Research on carbon emission factors of heavy chemical industry park based on generalized Divisia index method

: Based on the energy consumption and economic data of a heavy chemical industrial park in northwest China from 2013 to 2020, the carbon emissions of the park were calculated. The generalized Divisia index method (GDIM) was employed to analyze the effects of eight absolute and ten relative indicators of carbon emission changes in the heavy chemical industrial park. The results show that optimizing the electricity structure, reducing the energy output and carbon output intensities, and improving investment efficiency have a significant effect on inhibiting carbon emission. The inhibitory effect from reducing investment carbon intensity, fossil energy, and the total energy consumption scale was clearly evident. The deterioration of fossil fuel energy structure, and the increase in investment, output, and total electricity consumption scales are the main factors affecting carbon emission growth. Carbon emissions from industrial processes have a limited impact on carbon emissions. Finally, pertinent suggestions are provided.


Introduction
Climate change caused by greenhouse gases has increasingly serious impacts to society and the environment. Subsequently, China committed to reducing greenhouse gas emissions by 60% to 65% per unit of GDP compared with 2005 by 2030 [1] , which is a long-term and arduous task.
The heavy chemical industry is a powerful foundation for a country's national economy to realize modernization, and parks are important carriers of the heavy chemical industry. The energy consumption, process structure, and product type of the heavy chemical industrial park are very different from those of other ordinary parks. Therefore, analyzing the degree of different influencing factors on carbon emission changes in parks is conducive to the timely adjustment of carbon reduction measures in parks.
Currently, a many scholars have conducted research on the influencing factors of carbon emission change, including the national level, provinces, cities, industries. However, there are few studies on the influencing factors of carbon emission changes in industrial chemical parks. The exponential decomposition method is one of the most commonly used research methods [2] . The early exponential decomposition method was mostly based on the Kaya identity, which has many factorization defects. Vaninsky [3] improved the existing defects of the early index decomposition method and proposed a new method called the Generalized Divisia Index Method (GDIM). This method is also used to analyze the influence of different factors on the changes in carbon dioxide emissions in the United States during 1980-2012 [4] . In addition, Zhang [5] analyzed the influencing factors of carbon emissions in the Chinese logistics industry using GDIM. Yan [6] examined the driving factors behind CO 2 emission changes in China's thermal electricity generation using the GDIM. Shao [7] used GDIM to uncover the driving factors of carbon emissions from China's mining sector.

Data source
This study uses the research on a heavy chemical industrial park in Northwest China to obtain data. The enterprises in the park consisted of the coal chemical industry, petrochemical industry, and other chemical enterprises. In addition, the park consisted of cement, steel, and power generation enterprises, which are typical found in heavy chemical industrial parks. The methods of obtaining data included financial statements, warehouse receipt, production reports, and laboratory analysis ledgers of enterprises in the park.

Accounting boundary
Currently, no unified carbon emission accounting method for industrial chemical parks exists. Many researchers have conducted research on the carbon emission accounting for chemical parks. The key challenge of accounting is the boundary as different parks have varying boundaries. Combined with the research of pioneers [8] and the investigation of the target park, five boundaries were selected as the carbon emission accounting boundaries, including fossil fuel energy consumption, industrial process, recovery and utilization of greenhouse gases, net purchased electricity and heat, and carbon sinks.

Accounting result
Based on the research and collection of basic data from a heavy chemical industrial park in Northwest China, carbon emission accounting was undertaken. The main emission sources of the park were fossil fuel energy consumption, purchased power, and carbon emissions from industrial processes. Carbon reductions included the reduction of carbon emissions from waste heat generation and greenspace carbon sinks. Fig.1 shows the changing energy and electricity consumption trends during the accounting period of the park. Under the determined accounting boundary, the carbon emissions of the heavy chemical industrial park could be calculated using the following formula: Other greenhouse gases produced or reduced by industrial production and waste treatment were calculated after conversion according to their carbon dioxide potential (GWP); the accounting results are shown in Table 1.

Selection of influencing factors
Production and infrastructure construction in heavy chemical parks require increased investment. Energy consumption is high, and economic growth is heavily dependent on fossil fuels. It subsequently has the characteristics of carbon emission accounting boundaries, such as regions and industries with high energy consumption. Therefore, the influencing factors considered by researchers [9,10] of these carbon emission boundaries are included. In addition, this study subdivides the energy structure into fossil energy and electricity structures for a more indepth decomposition analysis, and analyzes the industrial process emissions of heavy chemical parks. Table 2 lists the symbols, definitions, and units of related variables contained in the GDIM model of the heavy chemical industry park.

