Effects Of Pollution Research Articles

The effect of air pollutants on COPD-hospitalized patients in Lanzhou, China (2015-2019).

Lanzhou is the largest heavy industrial city in northwest China and it is a typical geographical valley-like city. However, there are few studies on the relationship between air pollutants and COPD, and their respective sample sizes are small, resulting in inconsistent results. The aim of this study is to analyze the effects of air pollutants on COPD hospitalizations in Lanzhou, China. An ecological time series study with distributed lag non-linear model (DLNM) was used for analysis. Daily COPD hospitalization data in Lanzhou from 1 January 2015 to 31 December 2019 were collected from 25 hospitals, as well as air pollutant data and meteorological data. A total of 18,275 COPD hospitalizations were enrolled. For 10 μg/m3 increase in PM2.5, PM10, SO2, NO2, and 1 mg/m3 increase in CO at lag 07 day, the RR95%CI of COPD hospitalizations were 1.048 (1.030, 1.067), 1.008 (1.004, 1.013), 1.091 (1.048, 1.135), 1.043 (1.018, 1.068), and 1.160 (1.084, 1.242), respectively. The exposure-response curves between air pollutants (except O3-8h) and COPD hospitalizations were approximately linear with no thresholds. Female, and the harmful effect of PM on aged <65 years, the effect of gaseous pollutant on those aged ≥65 years, were stronger, particularly in the cold season. Exposure to air pollutants (except O3-8h) might increase the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD. Exposure to air pollutants (except O3-8h) increases the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD hospital admissions. The harmful effect of gaseous pollutants (except O3-8h) on COPD-hospitalized patients was stronger than that of PM.

Air pollution and firms' export product quality: Evidence from China

AbstractThis study provides causal estimates of the effect of air pollution on firms' export product quality, based on China's experience. Using thermal inversions as an instrument, a 1% increase in PM2.5 is associated with a 0.25% decrease in export product quality. A series of tests indicates the robustness of our main result. Heterogeneity analysis reveals that the negative impact of air pollution on export product quality is only significant among regions with high levels of air pollution. In addition, we find that air pollution also reduces firms' export sales, share and probability. Our study provides original evidence for the relationship between air pollution and firms' export product quality, offering a unique perspective for countries to enhance export competitiveness.

Laser-synthesized TiN-based nanoparticles as novel efficient electrostatic nanosorbent for environmental water cleaning

Abstract Dyes used in industries such as textile, paper, and leather are known to be harmful to both human health and aquatic ecosystems, which makes critically important the search of effective and sustainable methods for their removal from wastewater in order to mitigate the detrimental pollution effects. Here, we show that titanium nitride nanoparticles (TiN NPs) synthesized by scalable methods of pulsed laser ablation in liquid ambient (water, acetone and acetonitrile) can serve as extremely efficient sorbents for water decontamination from dye molecules (methylene blue, crystal violet, and malachite green). Our tests show that adsorption of TiN NPs is associated with the electrostatic effect due to a strong negative charge of laser-synthesized TiN NPs and the presence of pores in the NPs. Comprehensive characterization using scanning and transmission electron microscopy, along with Raman spectroscopy, evidenced that the appearance of surface charge is related to the formation of under-stoichiometric TiN (TiN1-x), associated with the predominance of nitrogen vacancies. This study identifies an optimal configuration of vacancy defects that maximizes dye adsorption, with TiN NPs synthesized in water exhibiting superior performance, achieving a dye sorption capacity of 136.5 mg/g at room temperature for methylene blue, which corresponds to best earlier reported values for nanomaterials. This study not only extends the utility of TiN NPs to environmental remediation but also highlights the critical influence of synthesis conditions on their functional properties, offering a pathway towards the design of more effective materials for pollution control.

Prevalence Characteristics of Osteoporosis Fractures in the Elderly in Two Regions of China and Analysis of the Lag Effect of Air Pollutants on them.

