Little is known about how forests adjust their gas-exchange mode while atmospheric CO₂ rises globally and air quality changes regionally. The present study aims at addressing this research gap for boreal spruce trees growing in three different regions of Canada, submitted to distinct levels of atmospheric emissions, by examining the amount of carbon gained per unit of water lost in trees, i.e., the intrinsic water use efficiency (iWUE).Under pristine air quality conditions, middle-to long-term trends passed from no-reaction mode to passive strategies due to atmospheric CO₂, and short-term iWUE variations mostly ensue from year-to-year climatic conditions. In contrast, in trees exposed to pollutants from a copper smelter and an oil-sands mining region, air quality deterioration generated swift, long-term iWUE rises immediately at the onset of operations. In this case, the very active foliar strategy sharply reduced the intra-foliar CO₂ (Ci) pressure. Statistical modeling allowed identifying emissions as the main trigger for the iWUE swift shifts; subsequent combined effects of emissions and rising CO₂ led to passive foliar modes in the recent decades, and short-term variations due to climatic conditions appeared all along the series.Overall, boreal trees under different regional conditions modified their foliar strategies mostly without changing their stem growth. These findings underline the potential of acidifying emissions for prompting major iWUE increases due to lowering the stomatal apertures in leaves, and the combined influence of rising CO₂ in modulating other foliar responses. A fallout of this research is that degrading air quality may create true divergences in the relationship between tree-ring isotopes and climatic conditions, an impact to consider prior to using isotopic series for paleo-climatic modeling.

Environmental exposure to arsenic is a major public health challenge worldwide. In detailing the hallmark signs of chronic arsenic exposure, previous studies have shown that epigenetic and immune dysfunction are associated with arsenic-induced skin lesions; however, knowledge regarding interactions between the mechanisms listed above is limited. In this study, a total of 106 skin samples were collected over the past 20 years. Based on the presence or absence of high arsenic exposure, the participants were divided into arsenic exposure (72) and reference (34) groups. Additionally, the arsenic exposure group was further divided into the non-cancer group (31, including skin hyperpigmentation and hyperkeratosis) and the skin cancer group (41, including Bowen’s disease, basal cell carcinoma and squamous cell carcinoma) according to a skin histopathological examination. First, the associations among miR-155, NF-AT1 with immunological dysfunction and arsenic-induced skin lesions and carcinogenesis were confirmed using these skin samples. In the arsenic-exposed group, miR-155–5p, keratin 1(Krt1), keratin 10 (Krt10), and keratin 6c (Krt6c) were significantly increased in the skin (p < 0.05), while NF-AT1, interleukin-2 (IL-2), and interferon-γ (IFN-γ) were significantly decreased (p < 0.05). Clear correlations were observed among these factors (p < 0.05). In immortalized human keratinocytes, silencing and overexpression of NF-AT1 could alter the expression and secretion of immunological dysfunction indicators (IL-2 and IFN-γ) that are induced by arsenic exposure (p < 0.05); however, miR-155–5p levels did not change significantly (p > 0.05). The miR-155–5p mimic and inhibitor could regulate the NF-AT1-mediated immunological dysfunction caused by arsenic (p < 0.05). Our study provides some limited evidence that miR-155–5p regulates the NF-AT1-mediated immunological dysfunction that is involved in the pathogenesis and carcinogenesis of arsenic. The second major finding was that Krt1 and Krt10 are markers of hyperkeratosis caused by arsenic, and Krt6c is a potential biomarker that can reflect arsenic carcinogenesis.

Spatiotemporal variations in PM₂.₅ are a key factor affecting personal pollution exposure levels in urban areas. However, fixed-site monitoring stations are so sparsely distributed that they hardly capture the dynamic and fine-scale variations in PM₂.₅ in urban areas with complex geographical features and urban forms. Recently, a distributed air sensor network (DASN) was deployed in Dezhou city, China, to monitor fine-scale air pollution information and obtain deep insight into variations in PM₂.₅. Based on the data collected by the DASN, this paper investigated the spatiotemporal patterns of PM₂.₅ using the time-series clustering method. The results demonstrated that there were four stages of PM₂.₅ daily variations, i.e., accumulation, continuous pollution, dispersion, and cleaning. Generally, the stage of dispersion occurred more rapidly than the stage of accumulation, and PM₂.₅ accumulated easily in warm and humid weather with low wind speeds. However, the stage of dispersion was affected mainly by high wind speeds and precipitation. Additionally, the results suggested that four variation stages did not strictly correspond to seasonal divisions. The spatial distributions of PM₂.₅ revealed that the main pollution source was located in a southeastern industrial park, which exhibited a significant impact throughout the four stages. Considering both the temporal and spatial characteristics of PM₂.₅, this study successfully identified pollution hotspots and confirmed the effect of industrial parks. The study demonstrates that the DASN has high prospective applicability for assessing the fine-scale spatial distribution of PM₂.₅, and the time-series clustering method can also assist environmental researchers in further exploring the spatiotemporal characteristics of urban air pollution.

