BackgroundExposure to particulate matter (PM) has been found to be associated with impaired cognitive function. However, limited evidence is available on the relationship between PM exposure in the prenatal period and toddler executive function (EF), and the potential influence of breastfeeding. MethodsThe study included 1,106 mother-toddler pairs recruited between 2015-2019. We assessed mothers’ PM1, PM2.5, and PM10 prenatal exposure with a satellite-based dataset at a 1× 1 km spatial resolution and assigned to participants based on residential addresses. Toddler EF was measured using the Behavior Rating Inventory of Executive Function for Preschoolers (BRIEF-P) questionnaire, higher BRIEF-P scores indicated poorer EF in toddlers. We determined the associations of PM exposure during pregnancy with BRIEF-P scores using multiple linear regression models. ResultsIn the first trimester, a 10 μg/m3 increase of PM was associated with 1.49 (95% confidence interval [CI]: 0.14-2.83; PM1), 0.68 (95% CI: 0.10-1.26; PM2.5), and 0.63 (95% CI: 0.07-1.20; PM10) elevated toddler global executive composite index scores, respectively. In the stratified analysis, a 10 μg/m3 increase in first trimester PM1 exposure was related to 0.54 (95% CI: 0.19-0.89) higher inhibition scores in toddlers who received complementary breastfeeding for less than six months and -0.15 (95% CI: -0.81-0.51) higher inhibition scores in toddlers who received complementary breastfeeding for six months or more (P for interaction: 0.046). Additionally, a 10 μg/m3 increment in first trimester PM1 exposure was related to 0.36 (95% CI: 0.13-0.59) higher emotional control scores in toddlers who received breastfeeding for less than 12 months and -0.54 (95% CI: -1.25-0.18) higher inhibition scores in toddlers who received breastfeeding for no less than 12 months (P for interaction: 0.043). ConclusionsPM exposure during the first trimester, especially PM1, has been linked to lower toddler EF performance in toddlers; feeding with breast milk may be a potential protective measure.

In this study, UiO-67 (Zr)/g-C3N4 composites (U67N) were synthesized at wt.% ratios of 05:95, 15:85, and 30:70 using the solvothermal method at 80 °C for 24 h followed by calcination at 350 °C. The composites were characterized using UV–Vis diffuse reflectance spectroscopy, Fourier-transform infrared spectroscopy, photoluminescence spectroscopy, X-ray photoelectron spectroscopy, X-ray diffraction, scanning electron microscopy–energy-dispersive X-ray spectroscopy, transmission electron microscopy, and nitrogen physisorption analysis. In addition, thermal stability analysis of UiO-67 was conducted using thermogravimetric analysis.The photocatalytic performance of the composites was assessed during the degradation and mineralization of a mixture of methylparaben (MeP) and propylparaben (PrP) under simulated sunlight. The adsorption process of U67N 15:85 was characterized through kinetic studies and adsorption capacity experiments, which were modeled using pseudo-first-order and pseudo-second-order kinetics and Langmuir and Freundlich isotherms, respectively.The influence of pH levels 3, 5, and 7 on the photocatalytic degradation of the mixture was investigated, revealing enhanced degradation and mineralization at pH 3. The U67N composite exhibited dual capability in removing contaminants through adsorption and photocatalytic processes. Among the prepared composites, U67N 15:85 demonstrated the highest photocatalytic activity, achieving removal efficiencies of 96.8% for MeP, 92.5% for PrP, and 45.7% for total organic carbon in 300 kJ/m2 accumulated energy (3 h of reaction time). The detoxification of the effluent was confirmed through acute toxicity evaluation using the Vibrio fischeri method.The oxidation mechanism of the heterojunction formed between UiO-67 (Zr) and g-C3N4 was proposed based on PL analysis, photoelectrochemistry studies (including photocurrent response, Nyquist, and Mott–Schottky analyses), and scavenger assays.

To investigate the inhibitory effects of various transition metal ions on nitrogen removal and their underlying mechanisms, the single and combined effects of Cu2+ Ni2+ and Zn2+ on Heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria Acinetobacter sp. TAC-1 were studied in a batch experiment system. The results revealed that increasing concentrations of Cu2+ and Ni2+ had a detrimental effect on the removal of ammonium nitrogen (NH4+-N) and total nitrogen (TN). Specifically, Cu2+ concentration of 10 mg/L, the TN degradation rate was 55.09%, compared to 77.60% in the control group. Cu2+ exhibited a pronounced inhibitory effect. In contrast, Zn2+ showed no apparent inhibitory effect on NH4+-N removal and even enhanced TN removal at lower concentrations. However, when the mixed ion concentration of Zn2++Ni2+ exceeded 5 mg/L, the removal rates of NH4+-N and TN were significantly reduced. Moreover, transition metal ions did not significantly impact the removal rates of chemical oxygen demand (COD). The inhibition model fitting results indicated that the inhibition sequence was Cu2+ > Zn2+ > Ni2+. Transcriptome analysis demonstrated that metal ions influence TAC-1 activity by modulating the expression of pivotal genes, including zinc ABC transporter substrate binding protein (znuA), ribosomal protein (rpsM), and chromosome replication initiation protein (dnaA) and DNA replication of TAC-1 under metal ion stress, leading to disruptions in transcription, translation, and cell membrane structure. Finally, a conceptual model was proposed by us to summarize the inhibition mechanism and possible response strategies of TAC-1 bacteria under metal ion stress, and to address the lack of understanding regarding the influence mechanism of TAC-1 on nitrogen removal in wastewater co-polluted by metal and ammonia nitrogen. The results provided practical guidance for the management of transition metal and ammonia nitrogen co-polluted water bodies, as well as the removal of high nitrogen.

