High Pollution Research Articles

Measurement and spatial and temporal characterization of logistics efficiency--Based on a three-stage DEA model

The logistics industry is an essential component of economic and social development. Enhancing its efficiency contributes to national economic progress. However, the sector faces challenges such as high costs and pollution. This paper conducts an empirical study on the logistics efficiency of 30 Chinese provinces (excluding Xinjiang Uygur Autonomous Region) from 2004 to 2021 using a three-stage DEA model. Findings reveal that before adjustment, five provinces, including Beijing and Shanghai, were on the efficiency frontier, reduced to three after adjustment. Other provinces exhibit room for improved logistics efficiency, particularly in addressing cost and pollution issues. The key to enhancing efficiency lies in technical and scale efficiency adjustments. External environmental factors significantly influence logistics efficiency; social retail goods consumption positively correlates, while Gross Regional Product negatively correlates. Overall, China's logistics efficiency displays an upward trend but with notable regional disparities, indicating higher efficiency in the eastern region and lower efficiency in central and western regions, resulting in an overall "high in the east, low in the west" pattern.

Source-specific ecological and human health risk analysis of topsoil heavy metals in urban greenspace: a case study from Tianshui City, northwest China.

Soil contamination of heavy metals in urban greenspaces can exert detrimental impacts on ecological biodiversity and the health of inhabitants through cross-media migration-induced risks. Here, a total of 72 topsoil samples were collected from greenspaces in the popular tourist city of Tianshui, ranging from areas with parks, residential, road, industrial and educational soils. The study aimed to evaluate an integrated source-specific ecological and human health risk assessment of heavy metals. Among the analyzed heavy metals, except Cr (mean), all exceeded the local background values by 1.30-5.67-fold, and Hg, Cd, Pb and As were the metals with large CV values. The Igeo and CF results showed Hg, Cd, As and Pb exhibited significantly high pollution levels and were the primary pollution factors. The mean PLI values indicated moderate pollution in educational (2.21), industrial (2.07), and road (2.02) soils but slight pollution in park (1.84) and residential (1.39) greenspaces. The Igeo, CF, and PLI results also revealing that these heavy metals are more likely to be affected by human activity. Four primary source factors were identified based on PMF model: coal combustion (25.57%), agricultural sources (14.49%), atmospheric deposition (20.44%) and mixed sources (39.50%). In terms of ecological risk, the mean IRI values showed considerable risks in educational soils (287.52) and moderate risks in road (215.09), park (151.27) and residential (136.71) soils. And the contribution ratio of atmospheric deposition for park, residential, road, industrial and educational greenspaces were 57.72%, 65.41%, 67.69%, 59.60% and 75.76%, respectively. In terms of human health risk, the HI (below 1) and CR (below 1.00E-04) for adults from soils of all land use types was negligible. However, children have more significant non-carcinogenic and carcinogenic hazards especially in residential soils, the HI (above 1) and CR (above 1.00E-04) revealed the significance of regarding legacy As contamination from coal combustion when formulating risk mitigation strategies in this area. The proposed method for source and risk identification makes the multifaceted concerns of pollution and the different relevant risks into a concrete decision-making process, providing robust support for soil contamination control.

High-accuracy full-coverage PM2.5 retrieval from 2014 to 2023 over China based on satellite remote sensing and hierarchical deep learning model

