A Review of Research Progress in Carbon Monitoring and Carbon Metering Methods: Comparison at Home and Abroad

Abstract

Carbon monitoring and carbon measurement are not only important foundations for realizing the marketization of carbon trading, but also a key link in realizing China’s strategic “dual carbon” goal. The aim of this research is to comprehensively summarize and compare carbon monitoring and carbon metering technologies, as well as to analyze their current status and challenges. This study adopts literature research, comparative analysis, case analysis, policy interpretation, and other methods to comprehensively and deeply explore the relevant content of carbon monitoring and carbon metering technology. An in-depth exploration of relevant methods, standards, and applications provides a reference for promoting the sustainable development of global carbon monitoring and carbon metering technologies. By summarizing the difficulties of carbon monitoring and the characteristics of existing technologies, as well as comparing carbon measurement methods and the relevant measurement standards, this paper focuses on the difficulty of carbon monitoring, which lies in the credibility and accuracy of the data, where remote sensing technology possesses higher applicability. The principles of carbon measurement methods mainly include direct underlying data measurements, indirect measurements through statistical modelling, and market mechanism measurements. The relevance and precision of carbon measurement methods have been gradually strengthened as the measurement standards have been developed and implemented. Finally, future development directions and relevant suggestions will be described in detail and put forward in combination with the application of carbon monitoring and carbon measurement. Among them, blockchain technology is considered to be one potential area for future development, and data standardization will play an important role in the development of carbon monitoring and measurement technology. We recommended establishing and perfecting data-sharing mechanisms in future policies to improve the accuracy and credibility of data.

1. Introduction

The Paris Agreement calls for global action to reduce emissions of CO₂. As countries strive to meet climate targets, developing accurate carbon measurement systems is crucial for supporting low-carbon economies and international cooperation. As one of the major emitting countries, China has made significant commitments in this area [1]. In 2020, China proposed a “carbon peak” by 2030 and “carbon neutrality” by 2060; thus, the importance of carbon monitoring and carbon metering is growing. With the development of carbon emission measurement patterns, a domestic low-carbon economy has gradually emerged [2], and international environmental cooperation is actively maintained through the regulation of carbon emissions [3].

To date, carbon monitoring technology has achieved certain advances in terms of internet technology integration and platform construction. In particular, in the research and development of monitoring equipment, not only can satellite remote sensing technology be used to improve monitoring accuracy [4], but also integration with internet technology can be realized by combining it with the infrared light absorption method [5,6]. For example, Li Yaowang et al. [7] established a lossless equivalent network model and pioneered a new method of carbon measurement using electricity. Chen Ying et al. [8] proposed a low voltage station area collaborative management method based on micro-grid carbon metering data to better adapt to the scenario of having different proportions of renewable energy in a power system, aiming to achieve a high proportion of new energy and multi-agent interconnection. Zhao Tong [9] designed a “dual carbon” data management platform based on blockchain technology to promote the development of carbon trading markets and establish global carbon measurement standards, laying a solid foundation for the development of carbon monitoring and carbon measurement engineering applications. In view of this, it is necessary to summarize and compare carbon monitoring and carbon measurement technologies, so that readers can fully understand the current technical status and carry out relevant research in this field. However, the current research rarely dissects the difficulties of carbon monitoring and carbon measurement in detail, and summaries of application scenarios are especially lacking. This affects the research and development and exploration of the relevant technology.

Therefore, this work employs the literature review method to summarize the difficulties of carbon monitoring and the characteristics of existing technologies, comparing the development of carbon measurement methods and measurement standards. At the same time, combined with current applications of carbon monitoring and carbon metering, this work puts forward a development forecast and makes relevant suggestions in order to provide a reference for promoting the sustainable development of carbon monitoring and carbon metering technology in China. Based on this, this study mainly focuses on the specific problems encountered in the current carbon monitoring and carbon measurement situation and how to choose corresponding solutions; it also summarizes and classifies existing technologies and their applications. This study conducts a comprehensive analysis of existing technologies and methodologies, identifies current research gaps, and proposes actionable recommendations. It aims to enhance the accuracy and reliability of carbon data, thereby contributing to the achievement of global carbon reduction targets.

