Studies have reported significant reductions in air pollutant levels due to the COVID-19 outbreak worldwide global lockdowns. Nevertheless, all of the reports are limited compared to data from the same period over the past few years, providing mainly an overview of past events, with no future predictions. Lockdown level can be directly related to the number of new COVID-19 cases, air pollution, and economic restriction. As lockdown status varies considerably across the globe, there is a window for mega-cities to determine the optimum lockdown flexibility. To that end, firstly, we employed four different Artificial Neural Networks (ANN) to examine the compatibility to the original levels of CO, O₃, NO₂, NO, PM₂.₅, and PM₁₀, for São Paulo City, the current Pandemic epicenter in South America. After checking compatibility, we simulated four hypothetical scenarios: 10%, 30%, 70%, and 90% lockdown to predict air pollution levels. To our knowledge, ANN have not been applied to air pollution prediction by lockdown level. Using a limited database, the Multilayer Perceptron neural network has proven to be robust (with Mean Absolute Percentage Error ∼ 30%), with acceptable predictive power to estimate air pollution changes. We illustrate that air pollutant levels can effectively be controlled and predicted when flexible lockdown measures are implemented. The models will be a useful tool for governments to manage the delicate balance among lockdown, number of COVID-19 cases, and air pollution.

This study demonstrated that nitrogen-doped carbon materials (NCMs) could effectively catalyze the chlorine elimination process in hexachloroethane (HCA) declorination in sulfide-containing environments for the first time. The kₒbₛ values of HCA dechlorination by sulfide in the presence of 10 mg/L NCMs were higher than that of no mediator at pH 7.3 by one or two orders of magnitude. The catalytic capabilities of NCMs on HCA dechlorination were evident in common ranges of natural pH (5.3–8.9) and it could be accelerated by the increase of pH but be suppressed by the presence of dissolved humic acid. Moreover, NCMs exhibited much better catalytic capability on HCA dechlorination compared to the carbon materials, mainly owing to the combined contributions of pyridine N, including enhanced nucleophilic attack to HCA molecule by generating newborn C–S–S and activation of HCA molecule by elongating C–Cl bonds. The functions of pyridine N in micron-sized NCMs with mesopores were better than in nano-sized NCMs on HCA dechlorination. These findings displayed the potential of NCMs, when released into sulfide-containing environments, may significantly increase the dechlorination of chlorinated aliphatic hydrocarbons.

Inhalation represents the most prevalent route of exposure with Thorium-232 compounds (Th-nitrate/Th-dioxide)/Th-containing dust in real occupational scenario. The present study investigated the mechanism of Th response in normal human alveolar epithelial cells (WI26), exposed to Th-nitrate or colloidal Th-dioxide (1–100 μg/ml, 24–72 h). Assessment in terms of changes in cell morphology, cell proliferation (cell count), plasma membrane integrity (lactate dehydrogenase leakage) and mitochondrial metabolic activity (MTT reduction) showed that Th-dioxide was quantitatively more deleterious than Th-nitrate to WI26 cells. TEM and immunofluorescence analysis suggested that Th-dioxide followed a clathrin/caveolin-mediated endocytosis, however, membrane perforation/non-endocytosis seemed to be the mode of Th internalization in cells exposed to Th-nitrate. Th-estimation by ICP-MS showed significantly higher uptake of Th in cells treated with Th-dioxide than with Th-nitrate at a given concentration. Both Th-dioxide and nitrate were found to increase the level of reactive oxygen species, which seemed to be responsible for lipid peroxidation, alteration in mitochondrial membrane potential and DNA-damage. Amongst HSPs, the protein levels of HSP70 and HSP90 were affected differentially by Th-nitrate/dioxide. Specific inhibitors of ATM (KU55933) or HSP90 (17AAG) were found to increase the Th- cytotoxicity suggesting prosurvival role of these signaling molecules in rescuing the cells from Th-toxicity.

