Air pollution can increase the risk of respiratory diseases, enhancing the susceptibility to viral and bacterial infections. Some studies suggest that small air particles facilitate the spread of viruses and also of the new coronavirus, besides the direct person-to-person contagion. However, the effects of the exposure to particulate matter and other contaminants on SARS-CoV-2 has been poorly explored. Here we examined the possible reasons why the new coronavirus differently impacted on Italian regional and provincial populations. With the help of artificial intelligence, we studied the importance of air pollution for mortality and positivity rates of the SARS-CoV-2 outbreak in Italy. We discovered that among several environmental, health, and socio-economic factors, air pollution and fine particulate matter (PM2.5), as its main component, resulted as the most important predictors of SARS-CoV-2 effects. We also found that the emissions from industries, farms, and road traffic - in order of importance - might be responsible for more than 70% of the deaths associated with SARS-CoV-2 nationwide. Given the major contribution played by air pollution (much more important than other health and socio-economic factors, as we discovered), we projected that, with an increase of 5–10% in air pollution, similar future pathogens may inflate the epidemic toll of Italy by 21–32% additional cases, whose 19–28% more positives and 4–14% more deaths. Our findings, demonstrating that fine-particulate (PM2.5) pollutant level is the most important factor to predict SARS-CoV-2 effects that would worsen even with a slight decrease of air quality, highlight that the imperative of productivity before health and environmental protection is, indeed, a short-term/small-minded resolution.

Artificial Light at Night (ALAN), which is the alteration of natural light levels as the result of anthropogenic light sources, has been acknowledged as an important factor that alters the functioning of marine ecosystems. Using LEDs light to mimic ALAN, we studied the effect on the physiology (symbiont and chlorophyll contents, photosynthesis, respiration, pigment profile, skeletal growth, and oxidative stress responses) of two scleractinian coral species originating from the Red Sea. ALAN induced the photoinhibition of symbiont photosynthesis, as well as an overproduction of reactive oxygen species (ROS) and an increase in oxidative damage to lipids in both coral species. The extent of the deleterious effects of ALAN on the symbiotic association and coral physiology was aligned with the severity of the oxidative stress condition experienced by the corals. The coral species Sylophora pistillata, which experienced a more severe oxidative stress condition than the other species tested, Turbinaria reniformis, also showed a more pronounced bleaching (loss of symbionts and chlorophyll content), enhanced photoinhibition and decreased photosynthetic rates. Findings of the present study further our knowledge on the biochemical mechanisms underpinning the deleterious impacts of ALAN on scleractinian corals, ultimately shedding light on the emerging threat of ALAN on coral reef ecology. Further, considering that global warming and light pollution will increase in the next few decades, future studies should be taken to elucidate the potential synergetic effects of ALAN and global climate change stressors.

Fulvic acid (FA) significantly influences the bioavailability and fate of heavy metals in environments, while its acid-base characters and metal binding processes are still unclear. Here, spectroscopic techniques combined with multiple models (e.g., NICA-Donnan model) and two-dimensional correlation spectroscopy (2D COS) were applied to explore the proton and copper binding properties of FA sub-fractions (FA3-FA13). The charge densities, average contents of carboxylic and phenolic groups, average dissociation constants pKa1 and pKa2 of sub-fractions ranged 0–16 meq∙g∙C−1, 5.03–9.58 meq∙g∙C−1, 2.52–4.67 meq∙g∙C−1, 4.15–4.33 and 8.52–9.72, respectively. FA sub-fractions had a relatively narrow distribution of carboxyl group and a broad distribution of phenolic group. FA sub-fractions also exhibited roughly two phenolic hydroxyl groups per every 1–3 phenyl rings. Differential absorbance spectra (DAS) derived Gaussian bands were associated to the inter-chromophore interactions, the changes of molecular conformations and functional groups with copper addition. Differential spectra slopes (DSlope275-295&325-375) were more significant with higher copper concentration and copper amounts bonded to carboxylic groups. UV–Vis and fluorescence spectra with 2D heterospectral COS revealed the copper binding heterogeneities and sequential orders of chromophores and fluorophores, quantitatively confirming by the order of conditional stability constants (log KCu: 4.64–5.56). Salicylic-/polyhydroxyphenolic, hydroxyl and amino groups were strongly associated to the basic units for fluorophores. Sequential changes followed the order of humic-like→fulvic-like materials for FA3/FA5, humic-like→fulvic-like→tryptophan-like materials for FA7, and humic-like→tryptophan-like→fulvic-like→tyrosine-like materials for FA9/FA13. Spectroscopic techniques combined with various models (especially for 2D COS) are beneficial to elucidate the binding heterogeneity and sensitivity for metal-organic matters at the functional group level.

