A Real-Time Accounting Method for Carbon Dioxide Emissions in High-Energy-Consuming Industrial Parks

Abstract

Industrial parks play a crucial role in carbon control and reduction. With energy-intensive enterprises at their core, such parks feature highly concentrated carbon emission sources and a significant demand for carbon trading. Nonetheless, the absence of precise and real-time carbon accounting methods makes it difficult for them to effectively manage and regulate carbon emissions. The real-time accounting methods for carbon dioxide emissions in high-energy-consuming industrial parks urgently need further study. Therefore, this paper initially examines three areas—fuel combustion, industrial engineering, and electricity usage—and proposes a real-time framework to account for carbon dioxide emissions in high-energy industrial parks. Secondly, it extracts real-time elements from each part and proposes a real-time carbon dioxide emission accounting method tailored to the actual needs of high-energy-consuming industrial parks. Finally, an empirical analysis is carried out on an aluminum production park as an example to verify the feasibility and effectiveness of the real-time accounting method for carbon dioxide emissions in high-energy-consuming industrial parks.

1. Introduction

High-energy-consuming industrial parks, as key focus areas for dual carbon (carbon peaking and carbon neutrality) efforts, play a critical role in energy conservation, carbon reduction, and efficiency improvement. Accurate quantification of carbon emissions is a fundamental technical basis for achieving dual carbon goals and represents a foundational issue requiring in-depth research [1]. In January 2024, China passed the Interim Regulations on the Administration of Carbon Emission Trading to actively and steadily promote carbon peak and carbon neutrality, promote green and low-carbon economic and social development, and promote the construction of ecological civilization.

The research on carbon emission accounting systems for industrial parks is still in the exploratory stage, and there is a lack of specialized standards or accounting methods both domestically and internationally. Most researchers rely on carbon emission accounting methods at the national, city, and industry levels. Among these, three primary carbon emission accounting systems are widely utilized [2]. The first system is the “Guidelines for National Greenhouse Gas Inventories 2006” [3], developed by the United Nations Intergovernmental Panel on Climate Change. The second is the “GHG Protocol,” jointly published by the World Resources Institute and the World Business Council for Sustainable Development in late 2011 [4,5]. The third is the Guidelines for the Compilation of Provincial Greenhouse Gas Inventories issued by the Department of Climate Change of the National Development and Reform Commission [6].

Currently, research on carbon emissions in industrial parks mainly focuses on carbon emission accounting frameworks and low-carbon pathway optimization. In the area of carbon emission accounting frameworks, the methods developed for national, provincial, or municipal levels are not suitable for park-level carbon accounting. Reference [7] developed an accounting method and framework for Chinese industrial parks based on enterprise-level data, providing a feasible approach for park-level carbon accounting. Reference [8] classified carbon emission sources in industrial parks into energy consumption, industrial processes, and waste treatment, proposing a corresponding carbon emission accounting method. Reference [9] established a greenhouse gas inventory including both direct and indirect carbon emissions and proposed emission reduction strategies. In terms of low-carbon pathway optimization, reference [10] explored the feasibility and optimization schemes for implementing electric-heat carbon-neutral industrial parks, developing a carbon-neutral framework based on an MILP (Mixed-Integer Linear Programming) energy optimization model for electric heat and ammonia. Reference [11] developed an integrated land-industry-carbon model and proposed carbon peak pathways for China’s industrial parks. Reference [12] calculated the lifecycle carbon emissions of coal-fired power generation in China based on a lifecycle model. Reference [13] introduced the concept of the whole-process carbon footprint and proposed an optimization framework for the whole-process carbon footprint of integrated energy systems in industrial parks based on the multi-energy flow virtual carbon flow transmission mechanism.