ABSTRACT Obtaining precise ground-level fine particulate matter (PM2.5) information is significant for human health. Spatial PM2.5 maps can be obtained by remote sensing technology, but considerable uncertainty exists when suffering from high pollution with complicated aerosol types. To address this issue, we propose using a hierarchical machine learning model to retrieve high-accuracy and daily full-coverage PM2.5 concentrations from 2014 to 2023 in China. Our hierarchical model was validated by the sample-based 10 cross-validation . Results suggest that our model performs better in terms of RMSE of 12.12 µg/m3, MAE of 8.14 µg/m3 and R2 of 0.95 than traditional model with RMSE of 18.18 µg/m3, MAE of 12.21 µg/m3 and R2 of 0.89, showing 27.49–37.41% improvements for RMSE, 21.85–39.26% improvements for MAE and 8.31–15.39% improvements for R2 at three-folds samples. On longer time scales, our model also shows better results than previous studies. Additionally, for high-pollution provinces, our model can capture PM2.5 trends more preciously than the traditional model. Under severe haze, our hierarchical model can also rightly reflect PM2.5 changes. Overall, due to the hierarchical strategy, our ML-based model can obtain daily full-coverage PM2.5 maps in China with high accuracy and can be applied for follow-up studies.

Anti-Vibration Method for the Near-Bit Measurement While Drilling of Pneumatic Down-the-Hole Hammer Drilling

Pneumatic down-the-hole (DTH) hammer drilling technology has been used extensively in the fields of heat reservoir exploitation and geological exploration owing to its advantages of high efficiency and low pollution. However, the vibration near the bit is up to 40 g while DTH hammer drilling, which significantly affects the performance and longevity of the near-bit measurement while drilling (MWD). To enhance the environmental adaptability of the near-bit MWD in pneumatic DTH operations, a design method for a vibration-damping system based on the parameter optimization of a non-dominated sorting genetic algorithm II (NSGA-II) is proposed in this study. First, the whole structure of the near-bit MWD is designed, including the MWD sub-shell, sensors, measurement circuits, batteries, and connecting structures (the circuit unit). Secondly, this study analyzes the vibration characteristics of the pneumatic DTH hammer near the bit. According to the damping structure, the vibration response model for the circuit unit and the damping model are established. Thirdly, NSGA-II is employed to optimize the parameters of the damping model in terms of the low-frequency, high-intensity vibration characteristics near the bit in pneumatic DTH operations, thereby devising a damping scheme tailored to the unique conditions of DTH hammer drilling. Finally, vibration experiments were conducted to verify the effectiveness of the vibration-damping device. The experimental results indicate that within the vibration frequency range of 5–20 Hz and vibration level of 10–40 g, the peak attenuation rate of the circuit unit is more than 86.446%, and the improvement rate of the vibration stability of the system is more than 75.214%; the anti-vibration performance of the near-bit MWD system in DTH hammer drilling is improved remarkably. This study provides strong technical support for the stability of MWD equipment under such special working conditions. It has broad engineering application prospects.

Environmental impact of modern agricultural practices: Strategies for reducing carbon footprint and promoting conservation

Modern agricultural practices have significantly transformed food production, leading to increased efficiency and productivity. However, these advancements have also had notable environmental impacts, particularly concerning carbon emissions and resource depletion. This study explores the environmental impact of contemporary agricultural practices, emphasizing the need for strategies to mitigate carbon footprints and enhance conservation efforts. Agriculture contributes substantially to greenhouse gas emissions through sources such as livestock, synthetic fertilizers, and fossil fuel consumption. These emissions contribute to climate change and global warming. Additionally, modern farming practices often lead to deforestation, habitat loss, and soil degradation, exacerbating biodiversity loss and reducing soil health. Water usage in agriculture also poses significant challenges, with high water consumption and pollution from runoff affecting water resources and aquatic ecosystems. To address these issues, several strategies can be employed to reduce the carbon footprint of agriculture. Adoption of sustainable farming practices such as conservation tillage and no-till farming can enhance soil carbon sequestration, improving soil health and reducing emissions. Agroforestry and cover cropping further contribute by capturing atmospheric carbon and improving soil structure. The integration of renewable energy sources like solar and wind power in farming operations, along with energy-efficient technologies, can also reduce reliance on fossil fuels and lower overall greenhouse gas emissions. Promoting conservation involves implementing practices that protect and restore natural resources. Soil conservation methods, including erosion control techniques like terracing and contour plowing, help maintain soil health and prevent degradation. Efficient water management strategies, such as drip irrigation and rainwater harvesting, reduce water consumption and mitigate pollution from runoff. Biodiversity conservation can be supported through the preservation of natural habitats and the promotion of biodiverse farming systems, which enhance ecosystem resilience and stability. Effective policy frameworks and support mechanisms are crucial for driving the adoption of these strategies. Government policies, including environmental regulations and incentives, play a pivotal role in encouraging sustainable practices. Research and innovation are essential for developing new technologies and practices, while education and extension services ensure the dissemination of knowledge and best practices to farmers. Modern agricultural practices have significant environmental impacts, but through the adoption of sustainable practices and innovative strategies, it is possible to reduce carbon footprints and promote conservation. Continued research, supportive policies, and effective implementation of conservation strategies are essential for achieving a more sustainable agricultural future. Keywords: Environmental Impact, Agricultural Practices, Carbon Footprint.

