Actual Monitoring Research Articles

Fugacity-based multimedia transport modeling and risk assessment of PAHs in Urumqi

Currently, there is a lack of a comprehensive understanding of the behavior of polycyclic aromatic hydrocarbons (PAHs) in complex multimedia urban environmental systems. Taking Urumqi City as a case study, we developed an integrated multimedia urban environmental model to simulate the inter-media transport processes of PAHs across air, water, soil, sediment, vegetation, and impervious surfaces. The predictive results of this model were in good agreement with the actual monitoring data from 2021, confirming its accuracy. Notably, the simulated data for 2021 indicate that the total amount of PAHs in the soil reached 1.06 × 106 kg, accounting for 97.44% of the total PAHs in Urumqi City, highlighting soil as the primary sink for PAHs. Further analysis of transport fluxes revealed that atmospheric transfer pathways to soil and vegetation are the main mechanisms driving the distribution of PAHs in urban environments. Additionally, sensitivity analysis identified temperature, soil, and vegetation-related parameters as the primary factors influencing PAHs. Based on the simulated concentration, the risk assessment results showed that soil PAHs had a higher risk of carcinogenesis to human body. This study deepens our understanding of the behavior of PAHs in urban environments and provides insights into how human activities affect the fate and transformation of these contaminants in multimedia urban systems.

Modal Parameter Identification of the Improved Random Decrement Technique-Stochastic Subspace Identification Method Under Non-Stationary Excitation

Commonly used methods for identifying modal parameters under environmental excitations assume that the unknown environmental input is a stationary white noise sequence. For large-scale civil structures, actual environmental excitations, such as wind gusts and impact loads, cannot usually meet this condition, and exhibit obvious non-stationary and non-white-noise characteristics. The theoretical basis of the stochastic subspace method is the state-space equation in the time domain, while the state-space equation of the system is only applicable to linear systems. Therefore, under non-smooth excitation, this paper proposes a stochastic subspace method based on RDT. Firstly, this paper uses the random decrement technique of non-stationary excitation to obtain the free attenuation response of the response signal, and then uses the stochastic subspace identification (SSI) method to identify the modal parameters. This not only improves the signal-to-noise ratio of the signal, but also improves the computational efficiency significantly. A non-stationary excitation is applied to the spatial grid structure model, and the RDT-SSI method is used to identify the modal parameters. The identification results show that the proposed method can solve the problem of identifying structural modal parameters under non-stationary excitation. This method is applied to the actual health monitoring of stadium grids, and can also obtain better identification results in frequency, damping ratio, and vibration mode, while also significantly improving computational efficiency.

Analysis of GNSS-RTK Monitoring Background Noise Characteristics Based on Stability Tests.

GNSS-RTK offers numerous advantages and broad prospects in structural dynamic monitoring in civil engineering. However, in practical applications, GNSS-RTK accuracy is susceptible to the monitoring environments, causing actual monitoring accuracy to fall below its calibrated accuracy. This study investigates the monitoring accuracy and spectral characteristics of GNSS-RTK based on stability tests under different environments related to reflection and obstruction conditions (i.e., concrete, grass, an obstructed balcony, and a water area). The findings indicate that in open environments of grass, concrete, and water, the standard deviation (STD) of GNSS-RTK monitored displacement is below 8 mm, its accuracy meeting the specifications of structural health monitoring. In the obstructed balcony environments, GNSS-RTK signals exhibit amplitude jumps, resulting in lower accuracy; however, during non-jump intervals, the STD of monitored displacement is below 10 mm, satisfying the structural health monitoring accuracy requirements. Moreover, the amplitudes of GNSS-RTK displacements in the concrete, grass, and water areas are basically consistent with the calibration accuracy of ±10 mm in the horizontal direction and ±20 mm in the elevation direction, while the amplitudes of GNSS-RTK displacements in the obstructed balcony condition are far greater than the calibration accuracy. The spectral analysis of GNSS-RTK signals reveals that multipath errors in concrete, grass, and obstructed balcony environments are primarily concentrated in the low-frequency range within 0.04 Hz, while the internal white noise of the instrument is widely and evenly distributed across the whole frequency domain. Based on these findings, adaptive methods, such as filter methods and multipath error correction techniques, are proposed for the de-noising of GNSS-RTK background noise.

Stability of Lead(IV) Oxide in a Lead Pipe Scale and Its Potential Role in Corrosion Control.

