Issue 08, 2026
Dynamic compaction characteristics and model construction of fly ash subgrade filling in road engineering
Hui Yingxin;Zheng Liyang;Guo Jukun;Yan Sheng;Dong Xuguang;Gu Shizhou;Using fly ash as a roadbed filler represents a significant and innovative advancement in civil engineering. This approach not only offers a sustainable solution for utilizing industrial solid waste but also helps alleviate the environmental pressures associated with waste disposal. By replacing traditional road construction materials with fly ash, engineers can reduce costs while simultaneously contributing to eco-friendly infrastructure development. However, the effective implementation of fly ash in roadbed construction presents challenges, with compaction control emerging as a critical issue. Poor compaction can lead to a range of problems, including uneven settlement, reduced bearing capacity, and compromised roadbed integrity. These issues can significantly impact the long-term performance and durability of the pavement, potentially resulting in costly repairs and safety hazards. To address these challenges, this study conducts a series of comprehensive electric compaction experiments and vibration compaction tests. By meticulously adjusting key parameters such as water content, compaction effort, vibration duration, and vibration frequency, the research aims to identify the optimal conditions for achieving maximum dry density and uniform compaction. The experimental results, rigorously validated through mathematical modeling, reveal several key insights. The relationship between dry density and water content follows a unimodal trend, with peak dry density occurring at an optimal water content of 44%-45%. Moreover, dry density increases with the number of compaction blows, reaching a satisfactory range of 1.05-1.14 g/cm3 after 98 blows. Interestingly, while dry density consistently increases with vibration frequency, it exhibits a peak at 30 seconds of vibration duration; beyond this point, excessive vibration may induce liquefaction, leading to a reduction in density. Based on these findings, a comprehensive compaction model covering the transition from drying to liquefaction is established. This model facilitates accurate predictions of dry density under various conditions, providing valuable references for optimizing construction parameters and enhancing compaction control. By implementing these optimized parameters, engineers can ensure more uniform and stable roadbeds, thereby promoting the wider application of fly ash in road construction. This, in turn, contributes to environmental sustainability and the development of resilient infrastructure, paving the way for a greener and more sustainable future.
Performance of ammonium oxalate modified orange peel on TVOC
Chen Li;Du Xiyuan;Cheng Zhaoxia;Xiong Xiaoming;This study aimed to develop an efficient biosorbent from agricultural waste, specifically orange peel, for the removal of indoor Total Volatile Organic Compounds(TVOC). The chemical pectin-breaking process was optimized using a quadratic regression orthogonal rotation design, with optimal conditions determined as follows: ammonium oxalate concentration of 0.16 mol/L, water bath temperature of 56.54 ℃, and water bath duration of 23.18 minutes, resulting in a maximum adsorption rate(Ymax) of 8.75%. Comprehensive characterization of the modified orange peel was conducted using BET, SEM, EDS, and FT-IR techniques. The results revealed a significant increase in specific surface area(from 60.332 m2/g to 210.325 m2/g), larger pore volume, and a more developed microporous structure, which collectively contributed to exposing a greater number of active functional groups(e.g., —OH and CN) that are beneficial for adsorption. Single-factor experiments identified the optimal adsorption conditions as a particle size of 100 mesh, a dosage of 5 g, and an adsorption temperature of 26 ℃. Analysis of adsorption equilibrium indicated that the adsorption isotherm was better fitted by the Freundlich model(R2 = 0.937 1), suggesting multilayer adsorption on heterogeneous active sites. Similarly, the adsorption kinetics followed the pseudo-second-order model(R2 = 0.980 9), indicating a physicochemical adsorption process primarily driven by chemical interactions. Thermodynamic analysis confirmed that the adsorption process was spontaneous and endothermic. In a comparative assessment with common commercial adsorbents, the modified orange peel exhibited significantly higher TVOC removal efficiency at the 1% significance level, ranking from best to worst as follows: modified orange peel, diatomite, activated carbon, macroporous resin, and bamboo charcoal. Furthermore, it demonstrated excellent regeneration capability, retaining 69.2% of its initial adsorption capacity after six adsorption-desorption cycles, highlighting its potential for repeated use. This work provides a sustainable and cost-effective approach for TVOC pollution control and the valorization of agricultural waste, offering a promising strategy for “treating waste with waste.”
