Real-time carbon emission monitoring in prefabricated construction

Automation in Construction 110 (2020) 102945

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Real-time carbon emission monitoring in prefabricated construction Guiwen Liu, Rundong Chen, Pengpeng Xu , Yan Fu, Chao Mao, Jingke Hong ⁎

T

School of Construction Management and Real Estate the Chongqing University, Chongqing, China

ARTICLE INFO

ABSTRACT

Keywords: Carbon emission Prefabricated construction Monitoring system Cyber-physical systems

The problem of carbon emissions from the construction industry should be a serious concern, because it contributes a very large share of the overall GHG emissions. However, because of traditional construction modes, most previous research has focused on forecasting ex-post analysis of carbon emissions, and few efforts have concentrated on real-time analysis, the lack of which leads to deficiencies in carbon emission control. The industrial transformation of construction has created opportunities for improvement, and similarly the developments in information technology, notably cyber-physical systems (CPS), have shown the potential to contribute to solving this problem. In several other industries, the application of CPS has made significant progress. To strengthen the monitoring and analysis of carbon emissions in prefabricated construction and thus prevent an excessive impact on the environment, this study proposes a real-time carbon emission monitoring (CEM) system for the whole industrial chain of prefabricated construction. To achieve this aim, previous studies on carbon monitoring in the construction industry are reviewed to investigate the applicability of CPS to CEM systems. The functionality of the system is designed according to the requirements of different end users, and five types of hardware are developed for automated data acquisition in real time. In addition, for better utilization of the monitoring system, three different data presentation platforms are developed for customers (desktop platform, browser, and smartphone app). The system can successfully perform real-time monitoring of carbon emissions， which is useful in preventing additional emissions.

1. Introduction Global warming is one of the biggest challenges currently facing humanity, and the increase in carbon emissions is one of the major causes of global warming [1,2]. The construction industry is a major source of carbon emissions, accounting for approximately 20% of global energy consumption, and has incrementally increased its carbon emissions to one-third of the global total. [2,3]. However，over the whole life cycle of a building, the operation stage of the constructed facility contributes the highest share of energy consumption and carbon emissions, followed by the construction stage, and the lowest share is contributed by the demolition stage [4,5]. As a result, most research on building energy conservation and emission reductions focuses on the operation stage, and some valuable contributions have been made [6,7]. However, with the gradual increase of energy saving in buildings, the carbon emission ratio of the construction stage has been increasing in proportion, and therefore it is a worthwhile subject of investigation [8,9]. In addition, the operation stage is a process lasting for several decades, including the use of equipment such as electricity, heating, and ventilation. However, the construction stage is relatively short

compared with the operation stage, with the result that carbon emissions in the construction phase occur in a more time-intensive manner [10]. Therefore, emission reduction in the construction stage needs to be taken more seriously. China's economy has been booming over the past 30 years, which has been accompanied by tremendous pressure on the environment. China has become the world's biggest carbon emitter, surpassing the United States for the first time in 2006 [11,12]，which shows the great importance of reducing emissions in China. Under such circumstances, China is in urgent need of effective control of carbon emissions and countermeasures for their reduction. On the eve of the UN Climate Change Conference in Copenhagen, Denmark, China unveiled a plan to reduce greenhouse gas emissions by 40% to 45% from 2005 levels by 2020. Further, during the Paris Climate Change Conference in 2015, the Chinese government pledged to cut carbon dioxide emissions per unit of GDP by 60%–65% from 2005 levels by 2030, which is a big challenge for China. The Chinese government has made considerable efforts in view of these commitments, such as industrial restructuring and mandatory emission reduction planning [11]. Urbanization has not only brought China booming economic development, but has also led to the

⁎ Corresponding author at: School of Construction Management and Real Estate, Chongqing University, No. 174 Shazhengjie, Shapingba, Chongqing 400044, China. E-mail address: [email protected] (P. Xu).

https://doi.org/10.1016/j.autcon.2019.102945 Received 15 April 2019; Received in revised form 3 August 2019; Accepted 29 August 2019 0926-5805/ © 2019 Elsevier B.V. All rights reserved.

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construction industry becoming a major energy consumer in China [13]. In 2014, China's construction industry accounted for more than 36% of the country's major energy consumption [14,15]. The above analysis shows how important it is to control the carbon emissions of the construction industry in China more effectively. Moreover, unlike the construction industry in other developed countries, China's construction industry is in the initial stage of industrialization [16], and the mode of production involving installation of prefabricated components is still new for China. Therefore, it is important to establish carbon emissions monitoring for prefabricated buildings in the initial stage for sustainable development. Cyber-physical systems (CPS) are a highly integrated technology that enables real-time monitoring and control of the physical world via a network. CPS comprises the interdisciplinary fields of engineering, ICT, computer science, and other sciences and applications [17]. CPSbased technology has the advantages of being dynamic, conducted in real time, and easy to control, and the advantages of CPS have been proved by examples in other industries. Therefore, it has potential applications in carbon emission monitoring [18]. Earlier implementation of real-time monitoring will be helpful for the formulation of an emission reduction plan, process control, and post-analysis. Understanding the present situation of carbon emissions of the industry is the first step in the formulation of a low-carbon roadmap and realization of sustainable development [19], which is also important for assessment of the emission reduction potential and technology demand of construction projects. A time map is an important tools that helps us to gain an understanding of the current status of carbon emissions. Meanwhile, real-time monitoring can conveniently accumulate time-distributed carbon emission statistical data, which makes a large amount of data available for creating a carbon emission time map after the project is completed. These data from real-time monitoring will be more reliable than data obtained from the previous bottom-up method: collecting front-line enterprise managers' views on enterprise energy saving and low carbon through a questionnaire-based survey. Moreover, real-time monitoring is the basis of dynamic deviation correction. After the carbon emission targets are formulated, carbon emission behavior could be constantly monitored to observe whether the predicted emission reduction is close to the target, and deviations from the target can be simultaneously controlled in a timely fashion. In turn, carbon targets could be developed by analyzing and summarizing the historical data of carbon emissions (data obtained from monitoring) to avoid unrealistic targets being set. This is a process of mutual reinforcement following the Plan-Do-Check-Act cycle(PDCA Cycle)concept. The core of the concept is real time and dynamic. There is a big difference, of course, between the effects of ex-post control and the effects of real-time control. The carbon emission peak point can be observed through the statistical data on carbon emission, making it possible to clearly analyze the cause of carbon emissions in this period, and the control can be strengthened or other methods can be adopted for improvement in time. This paper aims to develop a comprehensive carbon emission monitoring (CEM) system capable of monitoring the whole process of prefabricated construction—from prefabricated component production to transportation and installation—that is adopted in the development of CPS.