Air pollution is increasing and threatening human health. The objective of this study is to investigate the population distribution characteristics of elderly osteoporosis fractures in Hebei Province and Xinjiang Uygur Autonomous Region and to analyze the effects of air pollutants on the number of elderly osteoporosis fracture inpatients in the two regions. A retrospective collection of elderly osteoporosis fracture cases was conducted in selected hospitals in Hebei Province and Xinjiang Uygur Autonomous Region from January 1, 2018 to December 31, 2022. The chi-square test was used to compare the distributional characteristics of the population in the two regions. Additionally, we used a distributed lag nonlinear model (DLNM) in order to assess the effect of air pollutants on the number of daily hospital admissions of elderly osteoporosis fracture patients in different regions. A total of 19,203 elderly osteoporosis fracture patients were included in the study. The average age of these patients was 76.66 ± 7.55 years, and the majority of them were female (13,514 instances, 70.37%). The disparities in age distribution (χ2 = 133.9 p < 0.001), fracture site (χ2 = 62.0 p < 0.001), and hospitalization cost (Z = -15.635 p < 0.001) between the two regions were statistically significant. The lag effect curves of PM2.5, PM10, and NO2 on the number of elderly osteoporosis fracture hospitalizations in Xinjiang Uygur Autonomous Region exhibited a similar pattern resembling a "W"-shaped curve. All three pollutants reached their highest values after a lag time of 14 days (PM2.5: RR = 1.053, 95% CI: 1.031, 1.074; PM10: RR = 1.031, 95% CI: 1.018, 1.043; NO2: RR = 1.125, 95% CI: 1.070, 1.182). In Hebei Province, the largest impacts of PM2.5 and PM10 were observed after a lag of 14 days (PM2.5: RR = 1.022, 95% CI: 1.013, 1.028; PM10: RR = 1.013, 95% CI: 1.008, 1.018). Similarly, the maximum effect of NO2 was observed after a lag of 11 days (RR = 1.020, 95% CI: 1.010, 1.028). There were differences in the epidemiological characteristics of hospitalized patients with osteoporosis fractures between the two regions, PM2.5, PM10, and NO2 increased the number of hospitalizations for osteoporosis fractures. Exposure to air pollutants such as PM2.5 increases the risk of osteoporosis fractures in the elderly population.

Interpregnancy interval, air pollution, and the risk of low birth weight: a retrospective study in China

BackgroundBoth interpregnancy intervals (IPI) and environmental factors might contribute to low birth weight (LBW). However, the extent to which air pollution influences the effect of IPIs on LBW remains unclear. We aimed to investigate whether IPI and air pollution jointly affect LBW.MethodsA retrospective cohort study was designed in this study. The data of birth records was collected from the Jiangsu Maternal Child Information System, covering January 2020 to June 2021 in Nantong city, China. IPI was defined as the duration between the delivery date for last live birth and date of LMP for the subsequent birth. The maternal exposure to ambient air pollutants during pregnancy—including particulate matter (PM) with an aerodynamic diameter of ≤ 2.5 μm (PM2.5), PM10, ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO)—was estimated using a hybrid kriging-LUR-RF model. A novel air pollution score was proposed, assessing combined exposure to five pollutants (excluding CO) by summing their concentrations, weighted by LBW regression coefficients. Multivariate logistic regression models were used to estimate the effects of IPI, air pollution and their interactions on LBW. Relative excess risk due to interaction (RERI), attributable proportion of interaction (AP) and synergy index (S) were utilized to assess the additive interaction.ResultsAmong 10, 512 singleton live births, the LBW rate was 3.7%. The IPI-LBW risk curve exhibited an L-shaped pattern. The odds ratios (ORs) for LBW for each interquartile range increase in PM2.5, PM10, O3 and the air pollution score were 1.16 (95% CI: 1.01–1.32), 1.30 (1.06–1.59), 1.22 (1.06–1.41), and 1.32 (1.10–1.60) during the entire pregnancy, respectively. An additive interaction between IPI and PM2.5 was noted during the first trimester. Compared to records with normal IPI and low PM2.5 exposure, those with short IPI and high PM2.5 exposure had the highest risk of LBW (relative risk = 3.53, 95% CI: 1.85–6.49, first trimester).ConclusionThe study demonstrates a synergistic effect of interpregnancy interval and air pollution on LBW, indicating that rational birth spacing and air pollution control can jointly improve LBW outcomes.

Light pollution: time to consider testicular effects.