Research on VOCs emission reduction pathways in the catering industry: a case study of Beijing
Lu Qiuqin;Xiao Xiao;With the rapid development of China's economy, the market size of the catering industry has been continuously expanding. However, Volatile Organic Compounds(VOCs) generated by this sector have placed significant pressure on both the ecological environment and public health. This study aims to reduce VOCs emissions from the catering industry. By reviewing relevant literature, it briefly analyzes the challenges associated with VOCs emissions and the motivations for emission reduction within the sector. The study synthesizes local regulations regarding pollutant emissions in the catering industry and related theoretical frameworks, proposing four emission reduction pathways: policy-driven, equipment improvement, digital technology, and green preference, and examines the operational mechanisms of each pathway. Subsequently, utilizing system dynamics theory and Vensim software, a system dynamics model was developed to simulate the dynamic evolution process of VOCs emission reduction in the catering industry and quantify the implementation effects of different reduction pathways. Using Beijing as a case study, relevant data were employed for stability and historical validation. Once the model's effectiveness was confirmed, simulation modeling was conducted, comparing the baseline scenario with the four proposed reduction pathways. The results indicate that all four pathways positively influence VOCs reduction in Beijing's catering industry, although the intensity and evolution trends vary significantly. Among them, the equipment improvement pathway demonstrated the most substantial effect, while the green preference, policy-driven, and digital technology pathways exhibited comparatively weaker impacts. Furthermore, when these pathways are combined, a comprehensive reduction strategy emerges, which was then compared to the baseline scenario. Based on these findings, recommendations for reducing VOCs emissions in the catering industry are provided: during the VOCs reduction process, adopt a governance approach centered on ‘technology empowerment as the core, policy guidance as the guarantee, and multi-faceted collaboration as the pathway, ' prioritizing equipment improvements and integrated multi-path measures to achieve continuous emission reductions and contribute to enhanced urban air quality.
Performance and mechanism of FOX-7 wastewater degradation by the FeCo-MOF-71/PMS system
Tian Weiping;Yun Weiwei;This study investigates the degradation performance of FeCo-MOF-71 activated Peroxymonosulfate(PMS) for wastewater treatment. FeCo-MOF-71 was successfully synthesized via a solvothermal method and systematically characterized using X-ray Photoelectron Spectroscopy(XPS) to elucidate its chemical composition and surface charge characteristics before and after the reaction. The catalytic performance of FeCo-MOF-71-activated PMS in degrading FOX-7 was evaluated by examining the effects of catalyst dosage and PMS concentration, benchmarking against relevant literature, and assessing reusability through cycling experiments. Furthermore, in-depth mechanistic studies were performed to elucidate the underlying catalytic oxidation pathways. The results demonstrated that under optimal conditions(0.3 g/L FeCo-MOF-71 and 0.4 g/L PMS), a Chemical Oxygen Demand(COD) removal efficiency of 95.3% was achieved for FOX-7 wastewater, with a reaction rate constant of 0.030 min-1. After four consecutive cycles, the removal efficiency remained consistently at 82.4%, while metal leaching was well below 1.22 mg/L, demonstrating exceptional structural stability and ensuring high environmental safety. Radical quenching experiments revealed that sulfate radicals(SO4~-·) and hydroxyl radicals(·OH) were the predominant reactive species during the degradation process, indicating that FOX-7 removal was primarily driven by non-selective radical oxidation pathways with strong oxidative capacity and good environmental adaptability, thus enabling effective degradation of refractory pollutants. XPS analysis showed a significant change in the ratio of iron and cobalt ions in different valence states before and after catalyst use, suggesting that the synergistic redox cycles between Fe and Co(Co2+/Co3+ and Fe2+/Fe3+) effectively facilitated PMS activation, leading to a substantial improvement in pollutant removal rates. The presence of bimetallic sites contributed to enhanced catalytic activity and significantly reduced metal leaching. This study provides an environmentally friendly solution for the effective treatment of FOX-7 production wastewater and establishes a strong theoretical foundation for the development of novel bimetallic MOF catalysts. These advancements offer substantial potential for optimizing industrial wastewater treatment, presenting both practical and sustainable solutions for environmental management.