Process-based analysis mainly focuses on a case study of a specific building, usually collecting the actual data pertaining to the building and calculating the energy consumption or carbon emission of the building by formulas. The aims of studies that use this analysis method are varied, some of which aim to establish appropriate formulas for carbon emission at all stages of a building [21]. The process-based analysis method can calculate the carbon emission and energy consumption of a building for a specific construction method; hence, this method is suitable for comparing the carbon emissions of various prefabricated construction methods and traditional construction methods, as achieved in some studies [22–24]. A study using this method divided the different stages of a building's lifespan in detail, to determine the research system boundary. Building system boundaries can be divided into five stages according to the whole life cycle: building material production, transportation from production unit to point of use, construction, maintenance and replacement, and demolition [8]. Due to a lack of information, studies usually focus on one or several of these stages [21–25], which may lead to incomplete boundaries or missing critical phases. One obvious drawback of process-based analysis is that the information that studies need is usually second-hand data obtained by the construction side, and its accuracy is difficult to guarantee. In addition, the difficulty of obtaining information is also a barrier to research employing the process-based analysis method. Although it is considered as a more accurate method on the basis of its results, its accuracy depends on the data obtained from manufacturers or suppliers [26]. (2) Input–output analysis. Input–output analysis is a method to evaluate the pollutant or emission of goods or services from a macro perspective [27]. It is widely used to study the relationship between the two major categories of a national economy, the ratio between accumulation and consumption, and to predict the input volume and output volume of each sector [28]. Input–output analysis can systematically analyze the resources needed to produce a product, because it covers the economic system of an entire country or region [26]. However, compared with the processbased analysis method, the input–output method has the disadvantage that it is unable to evaluate GHG emissions or the energy generated by a specific building life-cycle type accurately, because the data used are based on the industry average rather than being specific to a building. This up-bottom approach usually studies all the buildings in an area at a certain time, and this approach can be used to assess the building industry's share of national carbon emissions or to compare it with process-based analysis [29,30]. (3) Hybrid analysis. It can be seen that although the process-based analysis method and the input–output method have their own advantages, they also have their own disadvantages. To remedy this deficiency, some people try to combine the two methods to achieve more comprehensive research results. This hybrid approach does make the research more complete, but the downside is that it relies on consultants to identify which processes are important to analyze, which means the hybrid approach only addresses upstream truncation errors related to user decisions [26].

2. Literature review

(4) Monitoring techniques of information technology.

2.1. Conventional analytical methods for carbon emission

Recently, with the developments in information technology, more monitoring techniques have been produced, and researchers have more ways of obtaining data and analyzing the energy consumption and carbon emissions of various stages of buildings. For example, the D4AR model can be used to generate the actual and expected carbon footprint of the project and visualize its deviation, or directly visualize the construction equipment [31,32]. A laser induction device is used to detect

Most previous studies have followed one of three methods to analyze the energy consumption and carbon emissions of buildings in each stage: process-based analysis, input–output analysis, and hybrid analysis [20]. (1) Process-based analysis. 2

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Table 1 Analytical methods for GHG emissions. Research stage

Boundary

Author

Method

Hui Yan et al. Milad et al. Monahan et al. Reza et al. Wong et al. Hajibabai et al. Nasse´ n et al. Acquaye et al. Lu Aye et al.

Process-based analysis D4AR model Process-based analysis GIS-based MR/CVP GIS-based/CAD I/O I/O Hybrid analysis

Prediction/emulation

Real-time √(daily)

√

√(daily)

Ex-post analysis

(1)

(2)

(3)

(4)

√

√ √ √

√ √

√ √ √

√ √ √ √ √ √

√ √ √ √

√

– – √

√

Note: Boundary (1) embodied carbon emission; (2) carbon emission of the production line; (3) carbon emission of the transportation stage; (4) carbon emission of the on-site stage.

from carbon emissions across the whole process, as the monitoring of each stage cannot be broken down into more detail. Therefore, it is useful to develop a carbon emission monitoring system that meets the needs of managers and is highly adaptable.

the discharge of the production line in the prefabricated factory, and RFID technology is used to detect embodied emissions in prefabricated components [33]. A system developed using GIS is usually utilized to present the carbon emission concentration distribution and applied to assess this at a construction site [7]. Emerging and existing video cameras can be used for automatic monitoring of the carbon footprint of earthwork construction activities and the greenhouse gases in construction operations [32,34]. An automated visual sensing technology is used, which performs a semantic analysis of the device's position and function. There are also techniques to model and predict building-related carbon emissions, such as MR(mixed reality)and CVP (construction virtual prototyping) [35]. All previous analytical and monitoring methods have provided valuable experience for subsequent studies. Table 1 lists the method, research stage, and boundary in some studies. Although there have been considerable achievements, previous studies still suffer from some limitations.

2.2. The application of CPS technology to CEM The application of some emerging information technologies in the construction industry has been summarized above. Although the application of these technologies in the construction industry is still in its infancy, it has shown potential. The applicability of CPS to the development of carbon emission monitoring systems can be illustrated by examining the limitations of current research. CPS emphasizes distributed applications, and future CPS will host a large number of coexisting distributed applications on hardware platforms, where thousands of network components communicate through open networks [36]. Distributed applications enable CPS to realize simultaneous collection and centralized processing of large amounts of data, which is more in line with realistic processes—a large number of events in the physical world occur at once [37]. Meanwhile, the realtime performance of CPS makes the control more effective, and enables the manager to track the information feedback from the real-world equipment dynamically. These processes are usually achieved with feedback loops in which physical processes affect computations and vice versa [37]. These characteristics meet the needs of large and 9complex project management that focuses on addressing climate change. CPS has been applied quite well in the manufacturing industry. For example，in the shipbuilding industry, CPS is used to automate many tasks in the pipe workshop to accelerate production processes and increase production [38]. In addition, CPS is used to evaluate and respond to dynamic production environments [39]. Although CPS has shown its potential for addressing problems in the construction industry—a CPS-based temporary structures monitoring system has been developed to address safety problems—research on CPS in the construction industry has lagged behind [18]. The research object of this paper is prefabricated construction, which is in the initial stages in China. Taking components to the factory for production is one of the core features of prefabricated construction. In the production stage of prefabricated components, the mode of prefabricated construction has a marked similarity with the manufacturing industry. For example, prefabricated components are produced in a standardized manner and are produced in the relatively stable environment of the factory. In general, multiple production lines are operated simultaneously, which is a great benefit for CPS that is to be used in a production plant of prefabricated components. Meanwhile, because a great deal of the prefabrication work is achieved in factories, the cast-in-situ work of the construction site has been greatly reduced, which has reduced the artificial workload and increased the utilization of other construction equipment (such as the tower crane) at the site.