Assessing the Heavy Metal Contamination Prevailing in Groundwater at Rishipur Village, West Bengal, India

The recent surge in interest surrounding water contamination has prompted a study to evaluate the water quality of groundwater in Rishipur village, Malda District, West Bengal, India. The area's groundwater is crucial for drinking, residential, and irrigation purposes due to its proximity to agricultural fields, where most local residents live. The intended purpose of the study is to comprehensively appraise the groundwater quality of a dug well, specifically analysing the intensities of different heavy-metals existing in the water, resulting in valuable insights into its quality. The native residents rely on the usage of this groundwater for drinking and domestic purposes without any purification. However, potential contamination may be present due to nearby agricultural activities. Thus, the study will enable us to make recommendations for mitigating any identified contamination. Exemplary samples of water from a well were consistently collected near the agricultural region over the course of a year, from April 2021 to March 2022. The groundwater samples were analysed for the presence of heavy elements: iron; zinc; copper; manganese; nickel; chromium; cobalt and lead to evaluate the water excellence. To ascertain the overall water eminence status, the Heavy-Metal-Pollution-Index; (HPI), was calculated, which is considered an efficient and reliable technique for water eminence assessment. In this study, the value of HPI; 101.66 in January, indicates high heavy-metal pollution, although it remained within the desired range for the rest of the months. In the analysis of the descriptive statistical data, both substantial positive and negative relations were observed, which were illustrated in a correlation coefficient matrix. Furthermore, the interaction of heavy-metal variables was also explored by utilising the R-Square values derived from the multiple linear regression analysis, which allowed to gain insights into how these variables interplayed with one another. The investigation conclusively established that the eminence of water is deemed appropriate for consumption alongside other domiciliary purposes, with the exception of January.

The asymmetric nexus between energy transition and its drivers: New evidence from China

The unpredictable surge in global warming and climatic issues urges serious efforts internationally to meet the Paris Agreement to keep the global temperature below 2 °C. Therefore, a sustainable solution is necessary for the future, as most regions are still under high pollution and carbon regimes borne by traditional sources of fuels. In this context, transitioning energy resources from conventional to more clean and sustainable energy resources is a key international political agenda. This study has investigated the asymmetric relationship of energy transition and its drivers in the case of China. The study employed time series data from 1989 to 2022 and adopted the nonlinear ARDL test. Through bounds testing, this study confirmed the existence of long-run asymmetric co-integration between the policy instruments. In the long and short run, the positive shocks of environmental technology augmented the asymmetric relationship with energy transition. However, it is interesting to observe that the positive shocks of green finance and trade openness has adverse effects on energy transition in the long run. Though, in the short run, a positive shock of trade openness improves the energy transition process. This study recommends policies to help policymakers and other stakeholders attain the SDG 7 goals.

