Particulate matter from wood burning emissions (Cwₒₒd) was quantified at five locations in the United Kingdom (UK), comprising three rural and two urban sites between 2009 and 2021. The aethalometer method was used. Mean winter Cwₒₒd concentrations ranged from 0.26 μg m⁻³ (in rural Scotland) to 1.30 μg m⁻³ (London), which represented on average 4% (in rural environments) and 5% (urban) of PM₁₀ concentrations; and 8% of PM₂.₅. Concentrations were greatest in the evenings in winter months, with larger evening concentrations in the weekends at the urban sites. Random-forest (RF) machine learning regression models were used to reconstruct Cwₒₒd concentrations using both meteorological and temporal explanatory variables at each site. The partial dependency plots indicated that temperature and wind speed were the meteorological variables explaining the greatest variability in Cwₒₒd, with larger concentrations during cold and calm conditions. Peaks of Cwₒₒd concentrations took place during and after events that are celebrated with bonfires. These were Guy Fawkes events in the urban areas and on New Year's Day at the rural sites; the later probably related to long-range transport. Time series were built using the RF. Having removed weather influences, long-term trends of Cwₒₒd were estimated using the Theil Sen method. Trends for 2015–2021 were downward at three of the locations (London, Glasgow and rural Scotland), with rates ranging from −5.5% year⁻¹ to −2.5% year⁻¹. The replacement of old fireplaces with lower emission wood stoves might explain the decrease in Cwₒₒd especially at the urban sites The two rural sites in England observed positive trends for the same period but this was not statistically significant.

Radioiodine is one of the long-lived fission products and also an important radionuclide released during nuclear accidents, which generates interest in its environmental fate. Its sorption has been studied in a wide range of materials, but no equivalent study exists for microplastics, an emerging environmental vector. Weathering and biofilm formation on microplastics can enhance radioiodine sorption. For the first time, we're reporting how radioiodine interacts with different types of polyethylene derived microplastics (pristine, irradiated, and biofilm developed microplastics). This study revealed that exposure to radiation and the marine environment significantly alters the physico-chemical properties of microplastics. In particular, in marine-exposed samples, a signature of biofilm development was detected. Speciation study indicates that iodine exists in the iodide form in the studied marine environment. The study revealed that, iodide ions attach to biofilm-developed microplastics via electrostatic, ion-dipole, pore filling, and van der Waals interactions. Pore filling, ion-dipole, and van der Waals interactions may cause iodide binding to irradiated microplastics, whereas pore-filling and van der Waals interactions cause iodide binding to pristine microplastics. The distribution coefficient (Kd) of iodine on microplastics is positively correlated with biofilm biomass, which signifies the role of biofilm in radioiodine uptake. The Kd indicates microplastics are potential iodide accumulators and could be a possible vector in the marine system.

Air pollution is a leading public health concern around the world. Assessing the public's knowledge about air quality is critical to calibrate public health interventions. However, previous efforts to measure knowledge about air quality (AQIQ) have not relied on consistent and validated measures, thus precluding cross-country comparisons. We aimed to develop a robust scale to assess AQIQ and tested it in multiple countries. To evaluate the psychometric properties and select the best performing items out of 10 AQIQ questions, we used methods from classical test theory and item response theory. We evaluated the scales using several scalability measures, including the Kuder-Richardson Formula 20 (KR-20), Loevinger's H, as well as trace lines. Volunteers from the United States (US, n = 400), India (n = 403), and China (n = 443) were recruited to validate the scale. Multiple linear regression was used to estimate the association between demographic factors and AQIQ. We found that participants from India had the highest AQIQ. In addition, not all questions performed well in each country. The scale was pruned and shorter subscales were validated. In the US, we obtained a 4-item scale (KR20 = 0.53, Loevinger's H = 0.34). In India, we obtained a 6-item scale (KR20 = 0.56; Loevinger's H = 0.48 for just 2 items). In China, we obtained a 5-item scale (KR20 = 0.39; Loevinger's H = 0.41 for just 2 items). Compared to the 10-item scale, the pruned scales showed stronger associations between measures of socioeconomic status and AQIQ. The results were robust to the scale used. Overall, general knowledge questions measured AQIQ more effectively in the US and India whereas knowledge of the air quality index better measured AQIQ in China. The findings suggest that careful measurement and validation are essential to develop knowledge scales for use in public health and environmental research.