In terms of calculating carbon emissions from electricity consumption, the widely used method at the national and regional levels involves the average grid emission factor to calculate the indirect carbon emissions from electricity use. The average grid emission factor method is based on the annual electricity fuel consumption data of users, resulting in the annual average electricity emission factor for the user [14]. Reference [15] conducted a study on electricity carbon emission measurement technology considering regional electricity transactions based on the emission factor method. However, due to the time lag of the average carbon emission factor, it is impossible to dynamically measure the carbon emissions from electricity use. To accelerate the dynamic measurement of carbon emissions, reference [16] proposed a real-time calculation of carbon emissions from coal-fired units based on the carbon accounting methods in the “Guidelines”, providing a reference for real-time continuous monitoring on the power generation side. However, this method is limited to the generation side. To extend the scope to all aspects of the source–grid–load, reference [17] proposed an indirect carbon emission measurement method for power systems, which enables real-time carbon emission measurement across all segments of the source, grid, and load. Nevertheless, this method requires the introduction of a carbon meter system and the mutual support and cooperation of the source, grid, and load, making its implementation in industrial parks challenging and excluding green electricity transactions. On this basis, reference [18,19], from the user’s perspective and based on the carbon flow tracking theory, proposed a method for calculating electricity carbon emissions considering green electricity transactions, quantifying the carbon emissions before and after users participate in green electricity transactions.

The research above, while providing some theoretical foundation for the successful low-carbon transformation of high-energy-consuming industrial parks in China, faces challenges due to the diversity of enterprises within the parks. Traditional accounting methods only assess the total annual carbon emissions of the enterprises in the park, with long cycles and a lack of real-time carbon emission calculation and analysis of emission characteristics. The current macro-level carbon measurement approach is no longer adequate for the in-depth research on carbon emissions in industrial parks. There is an urgent need for further exploration of dynamic carbon emission accounting. In parks where industrial processes generate significant carbon emissions, the existing methods are limited by narrow coverage, coarse time granularity in carbon accounting, and low precision, thus failing to meet the real-time and accurate carbon reduction goals. Furthermore, real-time carbon emissions from electricity usage are only calculated at the industry level, and a balance has yet to be achieved between the real-time completeness of the accounting results and the simplicity and feasibility of the accounting methods.

To address the aforementioned issues, this paper makes the following contributions.

(1)

It roposes a real-time carbon dioxide emission accounting method for high-energy-consuming industrial parks: Based on the practical needs of such parks, this method leverages real-time dynamic factors to enhance the parks’ ability to perceive carbon emissions at different moments, providing support for carbon reduction strategies. It further empowers enterprises to actively participate in real-time carbon trading, improving energy efficiency and boosting performance. In addition, through the implementation of the method, it can lay the foundation for enterprises in various industries to scientifically calculate carbon emissions and accelerate the implementation of the carbon verification and reporting system.

(2)

It develops a real-time carbon emission accounting framework tailored to high-energy-consuming industrial parks: This framework integrates the unique developmental characteristics and structural composition of these parks, incorporating three major emission sources—fuel combustion, industrial engineering, and electricity usage—into the accounting process, with real-time factors extracted from each component to enable more targeted emission monitoring.

2. Dynamic Accounting Framework for Carbon Emissions in High-Energy-Consuming Industrial Parks

This paper focuses on dynamic accounting for the primary emission sources in high-energy-consuming industrial parks to achieve dynamic updates on carbon emissions within the park. To facilitate subsequent calculations of carbon emission results, and with reference to the classification methods for carbon emission sources outlined in the Guidelines for Accounting Methods and Reporting of Enterprise Greenhouse Gas Emissions, this study builds upon the research in Reference [8] to propose a real-time carbon accounting framework tailored to the practical needs of high-energy-consuming industrial parks.

The real-time carbon emission accounting framework for high-energy-consuming industrial parks is shown in Figure 1. Considering the completeness of the measurement results and the development needs of the carbon emission trading market, three main sources of carbon emissions were selected: fossil fuel combustion emissions, industrial process emissions, and electricity consumption emissions. The activity data and emission factors for each of these three major sources are obtained separately, and are then used to calculate the total carbon emissions [20]. The total carbon emissions of the industrial park can be expressed as:

$$C_{total,t}=\sum _{t=1}^T{C}_{f,t}+C_{p,t}+C_{e,t}$$

(1)

where $C_{total,t}$ represents the total carbon emissions of high-energy-consuming industrial parks at time t, tCO₂; and $C_{f,t}$, $C_{p,t}$ and $C_{e,t}$ are the carbon emissions generated by fossil energy consumption, industrial processes, and electricity consumption of high-energy-consuming industrial parks at time t, tCO₂, respectively.