Stabilization effect of nano-SiO2@iron-phosphorus on ferrallisols, calcareous soil and organic soil heavily polluted by heavy metals: A fast reaction curing stabilization process

The remediation of soil pollution by heavy metals (HMs) presents a significant challenge in environmental restoration. Stabilization remediation technology has proven effective in treating HMs contaminated soil. However, its development is constrained by drawbacks such as slow reaction kinetics and low adsorption capacity. This research synthesized a nano-SiO2@iron‑phosphorus (FPOH) material by SiO32− encapsulating the iron-phosphate precipitate obtained from Fe ion and phosphate. In addition, this research applied this material to ferrallisols, calcareous soils and organic soils with three different levels of high pollution by Cd, Pb, Cu and Zn. The experimental results indicate that all experimental soils stabilized rapidly within 1 day and met the requirements of remediation engineering standards (ChinaMEE HJ 1282-2023). Analysis of the possible mechanisms suggests that the FPOH material effectively fills voids with phosphate mineral formation, preventing the secondary release of HMs. During the stabilization process, FPOH involves the adsorption of free ions and small organic molecules in the soil, which does not affect its high reactivity. The development and utilization of FPOH offer valuable insights for soil stabilization remediation.

POLLUTION OF THE FIFTH CANAL ON THE CRNA RIVER IN THE REGION OF BITOLA

Water is an irreplaceable natural resource. The main goal of this research is to see the pollution of the fifth canal on Crna River in the region of Bitola. As measuring points for sampling for this analysis are: measuring point 1 (Crna River near the village of Novaci), measuring point 2 (fifth canal exit of Bitola), measuring point 3 (fifth canal near the village of Kravari) measuring point 4 (fifth canal before flowing into the Crna River), measuring point 5 (Crna River before being mixed with water from the fifth canal), measuring point 6 (Crna River after mixing with water from the fifth canal) and measuring point 7 (Crna River near the village of Skocivir). Water samples were taken in May and November. To determine the water quality, the following physicochemical parameters were made: turbidity (by turbidimeter), suspended solids, total organic carbon, biological oxygen demand, and dissolved oxygen (determined with UV pastel). From the results, it has been concluded that the highest pollution is in the fifth channel, measuring point 2 for the following parameters in May: turbidity (35.3 mg/L), total organic carbon (210.8 mg/L), suspended solids (77.5 mg/L, and in November164.0 mg/L). Of the measuring points of Crna River, the highest pollution is in measuring point 6 in November: biological oxygen demand (14.5 mg/L), and total organic carbon (13.7 mg/L). That is why it is suggested to purify the wastewater before it is released into the rivers.

Capillary container array structures for efficient, energy-saving, and sustainable evaporative cooling and humidification

Evaporative cooling is a widely employed method for air conditioning and heat dissipation, utilizing the phase transition of water to achieve simultaneous cooling and humidification. It relies on high-surface-area solid materials to enhance air-liquid contact upon wetting. However, these water-absorbing materials have drawbacks such as increased air resistance, degradation of water quality, and limited water retention capabilities. This study introduces a novel structure called the capillary container array (CCA) for effective humidification and cooling. The CCA structure overcomes the limitations of traditional methods by incorporating interconnected capillary containers with adjustable spacing and utilizing capillary forces to capture liquid droplets while minimizing the solid component. Compared to commercial paper-based wet curtains, the CCA structure offers significant advantages including strong water retention capabilities, high humidification performance, low air resistance and high pollution resistance. It increases water capacity by 6 times, humidification capacity by 8 %, and temperature drop by 2.2 °C. Moreover, it exhibits a 5-fold longer in water retention duration, a 30 % reduction in air pressure drop and a 3-fold increase in the performance coefficient, and maintains excellent water quality (<1 NTU) over prolonged operation. These advancements make the CCA structure highly promising for various applications in agriculture, industry and environmental conservation.