Technological advances have led to a modern-day lighting and smartphone revolution, with artificial light exposure at night increasing to levels never before seen in the evolutionary history of living systems on Earth. Light as a pollutant, however, remains largely unrecognized, and the reproductive effects of light pollution are mostly if not entirely unconsidered. This is despite the reproductive system being intricately linked to metabolism and the circadian system, both of which can be disturbed even by low levels of light. Here, we aim to change this perspective by reviewing the physiological and pathophysiological mechanisms by which light exposure alters the intricate hormonal, metabolic and reproductive networks that are relevant to reproductive toxicology. Nascent human studies have recently identified the photoreceptors responsible for the light dose relationship with melatonin suppression and circadian re-entrainment, directly shown the association between the alignment of light-dark cycles with activity-rest cycles on metabolic health and provided proof-of-principle that properly timed blue light-enriched and blue light-depleted delivery can accelerate circadian re-entrainment. With these advances, there is now a need to consider testicular effects of light pollution.

Air pollution exposure, chemical compositions, and risk of expiratory airflow limitation in youth in Northeast China

BackgroundExpiratory airflow limitation (EAL) is closely associated with respiratory health in youth and adulthood. Owing to limited evidence, we aim to estimate the association between air pollutants, both individually and in combination, along with their chemical compositions, and the risk of EAL in youth based on data obtained from Northeast China Biobank. MethodsPulmonary function was evaluated using a medical-grade pulmonary function analyzer, with EAL defined as a forced expiratory flow in 1 s/ forced vital capacity ratio of < 0.8. Land use regression models were used to predict exposure to six air pollutants. Air pollution score (APS) for each participant was constructed as combined exposure. The chemical composition of particulate matter with an aerodynamic diameter of ≤ 2.5 µm (PM2.5) was determined using a validated machine-learning algorithm. Logistic regression models were employed to estimate effect sizes, and odds ratio (OR) and 95 % confidence intervals (CI) were calculated. ResultsIn total, 905 EAL cases were identified among the 4301 participants, with a prevalence of 21.04 %. Each inter-quartile range increase in APS was associated with a 25 % higher risk of EAL (OR = 1.25, 95 % CI: 1.12, 1.39). Among the pollutants analyzed, PM2.5 exposure had the strongest association with the risk of EAL (OR = 1.33, 95 % CI: 1.18, 1.52). Out of the five chemical components, sulfate (SO2-4) (OR = 1.39, 95 % CI: 1.24, 1.57) and ammonium (NH+4) (OR = 1.39, 95 % CI: 1.23, 1.57) exhibited the strongest associations with the risk of EAL. ConclusionsOverall, combined effects of air pollution increased the risk of EAL in youth, with SO2-4 and NH+4 emerging as the predominant contributing chemical components in Northeast China.

Effect modification of air pollution on the association between heat and mortality in five European countries

BackgroundEvidence suggests that air pollution modifies the association between heat and mortality. However, most studies have been conducted in cities without rural data. This time-series study examined potential effect modification of particulate matter (PM) and ozone (O3) on heat-related mortality using small-area data from five European countries, and explored the influence of area characteristics. MethodsWe obtained daily non-accidental death counts from both urban and rural areas in Norway, England and Wales, Germany, Italy, and the Attica region of Greece during the warm season (2000–2018). Daily mean temperatures and air pollutant concentrations were estimated by spatial-temporal models. Heat effect modification by air pollution was assessed in each small area by over-dispersed Poisson regression models with a tensor smoother between temperature and air pollution. We extracted temperature-mortality relationships at the 5th (low), 50th (medium), and 95th (high) percentiles of pollutant distributions. At each air pollution level, we estimated heat-related mortality for a temperature increase from the 75th to the 99th percentile. We applied random-effects meta-analysis to derive the country-specific and overall associations, and mixed-effects meta-regression to examine the influence of urban-rural and coastal typologies and greenness on the heat effect modification by air pollution. ResultsHeat-related mortality risks increased with higher PM levels, rising by 6.4% (95% CI: −2.0%–15.7%), 10.7% (2.6%–19.5%), and 14.1% (4.4%–24.6%) at low, medium, and high PM levels, respectively. This effect modification was consistent in urban and rural regions but more pronounced in non-coastal regions. In addition, heat-mortality associations were slightly stronger at high O3 levels, particularly in regions with low greenness. ConclusionOur analyses of both urban and rural data indicate that air pollution may intensify heat-related mortality, particularly in non-coastal and less green regions. The synergistic effect of heat and air pollution implies a potential pathway of reducing heat-related health impacts by improving air quality.