Study on splatter patterns of leaked electrolyte from energy storage battery compartments under fire water jet impact
Tao An;Shi Zhaohui;Zhang Lei;Hu Sen;Tan Bo;PowerChina Huadong Engineering Corporation Limited;State Key Laboratory of Hydraulics and Mountain River Engineering;This study utilized a geometrically scaled-down model(scale factor λ=62.22), combined with fluorescent tracing and 13 systematically designed fire water jet schemes, to analyze electrolyte splatter behavior. The experimental matrix consisted of two groups based on jetting height(3.11 m and 4.98 m) crossed with various horizontal distances(4.36-13.69 m), resulting in 13 unique test conditions. Fluorescent tracing techniques were employed to quantitatively map splatter patterns under each hydraulic condition. The test groups were strategically designed to encompass the full operational range of firefighting schemes, including:(1) short-range high-angle jets(horizontal distances 4.36-6.22 m; height 4.98 m),(2) short-range low-angle jets(horizontal distances 4.36-6.22 m; height 3.11 m),(3) medium-range high-angle jets(horizontal distances 7.47-9.33 m; height 4.98 m),(4) medium-range low-angle jets(horizontal distances 7.47-9.33 m; height 3.11 m),(5) long-range high-angle jets(horizontal distances 10.58-13.69 m; height 4.98 m), and(6) long-range low-angle jets(horizontal distances 10.58-13.69 m; height 3.11 m). Fluorescent tracing techniques were applied alongside these 13 distinct fire water jet schemes to systematically capture splatter dynamics under varying hydraulic conditions. The experimental results revealed that jet impact intensity significantly influenced splatter behavior. At low-impact velocities(≤7.52 m/s), the electrolyte splatter was primarily governed by its high viscosity, leading to localized deposition with minimal droplet fragmentation. In contrast, high-velocity impacts(>7.52 m/s) resulted in surface tension instability, causing liquid film breakup and subsequent atomization into fine droplets with extended splatter ranges. All tested jetting schemes exhibited a consistent bimodal distribution pattern characterized by a dense near-field flow zone and a far-field droplet splatter zone, separated by a transitional region of reduced splatter density. Comparative analysis indicated that existing protective measures, such as fixed-radius drainage trenches(≤5 m), failed to contain 95% of hazardous splatter, particularly under critical conditions where maximum splatter distances reached 11.36 m. To address this limitation, we proposed a tiered protection strategy based on observed splatter patterns. This design incorporated impermeable extensions using High-Density Polyethylene(HDPE) membranes combined with acid-resistant concrete cladding, dynamically adjusted to match operational jetting distances(5-15 m coverage for high-pressure schemes). Validation confirmed that this approach could effectively intercept 98.7% of distal droplets while accommodating spatial variations in splatter density. These findings provide a theoretical foundation for scientifically containing leakage incidents and revising protection standards in electrochemical energy storage systems.
Analysis of the instantaneous impact of subway train arrival and departure on in-station PM2.5 mass concentration
Feng Le;Wan Chuanfeng;Feng Jian;Yang Yiyang;Wei Wei;Liu Chunlan;Chen Long;Yang Ning;Beijing Municipal Research Institute of Eco-Environmental Protection;This study investigates the relationship between train arrival and departure scenarios and PM2.5 dispersion in underground metro stations. Representative monitoring sites were selected on an underground platform, and data were collected over 12 working days in June 2025. The field monitoring covered six different train arrival and departure scenarios. Data cleaning was performed using the Interquartile Range(IQR) method, and missing data were imputed through linear interpolation based on time series continuity and valid neighboring records. Spatial correlation was addressed using the Inverse Distance Weighting(IDW) method to fuse observations from adjacent sites. The final dataset was derived by integrating temporal interpolation with spatial weighting results, allowing for a systematic analysis of the spatiotemporal variation patterns of PM2.5 mass concentration in the metro stations. The results indicated that PM2.5 mass concentrations exhibited periodic fluctuations, with brief increases during the early morning peak followed by a continuous decrease. The fluctuation ranges diminished as train operation frequency declined, with mean mass concentration variations ranging from 75-195 μg/m3. Mean PM2.5 mass concentrations were positively correlated with train arrival and departure frequency. Spatially, higher mass concentrations were observed at the ends of the platforms compared to the central area, and symmetric sites near platform screen doors showed similar levels of mass concentration. PM2.5 levels ranked in descending order as follows: bilateral simultaneous arrival(198 μg/m3), unilateral arrival and departure, bilateral simultaneous departure, unilateral arrival, and unilateral departure(105 μg/m3). Notably, mass concentrations during bilateral simultaneous departures were 30%-50% lower than those during simultaneous arrivals. This study is the first to quantify the transient impacts of train operations on platform PM2.5 mass concentrations. Based on the findings, we recommend implementing intelligent ventilation controls integrated with a collaborative PM2.5 dispersion model. Priority should be given to monitoring site 1-1, located at the platform end in the direction of arrival with a higher frequency of departures. The results also suggest that differentiated waiting strategies can effectively minimize exposure to high PM2.5 mass concentrations. For single-sided arrivals, the far end of the arrival side serves as a low-exposure area, while for bilateral simultaneous arrivals, the platform center is the optimal waiting location. Compared to the near end of the arrival side and the platform ends, these strategies can reduce PM2.5 exposure by 34% and 45%, respectively.