Response of bacterial and fungal communities in natural biofilms to bioavailable heavy metals in a mining-affected river

Biofilms, known as “microbial skin” in rivers, respond to rapid and sensitive environmental changes. However, the ecological response mechanisms of bacterial and fungal communities in river biofilms toward heavy metal pollution (HMP) remains poorly understood. This study focused on the key driving factors of bacterial and fungal community diversity and composition and their ecological response mechanisms within periphytic biofilms of Asia's largest Pb–Zn mining area. The diversity, dominant bacterial taxa, and bacteria structure in biofilms were influenced by biologically available heavy metal (HM) fractions, with Ni-F3 (17.96 %) and Pb-F4 (16.27 %) as the main factors affecting the bacterial community structure. Fungal community structure and α-diversity were more susceptible to physicochemical parameters (pH and nutrient elements). Partial least squares path modeling revealed that environmental factors influencing bacterial and fungal communities in biofilms were ranked as water quality > metal fractions > total metals. Dispersal limitation was the most critical ecological process in bacterial (56.9 %) and fungal (73.4 %) assembly. The proportion of heterogeneous selection by bacteria (39.5 %) was higher than that of fungus (26.2 %), which increased with increasing HMP. Bacterial communities had a higher migration rate (0.48) and ecological drift proportion (3.6 %), making them more prone to escape environmental stress. Fungal communities exhibited more keystone species, larger niche width (23.24 ± 13.04 vs. 9.72 ± 5.48), higher organization level, and a more stable co-occurrence network than bacterial communities, which enabled them to better adapt to high environmental pollution levels. These findings expanded the understanding of the spatiotemporal dynamics of microbial communities within biofilms in HM-polluted watersheds and provided new insights into the ecological responses of microbial communities to HMP.

The impact of the destruction of the Kakhovka reservoir dam on the oceanographic conditions in the north-western part of the Black Sea according to the results of modeling

Based on the results of numerical modelling, characteristic features of distribution of transformed and polluted waters of the Dnieper River in the water area of the north-western part of the Black Sea (NWBS) are determined and analyzed. This pollution of the marine environment resulted from the extremely large man-made flood caused by the destruction of the Kakhovka Reservoir dam by the Russian occupation forces in June 2023. Various types of pollutants, which contained in the Kakhovka Reservoir, in the lower Dnieper River and in the bottom sediments, were carried out into the sea by the flood discharge. A significant amount of pollutants was washed into the sea from the flooded areas of the lower Dnieper basin. Special attention is given to changes in oceanographic conditions in the Dnieper-Bug estuary region (DBR) of the Black Sea, which determine the extent of marine pollution. Sea water salinity was used as an indicator of the degree of infiltration of polluted seawater from the estuary into the sea. It was identified that the least transformed river waters with low salinity correspond to high pollution levels. Delft3D-Flow Flexible Mesh hydrodynamic model, developed by Deltares, was used in this study. The simulation was performed for the time period 01 to 30 June 2023. During the first days after the dam break the desalinated and polluted transitional waters, flowing from the Dnieper-Bug estuary, spread over the entire water column down to 15-20 m depth in the DBR area. In this case, the spreading of transitional waters was atypical, as it usually occurs only within the thin near-surface layer of the sea. By mid-June the flow of transitional water with a salinity of 4-6 ‰ covered the entire water column from surface to bottom near the northern coast of the NWBS and over the Odessa Bank. This was facilitated by the supermassive volumes of transformed Dnieper river waters flowing out over a short period of time due to dam break, as well as by the resulting intense gradient currents and mixing caused by spatial gradients in the velocity of the generated currents. The width of the desalinated water plume and its area in the bottom layer were smaller than in the surface layer. The largest vertical salinity gradients were formed to the south of the Odessa Bank, where salinity was 4-6 ‰ in the surface layer and 14-17 ‰ in the bottom. Dilution of the desalinated water plume in the bottom water layer was much more intensive than in the surface water. The character of water circulation pattern in the northern part of the NWBS in the first days after the inflow of transient waters from the Dnieper-Bug estuary was determined by the runoff gradient currents, which later were replaced by wind-driven currents in the Odessa area and over the Odessa Bank, and by the meandering flow of gradient density currents further south. The findings of this study contribute to a better understanding of the impact of the inflow of transformed river waters from the Dnieper-Bug estuary on the variability of oceanographic characteristics and the ecological state of marine waters in the Dnieper-Bug region of the northwestern Black Sea.