The UK implemented a lockdown in Spring (2020) to curtail the person-to-person transmission of the SARS-CoV-2 virus. Measures restricted movements to one outing per day for exercise and shopping, otherwise most people were restricted to their dwelling except for key workers (e.g. medical, supermarkets, and transport). In this study, we quantified changes to air quality across the United Kingdom from 30/03/2020 to 03/05/2020 (weeks 14–18), the period of most stringent travel restrictions. Daily pollutant measurements of NO₂, O₃ and PM₂.₅ from the national network of monitoring sites during this period were compared with measurements over the same period during 2017–19. Comparisons were also made with predicted concentrations for the 2020 period from business-as-usual (BAU) modelling, where the contributions of normal anthropogenic activities were estimated under the observed meteorological conditions. During the lockdown study period there was a 69% reduction in traffic overall (74% reduction in light and 35% in heavy vehicles). Measurements from 129 monitoring stations, identified mean reductions in NO₂ of 38.3% (−8.8 μg/m³) and PM₂.₅ of 16.5% (−2.2 μg/m³). Improvements in NO₂ and PM₂.₅ were largest at urban traffic sites and more modest at background locations where a large proportion of the population live. In contrast, O₃ concentrations on average increased by 7.6% (+4.8 μg/m³) with the largest increases at roadside sites due to reductions in local emissions of NO. A lack of VOC monitoring limited our capacity to interpret changes in O₃ at urban background locations. BAU models predicted comparable NO₂ reductions and O₃ gains, although PM₂.₅ episodes would have been more prominent without lockdown. Results demonstrate the relatively modest contribution of traffic to air quality, suggesting that sustained improvements in air quality require actions across various sectors, including working with international and European initiatives on long-range transport air pollutants, especially PM₂.₅ and O₃.

To reduce direct discharges of surface runoff to receiving waters, separate sewer systems have been implemented, with runoff retention basins (RRB) for pollutant pretreatment by sedimentation and infiltration. However, due to frequent and intense precipitation events, most RRBs are overwhelmed by runoff resulting in overflow into the receiving freshwater bodies. Hence, the present study evaluates the impact of traffic-related runoff overflow on metal concentrations in sediment and Gammarus sp. Downstream of the RRB outfall in the receiving stream. Samples were collected from the RRB, upstream (reference site) and at different distances downstream from the RRB outfall in the stream. The samples were analyzed for the presence and distribution of metals using ICP-MS. Furthermore, ecotoxicological effects of the overflow on benthic species were assessed using Lumbriculus variegatus exposed to the field sediments. Our findings reveal that overflow of the RRB results in elevated traffic-related metal concentrations in sediment and biota of the stream. Within the first 50 m downstream increased sediment metal concentrations were found. The gammarids downstream of the RRB outfall showed an increased accumulation of several metals. Similarly, the metals were found to be taken up by the endobenthic L. variegatus under laboratory conditions and the bioaccumulation pattern was related to the sediment concentrations. Bioaccumulation by both organisms is an indication that overflow of the RRB also leads to uptake of increased element amounts in organisms downstream. Laboratory-based studies addressing standard toxicity endpoints showed no clear toxic effects on growth and reproduction. However, elevated levels of metallothioneins were measured in the annelids during the test period. This indicates a physiological response induced by increased metal concentrations due to RRB overflow. Hence, the results of this study show that discharges by the RRB increase the metal concentration in the receiving stream with the possibility of adverse effects on organisms.

Marine litter is widely distributed in marine environments and has been a severe concern worldwide, due to the disposal of waste from diverse sources. The severity of this threat has garnered increasing attention in India over the last decade, but the full consequences of this pollution are yet to be quantified. To estimate the spatiotemporal distribution, composition and beach quality of marine litter pollution, 17 beaches along the Hooghly estuary, a part of the Gangetic delta was studied. Marine litter was collected from 100 m long transects during two seasons (monsoon and post-monsoon). The OSPAR monitoring standard was applied to the 16,597 litter items collected, then grouped under 6 types and 44 categories. In terms of number, litter abundance was higher during monsoon (1.10 ± 0.39 items/m²) than that of post-monsoon (0.86 ± 0.32 items/m²). Most of the beaches were categorized as low cleanliness as computed by the general index and clean coast index and the good for the pellet pollution index. Hazardous litter constituted 6.5% of the total collected litter items. The model prediction revealed that the influence of high discharge from Hooghly, Rasulpur and Subarnarekha River carried enormous anthropogenic litter to the northeast beaches. The litter flux decreases with an increase in distance from the shore, and act as a sink to the sea-floor. The results denote that the distribution and typology of marine litter were representatives of household, tourism and fishing, which in turn highlights the need for better regional litter management measures. Suggested management practices include source reduction, mitigation, management of beach environment and change in littering behaviour through environmental education.