Spatiotemporal distribution of air quality dynamics and health risks study during 2019–2021 lockdown in urban and industrial cities of West Bengal, India

Globally, air pollution is the second most common cause of mortality from non-communicable diseases (NCDs), after tobacco smoking. Breathing polluted air has potential to cause a diverse array of health problems. This study comprehensively investigates the health risk of different areas of the population mainly industrial and urban belt by using AIRQ + health risk assessment model. This study also analyzes the spatiotemporal distribution of air quality in industrial and urban areas and correlation study was conducted between air pollutants and meteorological factors with episodic influences mainly lockdown phases. In Kolkata, Howrah, Asansol and Siliguri, the average Air quality index (AQI) varied from satisfactory (51–100) to moderate (101–200) values. The poor (201−300) to very poor (301−400) air quality observed in January, February, November and December month of the year. The higher AQI observed in the study area in winter season as compared to summer season. In the lockdown period overall air quality was improved. The meteorological factors, including rainfall and temperature played a crucial role in influencing air quality in this area. The regression analysis indicates a significant negative association between temperature and the following pollutants: PM2.5 (β = − 4.91, p < 0.01), PM10 (β = − 8.27, p < 0.01), NO2 (β = − 2.10, p < 0.01), NOx (β = − 4.05, p < 0.01), CO (β = − 0.04, p < 0.01), and SO2 (β = − 0.45, p < 0.01). The number of attributable cases of long-term PM2.5 exposure mortality due to lung cancer, stroke, IHD and COPD in four cities were 1132, 3969, 4381 and 974 in Kolkata; 1454, 4913, 5327 and 1221 in Howrah; 154, 531, 581 and 131 for Asansol; 137, 474, 520 and 117 in Siliguri respectively. IHD is the leading cause for mortality in the study area. The long-term effects of PM10 such as chronic bronchitis in adults and post-neonatal infant mortality were 30,860 and 738,450 in Kolkata, 53,961 and 898,920 in Howrah, 3782 and 89,460 in Asansol, and 3293 and 76,331 in Siliguri respectively. These study findings help policymakers, stakeholders and governments to take early action to reduce the effects of air pollution and implement interventions for the well-being of the population.

AYURVEDIC LIFESTYLE RECOMMENDATIONS FOR LIVING IN HIGH POLLU-TION AREAS - A REVIEW

Air pollution refers to the presence of harmful or excessive quantities of substances in the air that can be detrimental to human health, the environment, and the climate. These substances, often called pollutants, can originate from natural and human-made sources. Air pollution is a significant risk to public health, particularly in municipal and industrialised regions. This article explores Ayurvedic lifestyle recommendations to diminish the adverse effects of air pollution on health. Ayurved is an ancient system of natural healing. It can offer a holistic approach to strengthening the body's defence system and promoting overall well-being in polluted environments. Key recommendations include dietary modifications, herbal Rasayanas, breathing exercises, and daily routines that enhance the body's natural detoxification processes. By integrating Ayurvedic practices with modern preventive measures, individuals can better protect themselves from the harmful impacts of air pollution and improve their quality of life.

Are Children's Hospitals Doing Enough to Address the Climate Crisis?

The warming of our planet matters to the health, well-being, and future of every child. 1 Due to the nature of infants' and children's biological systems and cognitive immaturity, they are more vulnerable to the effects of climate change and air pollution. 1,2 The U.S. healthcare sector itself contributes to the problem and accounts for 8.5% of U.S. greenhouse gas emissions (GHGe). 3 These emissions come directly from hospital operations, indirectly from purchased energy, and the largest category, termed scope 3 emissions, includes purchased goods and services, employee commuting, and waste management. 4 Reducing GHGe can also improve hospitals' operating efficiency and promote healthcare resiliency. 1.

The environmental consequences of industrial agglomeration: New evidence from city-level data in China

In the context of sustainable development, environmental policies increasingly focus on reducing carbon emissions worldwide. Industrial agglomeration (IAGG) has emerged as a potential factor in achieving this objective by reducing carbon emissions and improving air quality. This study examines the direct and indirect impacts, spatial dynamics, and policy impacts of industrial agglomeration on air pollution levels. Panel data from 278 cities in China between 2011 and 2020 are utilized to investigate the potential of industrial agglomeration to reduce air pollution. Multiple regression models are employed, these models explore the mechanisms through which industrial agglomeration can have a positive effect on air pollution, highlighting economic growth, inclusive finance, digital economy and technological innovation as crucial factors. The study also investigates the spatial spillover effects of industrial agglomeration, finding that the concentration ratio and specialization of neighbouring cities significantly contribute to local air pollution levels. Furthermore, this contribution increases progressively with distance. The study investigates the spillover effects of environmental pollution and industrial agglomeration-related policies on PM2.5 concentration, concluding that such spillover effects lead to a decrease in PM2.5 concentration in neighbouring locations.