Comparative Analysis of Heavy Metal Content in Impacted Third Molars from Industrial and Non-Industrial Areas and Its Effect on the Isolation, Culture, and Proliferation of Dental Stem Cells (DSCs).

Background: This study investigates the impact of environmental pollution on the quality and viability of dental stem cells (DSCs) from impacted third molars. By comparing DSCs from patients in industrial areas with high air pollution and those from non-industrial regions, the research assesses the adverse effects of heavy metals on stem cell proliferation. Methods: Impacted lower third molars were collected from 28 patients-10 from industrial and 18 from non-industrial areas. Patients were divided into two age groups: 18-27 years and 28-38 years old. Dental pulp was extracted under sterile conditions, and DSCs were isolated and cultured. Heavy metal concentrations in dental tissues were measured using atomic absorption/emission spectrometry. Results: The study found significantly higher concentrations of copper and lead in the dental tissues of patients in industrial areas. Cell viability was lower in samples from these areas, with a statistically significant difference in average doubling time and the number of cells obtained after the first passage. There was no significant impact of gender on heavy metal content, except for higher iron levels in men. Conclusions: Exposure to industrial pollutants negatively affects the viability and proliferation of DSCs, but there are no differences in differentiation in the osteogenic medium regarding cell mineralization. These studies highlight the importance of environmental factors for oral health, suggesting that residents of polluted areas may face greater difficulties in dental and regenerative treatments. Further research is needed to develop strategies to mitigate the effects and improve clinical outcomes for affected populations.

Extreme particulate matter exposure at traffic intersections in a densely populated city

Commuters are exposed to significantly high pollution levels at traffic intersections. This study utilized the generalized Pareto distribution to model commuters’ exposure to extreme particulate matter (PM) levels across 36 traffic intersections in Varanasi, India. A Bayesian hierarchical framework was deployed to account for the seasonal variation. The monthly return levels for extreme PM2.5 (PM10) were 589 (1127), 474 (961), and 429 (902) µg/m3 during winter, spring, and summer, respectively. The extreme PM2.5 and PM10 concentrations exceeded the NAAQS severe category for all three seasons. There is a 0.72 % (1.47 %) chance that during winter, PM2.5 (PM10) levels would exceed that of the Delhi smog event (PM2.5: 585 µg/m3, PM10: 989 µg/m3). These findings raise concerns about public health and the environment, particularly in winter. The results would guide policymakers in enforcing stringent measures to reduce extreme exposures at traffic intersections in densely populated cities.

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.

High altitude air pollution and respiratory disease: Evaluating compounded exposure events and interactions