2. Difficulties and Challenges in Carbon Monitoring

2.1. Difficulties and Solutions of Current Carbon Monitoring

Through investigating the existing literature on this topic, this work was able to analyze and summarize the relevant information for this study. The research methods mainly involved the synthesis of existing research results. As shown in Figure 1, the existing difficulties in carbon monitoring mainly include the requirement for high-precision data, the challenges of technical limitations and regional variability, as well as the difficulty of data and model analysis.

2.1.1. Requirements for High-Precision Data

At present, the main difficulty faced by carbon monitoring technology is that the accuracy of monitoring data is very high. Faced with the unstable flow field of cross-section monitoring and the uncertainty of flue gas velocity measurements, the question of how to obtain accurate flue gas flow measurements is a key issue for carbon monitoring technology [10]. In this regard, first, it is necessary to establish an international standard and the high-precision transmission of comparable, domestic, quantitative value traceability/transmission technology systems to ensure that the reported data are based on evidence. The second requirement is to strengthen the standardization of instrument configurations, point layouts, and automatic monitoring. Third, the calibration and quality control of the relevant instruments should be carried out regularly to verify the accuracy of monitoring systems.

2.1.2. Challenges of Technical Limitations

Based on the present analysis, due to the constraints and limitations of monitoring technology, some greenhouse gas monitoring approaches continue to encounter great technical difficulties [11]. In order to achieve efficient, accurate, and dynamic carbon monitoring, various emerging monitoring technologies need to be utilized, for example, remote sensing monitoring technology, “sky and earth” integrated carbon sink resource monitoring technology, and other new technologies. In addition, the application of various cutting-edge emerging technologies should be expanded to achieve dynamic supervision and predictions of changes in carbon sink resources and actual reserves [11].

2.1.3. The Problem of Regional Variability

Among the difficulties faced in carbon monitoring, we also observe the problem of carbon monitoring differences in different regions, which may be related to specific human activities, geography, climate, and other factors. To this end, we need to encrypt the layout of the monitoring stations and also improve the spatial and temporal resolution of the monitoring data. In addition, city and regional management departments need to rely on integrated and intelligent platforms to promote the development of intelligent carbon monitoring approaches [12].

2.1.4. Problems in Data and Model Analyses

In carbon monitoring data processing, algorithms and models play a key role. Data processing may encounter errors, biases, and algorithm selection problems. Additionally, uncertainty in modeling and parameter settings can directly affect the reliability of the data.

To overcome the challenges associated with carbon monitoring data processing and model uncertainties, we should first strengthen machine learning and blockchain algorithm research to achieve accurate positioning and dynamic monitoring of carbon footprints. Secondly, we should optimize the database and model selection to ensure the authenticity and reliability of large-scale calculations. Thirdly, we should use intelligent monitoring equipment to collect data in real time and simulate predictions to effectively monitor changes and trends in carbon emissions. Finally, technologies such as base station measurements, remote sensing measurements, and meteorological observations should be used to ensure that scientific and reliable data are obtained [13].

2.2. Current Carbon Monitoring Technology

At present, emission factor methods and on-line monitoring methods are most widely used in China and elsewhere. Developed countries in Europe and the United States are taking the lead in terms of using carbon emission monitoring to assist in carbon emission reduction; these nations have formulated a relatively complete standard system and specific implementation rules [14]. In comparison, the construction of China’s carbon emission monitoring system started relatively late, and although it has achieved certain results in recent years, it still has problems and defects due to the short implementation time [12]. As shown in Figure 2, problems and defects persist in monitoring systems, monitoring capacity, institutional access and information sharing, and monitoring technology.

At present, a variety of carbon monitoring technologies are used around the world. The following is an introduction to several carbon monitoring technologies:

2.2.1. Emission Factor Method

The emission factor method is a monitoring method based on fuel end emissions which calculates the CO₂ emissions of enterprises through activity data and the corresponding emission factors [15]. The formula is as follows:

$$E_{rs}={\displaystyle \sum _{i=1}^n\left(F{C}_i\times C_{ar,i}\times O{F}_i\times \frac{44}{12}\right)}$$

(1)

where E_rs is emissions from fossil fuel combustion (calculated as CO₂), F_Ci is the i type of fossil fuel consumption (i.e., solid or liquid fuels), C_ar,i is the received base element carbon content of the i fossil fuel, OF_i is the carbon oxidation rate of fossil fuel i, and 44/12 is the relative molecular mass ratio of CO₂ and C.