Air quality prediction model based on improved Transformer-BiLSTM
Cui Yanrong;Wang Chunzhou;Accurate prediction of the Air Quality Index(AQI) is crucial for environmental governance, pollution early warning, and the development of effective prevention and control policies. To address the limitations of existing Transformer-BiLSTM-based prediction models—such as challenges in processing time-frequency data, insufficient capture of local temporal variation dependencies, and inadequate extraction of salient features—this study proposes an enhanced air quality prediction model. This model integrates a feature fusion embedding layer, a residual attention encoder, and a Temporal Convolutional Network(TCN). The proposed model decomposes the input time series into the frequency domain using Fast Fourier Transform, and the filtered frequency-domain features are fused with time-domain features after high-pass filtering to construct a more comprehensive feature representation. The residual attention encoder consists of one multi-head self-attention block and two residual blocks, where the multi-head self-attention mechanism works in conjunction with the Squeeze-and-Excitation attention mechanism to enhance the model's focus on critical features associated with air quality changes. The stacked residual blocks help mitigate issues of gradient vanishing and explosion during model training, thereby improving the model's representation capability and stability. Dilated convolutions within the TCN are employed to expand the receptive field and effectively capture local temporal dependencies that are often overlooked by global attention mechanisms. Finally, the bidirectional structure of BiLSTM enhances the model's sequential understanding and fully leverages contextual information in both forward and backward directions. Experiments conducted using a dataset containing pollutant concentrations and meteorological data from 12 districts in Wuhan City in 2024 demonstrate that, compared to baseline models, the proposed model reduces the root mean square error, mean absolute error, and mean absolute percentage error in AQI prediction by 53.1%, 57.5%, and 14.79 percentage points, respectively, achieving superior predictive performance and offering a novel and effective approach for air quality forecasting.
Ecological risk assessment of potentially toxic elements in industrial parks by integrating plant leaf bioindicators
Zhou Meichun;Peng Qian;Ge Jiali;Shen Fanglin;Yang Meng;This study establishes a comprehensive ecological risk assessment framework for Potentially Toxic Elements(PTEs) in industrial parks by integrating plant leaf bioindicators. It addresses existing knowledge gaps in evaluating multi-media migration pathways, including root uptake and foliar absorption, as well as multi-source pollution in complex industrial environments. Three common shrub species—Buxus megistophylla, Pittosporum tobira, and Photinia serrulata—were selected as bioindicators. To ensure consistency in environmental exposure conditions, synchronous sampling of leaves and 0-20 cm soil samples was conducted around the plants at each of the 28 sampling points. Concentrations of Cd, As, Mn, Zn, Cr, Cu, Ni, and Pb were quantified using Inductively Coupled Plasma Mass Spectrometry(ICP-MS). The Bioconcentration Factor(BCF) and Capture Rate(CR) were utilized to assess root uptake and foliar absorption. Ecological risk was evaluated using Håkanson's potential ecological Risk Index(RI). Source apportionment and contribution quantification were performed through Principal Component Analysis-Multiple Linear Regression(PCA-MLR). Results indicated that the average RI of soil PTEs was 115.86, suggesting a moderate overall ecological risk. Cd emerged as the predominant high-risk element, with an average single ecological risk index(E) of 72.42, categorized as moderate risk. Among all 28 sampling points, five exhibited a strong-risk status while three reached very strong-risk levels for this element. Arsenic was identified as the secondary high-risk element, with several samples exceeding the Class Ⅱ land screening value set forth in GB 36600—2018 of China(60 mg/kg). PCA-MLR revealed four sources: Alloy Manufacturing(AM; 44.0% RI contribution), Chemical Industry(CHEM; 30.0%), Thermal Power Generation(TPP; 15.0%), and Traffic(TP; 11.0%). AM and CHEM collectively contributed 74% to the RI, with Cd being the primary emitted element from these sources. Arsenic was chiefly associated with TPP emissions. Notably, thermal power generation and traffic sources contributed more significantly to the total PTEs in soil compared to those in leaves. Pittosporum tobira demonstrated efficient soil Cd bioaccumulation capacity, with a maximum bioconcentration factor reaching 6.42. Moreover, arsenic showed substantial retention of particulate matter-bound PTEs, with an average foliar capture rate of 57%. This indicates that atmospheric particulate matter capture and subsequent absorption are critical exposure pathways for this contaminant. For targeted remediation, Pittosporum tobira is recommended for planting adjacent to AM/CHEM facilities to facilitate the removal of soil Cd through periodic pruning of aboveground biomass. A mixed-shrub configuration, incorporating all three species, is advised throughout the park, particularly downwind of the thermal power plant, to mitigate atmospheric arsenic exposure risks via synergistic particulate matter capture. This study integrates pollution source identification, quantification of bioaccumulation and capture traits, and optimized species selection, thereby providing scientific support for precision management of PTE contamination in industrial parks.