Today, air pollution remains a significant issue, particularly in high-altitude areas where its impact on respiratory disease remains incompletely explored. This study aims to investigate the association between various air pollutants and outpatient visits for respiratory disease in such regions, specifically focussing on Xining from 2016 to 2021. By analysing over 570,000 outpatient visits using a time-stratified case-crossover design and conditional logistic regression, we assessed the independent effects of pollutants like PM2.5, PM10, SO2, NO2, and CO, as well as their interactions. The evaluation of interactions employed measures such as relative excess odds due to interaction (REOI), attributable proportion due to interaction (AP), and synergy index (S). We also conducted a stratified analysis to identify potentially vulnerable populations. Our findings indicated that exposure to PM2.5, PM10, SO2, NO2, and CO significantly increased outpatient visits for respiratory disease, with odds ratios (ORs) of 2.40 % (95 % CI: 2.05 %, 2.74 %), 1.07 % (0.98 %, 1.16 %), 3.86 % (3.23 %, 4.49 %), 4.45 % (4.14 %, 4.77 %), and 6.37 % (5.70 %, 7.04 %), respectively. However, exposure to O3 did not show a significant association. We found significant interactions among PM2.5, SO2, NO2, and CO, where combined exposure further exacerbated the risk of respiratory diseases. For example, in the combination of PM2.5 and SO2, the REOI, AP, and S were 0.07 (95 % CI: 0.06, 0.09), 0.07 (0.06, 0.07), and 1.07 (1.05, 1.09), respectively. Additionally, elderly individuals and females were more sensitive to these pollutants, but no statistically significant interaction effects were observed between different age and gender groups. In conclusion, our study highlights the strong link between air pollution and respiratory disease in high-altitude areas, with combined pollutant exposure posing an even greater risk. It underscores the need for enhanced air quality monitoring and public awareness campaigns, particularly to protect vulnerable populations like the elderly and females.

Evaluating nitrogen dynamic and utilization under controlled-release fertilizer application for sunflowers in an arid region: Experimental and modeling approach

Traditional nitrogen fertilizers (TNF), such as urea, percolate easily in arid fields, posing low nitrogen use efficiency (NUE) and a high non-point pollution risk. Controlled-release fertilizers (CRF) exhibit significantly lower deep seepage, rendering it a favorable choice in arid fields due to its ability to enhance NUE through slow-release mechanisms. However, current models do not fully account for the soil nitrogen dynamics and crop interactions under controlled-release conditions, and lack quantification. This study improved the APSIM model by adjustment the urea hydrolysis rate to assess the impact of CRF and TNF applications on soil health, crop growth, and water quality. Calibration and validation were conducted through experiments in the Hetao Irrigation District of China from 2019 to 2020, with different nitrogen application rates (135, 225, and 315 kg/ha). The model accurately simulated soil NO3-N concentration (SNC), cumulative NO3-N leaching (CNL), nitrogen uptake (NU), and sunflower yield. During the validation process, R2 and Nash-Sutcliffe efficiency (NSE) values were both above 0.75. Results indicated that the average SNC, NU, and yield under CRF application were significantly higher than those under TNF application, with increases of 38.62%, 44.92%, and 18.38%, respectively. Notably, the proportion of soil nitrogen available (PSNA), a novel metric proposed in this study, was 159.50% higher in the 0–40 cm soil layer with CRF compared to TNF. Additionally, CNL and NO3-N leaching loss rate (NLLR) decreased by 25.76% and 25.77%, respectively. Scenario simulations indicated that the optimal fertilization strategy for this region is to use 180–193.5 kg/ha of CRF with a release period of 80–85.5 d to balance agricultural productivity and ecological protection. This study confirms the significant advantages of CRF in enhancing yield, improving nitrogen management, and promoting environmental sustainability, providing a scientific basis for CRF management strategies and supporting the shift towards more efficient and environmentally friendly agricultural practices.

Optimization of a novel hydrogen production process integrating biomass and sorption-enhanced reforming for reduced CO2 emissions

Recently, there has been a growing demand for clean and sustainable energy sources to bridge the energy gap. Hydrogen has emerged as an attractive and environmentally friendly energy carrier due to its potential for high energy efficiency and minimal pollution generation, making it a promising alternative to fossil fuels. This study proposes and investigates a novel coupled process that utilizes chemical looping technologies for hydrogen production, simultaneously utilizing natural gas and biomass as feedstocks. The primary objective of this research is to develop a process model that maximizes hydrogen production while minimizing carbon dioxide emissions. Aspen Plus version 10 was employed to simulate and analyze the proposed process configuration to achieve this. One of the proposed process's key advantages is its competitiveness compared to conventional steam methane reforming (SMR) processes, which are widely used in industry. The novel process offers significant benefits, such as enhanced hydrogen purity and reduced CO2 content in the product gas. The simulation results obtained from Aspen Plus reveal the successful production of highly pure hydrogen with a molar ratio of H2/CO equal to 268 and syngas with a molar ratio of H2/CO approximately equal to 1. Additionally, the process demonstrates the capability to produce highly high-purity hydrogen with a molar ratio of H2/CO equal to 155,000 in three-section reactors.