Existing studies have been able to predict carbon emission factors quite accurately, but there are still problems such as the reduced accuracy caused by complex factors [16].

2.2.2. Online Monitoring Method

The basic principle of the online monitoring method is to calculate the total carbon emission rate through the online monitoring of parameters such as CO₂ concentration, flue gas flow rate, and the temperature and pressure in the tail flue [17]. Its calculation formula is

$$M={\displaystyle \frac{P_{ct}{V}_s(1-w)\times 44}{RT}}\phi \left({CO}_2\right)\times {10}^{-3}$$

(2)

where M is the carbon emission rate, P_ct is flue gas pressure, vs. is the volume flow rate of the flue gas, φ is the humidity of the flue gas, R is the standard molar gas constant, T is the flue gas temperature, and C (CO₂) is the volume fraction of CO₂ in the flue gas.

In the context of a carbon market, online carbon emission monitoring technology has various advantages, but there are still many problems in its application which need to be further improved.

2.2.3. Carbon Balance Method

Based on the principle of material balance, carbon balance methods calculate the amount of CO₂ released into the atmosphere by subtracting the amount of carbon in the ash after combustion from the amount of carbon consumed over a statistical period [14]. According to the material balance of carbon, the calculation method of CO₂ emissions is as follows:

$$E_{rs}={\displaystyle \frac{44}{12}}\times [{\sum }_{i=1}^n(F{C}_i\times C_{ar,i})-Q_a\times C_a-Q_b\times C_b]-E_{xs}$$

(3)

where Q_a is the amount of fly ash produced after combustion, C_a is the carbon content of fly ash after combustion, Q_b is the amount of slag produced after combustion, C_b is the carbon content of the slag after combustion, and E_xs is the CO₂ absorption amount of CCUS (Carbon Capture, Utilization, and Storage) process.

The carbon balance method can directly reflect the amount of carbon emitted and lost, which is of great significance for realizing energy saving and carbon reduction as well as carbon emission calculations and model construction [18].

2.2.4. Soft Sensing Method

The soft sensing method is an indirect measurement technology based on a mathematical model and calculation method. It estimates the variables which are difficult to measure directly by exploring the correlation between the measurable auxiliary variables and those to be measured. It includes mechanism modeling, data-driven modeling, hybrid modeling, and other methods; these need to go through auxiliary variable selection, data acquisition and preprocessing, model establishment, verification evaluation, online correction, and other steps. The soft sensing method offers advantages such as low cost, high reliability, real-time monitoring, and adaptability to complex processes. However, its accuracy depends heavily on the quality of the input data. Additionally, the method faces challenges such as limited adaptability, difficulty in model construction, and high real-time computational requirements. Despite these limitations, it is widely applied in fields like industrial process control, environmental monitoring, and energy management [19].

2.2.5. Satellite Monitoring Method

The satellite monitoring method can determine CO₂ column concentrations based on satellite remote sensing data and calculate CO₂ emissions using the Gaussian plume model. It has the advantages of objective, continuous, stable, large-scale, and repeatable observation. Remote sensing data can be utilized as environmental covariates, combined with other factors (such as climate, topography, etc.) to develop and improve the accuracy of carbon prediction models [20]. Satellite remote sensing is also being applied in a new generation of internationally recognized global carbon verification methods [21].

For the above mentioned carbon monitoring technologies, as shown in

Table 1. Advantages and disadvantages of carbon monitoring technologies.