2.1.1. Data acquisition Most of the previous research data were obtained from the contractor's second-hand data. Data acquisition is not only very difficult, but also the research results obviously depend on the accuracy of the data in the documents. 2.1.2. Real-time response In previous research on carbon emissions, process-based analysis methods mostly analyze the energy consumption and emissions of a building after it has been built. This method can provide a reference for the analysis of energy consumption and emissions of the same type of building. However, it has the very obvious shortcoming that we cannot include the carbon emissions of the component processing, transportation, and construction process of this building in a timely manner, which is due to the lack of a means of monitoring carbon emissions throughout the construction process in real time at the present stage. This missing approach is difficult to implement with process-based analysis and input–output methods, but it is critical for building managers to control carbon emissions because the core of control lies in the realization of dynamic activities and consequent emissions. 2.1.3. The boundary Some studies have developed systems that include monitoring of GHG emissions through emerging information technologies, which enable real-time monitoring of the development of carbon emission systems. Some researchers have developed different real-time monitoring systems through RFID technology (refer to the authors of these studies), laser induction technology (refer to the authors of these studies) [33], the D4AR model [31], automated visual sensing technology [32], and GIS technology [7]. However, most of these monitoring systems address only one or several stages in the building's full life cycle, which can cause problems for managers who wish to manage and learn 3

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Fig. 1. Framework of methods.

Therefore, a monitoring system based on CPS is more suitable for monitoring the site and determining the worst carbon emission behavior. As described above, CPS has been more mature in the monitoring of the manufacturing industry, which proves that CPS can also be applied to the manufacturing of prefabricated components [18]. Moreover, in terms of technical support, various CPS support technologies have been implemented, such as the virtual model, DAQ, and communication networks [40]. All of these provide evidence for the applicability of CPS technology to CME.

software development stage consists of four parts: (a) Select a database, a platform that stores data. (b) Develop the server: The main function of the server is to process the original data collected by the hardware module, and the processing approach is based on the quantitative carbon emission model. In addition, the server has the ability to send and receive data. (c) The third part is to build the virtual model according to the project to be monitored. The virtual model is used to better realize carbon emission visualization. (d) The final part is the development of the data presentation platform. This part will develop three data presentation platforms, which are the Web, desktop, and app.

3. Research method

3.3. System test

To contribute to solving the problem of prefabricated CEM, this paper will use three approaches: (I) Quantitative model, (II) System development, and (III) System implementation and testing. Fig. 1. illustrates the research framework of the whole study. The work content of each part will be explained in detail below.

The system will first carry out a pre-test in the laboratory to ensure the smooth operation of the whole system. We will test whether the hardware system can operate appropriately in the laboratory, whether the hardware can successfully upload data to the server, whether the hardware and software can work together, and whether the software can display data correctly. After the test is successful, a suitable prefabricated construction project will be selected for the actual monitoring of the system to determine whether the monitoring system can achieve the purpose of monitoring in a real environment in future work.

3.1. Quantitative model design In this paper, the carbon emission quantitative calculation model is determined by a literature review. To determine a quantitative model for carbon emissions, the system boundary of the study should be determined first, to avoid the repeated calculation of carbon emissions caused by the blurring of the boundary, and to avoid the infinite upstream or downstream extension of the system boundary, which would make the study infeasible. After determining the system boundary, the carbon source within the boundary can be easily and clearly identified. This is also a necessary condition for determining the data collection method of the carbon emission monitoring system, because different data collection methods can be designed according to the characteristics of different carbon sources. Finally, a quantitative model is established for the different types of carbon emissions.

4. Quantitative model design 4.1. Carbon emission sources identification 4.1.1. Calculation boundary determination The research boundary of this paper is the construction stage of prefabricated buildings, as has been pointed out and explained in the introduction. The construction stage of prefabricated buildings is different from that of traditional cast-in-situ construction because the construction of prefabricated buildings is equivalent to moving part of the work of traditional construction to a factory. Therefore, when studying the construction stage of precast buildings, the production stage of the precast component factory should also be included. The content within the research boundary will be subdivided, and the construction of prefabricated buildings will be divided into three stages: the production stage of prefabricated components, the transportation stage of prefabricated components, and the site construction stage.

3.2. System development The development of the system can be mainly divided into two parts, hardware and software, which can proceed simultaneously. The main content of hardware development is to determine the collection method of the original data according to the characteristics of the carbon source at different stages, and then develop an induction module according to the data acquisition method. The main work of the 4

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According to the analysis of the carbon source, carbon emission monitoring mainly comprises the following four parts: (1) embodied carbon emission of material, (2) carbon emission of prefabricated parts factory production line, (3) carbon emission of transport stage, and (4) carbon emission of on-site stage. By summarizing the carbon emission models used in the previous literature, the calculation models of various carbon sources in the four stages are provided below. All these carbon emission models and parameters are written to the server, and the data are processed after the server receives the data.