3. Real-Time Accounting Method for Carbon Dioxide Emissions in High-Energy-Consuming Industrial Parks

3.1. Real-Time Accounting Method for Carbon Emissions from Fuel Combustion in Parks Based on Real-Time Activity Data

Fuel combustion emissions refer to the carbon emissions generated from the burning of various fossil fuels, calculated as the product of activity data and emission factors for different fuels. In high-energy-consumption industrial parks, the data on fuel usage are sourced from park statistical reports and do not include byproducts or recovered exhaust gases from industrial production processes. However, the data derived from energy consumption ledgers and statistical reports often exhibit significant temporal and spatial delays, making it challenging to obtain real-time data that meet the needs of modern industrial parks. Since the production and operation processes in industrial parks remain stable over certain periods, the emission factors are assumed to be relatively constant during these periods. Therefore, the variations in carbon emissions are driven by activity data, and the contributions of changes in emission factors can be considered negligible [21]. Based on this assumption, this study achieves real-time quantification of carbon emissions using periodically updated real-time activity data and proposes a real-time carbon accounting method for fuel combustion in industrial parks to overcome the temporal and spatial delays in carbon emission data, as shown in Equations (2)–(4).

$$C_{f,t}=\sum _{i=1}^n{F}_{i,t}\times e_{f,i}$$

(2)

$$F_{i,t}=NC{V}_i\times F{C}_{i,t}$$

(3)

$${e_{\mathrm{c},}}_i=C{C}_i\times O_{FC,i}\times \beta$$

(4)

where: $C_{f,t}$ is the carbon dioxide emission produced by the combustion of fuel in the industrial park at time t, tCO₂; $F_{i,t}$ is the amount of the i-th fuel consumed by the industrial park at time t, t;$e_{f,i}$ is the carbon dioxide emission factor of the i-th fuel, tCO₂/GJ; $NC{V}_i$ is the net calorific value of the fuel i, GJ/10⁴Nm³, and $F{C}_{i,t}$ is the consumption of the fuel i at time t,10⁴ Nm³ (for solid and liquid fossil fuels, $C{C}_i$ is the carbon content per unit calorific value of fuel i, tC/GJ,$O_{FC,i}$ represents the carbon oxidation rate of fuel i, and $\beta$ represents the CO₂ gasification coefficient.

3.2. Real-Time Accounting Method for Carbon Emissions in Industrial Processes Considering the Correction of Emission Factors

Industrial process emissions refer to greenhouse gas emissions released during the physical and chemical reactions involved in the production of industrial products [22]. Unlike carbon emissions from the combustion of fossil fuels, these emissions cannot be reduced through the clean transition of the energy system. As the most challenging part of industrial systems to decarbonize, it is crucial to accurately measure industrial process carbon emissions.

The carbon emission factor of industrial processes is determined by the production process, but at present, the carbon emission factor of industrial processes covers a small number of types, which cannot meet the carbon emission calculation needs of an industrial process. Therefore, the carbon emission factor of industrial processes should be revised to more accurately calculate the carbon emission generated by them. Based on the research in ref. [23], this paper proposes a carbon measurement method for industrial processes considering the correction of carbon emission factors.