Lead(IV) oxide (PbO2) is an important component of the scale in many lead pipes used for water supply. Promoting conditions that maintain its stability could be an effective method for limiting lead release. In this study, we applied a method that combined electrochemical and free chlorine conditioning to form PbO2 scales on coupons. Lead coupons were then used to investigate the impacts of water stagnation time and residual free chlorine on PbO2 stability. Free chlorine depletion and associated lead release were investigated from 30 min to 5 days for different initial free chlorine concentrations (0.5-3.0 mg/L as Cl2). There was a lag time of up to 24 h between free chlorine depletion and observed lead increases. With daily readjustment of free chlorine to 0.2 mg/L or higher, the stability of the PbO2 scale on the lead coupon was maintained and dissolved lead remained consistently below 10 μg/L. This study provides information on key factors affecting reductive dissolution of PbO2 present in lead scales. It bridges the theoretical threshold free chlorine to maintain PbO2 stability with experimental results and provides implications for actual water quality monitoring and household drinking water use.

Research on structural vertical stiffness evaluation of track-specific suspension bridge under the action of the no-load first train

The track-specific bridge has the characteristics of a large volume of passenger traffic, narrow transverse width, and large excitation. The long-term and high-frequency operating conditions put forward strict requirements for the safety and comfort of the bridge. Aiming at the problem of achieving fast, accurate, and intelligent evaluation of bridges under the coupling action of trains and temperatures, this paper proposes a method for evaluating the structural vertical stiffness of track-specific suspension bridges under the action of the no-load first train. Firstly, the [Formula: see text] (deformation-velocity-time) data of trains on the bridge are analyzed through linkage numerical simulation, track train transponder, and structural safety monitoring system. Secondly, the CART algorithm establishes a regression model for data correction. The mapping relationship between the modified deformation monitoring value and the theoretical calculation value is analyzed to realize the current structural vertical stiffness evaluation. Finally, it is verified by the world’s largest span self-anchored track-specific suspension bridge. The results show that the theoretical deformation value of the most unfavorable deformation section is 268.55 mm, the actual monitoring value is 232.80 mm, the difference is 35.75 mm, and the relative error is 13.3%. The R2 score of the CART regression model is 0.94, and the accuracy of the CART regression model is higher than that of other algorithm regression models. The modified dynamic check coefficient is less than 1, and the ratio of the modified residual deformation value to the maximum deformation value is 7.6%, which meets the specification requirement not exceeding 20%, indicating that the current structural vertical stiffness is in normal operating conditions.

Safety management of deep excavation engineering in subway stations based on soil mechanics response simulation analysis

As the economy develops with the continuous acceleration of modern urban construction, the demand for subway construction has been increasing. When constructing subway stations, the safety management of deep foundation pit support engineering is particularly important. To balance the absolute safety and economic benefits of subway station construction projects, the safety management of subway station deep excavation projects based on soil mechanics response simulation analysis is studied. Taking the deep foundation pit project of Wuhan Metro Station as an example, this study uses numerical simulation analysis technology and actual monitoring data to conduct in-depth analysis of the deformation of the deep foundation pit. Meanwhile, through finite element technology, the influence of internal support system structural parameters on deep foundation pit deformation in deep foundation pit support engineering is studied, and the parameters of the original support structure are optimized. Results showed that the maximum horizontal displacement of the original scheme reached 25.7 mm, while that of the optimized parameter scheme was only 18.6 mm, which is a decrease of 27.62% compared to the original scheme. In summary, the research on safety management of subway station deep foundation pit engineering based on soil mechanics response simulation analysis is important in promoting the development of modern urban subway construction.

Monitoring of deformations of the deep pit wall and surrounding buildings in dense urban areas