Table 1.1 Material embodied GHG emission factors and loss factors library [45–47]. Material

Waste factor εi

GHG emission factor(kgCO2-e/kg)

Premixed concrete Cement Sand Steel Brick Glass

2.5% 2.5% 2.5% 5.0% 2.5% 0.0%

0.120 0.698 0.007 0.367 0.246 1.854

4.1.2. Emission sources identification 4.1.2.1. The production stage of prefabricated components. In the production stage of precast components, the main work is to produce precast components in the precast production line in accordance with the requirements of the building's raw materials (such as steel reinforcement and concrete). The carbon emission source in the production stage of prefabricated components is mainly divided into two parts: one is the embodied carbon emission of the prefabricated components, which is the carbon emission generated by the resources consumed by mining and processing construction raw materials. Previous studies have shown that the embodied emission of a prefabricated building accounts for more than 80% of the whole prefabricated building's total emissions [41]. This makes the embodied emission of materials an indispensable part of the research on carbon emissions. Another part of the study is the carbon emission generated by the processing of building raw materials into prefabricated components, which is generated by the production line. The production line consists of several systems: feeding system (vibrating platform, concrete feeder, screw feeder)； platform circulation system (side mold conveyor, component transport vehicle, driving wheel and supporting wheel); Platform Preprocessing system (Mold release agent spraying machine, Scratch machine, Polisher, Flattening machine)；and the maintenance system (Stacking machine, Curing kiln). These machines mainly consume electricity and water.

4.2.1. Embodied emission (E1) The materials involved in precast members are mainly steel and concrete. The carbon emission formula is as follows: n

E1 =

Mc =

Ms = M

Ms = M

(1.2)

Vc

Vc

(1.3)

r

(1.4)

Mc = (

c)

(1.5)

Vc

In addition, for some cases (such as component part library 2 in Appendix I) where the component mass M, concrete mass Mc, and steel bar mass Ms have been given, the total mass of the concrete and steel bar can be obtained by directly adding the corresponding parts. 4.2.2. Carbon emission of production line of prefabricated component factor (E2) The carbon emission E2 of the prefabricated factory mainly comes from the energy consumption of each equipment on the production line of the prefabrication plant. By calculating the electricity consumption (kWh) of each equipment, the carbon emission factor can be used to convert the electricity consumption into carbon emission, and the Table 2.1 Power carbon emission factors of various regions in China [48].

n i

(1.1)

where ρ is the component density. The density and steel content of each component can be obtained from the component part library (Appendix I). When the component's steel content cannot be obtained, the difference between the component mass and the concrete mass is used for calculation of the steel reinforcement mass Ms; that is:

GHGs are defined as CO2, N2O, CH4, HFC, PFC, and SF6 [42]. However, as HFC, PFC, and SF6 are rarely emitted in construction projects, the emission of CO2, N2O, and CH4 is generally considered in the construction industry [43]. Different GHG emissions have different impacts on the environment. To facilitate a comparison of the impacts of GHGs on the environment, GHGs are generally converted into CO2 equivalents through a global warming potential (GWP) value. The GWP value is used to calculate the GHG emission factor (kgCO2-e/kg) in this study. The formula is as follows:

GWPvalue

c

M=

4.2. Carbon emission quantitative model

fi

(1 + i )

The steel bar quality Ms can be calculated by multiplying the component mass by the steel ratio r, and the calculation formula is as follows:

4.1.2.3. The site construction stage. As the components of the building are completed in the factory, the on-site casting is greatly reduced. The assembly of precast components is mostly completed by a tower crane or truck crane. Therefore, the carbon emission source at the site is mainly composed of the tower crane, on-site transporter, and construction lift, which mainly consume electricity and oil.

i=1

f1, i

where Mi is the quality of material i, f1, i is its GHG emission factor, and εi is the loss factor [44]. Their values are given in Table 1.1. The concrete volume is approximately equal to the component volume. Therefore, the concrete volume can be calculated according to the dimensions of each component in the component part library (Appendix I). The concrete density ρc is also obtained from the component part library. Thus, this formula can calculate the concrete mass Mc:

4.1.2.2. The transportation stage of prefabricated components. The main work of this stage is to transport finished prefabricated components from the factory to the site. The carbon emission source at this stage is mainly composed of transportation vehicles, which mainly consume diesel or gasoline.

GHG emissions factor =

Mi i=1

(1)

where fi is the carbon emission factor of gas i, and GWPvalue−i is the GWP value of gas [44]. 5

Regions

f2(kg CO2/kWh)

North of China Northeast of China East of China Northwest of China Central China South of China

1.0416 1.1291 0.8112 0.9457 0.9515 0.8959

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Table 2.2 Provinces and cities covered by each region. Name of the grid

Provinces and cities covered

North China regional power grid Northeast regional power grid East China regional power grid Central China regional grid Northwest regional grid Southern regional grid

Beijing, Tianjin, Hebei, Shanxi, Shandong, Inner Mongolia autonomous region Liaoning, Jilin, Heilongjiang Shanghai, Jiangsu, Zhejiang, Anhui, Fujian Henan, Hubei, Hunan, Jiangxi, Sichuan, Chongqing Shaanxi, Gansu, Qinghai, Ningxia autonomous region, Xinjiang autonomous region Guangdong, Guangxi autonomous region, Yunnan, Guizhou, Hainan

Table 3.1 GHG emission factors during component transportation [44]. Conveyance

f3(kgCO2-e/ton km)

Truck (gasoline) Trucks (diesel) Trains (diesel) Ship (diesel)

0.288 0.207 0.036 0.035

Table 4.1 Energy consumption and GHG emission factors of the transshipment vehicle unit [50].

calculation formula is as follows:

Model of transshipment vehicle

EUj, i(kg or kWh/work-shift) Gasoline

Diesel

Electricity

4t 6t 8t 15 t

25.48 – – –

– 33.24 35.49 56.74

– – – –

ftrans(kg CO2-e/ work-shift) 89.43 122.32 130.6 208.8

km

E2 =

Pm, i

Tm, i

f2

i=1

Table 4.2 Unit energy GHG emission factors.

(2.1)

where Pm, i is the power of type i equipment in the manufacturing stage, which can be obtained from the corresponding part library (Appendix II); km is the number of equipment on the production line; Tm, i is the running time of type i equipment; f2 is the carbon emission factor of electricity consumption [41], which can be obtained from Table 2.1. Provinces and cities covered by each region can be obtain from Table 2.2.

