources are basically the same at the 4 sites, while some differences emerged with regard to source contributions. Factors related to secondary components seem to explain almost 50% or even more of PM₂.₅ mass concentration in all seasons. Traffic and biomass burning are the most relevant contributors to PM₂.₅ in terms of primary components. A not negligible contribution of biomass burning results in Rimini during the summer, suggesting other possible sources of wood combustion, such as cooking or open burning of agricultural pruning bonfires. Agriculture is not singled out as a PMF factor, but a rough estimate based on ammonium concentrations and ammonia data from emission inventory indicates a contribution from this source of about 10% of PM₂.₅ mass, thus resulting the single productive activity with the highest impact on PM₂.₅ at the investigated sites. Back trajectory analysis points out the relevant extra-regional contributions of two factors; indeed, oil combustion/ship emission is related to long-range transport of air masses overpassing the Mediterranean sea and secondary sulfate from Eastern Europe countries occasionally impacts on the Po Valley.

Statistical learning models have been applied to study the spatial patterns of ambient Nitrogen Dioxide (NO2), which is a highly dynamic, traffic-related air pollutant. Commonly, the validation process in most studies is based on bootstrapped split-sampling of training and test sets from fixed ground station measurements. As the ground stations distribute mostly sparsely over a region or country, this kind of cross-validation validation method does not consider how well models are capable of representing spatial variations in air pollution mostly occurring over distances shorter than the ground station sampling spacing. This may lead to inadequate hyperparameter optimisation and bias when comparing different statistical models. External mobile measurements are therefore needed for more reliable model evaluations as these provide detailed and spatially continuous information on air pollution patterns. However, most current designs of mobile NO2 sensing instruments suffer from the trade-off between flexibility and measurement accuracy, as high-end sensors are commonly too heavy to be carried by a person or on a bike. In addition, sufficient repetitions over time are needed so that the measurements are representative to concentrations over a relatively long-term period. In this study, we installed a mobile air quality station onboard a cargo-bike to collect a dataset suitable for external validation. With the external validation dataset the model hyperparameter setting and statistical model comparison results alter. Our model comparison results also differ from previous studies relying only on ground stations for cross-validation.

Cities in southern Chile are facing high levels of PM₂.₅ because of wood burning pollution. We quantify the contribution of wood smoke to fine particles in two mid-size cities: Molina and Valdivia, located in different climate zones. The sampling campaigns were carried out during austral winter (July to September) in 2018 (Molina) and 2019 (Valdivia). 24-h filter samples were analyzed for carbonaceous compounds, secondary ions, metals, and particle-phase organic molecular markers. Average winter concentrations of PM₂.₅ were 53 ± 32 μg/m³ (average ± standard deviation) in Molina and 89 ± 55 μg/m³ in Valdivia. The major component of fine particles was organic matter, representing more than 70% of PM₂.₅. Concentrations of organic molecular markers were used in a receptor model (US EPA CMB8.2) to identify and quantify primary sources of PM₂.₅. The major source of PM₂.₅ was wood smoke, which accounted for 41.55 ± 9.77 μg/m³ (62.9 ± 15.3%) in Molina and 43.65 ± 24.06 μg/m³ (51.7 ± 21.1%) in Valdivia. Secondary organic aerosols (SOA) generated from inefficient wood burning, contributed 20.4 ± 17.7% in Molina and 28.9 ± 27.6% in Valdivia. Secondary inorganic ions and dust are minor sources of PM₂.₅. The total contribution of wood smoke (adding primary wood smoke and SOA) could be as much as 83% in Molina and 81% in Valdivia, during the winter season.