Carbon Monitoring Method	Advantages	Drawbacks	References
Emission factor method	1. Simple calculation and easy statistics. 2. Can achieve accurate quantitative calculations of CO2 emissions.	1. Some values are not measured, which often causes measurement difficulties and data errors. 2. Monthly measurements can only count emissions on a monthly basis, and real-time data cannot be obtained. 3. There are too many human participation factors, leading to misreporting and the falsification of data.	[15]
On-line monitoring method	1. Each emission source requires only one set of monitoring equipment to determine CO2 emissions directly at the emission source. 2. Emission data monitoring and analyses can be highly automated. 3. Real-time emission data can be continuously obtained and automatically transmitted to the competent authorities. 4. Good timeliness, can achieve minute level monitoring. 5. Simple data analysis and processing, saving manpower.	1. Lack of appropriate support system. 2. Mainly applicable to the centralized flue, not applicable to dispersed emission sources.	[10]
Carbon balance method	1. Carbon balance methods can accurately calculate and inventory the “carbon bottleneck” in production links. 2. They can quickly and accurately measure the carbon content of fly ash.	The theoretical CO2 emissions calculated by the carbon balance method are still higher than the actual CO2 emissions.	[17]
Soft sensing method	1. Compared with traditional direct measurement methods, soft measurement technology is more flexible and cheaper. 2. Soft sensing methods have strong generalization ability and good robustness and comprise diverse types.	1. Building accurate soft-sensor models may require complex mathematical and statistical techniques. 2. The soft measurement method has high requirements in terms of the quality and reliability of the input data.	[15]
Satellite monitoring method	Satellite monitoring can quickly and accurately invert the spatial and temporal distribution of atmospheric parameters such as CH4 and CO2 and can accurately assess the carbon sequestration capacity and value of ecosystems. 2. Compared with traditional ground monitoring and manual verification means, satellite remote sensing has the advantages of wide coverage, short acquisition cycles, fast update speeds, and fewer restrictions.	1. Due to the limited monthly emission data of most thermal power plants and the influence of weather, wind speed, and other factors, errors may be large and the accuracy is low. 2. The use of carbon monitoring satellites is still in the early stage.	[21]

, their respective advantages and disadvantages are presented here for comparative analysis.

2.3. Development of Carbon Monitoring Technology in China and Abroad

Carbon monitoring technology includes remote sensing technology, carbon emission technology, land use change monitoring technology, and carbon storage and sequestration technology. In terms of carbon monitoring technology, developed countries usually adopt high-tech means such as satellite remote sensing, advanced sensor technology, and big data analysis to achieve global carbon monitoring; their satellite remote sensing technology has unique advantages in terms of monitoring large-area carbon emission sources and absorption sources [21]. Figure 3 shows a comparison of carbon monitoring and carbon metering technologies in China and abroad since the 1990s. Among countries focusing on the development of carbon monitoring and carbon measurements with high levels of precision, efficiency, and automation development, and in a context of the intensification of climate change and environmental awareness, although China’s development started late, it is expected to narrow the gap in policy support and technological innovation breakthroughs in the coming years. In the 21st century, China’s domestic carbon monitoring technology has gradually developed in the direction of automation and intelligence; it has also strengthened research in and the application of new technologies and methods.

3. Carbon Measurement Standards and Characteristics

3.1. Types of Carbon Measurement

3.1.1. Source-Based Carbon Metering

Source-based carbon measurement describes a method to quantify carbon emissions which focuses on measuring and calculating the greenhouse gas emissions generated by a specific emission source over a specific time period [22]. This method can help enterprises and organizations to better understand their emissions situation, so as to take corresponding emission reduction measures.

3.1.2. Carbon Measurements Based on Activity Levels

Carbon measurements based on activity levels describe a method to calculate greenhouse gas emissions by focusing on the activity level of the emission source [22]. Compared with source-based carbon metering, activity-based carbon metering focuses more on the activity level of the source rather than the source itself. It provides a quantifiable, comparable, and traceable way to drive action to reduce emissions and promote sustainable development.

3.1.3. Carbon Measurements Based on Life Cycle

Carbon measurement based on life cycle is a comprehensive study of energy consumption and material emissions during the entire life cycle of a product to evaluate carbon emissions during the life cycle [23]. Starting from the whole process of raw material mining to waste disposal, this method analyzes and evaluates the resource and energy input, output, and corresponding environmental impact of the product [24]. This method has a detailed calculation process and more accurate results and is suitable for micro level calculations. Its disadvantage is that the determination of life cycle stages and boundaries is complicated, and the accounting cost and time cost are high [25].

3.2. Carbon Measurement Methods

Carbon measurement methods typically describes methods and technical means used to calculate the carbon emissions generated by the industrial activities of institutions or enterprises. Current calculation methods are still developing and improving.

3.2.1. Carbon Emission Factor

This approach can be understood as adding a calculation factor to traditional energy measurement units. The calculation formula is as follows:

$${\mathrm{EF}}_i{{=\mathrm{CC}}_i}^{*}{{\mathrm{OF}}_i}^{*}{\displaystyle \frac{{\mathrm{Mr}}^{C{O}_2}}{{\mathrm{Mr}}^C}}$$

(4)

where EF_i is the carbon emission factor, CC_i is the carbon content per unit calorific value of fossil energy i, OF_i is the carbon oxidation rate of fossil fuel i, Mr^CO2 is the relative molecular weight of CO₂, and Mr^C is the relative molecular mass of C.