A multichannel microfluidic device for revealing the neurotoxic effects of Bisphenol S on cerebral organoids under low-dose constant exposure

Bisphenol S is a widely used plasticizer in manufacturing daily supplies, while little was known about its adverse effect on human health, especially on fetal brain development. Due to the complexity and subtlety of the brain, it remains challenging to reveal the hazardous effects of environmental pollution on human fetal brain development. Taking advantage of stem cell application, cerebral organoids generated from stem cells are becoming powerful tools for understanding brain development and drug toxicity testing models. Here, we developed a microfluidic chip for cerebral organoid culturing to reveal the neurotoxicity of low-dose constant BPS exposure on cerebral organoids. The organoids in our microfluidic system could be continuously cultured for 34 days and expressed all the essential properties of the cerebral organoids. Exposure to BPS was initiated from day 20 for concessive two weeks. The neurotoxic effects were evaluated by immunofluorescence staining and proteomics, and verified by quantitative real-time PCR. Our results indicated BPS exposure would inhibit neuron differentiation, hinder the Wnt signaling pathway, and cause alteration of signaling molecule expressions in brain regionalization. Even exposure to a low dose of BPS constantly might cause neurotoxicity during fetal brain development. Altogether, the multichannel microfluidic chip offers a general platform technique to reveal the effects of different hazardous chemicals on cerebral organoids.

Modeling health outcomes of air pollution in the Middle East by using support vector machines and neural networks

This study investigates the impact of air pollution on health outcomes in Middle Eastern countries, a region facing severe environmental challenges. As such, these are important in an effort to add up to policy-level as well as interventional changes that can be put in practice in the area of public health. Numeration analysis and association with health parameters was carried out by using Analytical tools such as, AIR Data, ARIMA,ANN, SVM and Exponential smoothing. Amongst the models, Support Vector Machine came again on top, with high accuracy yielding Mean Absolute Percentage Error of approximately 1%. Mortality of Air pollution in Qat from the case of Mortality of Air Pollution in Qatar is 959 while Auto regressive Integrated Moving average is 11.096, Exponential Smoothing 9.892 and Artificial Neural Networks are the source of inspiration for the development of this paper 4.61. The above perceptions indicate that there is need to adapt modeling strategies depending on the context and establish that it is possible to implement ML models in public health planning basket. This paper publishes the methodological frameworks for the purpose of modeling and analysis of the EHDs and serves as policy prescription for the policy makers to intending to reduce the effects of air borne pollution on health.

Unraveling the complex interactions between ozone pollution and agricultural productivity in China's main winter wheat region using an interpretable machine learning framework

Surface ozone has become a significant atmospheric pollutant in China, exerting a profound impact on crop production and posing a serious threat to food security. Previous studies have extensively explored the physiological mechanisms of ozone damage to plants. However, the effects of ozone interactions with other environmental factors, such as climate change, on agricultural productivity at the regional scale, particularly under natural conditions, remain insufficiently understood. In this study, we employed an interpretable machine learning framework, specifically the eXtreme Gradient Boosting (XGBoost) algorithm enhanced by SHapley Additive exPlanations (SHAP), to investigate the influence of ozone and its interactions with environmental factors on crop production in China's primary winter wheat region. Additionally, a structural equation model was developed to elucidate the mechanisms driving these interactions. Our findings demonstrate that ozone pollution exerts a significant negative effect on winter wheat productivity (r = −0.47, P < 0.001), with productivity losses escalating from −12.28 % to −22.09 % as ozone levels increase. Notably, the impact of ozone is spatially heterogeneous, with western Shandong province identified as a hotspot for ozone-induced damage. Furthermore, our results confirm the complexity of the relationship between ozone pollution and agricultural productivity, which is influenced by multiple interacting environmental factors. Specifically, we found that severe ozone pollution, when combined with high aerosol concentrations or elevated temperatures, significantly exacerbates crop productivity losses, although drought conditions can partially mitigate these adverse effects. Our study highlights the importance of incorporating the interactive effects of air pollution and climate change into future crop models. The comprehensive framework developed in this study, which integrates statistical modeling with explainable machine learning, provides a valuable methodological reference for quantitatively assessing the impact of air pollution on crop productivity at a regional scale.