Sea fish contain omega-3 polyunsaturated fatty acids (omega-3 PUFAs) which have been found to reduce triglyceride (TG) levels. However, sea fish may contain pollutants such as mercury which cause oxidative stress and increase TG levels. Therefore, the relationship between sea fish and TG remains unclear. We aimed to explore whether blood mercury (BHg) can affect the effect of sea fish consumption frequency on TG level among Chinese adults. A total of 10,780 participants were included in this study. BHg levels were measured using inductively coupled plasma mass spectrometry (ICP-MS). The associations of sea fish consumption frequency with BHg and TG levels as well as the association of BHg with TG levels were evaluated using multiple linear regression. Causal mediation analysis was used to evaluate the mediation effect of BHg levels on the association of sea fish consumption frequency with TG levels. The frequency of sea fish consumption showed a negative association with TG level. Compared with the participants who never ate sea fish, the TG level decreased by 0.193 mmol/L in those who ate sea fish once a week or more [β (95%CI): −0.193 (−0.370, −0.015)]. Significant positive associations were observed of BHg with TG levels. With one unit increase of log2-transformed BHg, the change of TG level was 0.030 mmol/L [0.030 (0.009, 0.051)]. The association between sea fish consumption and TG was mediated by log2-transformed BHg [total effect = −0.037 (−0.074, −0.001); indirect effect = 0.009 (0.004, 0.015)], and the proportion mediated by log2-transformed BHg was 24.25%. BHg may reduce the beneficial effect of sea fish consumption frequency on TG levels among Chinese adults. Overall, sea fish consumption has more benefits than harms to TG.

Rapid economic growth, industrialization, and urbanization have caused frequent air pollution events in East Asia over the last few decades. Recently, aerosol data from geostationary satellite sensors have been used to monitor ground-level particulate matter (PM) concentrations hourly. However, many studies have focused on using historical datasets to develop PM estimation models, often decreasing their predictability for unseen data in new days. To mitigate this problem, this study proposes a novel real-time learning (RTL) approach to estimate PM with aerodynamic diameters of <10 μm (PM₁₀) and <2.5 μm (PM₂.₅) using hourly aerosol data from the Geostationary Ocean Color Imager (GOCI) and numerical model outputs for daytime conditions over Northeast Asia. Three schemes with different weighting strategies were evaluated using 10-fold cross-validation (CV). The RTL models, which considered both concentration and time as weighting factors (i.e., Scheme 3) yielded consistent improvement for 10-fold CV performance on both hourly and monthly scales. The real-time calibration results for PM₁₀ and PM₂.₅ were R² = 0.97 and 0.96, and relative root mean square error (rRMSE) = 12.1% and 12.0%, respectively, and the 10-fold CV results for PM₁₀ and PM₂.₅ were R² = 0.73 and 0.69 and rRMSE = 41.8% and 39.6%, respectively. These results were superior to results from the offline models in previous studies, which were based on historical data on an hourly scale. Moreover, we estimated PM concentrations in the ocean without using land-based variables, and clearly demonstrated the PM transport over time. Because the proposed models are based on the RTL approach, the density of in-situ monitoring sites could be a major uncertainty factor. This study identified that a high error occurred in low-density areas, whereas a low error occurred in high-density areas. The proposed approach can be operated to monitor ground-level PM concentrations in real-time with uncertainty analysis to ensure optimal results.

Global warming is drastically altering the climate conditions of our planet. Soils will be among the most affected components of terrestrial ecosystems, especially in contaminated areas. In this study we investigated if changes in climate conditions (air temperature and soil moisture) affect the toxicity of historically metal(loid)-contaminated soils to the invertebrate Folsomia candida, followed by an assessment of its recovery capacity. Ecotoxicity tests (assessing survival, reproduction) were performed in field soils affected by metal(loid)s under different climate scenarios, simulated by individually changing air temperature or soil moisture conditions. The scenarios tested were: standard conditions (20°C + 50% soil water holding capacity-WHC); increased air temperature (daily fluctuation of 20–30°C + 50% WHC); soil drought (20°C + 25% WHC); soil flood (20°C + 75% WHC). Recovery potential was assessed under standard conditions in clean soil. Increased temperature was the major climate condition negatively affecting collembolans performance (decreased survival and reproduction), regardless of metal(loid) contamination. Drought and flood conditions presented less pronounced effects. When it was possible to move to the recovery phase (enough juveniles in exposure phase), F. candida was apparently able to recover from the exposure to metal(loid) contamination and/or climate alterations. The present study showed that forecasted climate alterations in areas already affected by contamination should be considered to improve environmental risk assessment.