Below is a formula to calculate the carbon emission factor. Here, we take the burning of solid fuels as an example:

$$E_{C{O}_2}={\displaystyle \sum _{i=1}^{n}F{C}_i\times NC{V}_i\times E{F}_i\times \frac{44}{12}}$$

(5)

where E_CO2 is the emission of solid fuel CO₂, FC_i is the consumption of fuel i, and NCV_i is the net calorific value of fuel i.

This method is suitable for a macroscopic accounting level and can roughly evaluate the overall situation in a specific region. The disadvantages of this method are that it cannot reflect spatio-temporal differences in product production and there may be large errors.

3.2.2. Mass Balance Method

In the carbon mass balance method [15], carbon emissions are determined based on the input carbon content minus the non-CO₂ carbon output.

$${\mathrm{E}}_{\mathrm{rs}}={\displaystyle \frac{44}{12}}\times \left[{\displaystyle \sum _{i=1}^n\left(F{C}_i\times C_{ar,i}\right)-Q_a\times C_a-Q_b\times C_b}\right]-E_{xs}$$

(6)

The method is based on specific facilities and processes, and the calculated emissions can reflect the actual regional emissions. It can not only distinguish the differences between various types of facilities but also the differences between individual and partial equipment; however, it requires high-level laboratory conditions and technical capabilities [25].

3.2.3. Measurement Method

This measurement method refers to the measurement of CO₂ emissions and energy consumption through the monitoring and statistical data of national and local monitoring, measurement and statistical institutions, or through standard experimental methods [24]. The obtained results are closer to the actual situation and are suitable for energy consumption and carbon emission evaluations of existing buildings. The key lies in obtaining payment data, metering data, and energy consumption data [24].

3.2.4. Emission Coefficient Method

The emission coefficient method refers to the statistical average and treatment of greenhouse gas emissions from a production unit product or secondary energy usage under an average productivity level, as the carbon emission coefficient of the process. This method is based on a carbon footprint factor and is often used for agricultural carbon measurements [26]. Taking building carbon emissions as an example, the calculation formula for building carbon emissions over a whole life cycle [27] is as follows:

$$P=P1+P2+P3+P4+P5+P6+P7$$

(7)

where P1 (carbon emissions in the material production stage) equals the product of the consumption of each material and the corresponding carbon emission factor, P2 equals the product of the energy consumption during material transportation and the corresponding carbon emission factors, P3 equals the product of the engineering quantity of prefabricated components and the corresponding carbon emission factor, P4 equals the product of the energy consumption during prefabricated component transportation and the corresponding carbon emission factor, P5 (carbon emissions during construction) equals the product of the consumption of machinery and the corresponding carbon emission factor, P6 is the carbon emissions in the operation stage, and P7 is the carbon emissions in the dismantling phase.

The calculation direction of carbon emission coefficient method is clear, the calculation logic is clear, and the applicability is broad [27].

3.3. Carbon Measurement Characteristics

To assess whether the aforementioned carbon measurement approaches are effective, reliable, and useful, their characteristics are summarized in Figure 4. The integrity of each method must cover all relevant emission sources and activities, including emissions along the entire value chain, such as energy production, industrial processes, etc.

Data collection, calculations, and reporting processes must be transparent to promote trust, communication, and cooperation among stakeholders. Also, the results must be accurate, reflecting the actual carbon emissions, and have repeatability and verifiability. Timeliness reflects the current emission status and emphasizes the need for regular updates and monitoring of carbon emission data. The chosen method should also facilitate comparisons of emissions between different organizations, industries, or countries. These methods are flexible and can be adapted to the characteristics and needs of different industries, organizations, and regions, since different emission sources and activities may require specific measurement methods and data sources. Finally, the target orientation of carbon measurements should be related to emission reduction targets and policies to help organizations and countries understand emission levels and formulate and track the progress of emission reduction targets [28].

3.4. Development of Carbon Measurement Standards

With the developments in science and technology, carbon measurement standards are also developing in a more scientific way. The development process is shown in Figure 5.