Mp, i

Lp

f3

Tt , i

f2

e

=

Pe, i

Te, i

f2

(4.3)

i=1

where Pe, i is the rated power of the ith construction elevator (kW)， and ke is the number of elevators to be constructed on-site. These parameters can be obtained from the equipment inventory (Appendix II). Te, i is the construction time of the elevator operation (h). (7) Transfer vehicle a. The on-site transfer vehicle is mainly used for the on-site transportation of prefabricated components and some building materials (such as concrete and steel). The carbon emission calculation formula is as follows: ktrans

E4

trans

J

= i=1

kt

Pt , i

(4.2)

ke

E4

a. The carbon emission calculation formula of the tower crane in the construction site is as follows:

i=1

f2

The carbon emission calculation formula for the construction elevator is as follows:

(5) Tower crane

=

Wt , i

(6) Construction elevator

4.2.4. On-site carbon emission (E4) The carbon emission generated in the on-site stage mainly comes from various processing machinery and engineering equipment. It mainly includes steel processing machinery, the on-site transporter, tower crane, crane, mixer, concrete pump, welding machine, and forklift. The construction machinery considered in this paper includes the tower crane, construction elevator, and transfer vehicle.

t

=

where Wt, i is the electricity consumption (kWh).

where mp, i is the quality of a single type i prefabricated component (kg), np, i is the number of type i components per shipment and Mp, i (kg) is the total mass of type i components in a single shipment. Lp is the distance between the prefabrication plant and the construction site (in km). f3 is the GHG emission factor of the transport stage; refer to Table 3.1.

E4

t

i=1

(3.2)

np , i

3.51 3.68

kt

E4

where Mp, i is the total mass of the type i prefabricated component of a batch of components (kg) [44], and

Mp, i = mp, i

Gasoline Diesel

b. Another formula for calculating the carbon row of tower crane is

(3.1)

1000

ftrans, j(kg CO2-e/kg)

where Pt, i is the rated power of the ith tower crane (kW), and kt is the number of on-site tower cranes. These parameters can be obtained from the equipment inventory (Appendix II). Tt, i is the running time of the ith tower crane (h).

4.2.3. Carbon emissions of transportation stage(E3) The carbon emission E3 in the transportation stage refers to the carbon emission from the prefabrication plant to the construction site. The calculation formula is as follows:

E3 =

Types of energy

j=1

Ttrans, i

EUj, i 8

ftrans, j (4.4)

where ktrans is the number of on-site transfer vehicles, and J is the total number of types of energy consumed by the ith transfer vehicle

(4.1) 6

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[49]. These parameters can be obtained from the equipment inventory (Appendix II). Ttrans, i is the running time of the ith transfer vehicle (h), EUj, i is the quality of type j energy consumed per shift by the ith transfer vehicle (kg), and the value of this parameter is shown in Table 4.1. ftrans, j is the GHG emission factor produced by type j energy of unit mass (kg), and the value of this parameter is shown in Table 4.2.

5.1.1.1. RFID system. This is a non-contact automatic identification technology that finds the target object through a radio frequency signal, and can quickly track items and exchange data. The applicability of RFID systems in the construction industry has been confirmed, as they are widely used in the industry. An RFID system is a good tracking system. It has rendered obsolete the previous labor-intensive mode of tracking and management by manually recording information with paper documents. The high speed and accuracy of information input and retrieval are particularly suitable for various construction management functions. In addition, RFID has excellent adaptability and is resistant to temperature and metal [51]. In this study, anti-metal ultra-high-frequency RFID tags are employed. They can be attached on the surface of metal objects without affecting the read-write operations. of readers, which is beneficial in the complex and changing construction environment. The reading range of RFID readers is a sector, and in future the construction industry should focus on the development of handheld RFID readers [52]. This study will use the RFID system for embodied carbon emission (E1) data acquisition of component materials, in particular, the basic information of the prefabricated components in the production order. Information is obtained from the manufacturer, after which the information on each prefabricated component to be processed is prerecorded into the database, and the embodied carbon emission of the raw material required for the component is calculated in the server. At the same time, the RFID tag corresponding to the data is tied on the steel grid of the prefabricated component. The staff reads the tag through a handheld RFID reader to obtain the embodied carbon emission of the prefabricated component. Considering the sensitivity of RFID readers to RFID tags, UHF readers will be used to increase the reading and writing distance of RFID readers and enhance the reading and writing stability of RFID; see Fig. 2.

b. Carbon emissions can be calculated directly according to the carbon emissions per unit shift in Table 4.1: ktrans

E4

trans

=

Ttrans, i

ftrans 8

i=1

(4.5)

Ttrans, i denotes the running time of the ith transfer vehicle (h). ftrans denotes carbon emissions from the shift vehicle per unit shift (8 h), and its value is shown in Table 4.1. The total carbon emission (E4) in the on-site stage is

E4 = E4

t

+ E4

e

+ E4

trans

(4.6)

The total carbon emissions can be obtained by adding the carbon emissions of part 4 E1–E4:

E = E1 + E2 + E3 + E4

(4.7)

5. CEM system development This study designed a complete monitoring system based on various carbon sources in the prefabricated construction to be tested. The development of this system is mainly divided into two parts: hardware and software. The hardware consists mainly of various types of sensing equipment, which are used to collect original data regarding the carbon source. The software mainly processes the collected original data and presents the processed data. Meanwhile, the development logic of this system is based on the construction logic of the whole process of prefabricated construction, which is divided into three stages for the system development design and development framework. These stages are as follows: (1) the production stage of prefabricated components (Fig. 3), (2) the transportation stage of prefabricated components (Fig. 4), and (3) the site construction stage (Fig. 5). The development of the system hardware is described below in the order in which the phases occur.

5.1.1.2. Proximity switch. The proximity switch is a position switch that can be operated without direct contact with the moving parts. When the object approaches the sensor surface of the switch within the operating distance, no mechanical contact is required, and any pressure applied enables the switch to operate, thus driving dc electrical appliances or providing control instructions to computer (PLC) devices. Due to these advantages, it can effectively protect against the dust interference of the factory and the interference of unrelated metals. The proximity sensor switch is installed in the supporting wheel position of various stations in the production line. When the mold platform is moved into the station, the proximity sensor switch immediately issues instructions to the computer and records time t1. When the proximity switch senses the moving module leaving the station, instructions are transmitted to the computer, and time t2 is recorded. The server receives the time information and calculates the carbon emission (E2) generated by the work station in that time period using the formula.