Sludge from a groundwater treatment plant was used to prepare biochar by pyrolysis. The Fe–Mn rich biochar was used to activate percarbonate for the remediation of polycyclic aromatic hydrocarbons (PAHs) contaminated aquatic sediments. Results showed that the sludge–derived biochar (SBC) produced at a pyrolysis temperature of 700 °C was the most effective in activating percarbonate, which exhibited significant oxidative removal of PAHs. PAHs degradation took place via a Fenton-like oxidation manners, contributed from the Fe³⁺/Fe²⁺ and Mn³⁺/Mn²⁺ redox pairs, and achieved the highest degradation efficiency of 87% at pH₀ 6.0. Reactions between oxygenated functional groups of biochar and H₂O₂ generated of O₂•– and HO• radicals in abundance under neutral and alkaline pH was responsible for the catalytic degradation of PAHs. Our results provided new insights into the environmental applications of SBC for the green sustainable remediation of organics-contaminated sediments and aided in reduction of associated environmental and health risk.

Several populations of the amphipod, Hyalella azteca, have developed resistance to pyrethroid insecticides due to non-target exposure, but the dominance of the resistance trait is unknown. The current study investigated the dominance level of point mutations in natural populations of insecticide-resistant H. azteca and determined whether H. azteca from different clades with and without resistant alleles can hybridize and produce viable offspring. A parent generation (P₀) of non-resistant homozygous wild type H. azteca was crossbred with pyrethroid-resistant homozygous mutant animals and the tolerance of the filial 1 (F₁) generation to the pyrethroid insecticide, permethrin, was measured. Then the genotypes of the F₁ generation was examined to assure heterozygosity. The resistant parents had permethrin LC₅₀ values that ranged from 52 to 82 times higher than the non-resistant animals and both crossbreeding experiments produced heterozygous hybrid offspring that had LC₅₀ values similar to the non-resistant H. azteca parent. Dominance levels calculated for each of the crosses showed values close to 0, confirming that the L925I and L925V mutations were completely recessive. The lack of reproduction by hybrids of the C x D breeding confirmed that these clades are reproductively isolated and therefore introgression of adaptive alleles across these clades is unlikely. Potential evolutionary consequences of this selection include development of population bottlenecks, which may arise leading to fitness costs and reduced genetic diversity of H. azteca.

Organic contaminants are frequently detected in fresh crops and can cause severe damage to human health. To help control this risk, we introduce a diffusion-based model framework for estimating the removal efficiency for organic contaminants in fresh crops using a simple water soaking method. The framework was developed based on the diffusion coefficient of the organic contaminants, and its application indicates that the removal factor (RF) for organic contaminants has an inverse-exponential relationship with log Kₒw (Kₒw is the octanol-water partition coefficient), which thermodynamically restricts the removal efficiency for chemicals with large steady state log Kₒw. Additionally, the diffusion coefficient of the chemical in water affects the kinetic removal efficiency. For example, the RF simulated for glyphosate, which has a relatively high diffusion coefficient, is 0.592 (61.9% of the steady state RF) after soaking for 1 h, while the RF of lindane is 0.224, which is only 25.0% of the steady state RF. However, if a refreshing method is applied, the RF of lindane can be significantly improved even if more potatoes are used in the water bowl, and this has been demonstrated theoretically with the refreshing function. Model validation indicates that the macro properties of crops, e.g., the active area through which crop tissues interact with water, have a larger impact on the results than do the micro-properties of crops and the physiochemical properties of the organic contaminants. Comparison of our results with those of other studies shows that the simulated ranges for some pesticides compare well with experimental data collected using other household washing methods. However, for other pesticides such as HCB and DDT, the simulated results and current studies are inconsistent due to physical interactions between the water and crop tissues not considered in our model.

Exposure to chemicals produced by petrochemical industrial complexes (PICs), such as benzene, ionizing radiation, and particulate matters, may contribute to the development of leukemia. However, epidemiological studies showed controversial results. This systematic review and meta-analysis aimed to summarize the association between residential exposure to PICs and the risk of leukemia incidence, focusing on exposure-response effects. We searched PubMed, Embase, Web of Science, and Cochrane Library databases for studies published before September 1st, 2019. Observational studies investigating residential exposure to PICs and the risk of leukemia were included. The outcome of interest was the incidence of leukemia comparing to reference groups. Relative risk (RR) was used as the summary effect measure, synthesized by characteristics of populations, distance to PICs, and calendar time in meta-regression. We identified 7 observational studies, including 2322 leukemia cases and substantial reference groups, in this meta-analysis. Residential exposure to PICs within a maximal 8-km distance had a 36% increased risk of leukemia (pooled RR = 1.36, 95% CI = 1.14–1.62) compared to controls, regardless of sex and age. In terms of leukemia subtypes, residential exposure to PICs was associated with the risks of acute myeloid leukemia (AML, pooled RR = 1.61, 95% CI = 1.12–2.31) and chronic lymphocytic leukemia (CLL, pooled RR = 1.85, 95% CI = 1.11–6.42). In meta-regression, the positive association occurred after 10 years of follow-up with a pooled RRs of 1.21 (95% CI = 1.02–1.44) and then slightly increased to 1.77 (95% CI = 1.35–2.33) at 30 years after follow-up. No effect modification was found by sex, age, and geographic locations.