The role of carbon metering standards in measuring and managing carbon emissions, carbon storage, and carbon-related activities includes the following. Firstly, carbon emission standards, as one of the main aspects, are mainly concerned with the measurement and management of carbon emissions generated by organizations or activities. For example, the ISO 14064 [29] series of standards provides standardized measurement methods, thereby helping organizations understand, report, and reduce their carbon emissions to achieve environmental goals. Secondly, remaining emissions are offset through renewable energy or carbon offset projects, such as the Verified Carbon Standard, which is used to assess and confirm the authenticity, sustainability, and positive impact of carbon offset projects [30].

Carbon footprint standards that aim to measure life-cycle carbon emissions include product carbon footprint standards and organizational carbon footprint standards, which help businesses and consumers understand and reduce the carbon footprint of their products or services; examples of these include the Publicly Available Specification 2050 and the Greenhouse Gas Protocol. Finally, the carbon finance standard focuses on the financial sector, regulating carbon markets, carbon trading and carbon financial products, and improving the transparency and reliability of carbon financial products.

Developed countries have formed a carbon measurement standard system from the enterprise level to the national level. In contrast, China needs to further strengthen research on carbon emission factors, as the accurate determination of emission factors in various industries and different activities is crucial for the establishment of scientific and reasonable carbon measurement standards [31].

Figure 5. Chronological development of carbon measurement era. VCS—verified carbon standard; GGP—greenhouse gas protocol [32,33,34].

Figure 5. Chronological development of carbon measurement era. VCS—verified carbon standard; GGP—greenhouse gas protocol [32,33,34].

4. Engineering Application Status and Development Suggestions

4.1. Technical Classification

The application status of carbon monitoring and carbon metering (as the two complement each other) is shown in

Table 2. Current Status of Carbon Monitoring and Carbon Measurement Applications.

Classification	Research Method	Focus on Key Points	Valid Conclusion	Literature
Carbon monitoring	Remote sensing technology	Atmospheric greenhouse gas concentrations	China Carbon Inventory satellite remote sensing research will achieve high spatial and temporal resolution atmospheric CO2 and CH4 satellite monitoring, combined with multi-source data for carbon assimilation system and data-driven high-resolution carbon flux and emission estimations. This initiative will also support global carbon inventory and carbon neutral verification.	[38]
	Marine surveying	Interannual change rate of global sea surface pCO2	CMIP5 shows that the interannual change of the global sea surface partial pressure of carbon dioxide (pCO2) will increase by about 64 ± 20% in the 2040–2090 period, mainly affecting the sensitivity of the ocean to dissolved inorganic carbon and temperature changes. There are differences in model projections. Decreasing inorganic carbon fluctuations offsets increases, and ocean pCO2 is driven by dissolved inorganic carbon, temperature changes, and the ability to fix CO2.	[39]
	Air sampling and analysis	Measurement of PM and CO2	Indoor air is affected by people and activities. PM concentrations below ASHRAE standards are critical for maintenance and filters. Double windows protect people against outdoor PM. The drop rate of fine particles is low, so the space design should be optimized. Low PM does not guarantee good air quality, and CO2 affects comfort. Automatic ventilation and sensor applications are beneficial, and cross-field cooperation is recommended. These results were preliminary, using a small data set, and did not measure CO2 and PM simultaneously.	[40]
Carbon accounting	Carbon offset certification	Carbon offset project review and certification	Social tree organizations focus on sustainability certifications, such as PlanVivo and Carbonfix, rather than just carbon offsets. Compliance market certification emphasizes carbon sequestration and is not suitable for serving the community. Cost is a factor in considering certification, and society relies on trust. Offset buyer demand or change as the market changes.	[41]
	Carbon footprint measurement	Full life-cycle stage carbon footprint	In order to reduce the carbon footprint of the production cycle of packaging and printing products, carbon emissions can be reduced by energy-saving retrofitting of equipment, reducing the use of film and glue, and optimizing structural design and implementing innovative processes in which electricity consumption and film and glue use are key influencing factors.	[42]
	Carbon financial transaction	Clean energy mechanism	Goals: China’s economic development, strengthening market demand, improving the legal system and monitoring mechanism, developing the carbon financial derivatives market, and strengthening the participation of market players.	[43]

. Carbon monitoring provides real-time and accurate carbon emission data, which provides a basis for the formulation of carbon measurement standards and the implementation of carbon emission reduction policies. Foreign countries are generally more developed in these two aspects, integrating various data sources and adopting advanced analysis methods [35]. Although China has made some progress in the construction of monitoring equipment, there is still room for improvement in data integration and analysis for carbon monitoring and carbon measurement, as well as in-depth research on the characteristics and rules of carbon emissions in different industries [36]. In general, there are differences in carbon monitoring technologies, carbon measurement standards, policies, and regulations at home and abroad. However, with the common goal of global carbon emission reductions, international cooperation and experience exchange will become the key to promote the continuous improvement of carbon management systems in various countries [37].