Based on the proportion of specific industrial product production processes, the weighted average values of carbon emission factors for each production process are calculated. Suppose a product is produced by different processes; the emission factor of these products largely depends on the proportion of different processes. First, collect the emission factors for different processes and calculate the weighted average value for each production process, ultimately forming a new comprehensive carbon emission factor for industrial processes. This method comprehensively considers the carbon emissions of different parts of the industrial production process, and is widely applicable to carbon accounting in different industries, especially for the aluminum production industry in the following example. To clearly describe the corrected emission factors, this paper defines the following matrix:

(1)

Industrial production process coefficient matrix

The weighted coefficient matrix of the industrial production process is an N × 1 matrix, which is defined as the weighting coefficient of the industrial production process k, which can be expressed as:

$$\xi ={\left[{\xi }_1,{\xi }_2,\cdots ,{\xi }_n\right]}^T$$

(5)

(2)

Matrix of emission factors in industrial production processes

The emission factor matrix of the industrial production process is an N × 1 order matrix, which defines the emission factor of the industrial production process k; this can be expressed as:

$$p\left(t\right)={\left[p_1\left(t\right),p_2\left(t\right),\cdots ,p_{\mathrm{n}}\left(t\right)\right]}^{\mathrm{T}}$$

(6)

The comprehensive carbon emission factors of industrial processes are:

$$e_p={\xi }^T\cdot p$$

(7)

The amount of carbon emissions generated by industrial processes can be expressed using Equation (8) as:

$$C_{p,t}=\sum _{i=1}^n{P}_{i,t}\times e_{p,i,t}$$

(8)

where: $C_{p,t}$ represents the carbon emissions generated by the industrial production process of the industrial park at time t, tCO₂, $P_{i,t}$ represents the industrial process activity data at time t, t, and $e_{p,i,t}$ is the carbon emission factor for the production process of product i in the industrial park at time t, tCO₂/t.

3.3. Dynamic Accounting Method for Carbon Emissions from Electricity Consumption in Industrial Parks

The current carbon emission accounting rules do not distinguish between the carbon emissions of renewable electricity and ordinary electricity but obtain an average carbon emission factor based on the total carbon emissions generated by all electricity in the regional power grid, which cannot track the source composition of electricity consumed in different periods; nor can it reflect the carbon emissions of electricity consumption in industrial parks at different times. Considering that high-energy-consuming industrial parks generally have self-supplied power plants inside, the electricity consumption of the park comes from two parts: one is the purchase of electricity outside the park, and the other is self-generated power generation in the park. Based on this, this paper proposes the concept of a comprehensive electricity emission factor, which is defined as the dynamic emission factor generated by the power consumption process of the park, which includes two parts: the electricity emission factor generated by the use of purchased electricity in the park and the electricity emission factor generated by the power supply of the power plant in the park. The schematic diagram of the carbon emission accounting method for electricity consumption in the park is shown in Figure 2.

The carbon emission factor of electricity consumption is expressed as follows by Equation (9):

$$e_t={\displaystyle \frac{E_{ex,t}{e}_{ex,t}+E_{in,t}{e}_{in,t}}{E_{ex,t}+E_{in,t}}}$$

(9)

where: $e_t$, $e_{ex,t}$ and $e_{in,t}$ are the carbon emission factors of electricity consumption at time t of the industrial park, tCO₂/MW·h, the carbon emission factor of purchased electricity and the carbon emission factor of self-generated electricity. $E_{ex,t}$, $E_{in,t}$ are the purchased electricity and self-generated electricity of the industrial park at time t, MW·h, respectively.

The carbon emission factor of purchased electricity is calculated according to the energy supply information on the source side, the energy consumption information on the load side, and the power flow information by using the carbon emission flow theory 14, which is denoted as:

$$e_{ex.t}=\left(\sum _{b\in \mathrm{B}}{\rho }_{b,t}\times L_{b,t}\right)/\left(\sum _{b\in \mathrm{B}}{L}_{b,t}\right)$$

(10)

where: ${\rho }_{b,t}$ is the carbon potential of node b in period t, tCO₂/MW·h, $L_{b,t}$ is the load of node b in period t, MW, and B represents the set of nodes within the coverage of the regional power grid.