Construction of GDIM model in heavy chemical industry Park
Based on the analysis and determination of influencing factors, and the basic principle of GDIM, carbon emissions and influencing factors of heavy chemical industrial parks can be expressed in the following form: For different influencing factor X, its contribution to carbon emission change can be expressed as a function of CO 2 (X), and a Jacobian matrix ΦX composed of various influencing factors can then be constructed from Formulas According to the principle of the GDIM model, the variation ΔCO 2 of carbon emissions can be decomposed into the following contribution sum form:

4.Results and discussion
The R-language was utilized to decompose and analyze the influencing factors of carbon emissions in the target heavy chemical industrial park. To more clearly reflect the dynamic impact of all factors on carbon emission change from 2013 to 2020, this study takes 2013 as the base period and calculates the cumulative contribution value of all factors annually by adding the contribution value of all factors to carbon emission change. The results are shown in Fig. 2 and 3, respectively. The increase in output and investment scales is the main growth factor of carbon emissions in the park. In addition, the cumulative contribution increased from 195,300 to 555,500 tons and from 194,600 to 637,300 tons, respectively, as the park developed steadily during this period. Fixed assets and output value increased by 78.73% and 31.67%, respectively, while the decrease in output and investment carbon intensities played the opposite role. The cumulative contribution of the former from 213,900 to -290,000 tons, with the latter being a more obvious change, reduced from 570,00 to -1.6092 million tons. The development of the park has gradually become green and high-end since the 13th Five-Year Plan [11] , and investment efficiency is an important manifestation. The cumulative contribution of investment efficiency increased from -117,400 to -682,900 tons. All of these indicate that the park's low-carbon investment was beneficial. The energy structure of the park includes fossil fuel energy and electricity. The electricity structure is divided into purchasing electricity and generating electricity, as shown in Fig.1(a). The scale of fossil fuel energy consumption in the park generally showed a slow increasing trend, however the overall work of overcapacity reduction in 2016 led to a large decline. Although the park continued to develop, the rate of increase was obviously controlled, and the cumulative contribution value was reduced from 132,600 to -948,700 tons. As the fossil fuel energy structure was not optimized, its cumulative contribution increased from 19,200 to 625,800 tons.
As a low-carbon energy source, electric power plays an increasingly important role in the heavy chemical industry park. As shown in Fig.1(b), the continuous increase in the total power consumption scale in the park increases its cumulative contribution from 579,900 to 1,0776,50 tons. Power generation enterprises in the park use fossil fuel energy to generate more carbon emissions, whereas the carbon emissions of purchased power are relatively low. In recent years, the continuous increase in the scale of waste heat generating units and purchased electricity in the park has led to continuous improvements of the power structure, which is mainly reflected in the cumulative contribution value of the power structure increasing from -18,100 to -181,800 tons. In general, the power structure of parks has improved in recent years. However, there is still room for improvement.
The contribution of energy consumption is essentially the same as that of fossil fuels. Although the energy structure of the park has been improved to some extent owing to the increase in the scale of electricity consumption, its contribution to the value rose from 171,700 to 908,700 tons. The cumulative contribution value of energy intensity changed greatly in 2016, from -7,800 tons in 2015 to -371,500 tons in 2016. This indicates that the removal of backward production capacity in the park has made significant progress.
Industrial process emissions are an important source of carbon emissions in parks. Although the emission performance fluctuated during 2013-2020, the overall change was small. The cumulative contribution value also increased and decreased, with the lowest being 174,600 tons in 2018 and the highest being 363,100 tons in 2014.
There are two main sources of carbon reduction in parks: waste heat power generation and greenspace carbon sinks. The power generation capacity of waste heat has always been stable however it is rising. As a large-scale heavy chemical industrial park, the target park has a large green area and can absorb approximately 1000 tons of carbon dioxide annually. However, its impact on the carbon emission volume of the heavy chemical industry park is very limited.

5.Conclusion and suggestion
This study calculated the carbon emissions of a heavy chemical industrial park in Northwest China from 2013 to 2020. The GDIM was used to analyze the influence direction and intensity of 18 different influencing factors on the carbon emission change for the target park over the years.
In conclusion, in recent years, the state has promoted the removal of outdated production capacity and green transformation in high-energy consuming and highemission industries. The pace of growth of carbon emissions in heavy chemical industrial parks has decreased.
However, current emission reduction efforts are still insufficient. Enterprises in parks need to further increase green and low-carbon investments. Existing enterprises increase the elimination of outdated production capacity and intensify innovation, research, and development processes. The new enterprises should be high-tech and aim to participate in the industrial chain of the park. This reduces the intensity of the energy output. The goal of carbon neutrality in the heavy chemical industrial park should be to avoid fossil fuel energy as a fuel production where possible, however to use it alternatively as a raw material for production. Measures for constant innovation processes to reduce carbon emissions from industrial processes are needed to explore the treatment and conversion of selected non-carbon dioxide greenhouse gases. Finally, terminal emission reduction is carried out with the help of terminal negative carbon technologies, such as Carbon Capture，Utilization and Storage (CCUS). Through these measures, heavy chemical industrial parks can make important contributions to the goal of double carbon.