The reliance solely on the government or enterprises to promote climate governance is contingent upon the vested interests of economic entities and the regulatory bodies' efficiency in governance. Can the model of government-enterprise green collaborative governance evolve into a long-term mechanism for addressing the climate crisis and achieving the goals of sustainable development? By crawling data on public-private partnerships (PPP), employing ChatGPT to identify green PPP projects, and building a generalized difference-in-differences framework based on the Guidance on Building a Green Financial System issued in 2016, this present study investigates whether the involvement of private capital in government-led environmental and climate governance can effectively facilitate government-enterprise green collaborative governance, thereby mitigating urban carbon emissions. The study finds government-enterprise green collaborative governance can significantly reduce urban carbon emissions. The conclusion remains valid even after several rounds of robustness tests, including removing the influence of pertinent climate policies, adjusting the settings of independent and dependent variables, and removing self-selection issues. Heterogeneity tests show, on the first hand, the carbon emission reduction effect of government-enterprise green collaborative governance differs due to the differences in the characteristics of green PPP(Pubic-private partnership) projects such as project return mechanism, project investment volume, and project cooperation term; on the other hand, the carbon emission reduction effect also shows heterogeneity with various urban characteristics such as geographical location, city type and city size. Mechanism tests indicate government-enterprise green collaborative governance affects urban carbon emissions mainly through structural effects, technological effects and co-investment effects. This paper offers a valuable framework for effectively promoting environmental and climate co-governance between governmental bodies and enterprises, while enhancing the market's role in resource benefit allocation within climate governance to mitigate the risks associated with climate change.

This review is aimed at researchers in air pollution control seeking to understand the latest advancements in volatile organic compound (VOC) removal. Implementing of plasma-catalysis technology for the removal of volatile organic compounds (VOCs) led to a significant boost in terms of degradation yield and mineralization rate with low by-product formation. The plasma-catalysis combination can be used in two distinct ways: (I) the catalyst is positioned downstream of the plasma discharge, known as the “post plasma catalysis configuration” (PPC), and (II) the catalyst is located in the plasma zone and exposed directly to the discharge, called “in plasma catalysis configuration” (IPC). Coupling these two technologies, especially for VOCs elimination has attracted the interest of many researchers in recent years. The term “synergy” is widely reported in their works and associated with the positive effect of the plasma catalysis combination. This review paper investigates the state of the art of newly published papers about catalysis, photocatalysis, non-thermal plasma, and their combination for VOC removal application. The focus is on understanding different synergy sources operating mutually between plasma and catalysis discussed and classified into two main parts: the effect of the plasma discharge on the catalyst and the effect of the catalyst on plasma discharge. This approach has the potential for application in air purification systems for industrial processes or indoor environments.

The FeOCl-based photo-Fenton heterojunction catalyst holds great promise for effective water pollution treatment. A novel heterojunction FeOCl/MOF-In2S3 (F/M-I) was fabricated by coating hollow MOF-In2S3 nanoflowers onto the surface of FeOCl. Under the optimal conditions, the maximum photo-Fenton degradation rate constants of FeOCl/MOF-In2S3 for oxytetracycline (OTC) within 20 min is 0.88192 L mg−1·min−1, which are 3.2 and 2.5 times that of pure FeOCl (0.27357 L mg−1·min−1) and MOF-In2S3 (0.35222 L mg−1·min−1). Density functional theory (DFT) results confirm that the electron-rich nature of MOF-In2S3 accelerates the cycle between Fe (III)/Fe (II)of FeOCl, promoting H2O2 adsorption by FeOCl/MOF-In2S3 and generating more hydroxyl radicals (·OH) for pollutant degradation. Based on the results of DFT, combined with the results of the reactive oxidation species scavenger (ROSs), electron paramagnetic resonance (EPR) and Mott-Schottky curves, the separation and transfer behavior of photoexcited charges in FeOCl/MOF-In2S3 heterojunction and the possible photocatalytic degradation mechanism were investigated. Finally, a Z-scheme heterostructure is proposed to elucidate the catalytic mechanism. This study provides a new perspective on designing and synthesizing semiconductor materials for water treatment by photo-Fenton catalysis.