Summary. The construction of buildings in dense urban areas is often characterized by the presence of deep pits, with the arrangement of parking lots, technical rooms and shelters in them. The timeframe for the installation of zero-cycle structures is usually quite long and can be measured in several months, and in complex cases and with large volumes of underground structures, it can last for tens of months. Such works are accompanied by the excavation of tens of thousands of cubic meters of pit soil, changes in the stress-strain state of the soil base and the supporting structures of neighboring buildings, and thus the need to monitor the technical condition of both the pit wall and the surrounding buildings. The paper analyzes the results of monitoring the state of the deep pit wall and the surrounding buildings in Kyiv. The monitoring of deformations of the pit wall was carried out using the classical method (the method of direct repeated linear-angular notching) and the modern method using inclinometers. Monitoring of the deformations of the existing surrounding buildings was carried out by determining additional foundation settlements by leveling. It is demonstrated that the modern tools used for monitoring have high accuracy, which is important when conducting observations in dense urban areas. Based on the results of monitoring the deformations of existing nearby structures, it was determined that the additional settlements of existing buildings do not exceed the limit values according to DBN B.2.1-10:2018 Bases and foundations of buildings and structures. This publication is the first in a series of articles on the assessment of the stress-strain state of the pit envelope and surrounding buildings, using the example of a specific construction site and includes both a description of the actual monitoring data in this article and numerical simulation of the stress-strain state in further publications.

Common Faults and Maintenance of Three-phase AC Asynchronous Motors

Application of three-phase AC asynchronous motor in industrial applied in many aspect following function that need to use. In operation use, many troubles may cause motor equipment not to operate or break down by the motor itself or caused by a system including protection, control system, interlocking device, and others causes. Aiming at the actual situation that three-phase AC asynchronous motors are widely used and have a high failure rate, this paper focuses on analyzing the common failures and abnormal phenomena of three-phase AC asynchronous motors and their main causes. This Research Method is reinforced by the actual monitoring of the locality where the equipment is installed. At the same time, some specific preventive measures and treatment methods are proposed to timely discover and eliminate the potential accidents of motors as much as possible and ensure the safe operation of motors. In conclusion, the aspects that need to be considered are one by one. There are 2 general classifications to determine possible faults, the first is about the operating conditions that the equipment motor should monitor and take the scheduled data to know about the actual conditions including power quality, temperature rise, vibration analysis, and physical abnormalities during the operation of the unit.

A novel Bayesian updating finite element model using enhanced unscented Kalman filter for time-dependent estimation of rockfill dam structure deformation

Due to the time-dependent effect of rockfill dams, the conventional time-invariant finite element method (FEM) can hardly meet practical engineering requirements. This paper proposes an updating Bayesian FEM method for accurate long-term deformation analysis. A combined FEM model is introduced accounting for both instantaneous and creep behaviors. The FEM model is then updated using a Bayesian algorithm, unscented Kalman filter (UKF). The UKF calibrates the prior FEM predictions by incorporating real-time measurement data, thus iteratively reducing discrepancies between model predictions and actual observations. To further enhance the algorithm accuracy, a power-law-based fading memory factor is proposed to mitigate measurement noise in standard UKF. For parameter identification, a slice approach of the high-dimensional covariance confidence ellipsoid is developed. The methodology is validated in Qingyuan rockfill dam, in Guangdong province, China. Results show that the updated FEM is more consistent with the actual monitoring data. The fading memory improves standard UKF performance with a lower relative root-mean-square error (RRMSE). Additionally, the slice method reveals that a specific three-parameter configuration behaves better than the others. The proposed approach can also be extended to other fields including slope and tunneling.

A basic and applied remote sensing research project (GRAPEX) for actual evapotranspiration monitoring to improve vineyard water management

A basic and applied remote sensing research project (GRAPEX) for actual evapotranspiration monitoring to improve vineyard water management

Numerical simulation study on the force of overwintering foundation support structure of unsaturated seasonal permafrost under indoor experiments.

When analysing the effect of negative temperature on overwintering pit constructions of unsaturated soil, using the mechanical parameter of saturated soil at room temperature leads to an inaccuracy in the research findings. The strength parameters are obtained through indoor experiments. The foundation pit model is created using FLAC3D numerical simulation software based on the indoor experimental data. The influence of different parameters on the stress and deformation of the overwintering deep foundation pit supporting structure is analysed. The numerical simulation results obtained are compared with the actual monitoring data. According to research, the matric suction of the silty clay in its natural state in the Changchun area is 70 kPa. As the temperature decreases, the total cohesion of the unsaturated soil increases, and the internal friction angle tends to decrease. The numerical simulation results are consistent with the actual monitoring data changes. With the excavation, the horizontal displacement of the supporting structure increases first and then decreases, reaching the maximum displacement at two-thirds of the foundation pit. Compared with room temperature, the deformation of the supporting structure is larger under a negative temperature condition. The deformation of the supporting structure simulated by the actual temperature mechanical parameters is larger than that under the condition of normal temperature mechanical parameters. The frost-heaving force increases with the overall excavation, and a surge occurs at the bottom of the pit. The frost-heaving force changes most significantly under the condition of freezing at -20°C for 30 days.