Liquefied petroleum gas (LPG) as an alternative fuel is increasingly used in mainland China, few reports are however available about emissions from LPG-fueled vehicles. In this study, 26 LPG-fueled taxis in Guangzhou, south China were tested using a chassis dynamometer to obtain their emission factors of nitrogen oxides (NOₓ) and volatile organic compounds (VOCs) under idle and cruising (10–60 km h⁻¹) modes. The emission factors of NOₓ on average increased with speed from 4.13 g kg-fuel⁻¹ at idling to 71.1 g kg-fuel⁻¹ at 60 km h⁻¹ at a slope of 10.6 g kg-fuel⁻¹ per 10 km h⁻¹ increase in speed. Alkanes were the most abundant (71.9%) among the VOCs in the exhaust, followed by alkenes (25.2%), ethyne (2.7%), and aromatic species (0.2%). Emission factors of VOCs at idling averaged 8.24 g kg-fuel⁻¹, higher than that of 6.23–7.36 g kg-fuel⁻¹ when cruising at 10–60 km h⁻¹, but their ozone formation potentials (OFPs) were lower at idling (15.8 g kg-fuel⁻¹) than under cruising (19.1–23.8 g kg-fuel⁻¹) largely due to higher emission of more reactive alkenes under cruising mode. Emissions of both NOx and VOCs increased significantly with mileages. Measured emission factors of NOₓ and reactive VOCs in this study suggested that replacing the gasoline-powered taxis with the LPG-fueled taxis with LPG-gasoline bi-fuel engines and no efficient after-treatment devices would not benefit in reducing the emissions of ozone precursors, and strengthening the emission control for LPG vehicles with dedicated LPG engines and after-treatment converters, as did in Hong Kong, could further benefit in reducing the emission of photochemically active species when using LPG as alternative fuels.

The surface organic horizons in forest soils have been affected by air and soil pollutants, including potentially toxic elements (PTEs). Monitoring of PTEs requires a large number of samples and adequate analysis. Visible–near infrared (vis–NIR: 350–2500 nm) spectroscopy provides an alternative method to conventional laboratory measurements, which are time-consuming and expensive. However, vis–NIR spectroscopy relies on an empirical calibration of the target attribute to the spectra. This study examined the capability of vis–NIR spectra coupled with machine learning (ML) techniques (partial least squares regression (PLSR), support vector machine regression (SVMR), and random forest (RF)) and a deep learning (DL) approach called fully connected neural network (FNN) to assess selected PTEs (Cr, Cu, Pb, Zn, and Al) in forest organic horizons. The dataset consists of 2160 samples from 1080 sites in the forests over all the Czech Republic. At each site, we collected two samples from the fragmented (F) and humus (H) organic layers. The content of all PTEs was higher in horizon H compared to F horizon. Our results indicate that the reflectance of samples tended to decrease with increased PTEs concentration. Cr was the most accurately predicted element, regardless of the algorithm used. SVMR provided the best results for assessing the H horizon (R² = 0.88 and RMSE = 3.01 mg/kg for Cr). FNN produced the best predictions of Cr in the combined F + H layers (R² = 0.89 and RMSE = 2.95 mg/kg) possibly due to the larger number of samples. In the F horizon, the PTEs were not predicted adequately. The study shows that PTEs in forest soils of the Czech Republic can be accurately estimated with vis–NIR spectra and ML approaches. Results hint in availability of a large sample size, FNN provides better results.

A total of 74 high volume air samples were collected at a background site in Czech Republic from 2012 to 2014 in which the concentrations of 20 per- and polyfluoroalkyl substances (PFASs) were investigated. The total concentrations (gas + particle phase) ranged from 0.03 to 2.08 pg m⁻³ (average 0.52 pg m⁻³) for the sum of perfluoroalkyl carboxylic acids (∑PFCAs), from 0.02 to 0.85 pg m⁻³ (average 0.28 pg m⁻³) for the sum of perfluoroalkyl sulfonates (ΣPFSAs) and from below detection to 0.18 pg m⁻³ (average 0.05 pg m⁻³) for the sum of perfluorooctane sulfonamides and sulfonamidoethanols (ΣFOSA/Es). The gas phase concentrations of most PFASs were not controlled by temperature dependent sources but rather by long-range atmospheric transport. Air mass backward trajectory analysis showed that the highest concentrations of PFASs were mainly originating from continental areas. The average particle fractions (θ) of ΣPFCAs (θ = 0.74 ± 0.26) and ΣPFSAs (θ = 0.78 ± 0.22) were higher compared to ΣFOSA/Es (θ = 0.31 ± 0.35). However, they may be subject to sampling artefacts. This is the first study ever reporting PFASs concentrations in air samples collected over consecutive years. Significant decreases in 2012–2014 for PFOA, MeFOSE, EtFOSE and ∑PFCAs were observed with apparent half-lives of 1.01, 0.86, 0.92 and 1.94 years, respectively.