Human factors/errors (such as inappropriate actions by operators and unsafe supervision by organizations) are a primary cause of oil spill incidents. To investigate the influences of active operational failures and unsafe latent factors in offshore oil spill accidents, an integrated human factor analysis and decision support process has been developed. The system is comprised of a Human Factors Analysis and Classification System (HFACS) framework to qualitatively evaluate the influence of various factors and errors associated with the multiple operational stages considered for oil spill preparedness and response (e.g., oil spill occurrence, spill monitoring, decision making/contingency planning, and spill response); coupled with quantitative data analysis by Fuzzy Set Theory and the Technique for Order Preference by Similarity to Ideal Solution (Fuzzy-TOPSIS) to enhance decision making during response operations. The efficiency of the integrated human factor analysis and decision support system is tested with data from a case study to generate a comprehensive priority rank, a robust sensitivity analysis, and other theoretical/practical insights. The proposed approach improves our knowledge on the significance of human factors/errors on oil spill accidents and response operations; and provides an improved support tool for decision making.

Natural halloysite nanotubes (HNTs) with a hollow lumen are already applied in numerous fields and enter the environment in increasing quantities, which may have effects on animal and human health. However their in vivo toxicity in mammals is still largely unclear. The aim of this study is to assess acute oral toxicity of HNTs in the stomach of mice and recovery. Oral HNTs at low dose (5 mg HNTs/kg BW) for 30 days increased in daily food and water intake and promoted mouse growth with no obvious adverse effect on the stomach. The promotive effect on mouse growth disappeared after cessation of oral administration of the nanotubes. Oral HNTs for 30 days at high dose (50 mg HNTs/kg BW) induced Si and Al accumulation in the stomach, which caused oxidative stress, inflammation and iNOS-mediated damage in the organ. The damage in the stomach led to slight atrophic gastritis and reduced mouse growth. Oral HNTs-induced changes at high dose were not observed after a 30-days recovery period. The findings provided the evidence that oral HNTs-induced acute toxicity in the stomach was reversible. More importantly, this research showed that Al and Si were cleared out of the mice by hepatic excretion and renal excretion, respectively, during the recovery period. The results suggest that HNTs at low concentration in environments have no adverse effect on mice, while there are health risks to mice under severe contamination by HNTs.

Rapid urbanization and industrialization in China stimulated the great increase of energy consumption, which leads to drastic rise in the emission of anthropogenic waste heat. Anthropogenic heat emission (AHE) is a crucial component of urban energy budget and has direct implications for investigating urban climate and environment. However, reliable and accurate representation of AHE across China is still lacking. This study presented a new machine learning-based top–down approach to generate a gridded anthropogenic heat flux (AHF) benchmark dataset at 1 km spatial resolution for China in 2010. Cubist models were constructed by fusing points-of-interest (POI) data of varying categories and multisource remote sensing data to explore the nonlinear relationships between various geographic predictors and AHE from different heat sources. The strategy of developing specific models for different components and exploiting the complementary features of POIs and remote sensing data generated a more reasonable distribution of AHF. Results showed that the AHF values in urban centers of metropolises over China range from 60 to 190 W m⁻². The highest AHF values were observed in some heavy industrial zones with value up to 415 W m⁻². Compared with previous studies, the spatial distribution of AHF from different heating components was effectively distinguished, which highlights the potential of POI data in improving the precision of AHF mapping. The gridded AHF dataset can serve as input of urban numerical models and can help decision makers in targeting extreme heat sources and polluters in cities and making differentiated and tailored strategies for emission mitigation.

Thallium (Tl) is a dispersed trace metal showing remarkable toxicity. Various anthropogenic activities may generate Tl contamination in river sediments, posing tremendous risks to aquatic life and human health. This paper aimed to provide insight into the vertical distribution, risk assessment and source tracing of Tl and other potentially toxic elements (PTEs) (lead, cadmium, zinc and copper) in three representative sediment cores from a riverine catchment impacted by multiple anthropogenic activities (such as steel-making and Pb–Zn smelting). The results showed high accumulations of Tl combined with associated PTEs in the depth profiles. Calculations according to three risk assessment methods by enrichment factor (EF), geoaccumulation index (Igₑₒ) and the potential ecological risk index (PERI) all indicated a significant contamination by Tl in all the sediments. Furthermore, lead isotopes were analyzed to fingerprint the contamination sources and to calculate their quantitative contributions to the sediments using the IsoSource software. The results indicated that a steel-making plant was the most important contamination source (∼56%), followed by a Pb–Zn smelter (∼20%). The natural parental bedrock was found to contribute ∼24%. The findings highlight the importance of including multiple anthropogenic sources for quantitative fingerprinting of Tl and related metals by the lead isotopic approach in complicated environmental systems.