High mechanical, self-adhesive oxidized guar gum/chitosan hydrogel prepared at room temperature based on a nickel-urushiol catalytic system for wireless wearable sensors

Recently, sensors constructed on the basis of hydrogel are playing a major role in health detection such as motion detection and breathing monitoring. However, the common hydrogels have poor mechanical properties, insufficient adhesion and complex preparation processes, which hinder the further use of such sensors. In this paper, the conductive hydrogel (P(AA-UH)-OGG-CS/NiCl2) composed of acrylic acid (AA), oxidized guar gum (OGG) and chitosan (CS) was prepared at room temperature through the dynamic redox reaction of nickel chloride (NiCl2) and urushiol (UH). In detail, the reduction group (phenolic hydroxyl) of UH and Ni2+/Ni3+ pair form a semi-quinone/quinone redox dynamic cycle system, allowing the hydrogel to quickly gel at room temperature for 3 min. The catechol group in UH also promotes the hydrogel to have a superior adhesion strength of 25.23 kPa to pig skin and a strong repeated adhesion performance. In addition, the dynamic Schiff base bond created by the interaction of OGG and CS elevated the tensile stress of the hydrogel to 67.54 kPa. After the hydrogel is assembled into the sensor, it has high sensitivity and high stability to different strains, and has great application prospects in the field of actual human health monitoring.

Smart photonic crystal hydrogels for visual glucose monitoring in diabetic wound healing

Diabetes is a global chronic disease that seriously endangers human health and characterized by abnormally high blood glucose levels in the body. Diabetic wounds are common complications which associate with impaired healing process. Biomarkers monitoring of diabetic wounds is of great importance in the diabetes management. However, actual monitoring of biomarkers still largely relies on the complex process and additional sophisticated analytical instruments. In this work, we prepared hydrogels composed of different modules, which were designed to monitor different physiological indicators in diabetic wounds, including glucose levels, pH, and temperature. Glucose monitoring was achieved based on the combination of photonic crystal (PC) structure and glucose-responsive hydrogels. The obtained photonic crystal hydrogels (PCHs) allowed visual monitoring of glucose levels in physiological ranges by readout of intuitive structural color changes of PCHs during glucose-induced swelling and shrinkage. Interestingly, the glucose response of double network PCHs was completed in 15 min, which was twice as fast as single network PCHs, due to the higher volume fraction of glucose-responsive motifs. Moreover, pH sensing was achieved by incorporation of acid-base indicator dyes into hydrogels; and temperature monitoring was obtained by integration of thermochromic powders in hydrogels. These hydrogel modules effectively monitored the physiological levels and dynamic changes of three physiological biomarkers, both in vitro and in vivo during diabetic wound healing process. The multifunctional hydrogels with visual monitoring of biomarkers have great potential in wound-related monitoring and treatment.Graphical abstract

Numerical Analysis and Safety Assessment of the Former Site of Shanghai South Downtown Library Reinforced by U-Steel During Integral Translation

ABSTRACT The utilization of overall translation techniques in buildings offers numerous advantages, including cost-effectiveness, shortened construction timelines, and environmental sustainability. These techniques are increasingly being employed for the conservation and renovation of existing historic structures. Taking the former site project of the South Downtown Library in Shanghai, which requires the overall translation due to the requirements of urban renewal, as an example, a systematic detection and identification of the damage and safety states of the overall structure were conducted. The damaged condition and overall structural safety were evaluated, and the corresponding reinforcement and repair suggestions were proposed. The former site of the library, a brick-timber mixed structure, was reinforced using U-steel through internal support and external pulling. The structure was also lifted and translated using the overall translation technique. The displacement responses of the key parts of the structure were monitored using the displacement sensors during the translation. The detailed finite element model of the former site of the Shanghai south downtown library, strengthened by U-steel, was established using the ABAQUS. The displacement responses of the structure’s key components during the jacking and translation were analyzed, and compared with the actual monitoring results. Good agreements were observed between the model predictions and test results. Utilizing the validated finite element model, parametric analyses were carried out. The effects of the rate of jacking and translation as well as the ground flatness on the displacement responses of a structure were analyzed, the mechanical and safety states of the structure reinforced with U-steel were further evaluated. This study can provide a reference for the overall translation technique and safety assessment of similar historic buildings in the urban renewal processes.