In this study, bimetallic Cu–Fe nanoparticles were synthesized using the green approach with Piper betle leaves, and the removal efficiency of one of the pharmaceutical compounds, Atorvastatin, was investigated. UV, SEM, FTIR, EDAX, particle size, and zeta potential measurements were used to confirm nanoparticle fabrication. The removal efficiency of Atorvastatin (10 mg/L) by bimetallic Cu–Fe nanoparticles was 67% with a contact time of 30 min at pH 4, the adsorbent dosage of 0.2 g/L, and stirring at 100 rpm. Piper betle bimetallic Cu–Fe nanoparticles have demonstrated excellent stability, reusability, and durability, even after being reused five times. Furthermore, the synthesized bimetallic Cu–Fe nanoparticles demonstrated remarkable antimicrobial properties against gram-negative strains such as Escherichia coli and Klebsiella pneumoniae, gram-positive strains such as Staphylococcus aureus and Bacillus subtilis, and fungi such as Aspergillus niger. In addition, the antioxidant properties of the synthesized bimetallic Cu–Fe nanoparticles were assessed using the DPPH radical scavenging assay. The results indicated that the nanoparticles had good antioxidant activity. Thus, using Piper betle extract to make Cu–Fe nanoparticles made the procedure less expensive, chemical-free, and environmentally friendly, and the synthesized bimetallic Cu–Fe nanoparticles helped remove the pharmaceutical compound Atorvastatin from wastewater.

BackgroundAsthma exacerbations are an important cause of emergency department visits but much remains unknown about the role of environmental triggers including viruses and allergenic pollen. A better understanding of spatio-temporal variation in exposure and risk posed by viruses and pollen types could help prioritize public health interventions. ObjectiveHere we quantify the effects of regionally important Cupressaceae pollen, tree pollen, other pollen types, rhinovirus, seasonal coronavirus, respiratory syncytial virus, and influenza on asthma-related emergency department visits for people living near eight pollen monitoring stations in Texas. MethodsWe used age stratified Poisson regression analyses to quantify the effects of allergenic pollen and viruses on asthma-related emergency department visits. ResultsYoung children (<5 years of age) had high asthma-related emergency department rates (24.1 visits/1,000,000 person-days), which were mainly attributed to viruses (51.2%). School-aged children also had high rates (20.7 visits/1,000,000 person-days), which were attributed to viruses (57.0%), Cupressaceae pollen (0.7%), and tree pollen (2.8%). Adults had lower rates (8.1 visits/1,000,000 person-days) which were attributed to viruses (25.4%), Cupressaceae pollen (0.8%), and tree pollen (2.3%). This risk was spread unevenly across space and time; for example, during peak Cuppressaceae season, this pollen accounted for 8.2% of adult emergency department visits near Austin where these plants are abundant, but 0.4% in cities like Houston where they are not; results for other age groups were similar. ConclusionsAlthough viruses are a major contributor to asthma-related emergency department visits, airborne pollen can explain a meaningful portion of visits during peak pollen season and this risk varies over both time and space because of differences in plant composition.

Polycystic kidney disease is the most prevalent hereditary kidney disease globally and is mainly linked to the overexpression of a gene called PKD1. To date, there is no effective treatment available for polycystic kidney disease, and the practicing treatments only provide symptomatic relief. Discovery of the compounds targeting the PKD1 gene by inhibiting its expression under the disease condition could be crucial for effective drug development. In this study, a molecular docking and molecular dynamic simulation, QSAR, and MM/GBSA-based approaches were used to determine the putative inhibitors of the Pkd1 enzyme from a library of 1379 compounds. Initially, fourteen compounds were selected based on their binding affinities with the Pkd1 enzyme using MOE and AutoDock tools. The selected drugs were further investigated to explore their properties as drug candidates and the stability of their complex formation with the Pkd1 enzyme. Based on the physicochemical and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties, and toxicity profiling, two compounds including olsalazine and diosmetin were selected for the downstream analysis as they demonstrated the best drug-likeness properties and highest binding affinity with Pkd1 in the docking experiment. Molecular dynamic simulation using Gromacs further confirmed the stability of olsalazine and diosmetin complexes with Pkd1 and establishing interaction through strong bonding with specific residues of protein. High biological activity and binding free energies of two complexes calculated using 3D QSAR and Schrodinger module, respectively further validated our results. Therefore, the molecular docking and dynamics simulation-based in-silico approach used in this study revealed olsalazine and diosmetin as potential drug candidates to combat polycystic kidney disease by targeting Pkd1 enzyme.

Indoor air quality is a critical factor influencing athletic performance, particularly in professional sports settings, yet its impact remains underexplored. This study utilizes a panel dataset from 2516 Chinese Basketball Association (CBA) matches across 20 cities in China between 2014 and 2019. We integrate daily air pollution metrics with player efficiency ratings (PER) to investigate the effects of air quality on individual performance. We find that a 10% increase in the air quality index (AQI) corresponds to a 1.4223 decrease in PER, indicating a strong negative effect of poor air quality on player productivity. Different pollutants have varying effects, with some exacerbating the decline in both overall performance and precision in tasks. Notably, older players and international players exhibit greater resilience to air pollution. These insights contribute to the development of a comprehensive index for assessing work efficiency under varying air quality conditions and suggest targeted strategies to mitigate the negative impacts of air pollution in competitive athletic settings.