Well integrity failure resulting in migration of natural gas outside of the surface casing can cause atmospheric greenhouse gas emissions and groundwater quality impacts from existing and historic energy wells. Spatial and temporal variability in gas migration can result in errors in detection (i.e., presence/absence) and efflux estimations. This field-based case study used automated dynamic closed chambers to record repeated (~every 18 min) CO₂ and CH₄ efflux measurements over a two-week period around a single petroleum production well in Alberta, Canada. Long-term efflux measurements supplemented soil gas compositional and isotopic characterization, along with surface concentration measurements. Effluxes were spatially concentrated around the wellhead and only occasionally detectable more than a few meters away. Estimated total emissions attributable to gas migration ranged from 48 to 466 g CH₄ d⁻¹ (or 0.07–0.7 m³ CH₄ d⁻¹). Methane effluxes and concentrations were temporally variable on second-to-hourly and diel scales. Multivariate stepwise regression analysis indicates that multiple meteorological factors, particularly wind speed and air temperature, were related to the temporal variability. Despite temporal variability, elevated concentrations and effluxes were consistently detectable around the well. Major soil gas composition suggests that gas migration near the wellhead causes advective displacement of soil gas, while more distal measurements are indicative of episodic and diffusion-dominated transport. Values of ¹³C–CO₂ and ¹³C–CH₄ samples were consistent with CH₄ oxidation within the unsaturated zone. Although these results reflect a single well, the findings are salient to gas migration detection and emission estimation efforts.

This report presents a flexible scientific blueprint for how the climate change, biodiversity and pollution emergencies can be tackled jointly within the framework of the SDGs. The first of its kind, this report gathers expertise from across recent global assessments to gauge Earth’s environmental decline and suggest how society at large can best respond. The expert analysis synthesizes key findings from the assessments with those from additional high-impact peer-reviewed literature and grey literature. Part I of this report shows how the findings of the assessments are interlinked and add up to an unparalleled planetary emergency. It presents a diagnosis of how the human transformation of Earth’s natural systems puts the collective human future at risk.

The presence of toxic chlorinated compounds in drinking water, generated during the disinfection step in water treatment plants, is of great concern for public health. In the present study, the performance of the UVC/H₂O₂ process, preceded by zero-valent-copper reduction, was evaluated for degrading 2,4,6-trichlorophenol (TCP). With this aim, the oxidation performed alone or in combination with the pre-reductive step was evaluated regarding TCP concentration over time, removal rate, mineralization, and toxicity to Vibrio fischeri, as well as oxidant dosage and the effect of water matrix. The UV/H₂O₂ process achieved fast (kₒbₛ = 1.4 min⁻¹) and complete TCP degradation, as well as important mineralization (40.4%), with best results obtained for initial H₂O₂ concentration of 0.056 mmol L–¹. Coupling of reductive and oxidative processes intensified contaminant mineralization, due to the synergistic effect of copper ions leached in the reductive process, particularly Cu(I), providing an additional route of H₂O₂ activation for generating HO• radicals (photo-Fenton-like process). High toxicity removals and increased mineralization could be successfully accomplished by the combined processes even in tap water, which is a clear advantage for practical application.

Lead is one of the major environmental pollutions worldwide, particularly in developing countries. Though, various occupational and public health measures have been undertaken to control lead exposure. The present study is designed to investigate the role of zinc oxide nanoparticles (ZnO-NPs) to reduce the bioaggregation of lead in the brain, liver, and kidneys and prevent these organ oxidative damage and apoptosis. Twenty male Wistar rats were grouped into 4 gatherings and exposed to the following materials daily on the skin for 2 weeks: 1—normal saline, 2—ZnO-NPs, 3—PbO, and 4—ZnO-NPs+ PbO. Topical application of PbO to rats increased lead contents in blood and different organs causing remarkable oxidative stress damage, apoptosis, and histopathological alterations in these organs. Moreover, PbO-receiving group showed strong positive caspase-3 protein expression with up-regulation of mRNA levels of BAX and COX-2. Co-treatment of ZnO-NPs with PbO could diminish the toxicologic parameters and the above-mentioned immune marker and gene expression levels. Our data suggest the role of ZnO-NPs cream to reduce the risk of lead dermal exposure via preventing absorption and accumulation of it in the internal organs so that it protects these organs from further damage.