Predicting plateau atmospheric ozone concentrations by a machine learning approach: A case study of a typical city on the southwestern plateau of China

Atmospheric ozone (O3) has been placed on the priority control pollutant list in China's 14th Five-Year Plan. Due to their unique meteorological conditions, plateau regions contain high concentrations of atmospheric O3. However, traditional experimental methods for determining O3 concentrations using automatic monitoring stations cannot predict O3 trends. In this study, two machine learning models (a nonlinear auto-regressive model with external inputs (NARX) and a temporal convolution network (TCN)) were developed to predict O3 concentrations in a plateau area in the Kunming region by considering the effects of meteorological parameters, air quality parameters, and volatile organic compounds (VOCs). The plateau O3 prediction accuracy of the machine learning models was found to be much higher than those of numerical models that served as a comparison. The O3 values predicted by the machine learning models closely matched the actual monitoring data. The temporal distribution of plateau O3 displayed a high all-day peak from February to May. A correlation analysis between O3 concentrations and feature parameters demonstrated that humidity is the feature with the highest absolute correlation (−0.72), and was negatively correlated with O3 concentrations during all test periods. VOCs and temperatures were also found to have high positive correlation coefficients with O3 during periods of significant O3 pollution. After negating the effects of meteorological parameters, the predicted O3 concentrations decreased significantly, whereas they increased in the absence of NOx. Although individual VOCs were found to greatly affect the O3 concentration, the total VOC (TVOC) concentration had a relatively small effect. The proposed machine learning model was demonstrated to predict plateau O3 concentrations and distinguish how different features affect O3 variations.

Arc Ignition Methods and Combustion Characteristics of Small-Current Arc Faults in High-Voltage Cables

High-voltage cables will continue to operate for a period of time in the event of a small current arc fault, which poses a risk of fire. Two simulated ignition methods, moving electrode and melting fuses, are proposed to analyze the ignition characteristics of low-current arcs. The ignition test was carried out, and the combustion effect was compared. The results indicate that the moving electrode ignition method can achieve long-distance arc ignition test when the current is small and is suitable for simulating the arc ignition situation of cable outer protective layer damage. By controlling the movement speed, it can be ensured that the arc will not be interrupted during the electrode movement process. However, the arc is difficult to sustain using the fuse melting method when the current is small and the distance is long. The fuse melting method is suitable for simulating insulation breakdown situations. The results show that the critical arc duration for cable ignition under five different current conditions of 2–10 A is 28 s, 21 s, 14 s, 9 s, and 4 s, respectively. The maximum height of the cable flame under 2–10 A arc current is 9–52 cm and 16–63 cm, respectively, when the arc duration is 50 s and 100 s. The self-ignition time of the cable after the arc extinguishing is 8–95 s and 14–261 s, respectively. The maximum temperature of the cable flame is positively correlated with arc current, and the maximum flame temperature of the cable under 2–10 A arc current is 540–980 °C. Based on the actual current monitoring data in cable tunnels, the research results can provide reference for the risk assessment and protection of cable tunnel fires.

Assessment of earthquake location uncertainties for the design of local seismic networks

The ability to estimate earthquake source locations, along with the appraisal of relevant uncertainties, is paramount in monitoring both natural and human-induced micro-seismicity. For this purpose, a monitoring network must be designed to minimize the location errors introduced by geometrically unbalanced networks. In this study, we first review different sources of errors relevant to the localization of seismic events, how they propagate through localization algorithms, and their impact on outcomes. We then propose a quantitative method, based on a Monte Carlo approach, to estimate the uncertainty in earthquake locations that is suited to the design, optimization, and assessment of the performance of a local seismic monitoring network. To illustrate the performance of the proposed approach, we analyzed the distribution of the localization uncertainties and their related dispersion for a highly dense grid of theoretical hypocenters in both the horizontal and vertical directions using an actual monitoring network layout. The results expand, quantitatively, the qualitative indications derived from purely geometrical parameters (azimuthal gap (AG)) and classical detectability maps. The proposed method enables the systematic design, optimization, and evaluation of local seismic monitoring networks, enhancing monitoring accuracy in areas proximal to hydrocarbon production, geothermal fields, underground natural gas storage, and other subsurface activities. This approach aids in the accurate estimation of earthquake source locations and their associated uncertainties, which are crucial for assessing and mitigating seismic risks, thereby enabling the implementation of proactive measures to minimize potential hazards. From an operational perspective, reliably estimating location accuracy is crucial for evaluating the position of seismogenic sources and assessing possible links between well activities and the onset of seismicity.