Distinct cropland acidification has been reported in China due to nitrogen (N) fertilizer overuse. However, the impacts on food production and thereby on food security are largely unknown. Yield losses in the period 1980–2050 were therefore assessed by simulating soil pH changes combined with derived pH-yield relationships for wheat, maize and rice. If the N fertilizer input continues to increase at 1% annually, the predicted average soil pH decline is about one unit and relative yield losses are expected to increase from approximately 4%–24% during 2010–2050. If the N fertilizer increase stops in 2020 (N2020), the expected losses are approximately 16% in 2050, which is comparable to a scenario of 100% crop residue return (100%RR). However, if 30% of the N fertilizer is replaced by manure N (30%MR), the losses reduce to near 5% in 2050. Soil acidification was predicted to reverse and expected losses are only 2.5% in 2050 in a combined scenario of N2020, 100%RR and 30%MR. Our results illustrate the potential food insecurity induced by cropland acidification and address the necessity of mitigation.

To highlight the levels and distributions and to assess the risk of human exposure of chlorinated paraffins (CPs) in PM₂.₅ in China, the concentrations and homologue patterns of short−chain chlorinated paraffins (SCCPs) and medium−chain chlorinated paraffins (MCCPs) in PM₂.₅ from 10 cities in China were studied in 2013 and 2014. The mean concentrations of ΣSCCPs and ΣMCCPs were 19.9 ± 41.1 ng m⁻³ and 15.6 ± 18.6 ng m⁻³, respectively. Unexpectedly, the highest pollution levels occurred in two central cities (Xinxiang and Taiyuan) rather than in well−known eastern megacities such as Beijing, Nanjing, Shanghai, and Guangzhou. By comparing with earlier research, it has indicated the trend of CPs industry shifting from large eastern cities to small and medium-sized cities in central China to some extent. In addition, the composition pattern of SCCPs demonstrated an obviously differences from previous studies, with C₁₁ and Cl₇ predominating and accounting for 45.1% and 24.9%, respectively. Meanwhile, the ratio of MCCPs/SCCPs in most cities was less than 1.00 except for Guangzhou (1.92), Shanghai (1.29), and Taiyuan (1.11). Combined with the results of correlation analysis and principal component analysis, the observed pollution characteristics of CPs in PM₂.₅ had similar sources, which were more influenced by the ratio of MCCPs/SCCPs than by organic carbon, elemental carbon, temperature, population, and gross domestic product. Overall, the composition of CPs reflected the characteristics of local industrial production and consumption, and also implied efforts of Chinese enterprises to reduce the content of short carbon groups of CPs production. The CPs mainly deposited in head airways during the process of entering the human respiratory system. However, at the present levels, there was no significant carcinogenic effect for human health.

Australian tropical freshwaters can experience extreme seasonal variability in rainfall and run off, particularly due to pulse events such as storms and cyclones. This study investigated how seasonal variability in dissolved organic matter (DOM) quality impacted the chronic toxicity of copper to a tropical green alga (Chlorella sp.) in the presence of two concentrations of DOM (low: ∼2 mg C/L; high: ∼10 mg C/L) collected from three tropical waters. Copper speciation and lability were explored using diffusive gradients in thin-films (DGT) and modelled maximum dynamic concentrations (cᵈʸⁿₘₐₓ) using data derived from the Windermere Humic Aqueous Model (WHAM VII). Relationships between copper lability and copper toxicity were assessed as potential tools for predicting toxicity. Copper toxicity varied significantly with DOM concentration, source and season. Copper toxicity decreased with increasing concentrations of DOM, with 50% growth inhibition effect concentrations (EC₅₀) increasing from 1.9 μg Cu/L in synthetic test waters with no added DOM (0.34 mg C/L) up to 63 μg Cu/L at DOM concentrations of 9.9 mg C/L. Copper toxicity varied by up to 2-fold between the three DOM sources and EC₅₀ values were generally lower in the presence of wet season DOM compared to dry season DOM. Linear relationships between DGT-labile copper and dissolved copper were significantly different between DOM source, but not concentration or season. Modelled cᵈʸⁿₘₐₓ consistently under-predicted labile copper in high DOM treatments compared to DGT measurements but performed better in low DOM treatments, indicating that this method is DOM-concentration dependent. Neither speciation method was a good surrogate for copper toxicity in the presence of different sources of natural DOM. Our findings show that DOM source and season, not just DOM concentration, affect copper toxicity to freshwater biota. Therefore, DOM quality should be considered as a toxicity-modifying factor for future derivation of bioavailability-based site-specific water quality guideline values.