Efficacy of DHA-enriched phosphatidylserine and its underlying mechanism in alleviating polystyrene nanoplastics-induced hepatotoxicity in mice

ObjectivePlastic pollution has become a global pollution problem that cannot be ignored. As the main destination of human oral intake, the toxic effects of plastic on the digestive system represented by the intestine and liver are the focus of current research. Marine-derived DHA-PS has a variety of biological activities, mainly focusing on improving brain function and regulating lipid metabolism. However, whether it has an improvement effect on PS-NPs-induced hepato-intestinal injury and the underlying mechanism remain unclear. MethodsA murine liver injury model was established by gavage of PS-NPs for six weeks. By integrating approaches from lipidomics, transcriptomics, and gut microbiota analysis, the molecular mechanism by which DHA-PS alleviates PS-NPs-induced murine hepatotoxicity was explored through the “gut-liver axis”. ResultsOur findings reveal that prolonged exposure to PS-NPs results in significant murine liver damage and dysfunction, characterized by increased oxidative stress and inflammation, along with exacerbated hepatic lipid accumulation. Mechanistically, PS-NPs disrupt the hepatic SIRT1-AMPK pathway by suppressing the expression of SIRT1, AMPKα, and PPARα, while enhancing the expression of SREBP-1c, ultimately leading to disordered hepatic lipid metabolism. The sphingolipid and glycerophospholipid metabolic pathways were particularly affected. Additionally, in agreement with transcriptomic analyses, PS-NPs activate the hepatic TLR4/NF-κB pathway. At the same time, exposure to PS-NPs decreases the expression of ZO-1, occludin, and claudin-1, diminishes the relative abundance of beneficial gut bacteria (norank_f_Muribaculaceae, Akkermansia, and norank_f_norank_o_Clostridia_UCG-014), and increases the prevalence of pathogenic gut bacteria (Coriobacteriaceae_UCG-002 and Desulfovibrio), exacerbating liver injury through the gut-liver axis. However, administering DHA-PS (50 mg/kg) effectively alleviated these injuries. ConclusionThis study was the first to employ multi-omics techniques to elucidate the potential mechanisms underlying hepatotoxicity induced by PS-NPs, thereby supporting the use of DHA-PS as a dietary supplement to mitigate the effects of nanoplastic pollutants.

Biodegradation of Spent Automobile Engine Oil in Soil Microcosms Amended with Coconut Shell

Food insecurity and low yield have resulted from the detrimental effects of petroleum hydrocarbon pollution on agricultural soils over time. This study was carried out to determine the bioremediation efficacy of coconut shell on microbiological composition and total petroleum hydrocarbon degradation in spent engine oil polluted soil. Top soil (0-15 cm depth) samples were randomly collected from areas with history of spent engine oil pollution within Anyigba, Kogi State, Nigeria. One kilogram of the polluted-soil was measured into each of nine plastic containers. Coconut shell collected from the Prince Abubakar Audu University, Anyigba, was standardly prepared and mixed with the soil at the rate of 0, 50 and 100 g kg-1 soil in triplicate. The experiment used a completely randomized design. Soil samples were taken from each container at 0 and 28 days for hydrocarbon utilizing bacteria and total petroleum hydrocarbon determination using standard methods. Data obtained from the experiment were subjected to descriptive and inferential statistics. The species identified were Enterobacter sp and Escherichia coli, with Enterobacter sp being the most predominant isolate. The total petroleum hydrocarbon (mgkg-1) of the soil on day 0 was 59.78 ± 1.85. After the amendments (at control, 50 and 100 g kg-1), the total petroleum hydrocarbon (mgkg-1) values were 44.92 ±2.26, 34.82 ± 1.78 and 31.49 ± 0.87 at 28 days respectively. Coconut shell and the high level carbon utilizing bacteria, Enterobacter sp, significantly enhanced the biodegradation process as an impressive 47.32% remediation efficiency was achieved 28 days after amendment in soil treated with 100g of coconut shell. It is recommended that a biostimulation strategy that uses coconut shell and Enterobacter sp be employed in the remediation of spent engine oil and petroleum hydrocarbon polluted soils.