Developing a BIM based digital twin system for structural health monitoring of civil infrastructure

Abstract The utilization of building information modeling (BIM) within digital technology facilitates the creation of three-dimensional representations for monitoring data in large-scale civil infrastructure. In response to the need for intelligent structural management, this study establishes a structural health monitoring (SHM) system and foundational framework based on digital twins. This framework integrates information from various sources and facilitates collaborative efforts for structural operation and maintenance. Additionally, the SHM system integrates actual monitoring measurements and early warning mechanisms to consolidate multi-source monitoring data with BIM. Through real-time analysis, the system provides insights into the operational status of bridges, capturing geometric, physical, and performance evolution characteristics. To construct the system, engineering challenges are initially digitized, with appropriate sensors deployed on real bridge structures to monitor dynamic (acceleration) and static (strain, displacement) physical information during bridge operation. Subsequently, through wireless communication and data storage technologies, the monitored physical data serves as input for mode identification and early warning algorithms, facilitating the acquisition of structural performance information. Finally, three-dimensional display technology enables real-time calculation and rendering of BIM models, fostering the exchange and interaction of monitoring and BIM information, thus enhancing the intelligence of SHM system.

Development and engineering application of fiber bragg grating intelligent cable in large-span hyperbolic parabolic spatial cable network

In order to accurately control the prestress force of cables in long-span cable net structures, a new type of fiber Bragg grating (FBG) intelligent cable was developed. The FBG sensor was directly encapsulated inside the cable, and the sensing performance of the intelligent cable was verified by the cyclic tensile tests. The results show that the sensitivity coefficients of FBG monitoring are basically consistent, and the linearity deviation of the fiber Bragg grating is less than 4.67 %. Based on a real project Shunde Desheng Sports Center, a 114 m long-span saddle-shaped cable net structure model was established using finite element analysis, and the distribution and correlation of internal forces of cables in different tension stages were calculated and compared with the actual monitoring results of intelligent cables. The analysis results indicate that the force changes of intelligent cables is basically consistent with the value of finite element simulation. According to the data of long-term intelligent cable monitoring, the change of cable force caused by the temperature deformation of the steel ring beam is much greater than the influence of the temperature rise and fall of the cable itself on the cable force. Intelligent cables can provide a reference for cable force monitoring of long-span cable net structures.

A Study of Carbon Emissions during the Operational Period of an Integrated Expressway Construction Station

An integrated construction station for an expressway is characterized by complex carbon emission sources and high carbon emission intensity. Conducting carbon emissions accounting makes possible a comprehensive understanding of these characteristics, enabling targeted and guided carbon reduction efforts, which is crucial for advancing the low-carbon development of expressway construction. This paper, based on an in-depth analysis of the carbon emission structure during the operational period of an integrated expressway construction station identifies, as calculation boundaries, eight categories: residential areas, station transportation, mixing stations, precast beams, steel bar yards, artificial carbon emissions, chemical reactions during construction, and construction conditions. The study adopts a “bottom-up” approach to carbon emission measurement and constructs a carbon emission model for the production and operational period of the integrated construction station, based on the carbon emission factor method. Using the SG-2 section of the Fengqiu to Xiuwu stretch of the Changxiu Expressway as an engineering case, carbon emissions accounting for each component of the integrated construction station’s operational period was conducted, and the results were compared with the station’s monitoring system. High-precision characterization and calculation of total carbon emissions, as well as emissions from each process and piece of equipment during the operational period, were achieved. The results indicate that: (1) the relative error between the overall calculation results and actual monitoring is 3.6%, verifying the model’s accuracy; (2) the monthly carbon emissions of the integrated construction station during the operational period reached 72.15 tons; (3) there is a significant difference in carbon emissions among the different processes, with the highest emissions coming from transportation and residential areas, accounting for 43.4% and 23.7%, respectively. Therefore, electrification of transportation equipment could significantly reduce the overall carbon emissions of the integrated construction station.