While evidence indicates that groundwater is a potential source for greenhouse gas (GHG) emissions, information for such emissions in groundwater used for irrigation is lacking. Based on 23 wells in the mid-western Guanzhong Basin of China, we investigated the dissolved CO₂, N₂O, and CH₄ distributions in groundwater, their relationships with water indicators, and emission fluxes during flood irrigation. We found zero methane, but CO₂ and N₂O were 30 and 25 times, respectively, supersaturated compared to atmospheric concentrations. Dissolved N₂O in groundwater was positively correlated with NO₃⁻-N (P = 0.009), while CO₂ depended mainly on low pH and high dissolved inorganic carbon. The CO₂ and N₂O emission fluxes detected in wellheads, especially in shallow wells, implied potential emissions. Flood irrigation experiments showed that 24.55% of dissolved CO₂ and 36.81% of dissolved N₂O in groundwater was degassed immediately (within 12 min of irrigation) to the atmosphere. Our study demonstrates that direct GHG emissions from groundwater used for agricultural irrigation in the Guanzhong Basin are potentially equivalent to about 2–4% of the GHG emissions from 3 years of fertilizer use on these farmlands, so further research should focus on optimizing irrigation strategies to mitigate GHG emissions.

Dismantling and recycling e-waste has been recognized as a potential emission source of rare earth elements (REEs). However, the presence of REEs in typical regional soils has yet to be studied. Given the potential health implications of such soil contamination, it is vital to study the characteristics, spatial distribution, and pollution level of REEs caused by e-waste dismantling as well as determine the influencing mechanism. This study focused on Guiyu Town as an example site, which is a typical e-waste dismantling base. From the site, 39 topsoil samples of different types were collected according to grid distribution points. Soil profiles were also collected in the dismantling and non-dismantling areas. The REE characteristic parameters showed that the REE distribution was abnormal and was affected by multiple factors. The results of the integrated pollution index showed that approximately 61.5% of soil samples were considered to be lightly polluted. Spatial distribution and correlation analysis showed that hot spots of REE-polluted soil coincided with known, main pollution sources. Moreover, there was a significant negative correlation (p ≤0.05) between the REE concentration and the distance from the pollution source. E-waste disassembly and recycling greatly affect the physical and chemical properties of the surrounding soil as well as downward migration areas. In the disassembly area, REE accumulated more easily in the surface layer (0–20 cm). Geographical detector results showed that distance factor was the main contribution factor for both light rare earth elements (LREE) and heavy rare earth element (HREE) (q = 34.59% and 53.33%, respectively). REE distribution in soil was nonlinear enhanced by different factors. Taken together, these results showed that e-waste disassembling and recycling not only directly affected the spatial distribution of REEs, but that their distribution was also affected by land use type and soil properties.

Long-term exposure to PM₂.₅ has been linked to lung cancer incidence and mortality, but limited evidence existed for other cancers. This study aimed to assess the association between PM₂.₅ on cancer specific mortality. An ecological study based on the cancer mortality data collected from 5,565 Brazilian cities during 2010–2018 using a difference-in-differences approach with quasi-Poisson regression, was applied to examine PM₂.₅-cancer mortality associations. Globally gridded annual average surface PM₂.₅ concentration was extracted and linked with the residential municipality of participants in this study. Sex, age stratified and exposure-response estimations were also conducted. Totalling 1,768,668 adult cancer deaths records of about 208 million population living across 5,565 municipalities were included in this study. The average PM₂.₅ concentration was 7.63 μg/m³ (standard deviation 3.32) with range from 2.95 μg/m³ to 28.5 μg/m³. With each 10 μg/m³ increase in three-year-average (current year and previous two years) concentrations of PM₂.₅, the relative risks (RR) of cancer mortality were 1.16 (95% confidence interval [CI]: 1.11–1.20) for all-site cancers. The PM₂.₅ exposure was significantly associated with several cancer-specific mortalities including oral, nasopharynx, oesophagus, and stomach, colon rectum, liver, gallbladder, larynx, lung, bone, skin, female breast, cervix, prostate, brain and leukaemia. No safe level of PM₂.₅ exposure was observed in the exposure-response curve for all types of cancer. In conclusion, with nationwide cancer death records in Brazil, we found that long-term exposure to ambient PM₂.₅ increased risks of mortality for many cancer types. Even low level PM₂.₅ concentrations had significant impacts on cancer mortality.