The relationship between heavy metal(loid)s exposure and oxidative stress damage is a matter of research interest. Our study aimed to investigate the distribution patterns of the nine heavy metal(loid)s in blood of pregnant women, including four toxic heavy metal(loid)s [arsenic (As), cadmium (Cd), lead (Pb) and mercury (Hg)] and five typical heavy metal(loid)s [manganese (Mn), cobalt (Co), copper (Cu), zinc (Zn), and selenium (Se)] in blood. Blood samples of 348 women were collected and their concentrations in the serum (sr) and blood cells (bc) were measured, as well as serum heme oxygenase-1 (HO-1) (an oxidative stress marker). Total blood (tb) concentrations of these metal(loid)s and serum-to-blood cell concentration ratios (sr/bc) were further calculated. We found Cu mainly accumulated in the serum compared to the blood cells with Cuˢʳ/ᵇᶜ = 2.30, whereas Co, Se, and As evenly distributed between these two fractions. Other metal(loid)s mainly concentrated in the blood cells. Coˢʳ, Cuˢʳ, Cuᵇᶜ, Mnᵇᶜ, Znᵇᶜ, Cdᵇᶜ, Coᵗᵇ, Cuᵗᵇ, Mnᵗᵇ, Znᵗᵇ, Cdᵗᵇ, and Cuˢʳ/ᵇᶜ were negatively associated with serum HO-1, whereas Asˢʳ, Asᵇᶜ, Asᵗᵇ, Znˢʳ/ᵇᶜ, Cdˢʳ/ᵇᶜ, and Hgˢʳ/ᵇᶜ were positively, indicating of their potential toxicity. We concluded that the distribution patterns of blood heavy metal(loid)s, in particular for Cd, Hg and Zn, which either increased in serum or decreased in blood cells, might be associated with elevated serum oxidative stress, should be considered in environmental health assessments.

Dispersion modelling is an effective tool to estimate traffic-related fine particulate matter (PM₂.₅) concentrations in near-road environments. However, many sources of uncertainty and variability are associated with the process of near-road dispersion modelling, which renders a single-number estimate of concentration a poor indicator of near-road air quality. In this study, we propose an integrated traffic-emission-dispersion modelling chain that incorporates several major sources of uncertainty. Our approach generates PM₂.₅ probability distributions capturing the uncertainty in emissions and meteorological conditions. Traffic PM₂.₅ emissions from 7 a.m. to 6 p.m. were estimated at 3400 ± 117 g. Modelled PM₂.₅ levels were validated against measurements along a major arterial road in Toronto, Canada. We observe large overlapping areas between modelled and measured PM₂.₅ distributions at all locations along the road, indicating a high likelihood that the model can reproduce measured concentrations. A policy scenario expressing the impact of reductions in truck emissions revealed that a 30% reduction in near-road PM₂.₅ concentrations can be achieved by upgrading close to 55% of the current trucks circulating along the corridor. A speed limit reduction of 10 km/h could lead to statistically significant increases in PM₂.₅ concentrations at twelve out of the eighteen locations.

The acidogenic fermentation of dairy wastewater (DW) was evaluated for carboxylic acids (CA) production, investigating the influence of substrate/microorganism (S/X) ratio and applying different mathematical models to the bioproduct formation data. The experiments were performed in batch reactors for 28 days, and four S/X ratios were tested (0.8, 1.2, 1.6, and 1.9 gCOD gVSS⁻¹). The S/X ratio increase did not influence the percentage of DW conversion into carboxylic acids (42–44%), but the productivity was positively affected (100–200% in general). Acetic acid was the CA formed in the highest concentration for all experiments, followed by propionic and butyric acids. Exponential models were better suited to describe this kinetics process. Therefore, according to the estimated kinetic parameters, the S/X ratio 1.6 was more suitable for CA production from acidogenic fermentation of dairy wastewater, in which the concentrations of longer CA, such as propionate and butyrate, were formed in higher quantities. In addition, it was determined a correlation between the S/X ratio and kinetic parameters like degradation/production rate constant (K) and maximum productivity rate (μₘ).

In this study, we analyzed 30 legacy and emerging poly- and perfluoroalkyl substances (PFASs) in paired atmospheric particulate and bark samples collected around a Chinese fluorochemical manufacturing park (FMP), with the aim to explore the sources of PFASs in tree bark. The results showed that PFASs in atmospheric particulate and tree bark samples were consistently dominated by perfluorooctanoate (mean 73 ng/g; 44 pg/m³), perfluorohexanoate (47 ng/g; 36 pg/m³), perfluorononanoate (9.1 ng/g; 8.8 pg/m³), and 10:2 fluorotelomer alcohol (10:2 FTOH; 5.6 ng/g; 12 pg/m³). Spatially, concentrations of C₈–C₁₂ perfluoroalkyl carboxylates (PFCAs) and 10:2 FTOH all showed a similar and exponentially decreased trend in both bark and atmospheric particulate samples with the increasing distance from the FMP. For the first time, we observed strongly significant (Spearman’s correlation coefficient = 0.53–0.79, p < 0.01) correlations between bark and atmospheric particulate concentrations for C₈–C₁₂ PFCAs and 10:2 FTOH over 1–2 orders of magnitude, suggesting that the continues trapping of atmospheric particulates resulted in the accumulation of these compounds in bark. Overall, this study provides the first evidence that atmospheric particulate is an obvious source of C₈–C₁₂ PFCAs and 10:2 FTOH in tree bark. This result may further contribute to the application of tree bark as an indicator of certain PFASs in atmospheric particulate.