Much has happened in the pollution field since 1982 when the first edition of this work was written. This edition includes new subject areas such as radioactive pollution and chemistry and pollution of the stratosphere.

The adverse health effects associated with the inhalation and ingestion of naturally occurring radon gas produced during the uranium decay chain mean that there is a need to identify high-risk areas. This study detected radon-prone areas using a geographic information system (GIS)-based probabilistic and machine learning methods, including the frequency ratio (FR) model and a convolutional neural network (CNN). Ten influencing factors, namely elevation, slope, the topographic wetness index (TWI), valley depth, fault density, lithology, and the average soil copper (Cu), calcium oxide (Cao), ferric oxide (Fe₂O₃), and lead (Pb) concentrations, were analyzed. In total, 27 rock samples with high activity concentration index values were divided randomly into training and validation datasets (70:30 ratio) to train the models. Areas were categorized as very high, high, moderate, low, and very low radon areas. According to the models, approximately 40% of the study area was classified as very high or high risk. Finally, the radon potential maps were validated using the area under the receiver operating characteristic curve (AUC) analysis. This showed that the CNN algorithm was superior to the FR method; for the former, AUC values of 0.844 and 0.840 were obtained using the training and validation datasets, respectively. However, both algorithms had high predictive power. Slope, lithology, and TWI were the best predictors of radon-affected areas. These results provide new information regarding the spatial distribution of radon, and could inform the development of new residential areas. Radon screening is important to reduce public exposure to high levels of naturally occurring radiation.

Bacterial communities in antimony (Sb) polluted soils have been well addressed, whereas the important players fungal communities are far less studied to date. Here, we report different responses of bacterial and fungal communities to Sb contamination and the ecological processes controlling their community assembly. Soil samples in the Xikuangshan mining area were collected and subjected to high through-put sequencing of 16S rRNA and ITS1 to investigate bacterial and fungal communities, respectively, along an Sb gradient. Sb speciation in the soil samples and other physicochemical parameters were analyzed as well. Bacterial communities were dominated by Deltaproteobacteria in the soil with highest Sb concentration, whereas Chloroflexi were dominant in the soil with lowest Sb concentration. Fungal communities in high-Sb soils were predominated by unclassified Fungi, whilst Leotiomycetes were dominant in low-Sb soil samples. Multivariate analysis indicated that Sb, pH and soil texture were the main drivers to strongly impact microbial communities. We further identified Sb-resistant microbial groups via correlation analysis. In total, 18 bacterial amplicon sequence variants (ASVs) were found to potentially involve in biogeochemical cycles such as Sb oxidation, sulfur oxidation or nitrate reduction, whereas 12 fungal ASVs were singled out for potential heavy metal resistance and plant growth promotion. Community assembly analysis revealed that variable selection contributed 100% to bacterial community assembly under acidic or high Sb concentration conditions, whereas homogeneous selection dominated fungal community assembly with a contribution over 78.9%. The community assembly of Sb-resistant microorganisms was mainly controlled by stochastic process. The results offer new insights into microbial ecology in Sb-contaminated soils, especially on the different responses of microbial communities under identical environmental stress and the different ecological processes underlining bacterial and fungal community assembly.

Particulate-filtering respirators (PFRs) have been recommended as a practical personal-level intervention to protect individuals from the health effects of particulate matter exposure. However, the cardiovascular benefits of PFRs including improvements in key surrogate endpoints remain unclear. We performed a systematic review and meta-analysis of randomized studies (wearing versus not wearing PFRs) reporting the effects on blood pressure (BP) and heart rate variability (HRV). The search was performed on January 3, 2022 to identify published papers until this date. We queried three English databases, including PubMed, Web of Science Core Collection and Scopus. Of 527 articles identified, eight trials enrolling 312 participants (mean age ± standard deviation: 36 ± 19.8; 132 female) met our inclusion criteria for analyses. Study participants wore PFRs from 2 to 48 h during intervention periods. Wearing PFRs was associated with a non-significant pooled mean difference of −0.78 mmHg (95% confidence interval [CI]: −2.06, 0.50) and −0.49 mmHg (95%CI: −1.37, 0.38) in systolic and diastolic BP (SBP and DBP). There was a marginally significant reduction of mean arterial pressure (MAP) by nearly 1.1 mmHg (95%CI: −2.13, 0.01). The use of PFRs was associated with a significant increase of 38.92 ms² (95%CI: 1.07, 76.77) in pooled mean high frequency (power in the high frequency band (0.15–0.4 Hz)) and a reduction in the low (power in the low frequency band (0.04–0.15Hz))-to-high frequency ratio [−0.14 (95%CI: −0.27, 0.00)]. Other HRV indices were not significantly changed. Our meta-analysis demonstrates modest or non-significant improvements in BP and many HRV parameters from wearing PFRs over brief periods. However, these findings are limited by the small number of trials as well as variations in experimental designs and durations. Given the mounting global public health threat posed by air pollution, larger-scale trials are warranted to elucidate more conclusively the potential health benefits of PFRs.