Exploring macroalgae biorefinery: Extraction of bioactive compounds and production of volatile fatty acids

Macroalgae have gained significant attention in recent research owing to their potential as novel food source and their noteworthy nutritional properties. However, a substantial amount of these macroalgae accumulates along the coast without being utilized, highlighting the need for proper treatment and disposal methods to mitigate secondary pollution effects. Previous studies on macroalgae have primarily focused on extracting bioactive compounds or anaerobic digestion processes to produce methane or volatile fatty acids (VFA), with observed improvements following different pre-treatments. In this study, three biorefinery options for macroalgae have been compared. Additionally, the extraction of bioactive compounds followed by VFA production is proposed as a promising new valorization strategy. Milled macroalgae exhibited a low methane production yield (138 ± 17 NmL CH4·g volatile solid−1), corresponding to 31 ± 4 % biodegradability, while the acidification percentage was higher (45 ± 1%). Among the three solvents applied (water, ethanol and acetone), ethanol (80%) at 25 °C was the most effective in recovering bioactive compounds, such as chlorophylls, sugars, and phenolic compounds with antioxidant activity. The extraction of chlorophylls and phenolic compounds was not influenced by particle size reduction. However, a more efficient extraction of sugars was observed with lower particle size. Moreover, ethanol treatment demonstrated the good efficiency in VFA production, reaching up to 3.6 ± 0.2 g VFA-(chemical oxygen demand, COD)·L−1, with a VFA spectrum (in COD basis) consisting of 51% acetic acid, 29% propionic acid, 5% i-butyric acid, 7% butyric acid, and 7% i-valeric acid. These findings highlight the potential of ethanol for efficient compound recovery and VFA production from macroalgae.

Interactive effect of air pollution and genetic risk of depression on processing speed by resting-state functional connectivity of occipitoparietal network

BackgroundAir pollution, a reversible environmental factor, was significantly associated with the cognitive domains that are impaired in major depressive disorder (MDD), notably processing speed. Limited evidence explores the interactive effect of air pollution and the genetic risk of depression on cognition. This cross-sectional study aims to extend the research by specifically examining how this interaction influences depression-related cognitive impairment and resting-state brain function.MethodsEligible participants were 497 healthy adult volunteers (48.7% males, mean age 24.5) living in Beijing for at least 1 year and exposed to relatively high air pollution from the local community controlling for socioeconomic and genomic. Six months’ ambient air pollution exposures were assessed based on residential addresses using monthly averages of fine particulate matter with a diameter of less than or equal to 2.5 μm (PM2.5). A cross-sectional analysis was conducted using functional magnetic resonance imaging (fMRI) and cognitive performance assessments. The polygenic risk score (PRS) of MDD was used to estimate genetic susceptibility.ResultsUsing a general linear model and partial least square regression, we observed a negative association between resting-state local connectivity in precuneus and PRS-by-PM2.5 interactive effect (PFWE = 0.028), indicating that PM2.5 exposure reduced the spontaneous activity in precuneus in individuals at high genetic risk for MDD. DNA methylation and gene expression of the SLC30A3 gene, responsible for maintaining zinc-glutamate homeostasis, was suggestively associated with this local connectivity. For the global functional connectivity, the polygenic risk for MDD augmented the neural impact of PM2.5 exposure, especially in the frontal-parietal and frontal-limbic regions of the default mode network (PFDR < 0.05). In those genetically predisposed to MDD, increased PM2.5 exposure positively correlated with resting-state functional connectivity between the left angular gyrus and left cuneus gyrus. This connectivity was negatively associated with processing speed.ConclusionsOur cross-sectional study suggests that air pollution may be associated with an increased likelihood of cognitive impairment in individuals genetically predisposed to depression, potentially through alterations in the resting-state function of the occipitoparietal and default mode network.

Assessing the Impact of Environmental Quality on Public Health Expenditure Central Asia

This study utilizes panel data from 2002 to 2022 in Central Asia to analyze the impact of environmental quality on public health expenditures. This study employs the ARDL model to examine the short-run and long-run relationships between healthcare expenditure and pollution levels, namely carbon dioxide (CO2), sulfur dioxide (SO2), and nitrogen dioxide (NO2). The data indicate a robust positive correlation between greenhouse gases and healthcare expenditures, demonstrating the effect of environmental pollution on public health. The study examines the relationship between socioeconomic variables, including GDP, death rates, and healthcare expenditures. This study concludes that reversing this trend hinges on improving environmental policy in the energy and industrial sectors. This research contributes to the existing knowledge by analyzing how various environmental elements and economic structures persistently impact health policy evolution in the region.