Since the carbon emission per kilowatt-hour of electricity generated by new energy power generation in the industrial park is equivalent to zero, the carbon emission factor of self-power generation in the industrial park is essentially the carbon emission factor of power generation of thermal power units. The carbon emission factor of self-generated electricity can be calculated using Equation (11):

$$e_{in,t}={\displaystyle \frac{{\sum }_{g=1}^m{\zeta }_{g,t}{W}_{h,g,t}}{{\sum }_{g=1}^m{W}_{h,g,t}}}$$

(11)

where: ${\zeta }_{g,t}$ is the carbon emission coefficient of the (g)-th generator unit in the industrial park at time t, tCO₂/MW·h, $W_{h,g,t}$ represents the electricity generation of the (g)-th generator unit in the industrial park at time t, MW; m is the number of thermal power generator units.

The carbon emission measurement model of electricity consumption in the park is as follows:

$$C_{e,t}=\sum _t{e}_t\cdot E_t$$

(12)

where: $C_{e,t}$ denotes the carbon emissions from electricity consumption at time t in the industrial park, tCO₂$;E_t$ is the electricity consumption of the industrial park at time t, MW.

3.4. Dynamic Accounting Model of Carbon Emissions from Waste Disposal

The carbon emissions generated by waste treatment in industrial parks can be calculated using the following formula:

$$E_{WD,t}=E_{S,t}+E_{W-C{H}_4,t}+E_{W-N_{2}O,t}$$

(13)

For the carbon emissions of solid waste incineration, which involve the carbon emissions caused by the treatment and disposal of domestic waste, hazardous waste, and sludge, the calculation formula is as follows:

$$E_{S,t}=A{D}_{S,t}\cdot E{F}_S$$

(14)

$$E{F}_s=CC{W}_i\cdot FC{F}_i\cdot \beta$$

(15)

where: $E_{S,t}$ is the carbon emissions generated by solid waste incineration at time t, tCO₂; $A{D}_{S,t}$ is the amount of solid waste generated at any given time, t; $E{F}_S$ represents emission factors, tCO₂/t; $CC{W}_i$ is the proportion of carbon content of Category 1 waste; $FC{F}_i$ is the proportion of mineral carbon in the first category of waste.

For the wastewater treatment part, carbon emissions mainly include CH₄ and N₂O, which can be calculated by the following formulas:

$$E_{W-C{H}_4,t}=W_t\cdot E{F}_{C{H}_4}-R_{C{H}_4,t}$$

(16)

$$E_{W-N_{2}O,t}=T{N}_t\cdot E{F}_{N_{2}O}$$

(17)

where: $W_t$ is the total amount of degradable organic matter that is degraded by sludge removal, t; $E{F}_{C{H}_4}$ is the emission factor of CH₄, tCO₂/t; $R_{C{H}_4,t}$ is the amount of CH₄ that is recycled, t; $T{N}_t$ is the nitrogen content of sewage; $E{F}_{N_{2}O}$ is the emission factor of N₂O, tCO₂/t.

4. Case Analysis

A high-energy-consuming industrial park in Sichuan Province is used as a case to verify the correctness and effectiveness of the proposed method. The industrial park covers an area of 0.5 square kilometers, and its main products are liquid aluminum ingots and downstream products, and the working mechanism of three shifts is implemented.

4.1. Park Boundaries and Measurement Range

Figure 3 shows the carbon emission measurement boundary of the industrial park. The main process includes four processes: alumina production, anodic effect, electrolytic aluminum, and pouring.

Table 1. Schematic table of carbon emission sources and greenhouse gas types in an industrial park.

Emission Category	Types of Greenhouse Gas Emissions	Type of Energy	Name of the Device
Fuel combustion emissions	CO2	Natural gas	Roaster
	CO2	Coke	Roaster
Industrial production	CO2, C2F6, CF4	Carbon anode	Electrobath
Electricity	CO2	Electricity	Electrical facilities

shows the accounting scope of the industrial park. The scope of accounting mainly includes: (1) fuel combustion emissions: this part is mainly CO₂ emissions caused by natural gas and coke combustion; (2) industrial production process emissions: mainly CO₂ emissions caused by carbon anode consumption (carbon anode is a reducing agent for electrolytic aluminum production) and perfluorocarbon (C₂F₆ and CF₄) emissions caused by the anode effect; (3) purchased electricity emissions: the park purchases electricity from the grid and has no power output. Solid and hazardous waste in the park are both recycled, and waste treatment has a negligible impact on total emissions; therefore, this portion of emissions is excluded from the accounting. The real-time carbon accounting method for CO₂ emissions in high-energy-consuming industrial parks proposed in this paper does not require the purchase of high-cost equipment. Instead, it achieves high-precision real-time carbon accounting for the park through dynamic algorithms. The additional labor costs incurred are negligible across the entire park.