Can ecological zoning act as an environmental management tool for protecting regional habitat quality: Causal evidence from the national key ecological function zone in China

Habitat degradation is one of the most serious environmental problems worldwide, which threatens human wellbeing and sustainable development. Exploring how to protect natural habitats has become a research hotspot in the environmental management field. Ecological zoning has been widely used in habitat protection, but its actual effectiveness has been rarely revealed, especially with the robust and reliable causal inference method. Therefore, taking the Yangtze River Economic Belt (YREB) in China as the study area, we first quantified habitat quality and changes at the district/county scale during 2005–2019. Then, we used the National Key Ecological Function Zone (NKEFZ) as a representative ecological zone scheme, and explored the effectiveness of the NKEFZ in protecting habitat quality with the Propensity Score Matching and Difference-in-Difference combined method, which is a representative causal inference method. We found that habitat quality showed an uneven distribution during the study period, and habitat quality of districts/counties within the NKEFZ was higher than that outside the NKEFZ with statistical significance. Most districts/counties experienced a habitat quality decrease, but the decrease within the NKEFZ is less than that outside the NKEFZ. We observed that the NKEFZ can protect habitat quality from the causal relationship perspective, but there was the spatio-temporal heterogeneity of the NKEFZ effectiveness. In terms of the spatial dimension, the NKEFZ was the most effective in the Lower Reach of the YREB. In terms of the temporal dimension, there was a 1-year time-lag effect of the NKEFZ effectiveness, and NKEFZ effectiveness experienced a sharp increase from 2016. The NKEFZ contributed to protecting habitat quality through multiple management strategies such as urban land quota, high pollution industry prohibition, and ecological compensation. Overall, this study verified that the ecological zone scheme can contribute to habitat quality protection, and emphasizes that the effectiveness of ecological zoning may vary across time and space. This work can support ecological zoning implementation with robust evidence, and provides a novel perspective for understanding the effectiveness of ecological zoning.

Global assessment of climatic responses to ozone–vegetation interactions

Abstract. The coupling between surface ozone (O3) and vegetation significantly influences the regional to global climate. O3 uptake by plant stomata inhibits the photosynthetic rate and stomatal conductance, impacting evapotranspiration through land surface ecosystems. Using a climate–vegetation–chemistry coupled model (the NASA GISS ModelE2 coupled with the Yale Interactive terrestrial Biosphere, or ModelE2-YIBs), we assess the global climatic responses to O3–vegetation interactions during the boreal summer of the present day (2005–2014). High O3 pollution reduces stomatal conductance, resulting in warmer and drier conditions worldwide. The most significant responses are found in the eastern US and eastern China, where the surface air temperature increases by +0.33 ± 0.87 and +0.56 ± 0.38 °C, respectively. These temperature increases are accompanied by decreased latent heat and increased sensible heat in both regions. The O3–vegetation interaction also affects atmospheric pollutants. The surface maximum daily 8 h average O3 concentrations increase by +1.46 ± 3.02 ppbv in eastern China and +1.15 ± 1.77 ppbv in the eastern US due to the O3-induced inhibition of stomatal uptake. With reduced atmospheric stability following a warmer climate, increased cloud cover but decreased relative humidity jointly reduce aerosol optical depth by −0.06 ± 0.01 (−14.67 ± 12.15 %) over eastern China. This study suggests that vegetation feedback should be considered for a more accurate assessment of climatic perturbations caused by tropospheric O3.