Nonlinear impact and multi-scenario prediction of carbon emissions in the Yangtze River Delta urban agglomeration
He Gang;Li Bingyan;Wu Ting;Zhang Shangyun;Zhou Jian;In advancing the global endeavor of climate governance, achieving a deep decoupling between economic development and carbon emissions is of utmost importance. This study first employs cold-hot spot analysis and Moran's index to assess the current carbon emission situation in the Yangtze River Delta urban agglomeration. It then utilizes the Kaya Identity-Logarithmic Mean Divisia Index(Kaya-LMDI) model to measure the impact of various influencing factors on carbon emissions. Subsequently, the study constructs the Stochastic Impacts by Regression on Population, Affluence, and Technology(STIRPAT) non-parametric additive regression model to diagnose the nonlinear interactions among population size, economic development, energy consumption, and industrial added value with respect to carbon emissions. Finally, it applies a multi-scenario analysis method to predict carbon emissions and peak carbon levels for each city in the Yangtze River Delta region from 2024 to 2035. The results indicate:(1) Carbon emissions in the Yangtze River Delta urban agglomeration have generally increased from 2009 to 2023.(2) According to the Logarithmic Mean Divisia Index(LMDI) calculations, economic benefits have the most significant impact on carbon emissions across cities in the Yangtze River Delta urban agglomeration among the five factors analyzed. From 2009 to 2023, the carbon emissions exhibited a “U”-shaped nonlinear relationship with economic development, with fitting results for three time slices and three urban clusters demonstrating fluctuating patterns.(3) Provincial-level predictions show that the peak timing of carbon emissions occurs earlier in Shanghai City and Zhejiang Province, is intermediate for Jiangsu Province, and later for Anhui Province. At the group level, predictions indicate that the peak carbon emissions for the second and third groups of cities will occur between 2025 and 2030, while first and fourth groups face more severe challenges. Under different emission reduction scenarios, the timing and levels of peak carbon emissions for each province and city within the Yangtze River Delta urban agglomeration vary significantly. These research findings provide a scientific basis for formulating differentiated regional emission reduction management strategies.
New quality productive forces enabling the synergistic effect of pollution reduction and carbon emission reduction: mechanisms and empirical evidence
Nie Lei;Wang Xuerong;Zhang Jing;This study empirically investigates the impact of New Quality Productive Forces(NQPF) on the synergistic effects of pollution reduction and carbon mitigation, utilizing a comprehensive panel dataset from 284 Chinese prefecture-level cities spanning 2011 to 2023. Methodologically, we first construct a theoretical framework and measure the levels of urban NQPF and the synergy index. We then employ a two-way fixed effects model to identify the direct causal relationships and a mediation effect model to uncover the underlying transmission mechanisms. To address potential endogeneity concerns, we implement an Instrumental Variables Two-Stage Least Squares(IV-2SLS) approach, with robustness further confirmed through multiple checks, including winsorization, alternative variable measures, sample period adjustments, additional control variables, and a Spatial Durbin Model that accounts for spatial dependence. Our findings are robust and highly significant. First, NQPF exerts a substantial positive effect on synergy levels. Specifically, a 0.1-unit increase in the NQPF index leads to a 1.58-percentage-point improvement in synergy levels. This effect exhibits notable heterogeneity, being significantly more pronounced in non-resource-based cities and those located in eastern China. Second, mechanism analysis confirms that NQPF operates primarily through two key channels: by strengthening industrial chain resilience and by improving energy efficiency, thereby enabling synergistic gains. Third, our investigation into boundary conditions reveals a critical negative moderating effect of Fiscal Investment Intensity, suggesting that traditional government spending may crowd out resources for green innovation. In stark contrast, the Degree of Openness demonstrates a strong positive moderating effect, as international engagement facilitates the inflow of advanced green technologies and management practices. In conclusion, this research provides compelling empirical evidence that NQPF is a pivotal driver for achieving integrated environmental governance. It not only confirms the direct positive impact but also meticulously delineates its operational pathways and contextual contingencies. The findings strongly advocate for policy strategies that prioritize the cultivation of NQPF through technological innovation and industrial upgrading. Furthermore, it is imperative to optimize fiscal expenditure structures away from traditional high-carbon investments and towards green initiatives, while simultaneously deepening international cooperation to fully unlock the immense synergistic potential of NQPF in driving a comprehensive green socio-economic transformation.