4.2. Carbon Emission Results of the Park

In this paper, a typical day from the high-energy-consuming industrial park is chosen for the calculation and analysis of carbon emissions. The data required for this analysis come from both the on-site measurements at the industrial park and relevant domestic research institutions 24. As the measured data from the industrial park may contain uncertainties that could affect the results, we would like to emphasize that these uncertainties do not disrupt the conclusions drawn from this research.

Figure 4 shows the real-time calculation results and changes in fuel combustion carbon emissions in the industrial park on a typical day. Among the carbon emissions from fuel combustion, the carbon emissions from coke combustion account for about 63%, and the carbon emissions from natural gas combustion account for 37%. The dynamic accounting method of fuel combustion carbon emissions in industrial parks based on real-time activity data proposed in this paper is effective and reliable, and the accurate quantification of fuel combustion carbon emissions can be achieved by regularly updating dynamic activity data and overcoming the problem of the spatiotemporal lag in fuel combustion in industrial parks.

The industrial processes in the park primarily include anode consumption and anode effects. This paper references the carbon emission calculation method for electrolytic aluminum production detailed in reference [24] to calculate the carbon emissions from anode consumption and anode effects during the electrolytic process. Figure 5 illustrates the real-time calculation results and variations in carbon emissions from the industrial processes in a typical industrial park.

The dynamic curve of the emission factor and carbon emissions from electricity consumption at different time periods in the park is shown in Figure 6. Figure 6 displays the real-time variations in carbon emissions from electricity consumption in the industrial park on a typical day. As shown in Figure 6, the high carbon emission factor periods for electricity consumption in the industrial park are from 1:00 to 8:00, 13:00 to 15:00, and 22:00 to 24:00. During the electrolytic aluminum production process, the majority of carbon emissions stem from the park’s electricity consumption. The park can use the real-time electricity carbon emission factor to sense the differences in electricity carbon emissions at various time periods, aiming to minimize periods with high carbon emission factors and reduce overall carbon emissions.

Figure 7 shows the proportion of daily carbon emissions by source in industrial parks. According to the analysis, the most important carbon emission for the high-energy-consuming industrial park is electricity consumption, and the carbon emissions corresponding to the electricity consumption of the industrial park account for 69% of the total carbon emissions of the entire park.

5. Conclusions

Based on a comprehensive review and summary of existing carbon accounting methods for industrial parks, this study conducts an in-depth investigation into the dynamic carbon accounting of industrial parks, taking into account their unique development characteristics and structural composition. The main conclusions are as follows:

(1)

A dynamic carbon accounting framework for industrial parks is proposed. Based on three dynamic real-time factors of the park, a real-time carbon accounting method tailored to energy-intensive industrial parks is developed, along with a dynamic carbon accounting model designed to meet the practical needs of industrial parks.

(2)

Using an energy-intensive aluminum industrial park in Sichuan Province as a case study, real-time carbon emissions for a specific day were calculated, and the variations in carbon emissions were dynamically demonstrated. The results show that the proposed method, while considering industrial processes, maintains simplicity and feasibility, enabling real-time carbon accounting. This allows energy-intensive industrial parks to effectively perceive carbon emissions at different times, aiding enterprises to participate in real-time carbon trading markets to improve energy efficiency and performance.

(3)

Future work will focus on developing online carbon emission monitoring methods for industrial parks, analyzing the uncertainty of carbon emission activity data, and enhancing the accuracy of data validation methods. These efforts aim to provide effective strategies for emission reduction in energy-intensive industrial parks.