4.2. Engineering Application Status

In fact, there are many industrial applications, even including carbon emissions in the pyrolysis of carbon-containing minerals and desulfurization and denitrification. However, due to limitations of space, this paper focuses on the main application situations and the application scenarios that scholars are paying the most attention to.

4.2.1. Application in Construction Engineering

Reducing carbon emissions in construction projects mainly includes the selection of environmentally friendly materials and construction technology and intelligent monitoring and management. SooHuey Teh et al. [44] believe that the use of renewable materials can reduce energy consumption in the production process. Under the trend of the widespread application of prefabricated buildings, Zhikun Ding et al. [45] established a carbon emission measurement model based on BIM technology to confirm that the production and construction stages of building materials are the main sources of carbon emissions, and that the carbon emission of prefabricated components is 20.11% lower than that of cast-in-place components. In addition, real-time monitoring of energy consumption and optimization through intelligent systems is a key issue in the operational phase of buildings, aiming to reduce energy waste and to lower carbon emissions [46].

4.2.2. Application in Traffic Engineering

Carbon monitoring and carbon metering combined with advanced technologies, such as artificial intelligence and big data analysis, have the potential to optimize traffic flow, thereby reducing congestion and carbon emissions [47]. For example, WeiYu et al. [48] used AI and big data analysis to monitor traffic flow in real time, optimize traffic signal control, and provide optimal route planning. Ji Yangbeibei et al. [49] monitored and assessed the carbon emissions of different traffic modes to provide a scientific basis for formulating emission reduction policies.

4.2.3. Applications in Manufacturing Engineering

Carbon monitoring and carbon metering help in the manufacturing of cleaner production, reducing emissions, and improving resource efficiency. The application of efficient energy utilization technology, energy-saving technology, and alternative energy sources reduces dependence on traditional high-carbon energy sources [50]. The application of big data and artificial intelligence helps enterprises to accurately quantify carbon emissions and provide optimization suggestions [51]. In addition, the implementation of a carbon trading and carbon emission quota system also encourages enterprises to take emission reduction measures to a certain extent and promote the reduction of carbon emissions [52].

Table 3. Engineering Applications of Carbon Monitoring and Carbon Measurement.

Species	The Main Research Techniques and Methods	Research Results	Bibliography
Architectural engineering	Life Cycle Assessment (LCA), Input-output Analysis (IOA) and Material Flow Analysis (MFA)	Implement life cycle assessments, business assessments, and forum integration for accurate results. Establish a database of Australia’s carbon life cycle inventory to support the building industry and government in developing sustainable planning strategies.	[44]
	Building Information Modeling (BIM)	Create a carbon emission measurement system with BIM and Microsoft Access. Accurately predict the carbon emissions of public building projects in the early design stage and determine the key areas of carbon emission pre-controls.	[45]
	Decision-making Trial and Evaluation Laboratory (DEMATEL), Interpretative Structural Modeling Method (ISM), and Matrices Impacts Croises-multiplication Appliance Classement (MICMAC)	18 low carbon building factors: energy efficiency, environmentally friendly materials, optimized design, efficient heating and cooling systems, solar energy utilization, water conservation measures, waste management, green landscaping and roof utilization, etc. Dematel-ism model and MICMAC analysis results: Laws and regulations are the driving force, and developers’ willingness and consumer demand are direct influencing factors.	[46]
Traffic engineering	Carbon emission monitoring and simulation analysis	To explore the characteristics of carbon emission diffusion, build carbon emission indicators and promote the wide application of monitoring technology in the transportation field.	[46]
	Big data analytics and complex network methods	The Nanjing subway network model was established to accurately calculate the individual carbon emissions of passengers. The model’s accuracy was comprehensively monitored and improved.	[47]
	Carbon emission model	Based on a carbon emission intensity index (CEI) to reduce emissions, a flow control strategy was introduced. The study predicted that by 2030, electric vehicle penetration will reach 73%.	[49]
Manufacturing engineering	Literature survey method	An integrated conceptual framework that provides a comprehensive overview of energy efficiency research in manufacturing, covering energy diagnostics, metering, optimization, technologies, strategic paradigms, and drivers and barriers.	[50]
	Artificial intelligence Big data analysis	Build a carbon management system, deploy professional personnel and information support to ensure orderly operation and data management.	[51]
	Double difference method	After the implementation of China’s carbon trading pilot policy, the carbon trading market has significantly reduced the total carbon dioxide emissions and per capita emissions, with a contribution rate of about 0.26%. The trading volume of carbon quotas and carbon prices in a carbon trading market has a significant inhibitive effect on carbon emissions. The participation of enterprises is the key to carbon emission reductions.	[52]