Several studies have reported an association between residential surrounding particulate matter with an aerodynamic diameter ≤2.5 μm (PM₂.₅) and coronary heart disease (CHD). However, the underlying biological mechanism remains unclear. To fill this research gap, this study enrolled a residentially stable sample of 942 patients with CHD and 1723 controls. PM₂.₅ concentration was obtained from satellite-based annual global PM₂.₅ estimates for the period 1998–2019. MicroRNA microarray and pathway analysis of target genes was performed to elucidate the potential biological mechanism by which PM₂.₅ increases CHD risk. The results showed that individuals exposed to high PM₂.₅ concentrations had higher risks of CHD than those exposed to low PM₂.₅ concentrations (odds ratio = 1.22, 95% confidence interval: 1.00, 1.47 per 10 μg/m³ increase in PM₂.₅). Systolic blood pressure mediated 6.6% of the association between PM₂.₅ and CHD. PM₂.₅ and miR-4726-5p had an interaction effect on CHD development. Bioinformatic analysis demonstrated that miR-4726-5p may affect the occurrence of CHD by regulating the function of RhoA. Therefore, individuals in areas with high PM₂.₅ exposure and relative miR-4726-5p expression have a higher risk of CHD than their counterparts because of the interaction effect of PM₂.₅ and miR-4726-5p on blood pressure.

Groundwater nitrate (NO₃⁻) pollution is a worldwide environmental problem. Therefore, identification and partitioning of its potential sources are of great importance for effective control of groundwater quality. The current study was carried out to identify the potential sources of groundwater NO₃⁻ pollution and determine their apportionment in different land use/land cover (LULC) types in a traditional agricultural area, Weining Plain, in Northwest China. Multiple hydrochemical indices, as well as dual NO₃⁻ isotopes (δ¹⁵N–NO₃ and δ¹⁸O–NO₃), were used to investigate the groundwater quality and its influencing factors. LULC patterns of the study area were first determined by interpreting remote sensing image data collected from the Sentinel-2 satellite, then the Bayesian stable isotope mixing model (MixSIAR) was used to estimate proportional contributions of the potential sources to groundwater NO₃⁻ concentrations. Groundwater quality in the study area was influenced by both natural and anthropogenic factors, with anthropological impact being more important. The results of LULC revealed that the irrigated land is the dominant LULC type in the plain, covering an area of 576.6 km² (57.18% of the total surface study area of the plain). On the other hand, the results of the NO₃⁻ isotopes suggested that manure and sewage (M&S), as well as soil nitrogen (SN), were the major contributors to groundwater NO₃⁻. Moreover, the results obtained from the MixSIAR model showed that the mean proportional contributions of M&S to groundwater NO₃⁻ were 55.5, 43.4, 21.4, and 78.7% in the forest, irrigated, paddy, and urban lands, respectively. While SN showed mean proportional contributions of 29.9, 43.4, 61.5, and 12.7% in the forest, irrigated, paddy, and urban lands, respectively. The current study provides valuable information for local authorities to support sustainable groundwater management in the study region.

Corrosion is an environmental and economic global problem. “Smart” or stimuli-responsive colorimetric nanosensors for maritime coatings have been proposed as an asset to overcome the limitations of the current monitoring techniques by changing color in the presence of triggers associated with the early stages of corrosion. Layered double hydroxides (Zn–Al LDH; Mg–Al LDH) and silica mesoporous nanocapsules (SiNC) were used as precursor nanocarriers of active compounds: hexacyanoferrate ions ([Fe(CN)₆]³⁻) and phenolphthalein (PhPh), respectively. Additionally, the safer-by-design principles were employed to optimize the nanosensors in an eco-friendly perspective (e.g., regular vs. warm-washed SiNC-PhPh; immobilization using different carriers: Zn–Al LDH-[Fe(CN)₆]³⁻ vs. Mg–Al LDH-[Fe(CN)₆]³⁻). Therefore, the present study aims to assess the environmental behavior in saltwater and the toxic effects of the nanosensors, their nanocarriers, and the active compounds on the marine microalgae Tetraselmis chuii and the crustacean Artemia salina. Briefly, tested compounds exhibited no acute toxic effects towards A. salina (NOEC = 100 mg/L), apart from SiNC-PhPh (LC₅₀ = 2.96 mg/L) while tested active compounds and nanosensors caused significant growth inhibition on T. chuii (lowest IC₅₀ = 0.40 mg/L for SiNC-PhPh). The effects of [Fe(CN)₆]³⁻ were similar regardless of the nanocarrier choice. Regarding SiNC-PhPh, its toxicity can be decreased at least twice by simply reinforcing the nanocapsules washing, which contributes to the removal (at least partially) of the surfactants residues. Thus, implementing safe-by-design strategies in the early stages of research proved to be critical, although further progress is still needed towards the development of truly eco-friendly nanosensors.

Phenanthrene (PHE) is widely distributed, and it can cause genotoxicity in humans by interacting with enzymes in the body. A current challenge for PHE bioremediation is the inhibitory effect of biotoxic intermediates on bacterial growth. Notably, the aerobic biotransformation processes for PHE in the presence of sophorolipids have been poorly studied. Here, a PHE-degrading strain was isolated from sediments and identified as Pseudomonas stutzeri and named LSH-PAH1. It was observed that 1-naphthol (a biotoxic substance that can inhibit strain growth) was produced during the PHE metabolism process of LSH-PAH1. The biodegradation ratio increased from 21.4% to 91.7% within 48 h after the addition of sophorolipids. Unexpectedly, this addition accelerated the metabolic process for 1-naphthol rather than causing its accumulation. The cometabolism of 1-naphthol and sophorolipids alleviated the biotoxic effects for the strain, which was verified by gene expression analysis. We identified a new PHE-degrading strain and provided a mechanism for PHE biodegradation using LSH-PAH1 with the addition of sophorolipids, which provides a reference for practical applications of the bioremediation of PHE and study of the cometabolism of biotoxic intermediates.