5.1. Data acquisition methods and sensor development Carbon emission sources in the whole process of construction of the fabricated building that need to be studied have been identified in Section 4.1.2. The original data acquisition method will be determined based on the characteristics of the different carbon sources. From the foregoing, sources that generate carbon emissions are divided into three stages. The environments in both the construction site and the prefabricated factory are very complex. For safety and convenience, this study design employs the operation time of the various carbon sources in the collection to indirectly calculate and detect the source of carbon emissions. Therefore, this research intends to adopt different sensors to obtain the various mechanical work times.

5.1.2. Data acquisition method in the transportation stage In the transportation stage of prefabricated components, the main carbon emissions are generated by the transportation vehicles. For freight vehicles with prefabricated components, this study will monitor carbon emission using the GPS facility in smartphones. 5.1.2.1. GPS. GPS has the function of positioning and navigation on a global scale. Using smartphones to obtain GPS data to evaluate the energy consumption of vehicles is a reliable and effective approach [53]. In recent years, GPS has also been used to track vehicles to obtain carbon emission data. Among various vehicle that track data, taxi GPS data has become a popular data source for monitoring traffic, and estimating fuel consumption and emissions [53]. In this study, a smartphone app will be developed that uses the smartphone GPS to track transport vehicles. The driver will click the “Start Shipment” button on the app before departure and click the “End of Shipment” button after arriving at the destination. The tracked distance data of the

5.1.1. Data acquisition method in the production stage In the production stage of prefabricated components, the carbon emission generated by the processing machinery of the prefabricated components production line and the embodied carbon emission of raw materials required by the components are mainly monitored. An RFID system will be used to obtain the data for the embedded carbon emission of raw materials required by components， and the working times of the machinery on the production line of prefabricated components will be monitored by means of a proximity switch. 7

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Fig. 2. Monitoring system in production stage

truck will be uploaded to the server and calculated to obtain the carbon emissions generated in the transportation process (E3).

pressure. Therefore, it is not affected by obstacles in the process of measurement. The height range is wide and convenient to move. Further, the absolute altitude and relative altitude can be measured.

5.1.3. Data acquisition method in the on-site stage In the on-site stage, this study used three different types of sensor devices to monitor tower cranes, construction elevators, and transfer vehicles: the acceleration sensor, pressure sensor, and GPS sensor, respectively. Fig. 5 presents the framework of the monitoring system in the on-site stage.

5.1.3.3. A9G module. For transport vehicle monitoring, the A9G module will be used to obtain the position of the transport vehicle, velocity, and other information, and the motor speed will be used to judge the working state of the transport vehicle. The A9G module not only includes a GPS module, but it also has a GPRS module to conduct network and base station auxiliary positioning. Three sensors are integrated into one module (Fig. 6), which can meet the monitoring requirements of the three types of construction machinery in the on-site stage. The on-site carbon emission (E4) is calculated indirectly through the acquisition of the working time information of different machines.

5.1.3.1. Acceleration sensor. Tower crane monitoring will use the acceleration sensor, which estimates the working time of the tower crane by measuring the motion state of the tower rope. The sensor can obtain the angular velocity and acceleration components in the X, Y, and Z directions to judge the working state of the tower crane. Environmental factors, such as wind, can be eliminated by integrating acceleration and setting a threshold.

5.2. Software of GHG system development

5.1.3.2. Pressure sensor. The pressure sensor is used for construction elevator monitoring. Its working principle is to use the pressure difference method to measure the height through the change of

The software mainly includes the development of the database, server, and presentation platform (Web platform, desktop platform, and smartphone platform). Fig. 7 shows the framework of the software

Fig. 3. Framework of monitoring system in production stage. 8

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Fig. 4. Framework of monitoring system in the transportation stage.

logic, and the following list describes their functions in detail:

processing of data source for external incoming data and the data in the database, and the results are stored in the database.

5.2.1.1. Database. The database has the function of storage, data request interception, security, and backup. The data processed by the server will be stored in the database for easy recall at any time. The types of data stored in the database are (1) basic information on prefabricated components, (2) the type and power of tower cranes, construction elevators, on-site transfer vehicles, and (3) the calculated carbon emission result.

5.2.1.3. Presentation platform. Three presentation platforms have been developed for the benefit of the user: Web platform, desktop platform, and a smartphone app. The presentation platform can request the data to be displayed from the database. The real-time carbon emission data in the production, transportation, and construction stages are presented in the form of charts. The real-time location of the transportation process of the prefabricated components and the path will also be displayed in the presentation platform.

5.2.1.2. Server. The server is the core of the software. Its main function is to accept and transmit data, the server for the data processing center,

Fig. 5. Framework of monitoring system in the on-site stage. 9

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Fig. 6. Monitoring system in the on-site stage.

6. Implementation

development of the smartphone platform is mainly to enable staff who need to change their location constantly to participate in the feedback mechanism. The desktop platform is the core of the presentation platform. In addition to the display functions, there are also information input (component information, device information) functions. According to the sequence of stages from prefabricated component manufacturing to installation, the platform can be divided into three stages: the prefabricated component manufacturing stage, the prefabricated component transportation stage, and the on-site stage.

PC factory managers, logistics managers, and construction managers will control the carbon emission behavior of each link through the data presentation platform. The Web platform, desktop platform, and smartphone platform are three different platforms used to present carbon emission data, and they are coordinated by the server. The Web platform mainly displays the carbon emission data analysis, which enables personnel who have not downloaded the app to view the carbon emission information for communication and feedback. The

Fig. 7. Framework of software used by the monitoring system. 10

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Fig. 8. Monitoring system interface: (a) information entry interface, (b) visual monitoring interface.