below analyzes and cites the literature to show some applications of carbon detection and carbon measurement in construction, transportation, and manufacturing engineering. Through life cycle assessments, carbon emission monitoring and simulation analysis, big data analysis, and other methods, researchers have successfully provided assessments, predictions, and means of controlling carbon emissions, providing important support and guidance for carbon reduction work in various industries.

5. Conclusions

This paper summarizes the research progress and technical application of carbon monitoring and carbon metering, pointing out the main challenges faced by carbon monitoring and putting forward relevant strategies, discussing the current mainstream carbon monitoring technologies, and analyzing their advantages and disadvantages. Regarding carbon measurement, various methods are introduced, and the development course of carbon measurement standards is reviewed. Finally, the development characteristics of carbon monitoring and carbon metering in three application scenarios (construction engineering, traffic engineering, and manufacturing engineering) are summarized. However, facing the emerging field and a limited number of references, the study may be biased toward exploratory research or otherwise affected by a lack of access to previous studies. Nevertheless, for policymakers, the findings of this study provide valuable insights into the essential role of technology in achieving net-zero emissions targets.

At the technical level, the Chinese government should actively encourage technological innovation, increase investment in research and development, promote collaboration between scientific research institutions and enterprises, and strive to break through the technical bottlenecks of carbon monitoring and measurement from many aspects, such as improving monitoring accuracy, optimizing online monitoring support systems, and improving measurement methods, so as to meet the growing demand for high precision and high efficiency in carbon management. In terms of data management, it is essential to establish unified and strict data standards, standardize data collection, calculation, and reporting processes, strengthen data quality management, ensure the accuracy, comparability, and credibility of data, and build a data sharing platform to promote the efficient circulation and utilization of data, so as to provide a solid data foundation for policy formulation. At the same time, different carbon management policies should be formulated for different industries, and the construction, transportation, manufacturing, and other industries should be guided to choose reasonable technologies and methods according to their own characteristics so as to promote the green transformation of the industry. In addition, researchers should be actively encouraged to participate in international cooperation and exchanges. By strengthening cooperation with international organizations, China will play an active role in the development process of global carbon monitoring and measurement technology and enhance its voice and influence in the field of international carbon governance.

(1)

Blockchain technology protects carbon data

Blockchain technology will provide an open and transparent carbon emission data recording platform which can improve the reliability and efficiency of carbon monitoring and carbon measurement and positively feedback the development of carbon monitoring and carbon measurement from downstream.

(2)

Data standardization contributes to carbon emission reductions

The development of a unified carbon emission data standard can not only improve the comparability and credibility of data but also provide more accurate and reliable data support for policy and decision making. With the continuous improvement of carbon emission management requirements, the demand for carbon emission data standardization will show an increasing trend.

(3)

Harnessing AI for enhanced carbon monitoring

AI has the potential to revolutionize carbon monitoring through predictive analytics, where machine learning algorithms can analyze vast datasets to forecast carbon emissions based on various inputs, such as economic activity, energy consumption patterns, and regulatory changes. A more detailed examination of the specific AI models used in predictive carbon modeling, including their accuracy and adaptability to different contexts, is therefore desirable.

(4)

A digital divide remains in international cooperation

To bridge the digital divide, we must ensure equitable access to technology and training for carbon monitoring [53]. International cooperation is essential, as each country has unique strengths from the perspective of the development process of carbon monitoring technology in China and abroad. Working together, we can advance carbon reduction efforts and ensure that all nations benefit.