Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 18, No. 1, 2025 162 Carbon Emission Accounting and LMDI Factor Analysis of Fossil Energy in Henan Province Yaoling Shi, Jinshan Ma Henan University of Science and Technology, School of Business Administration, Jiaozuo, Henan 454003, China Abstract: The cultivation of fossil energy consumption in Henan Province between 2005 and 2022 is key to formulate carbon reduction strategies. This study uses the Logarithmic Mean Divisia Index (LMDI) method to decompose the factors of carbon emissions. The total carbon emissions from fossil energy in Henan Province amounted to 3.075 billion tons of CO2, showing an initial increase followed by a decrease, with fluctuations ranging from 125.59 million tons to 209.98 million tons. The LMDI analysis results show that the total effect of fossil energy carbon emissions fluctuated over time. From 2006 to 2011, the total effect was 84.39 million tons. From 2012 to 2019, it was -56.70 million tons. rom 2020 to 2022, it was 14.93 million tons. The greatest positive impact is the economic factor, accounting for 52.36% of the total effect. The greatest negative impact is the technological factor, accounting for 46.32%.Based on this, the study proposes the following carbon reduction strategies: adjusting the energy structure, fostering green technological innovation, and enhancing energy consumption management. Keywords: Henan Province, Fossil energy carbon emissions, Fossil energy consumption, LMDI method, Carbon reduction strategies. 1. Introduction As a big province of energy consumption in our country, Henan province has a high degree of industrialization, and its energy structure is dominated by coal, so it faces great pressure of carbon emissions. Therefore, it is very important to carry out the accounting of fossil fuel carbon emissions in Henan province and analyze its influencing factors for formulating practical carbon emission reduction countermeasures. Through in-depth analysis of the main sources of carbon emissions in Henan province and its key influencing factors, it can provide reference for related research. In the calculation of carbon emissions from fossil fuels, scholars have used a variety of different calculation methods. Li Ching et al [1] used the emission factor method proposed by the United Nations Committee on climate change to calculate the carbon emissions from energy consumption in the Beijing-Tianjin-Hebei region. Tang Cheng Cai et al [2] calculated the carbon emission of energy consumption in Hubei province by using the method of carbon emission measurement. Hu Wen bao et al [3] proposed a calculation strategy combining primary energy factor and carbon emission factor, which considers the carbon emission of indirect energy. However, among many carbon emission calculation methods, the emission factor method has become the most widely used method because of its simple calculation, mature formula and authority [4]. On the choice of decomposition methods of carbon emission factors, scholars mostly use Generalized Divisia Index Method and Logarithmic Mean Divisia Index Method. Guo Wenqiang et al [5] used the GDMI method to decompose the driving factors of carbon emissions in our country. Lau Siu-lai et al [6] used the LMDI method to analyze the carbon emission factors of our country's manufacturing industry. Yang di [7] used LMDI method to study the driving factors of energy consumption in Xinjiang. In general, GDMI is suitable for complex multi-factor analysis, and LMDI is more suitable for carbon emission analysis due to its simple calculation and clear interpretation. Therefore, based on the data of fossil energy consumption in Henan province from 2005 to 2022, this study adopts the emission factor method proposed by the United Nations Panel on Climate Change (IPCC) to account for the carbon emissions of fossil energy consumption, and the carbon emission factor method is used to calculate the carbon emissions of fossil energy consumption, and through the LMDI model to analyze the driving factors of carbon emissions, provide targeted recommendations for carbon emission reduction in Henan province. 