6.1. Manufacturing monitoring of prefabricated components

equipment for that day. Unfinished components that are being processed can also be monitored, which is the information added to the visual interface after the components are scanned by the RFID reader. The third function is carbon emission data analysis. The original data uploaded to the server are processed, and the carbon emission data are displayed on the interface. Fig. 9 shows the dynamic display curve of the carbon emission data, which is refreshed every 15 s. As the plant's equipment continues to work, the curve will continue to change, representing increasing carbon emissions. The curve shows the carbon emissions at each time period, and the different colors represent the different carbon emission processes of different types of equipment. For example, as shown in the figure, red represents the carbon emission of the curing kiln, green represents the carbon emission of the vibrating table, and purple represents the carbon emission of the horizontal moving vehicle of the mold platform. The orange color indicates the prefabricated component's embodied carbon emission (E1). Pointing the cursor at the dot on the curve makes the specific values visible. The system also sets a warning line of carbon emission to remind the project manager when the carbon emission exceeds the normal value. In addition, the system also provides the function of historical data query. Users can observe the daily carbon emission data through the historical query. The cumulative carbon emission data also can be presented in the interface, through which the moment of the sharp rise of carbon emission data can be clearly observed. There are three types of pie chart: the direct carbon row pie chart, the direct carbon emission and the embodied carbon emission pie chart, and the carbon emission of different energy consumptions pie chart. The pie chart allows for a

Users can observe the carbon emission information in real time through the GEM system. For the benefit of users, three major functions are designed for the interface during the production of prefabricated components. The first is the information entry function, which is shown in Fig. 8(a). Users can input the order information of components to be produced in the information entry interface, including the component number, component type, component size, density, quality, and quantity. Furthermore, the user can add equipment according to the machine employed in the production line of the factory. As a result, the system can be adapted to a factory with different production lines. Meanwhile, for the convenience of operation, the function of importing Excel tables was added. These functions achieve the following goals:

• The carbon emission of components can be obtained from the component information. • Production line equipment can be added for visual rendering of prefabricated components. • The component transporter loads and unloads components to match the order.

The second function is visual management, which is shown in Fig. 8(b). After information on the production line is input, the userdefined production line will be generated in the visual interface. In this interface, the user can see which device is working on the current production line, and also the working hours and carbon emissions of the 11

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clearer picture of how carbon emissions are generated, allowing managers to strengthen their management of the major parts of the emissions. 6.2. Component transportation monitoring The component transportation stage involves developing an app for the driver. Before starting the vehicle, the driver can use the app to check the order information of the transportation components. After confirming that the transportation information is correct, the driver sets the departure and destination and clicks the Start Shipment button. The system will begin to locate the vehicle's trajectory, as well as measure the transportation distance and the carbon emissions produced by the truck. Other managers can monitor the information on vehicles on other display platforms at the same time. Fig. 10 shows the transportation interface. 6.3. On-site stage monitoring

Fig. 9. Analysis interface.

The carbon emission monitoring interface in the on-site stage is similar to the prefabricated component production stage. Various types of construction machinery can be added through the information entry interface. When adding a new construction machine, one can easily view its working status and carbon emission information on the visual interface. Moreover, information on prefabricated components arriving at the site can also be entered manually. The project manager can check the number and types of prefabricated components through the system. Fig. 11 shows the on-site interface. Data analysis of the on-site stage is similar to that for the production process of prefabricated components; therefore, it is unnecessary to go into the details here. 6.4. System pre-testing To ensure smooth operation of the GEM system, different parts of the system are pre-tested in each stage of system development. A precast component factory and a precast component project in Chongqing were selected for the pre-test. The pre-test is only to verify that the GEM system can work; the pre-test team has not yet worked on data acquisition. Furthermore, the duration of pre-test processes is relatively brief, thereby enabling the validity and applicability of the GEM system to be verified. (See Figs. 12 and 13.) 7. Discussion Several potential benefits of the monitoring system have been demonstrated in the development and pre-test, and some deficiencies of the system can be eliminated to bring it closer to reality. 7.1. Benefits 1. Real-time monitoring: The system provides a tool for real-time monitoring of carbon emissions. The project team can monitor in real time the carbon emissions generated during the three stages of manufacturing, transportation, and installation of prefabricated components with the aid of a variety of sensors. These data are further processed in the system software and displayed in three presentation platforms, enabling managers to detect fluctuations and spikes in carbon emissions at various stages in a timely manner. The system allows managers to control the production process, transportation process, and installation process to minimize the impact of carbon emissions. 2. Practical sensors: The sensors included in the system are small, and therefore they have little impact on prefabrication factories and construction sites. The system automatically collects data through the installed sensors, which improves the accuracy of data acquisition and reduces labor costs. The sensors are practical and easy to 12

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Fig. 10. Transportation interface: (a) smartphone platform, (b) desktop platform.

produce, which lays the foundation for the popularization of realtime CEM systems in future. 3. Covers the whole process of prefabricated construction: Unlike previous studies, the developed monitoring system is based on the whole process of prefabricated components from production to installation, and can monitor carbon emissions across the whole process of prefabricated building construction. As a more comprehensive range of carbon emissions is considered, the data collected by the system can better reflect the carbon emission of prefabricated buildings.

manual operation of the prefabricated components. In the transportation stage, the activities of loading and unloading prefabricated components to and from vehicles are not monitored either. In the construction site, in addition to the machinery mentioned in this paper, some other mechanical and artificial carbon emissions are not monitored in the system. 2. Improvement of sensors. The CEM system uses a variety of sensors. These sensors have certain advantages, because they are independent of the circuit, and the carbon emissions generated by the related machinery is calculated by an indirect method, which has the advantage of improved safety. However, in the factory, the method employing a smart meter may be more convenient and accurate, but the factory and site managers will need to take the safety of the researchers and impediments to the project into consideration. In the future, it will be more convenient and user-friendly to monitor carbon emissions through various smart meters, and various sensors will be used to measure the carbon emission activities generated by worker behaviors. 3. Improvement of quantitative calculation model. The choice of the quantitative model of carbon emissions in each stage is worth further consideration. For example, the formula for carbon

7.2. Deficiencies 1. The scope of carbon emission sources. In addition to the carbon emission sources mentioned in this paper, other carbon emission behaviors occur in the whole process of constructing fabricated buildings. There are few fully automatic prefabricated component production lines in China, and many prefabricated part factories use a combination of manual and semi-automatic production lines. The result is that in addition to the energy consumption generated by the machine, a portion of the carbon emissions is generated by the

Fig. 11. On-site interface: (a) information entry interface, (b) visual monitoring interface.

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Fig. 12. Pre-testing: (a) Installation of acceleration sensor, (b) testing RFID system, (c) testing mobile phone GPS system.

emissions produced by vehicles in the transportation stage can be improved, because the difference between fuel consumption during acceleration and during the static state is not taken into account, which is obviously a factor that influences carbon emissions.

summarizes the quantitative model of carbon emission calculation. Finally, the paper considers the requirements of users and develops three types of data and visual presentation platforms. This study advances our knowledge of research methods (e.g. CPS is used to collect and analyze carbon emissions), which help promote research into and application of the CPS concept in the construction industry. The development of this system is helpful for analysis and control of carbon emissions in the whole process of constructing fabricated buildings. Carbon emission monitoring is of great significance for the establishment of a mature energy conservation and emission reduction policy. The accurate and timely determination of the carbon emission of each construction activity of industrial buildings will help improve the environmental performance of China's industrial buildings, and will aid the formulation of carbon tax and carbon emission trading policies in China. However, it is worth mentioning that the system is still in its infancy. More functions of the system will be developed in the future, such as the use of RFID tags to track the carbon emissions generated by prefabricated components having the same function but made of different materials. Meanwhile, more work will be performed, such as using the system to monitor and compare the carbon emissions produced at different stages of prefabricated construction for further research on prefabricated construction.

8. Conclusion The utilization of emerging information technology is the future development trend of the construction industry. Carbon emissions are a new dimension of building measurement and have raised concerns; hence, they have been widely studied. IoT, CPS, and other technologies make it feasible to monitor and control carbon emissions from buildings. The author and his team designed a complete CEM framework for the whole process of constructing fabricated buildings, and developed a carbon emissions monitoring system based on this framework. On the theoretical basis of CPS, the system monitors the carbon emissions generated at all stages from the production of prefabricated components to installation and provides data analysis. Through a literature review, this paper puts forward the necessity for and feasibility of real-time carbon emission monitoring, defines the construction boundary of prefabricated buildings, and summarizes the carbon emission source at each stage. The paper then focuses on developing different types of data acquisition systems for large carbon sources, and

Fig. 13. Pre-testing: (a) testing proximity switch, (b) testing A9G module.

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Acknowledgments

work described in the current paper was supported by grants from the National Key Research and Development Program of China (Grant No. 2016YFC0701807), and the Fundamental Research Funds for the Central Universities (No. 2017CDJSK03XK20).

The authors wish to express their sincere gratitude to the Research Center of Construction Industrialization and Innovation of Chongqing University for their help in data collection and technical support. The Appendix I Component part library (1) Types

Serial number

Composite slab

DBS1 DBS2 DBS3 DBS4 JLQ1 JLQ2 JLQ3 JLQ4 JLQ5

Shear wall

Size (m) 2.73 × 0.4 × 0.1 2.75 × 0.4 × 0.1 5.51 × 0.4 × 0.1 5.51 × 0.5 × 0.1 3.8 × 2.9 × 0.24 3.6 × 2.9 × 0.24 1.5 × 2.9 × 0.4 0.8 × 2.9 × 0.4 1.2 × 2.9 × 0.4

Component density ρ (kg/m3) 3

2.52 × 10 2.52 × 103 2.52 × 103 2.52 × 103 2.54 × 103 2.54 × 103 2.54 × 103 2.54 × 103 2.54 × 103

Concrete density ρc (kg/m3)

Steel content r

3

2.4 × 10 2.4 × 103 2.4 × 103 2.4 × 103 2.4 × 103 2.4 × 103 2.4 × 103 2.4 × 103 2.4 × 103

– – – – – – – – –

Component part library (2) Types Stair

Dogleg stair

Scissor Stair

Beam

Serial number

Size(m)

Mass of the component (kg)

Mass of the concrete (kg)

Mass of the steel bar (kg)

ST-28-24 ST-28-25 ST-29-24 ST-29-25 ST-29-24 ST-30-25 JT-28-25 JT-28-26 JT-29-25 JT-29-26 JT-30-25 JT-30-26 GL1 GL2 GL3 GL4 GL5 YTL1 YTL2 YTL3 YTL4 YTL5

1.125 × 0.175 × 0.26 1.195 × 0.175 × 0.26 1.125 × 0.1611 × 0.26 1.195 × 0.1611 × 0.26 1.125 × 0.1666 × 0.26 1.195 × 0.1666 × 0.26 1.16 × 0.175 × 0.26 1.21 × 0.175 × 0.26 1.16 × 0.1706 × 0.26 1.21 × 0.1706 × 0.26 1.16 × 0.1667 × 0.26 1.21 × 0.1667 × 0.26 0.12 × 0.24 0.18 × 0.24 0.24 × 0.24 0.30 × 0.30 0.30 × 0.36 4.00 × 0.16 × 0.14 4.00 × 0.24 × 0.14 6.00 × 0.16 × 0.14 6.00 × 0.24 × 0.14 6.00 × 0.38 × 0.14

1610 1720 1810 1920 1840 1950 4340 4500 4640 4830 4980 5200 480 524 600 658 722 9000 9500 12,440 14,200 15,400

1537.82 1646.68 1735.85 1844.71 1765.17 1874.03 4145.65 4306.23 4433.33 4621.49 4766.74 4984.8 467.5 508.5 582.5 637.5 699.5 8600 9090 12,020 13,770 14,960

72.18 73.32 74.15 75.29 74.83 75.97 194.35 193.77 206.67 208.51 213.26 215.20 12.5 15.5 17.5 20.5 22.5 400 410 420 430 440

Appendix II Equipment inventory (1) Equipment name

Types

Rated power (kw)

Tower crane

QTZ40 QTZ63 QTZ80 QTZ125 QTZ160 SC200/200TD SCD200/200GZ SCD200/2002/200TD SCD200/200 SCD200/200GZ SCD200/200 SCD200/200TD SCD270/270TD SCD320/320TD SC100/100 SC100/100TD SC150/150

24.3 39.6 45.6 52.6 62.3 2 × 3 × 11 2 × 3 × 11 2 × 3 × 11 2 × 3 × 11 2 × 3 × 18.5 2 × 2 × 11 2 × 2 × 11 2 × 3 × 11 2 × 3 × 11 2 × 2 × 11 2 × 2 × 11 2 × 2 × 15

Construction elevator

Construction elevator with counterweight

Construction elevator without counterweight

15

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2 × 3 × 15 2 × 3 × 11 2 × 3 × 15 2 × 3 × 18.5

Equipment inventory (2) Equipment name

Types

Energy consumption types

Transfer vehicle

JX1042TPG25 BJ1043V9AB5 JX1073TG25 JX1043TG25

Diesel Diesel Diesel Diesel

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