2. Fossil Energy Data of Henan Province The data source of this paper is the Statistical Yearbook of Henan Province (2005-2022). The fossil energy consumption data of Henan province is obtained by querying the yearbook, the Table 1 for details. As can be seen from Figure 1, the consumption of raw coal is the highest, accounting for 85.45% of total fossil energy consumption, at 4.761 billion tons of coal equivalent. As can be seen from Figure 2, the second largest consumer is coke, with a consumption of 286 million tons of standard coal, accounting for 5.14%, showing a trend of first rising and then falling. In third place is crude oil, with consumption of about 144 million tons of standard coal, accounting for 2.58%. Its consumption curve fluctuates a lot, but the overall trend is slightly upward. 163 Table 1. fossil energy consumption in Henan province from 2005 to 2022.Unit: ten thousand tons of standard coal Year Raw Coal Coke Crude Oil Gasoline Kerosene Diesel Fuel Oil Natural Gas 2005 20213.70 992.80 667.95 233.60 13.91 328.50 76.65 237.25 2006 23754.20 1193.55 697.15 248.20 16.02 346.75 69.35 305.14 2007 26582.95 1438.10 715.40 211.70 17.05 459.90 62.05 331.42 2008 26794.65 1489.20 704.45 193.45 18.25 543.85 47.45 365.00 2009 29820.50 1463.65 795.70 200.75 25.55 532.90 25.55 438.00 2010 30229.30 1759.30 846.80 302.95 32.85 569.40 18.25 474.50 2011 33853.75 2080.50 886.95 365.00 51.10 671.60 43.80 547.50 2012 30806.00 2222.85 1011.05 427.05 54.75 737.30 14.60 730.00 2013 28112.30 1817.70 963.60 558.45 47.45 777.45 32.85 766.50 2014 26933.35 2701.00 846.80 529.25 51.10 799.35 51.10 766.50 2015 28455.40 1412.55 605.90 682.55 69.35 861.40 40.15 872.35 2016 27681.60 1343.20 686.20 700.80 73.00 927.10 40.15 879.65 2017 27656.05 1233.70 649.70 740.95 73.00 974.55 29.20 985.50 2018 24130.15 1423.50 828.55 762.85 80.30 992.80 32.85 1058.50 2019 22232.15 1430.80 799.35 770.15 91.25 1007.40 10.95 1058.50 2020 22243.10 1481.90 890.60 762.85 94.90 1025.65 3.65 1058.50 2021 22421.95 1580.45 923.45 777.45 91.25 1120.55 7.30 1168.00 2022 24217.75 1584.10 876.00 799.35 94.90 1171.65 51.10 1241.00 Total 476138.85 28648.85 14395.60 9267.35 995.98 13848.10 657.00 13283.81 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 10000 15000 20000 25000 30000 35000 R a w c o a l （ 1 0 ,0 0 0 t o n s o f st a n d a rd c o a l） Year Raw coal 10000 15000 20000 25000 30000 35000 40000 Total energy consumption T o ta l e n e rg y c o n su m p ti o n （ 1 0 ,0 0 0 t o n s o f st a n d a rd c o a l） Figure 1. Total fossil energy consumption and raw coal consumption in Henan province from 2005 to 2022 Figure 3 shows that diesel, natural gas and gasoline accounted for 2.49%, 2.38% and 1.66% of total consumption of 138,132.8 and 92.67 million tons of coal equivalent, respectively. The consumption of the three kinds of energy showed a clear upward trend. Figure 4 shows that the consumption of fuel oil and kerosene is the lowest among all fossil fuels, accounting for 0.12% and 0.18% of total energy consumption at 6.57 million and 9.9598 million tons of coal equivalent, respectively. The consumption of fuel oil showed a fluctuating downward trend and began to rise in 2021, while the consumption of kerosene showed a fluctuating upward trend. 164 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 500 1000 1500 2000 2500 3000 U n it : te n t h o u sa n d t o n s o f st a n d a rd c o a l Year Coke Crude oil Figure 2. Coke and crude oil consumption in Henan province from 2005 to 2022 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 0 200 400 600 800 1000 1200 U n it : te n t h o u sa n d t o n s o f st a n d a rd c o a l Year Diesel fuel Gasoline Natural gas Figure 3. Consumption of diesel, gasoline and natural gas in Henan province from 2005 to 2022 165 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 0 20 40 60 80 100 U n it : te n t h o u sa n d t o n s o f st a n d a rd c o a l Year Fuel oil Kerosene Figure 4. Consumption of fuel oil and kerosene in Henan province from 2005 to 2022 3. Calculation of Carbon Emissions from Fossil Fuels in Henan Province 3.1. Research Methods Among many carbon emissions calculation methods, the IPCC carbon emissions calculation method can account for countries, enterprises, projects in the industrial sector greenhouse gas emissions [8]. In order to calculate the carbon emission data of fossil energy in Henan province, the carbon emission calculation method in the IPCC guidelines for National Greenhouse Gas inventories (2006) was adopted. Greenhouse gas emissions activity data emission factors=  (1) Where activity data is a measure of production or consumption activities that contribute to greenhouse gas emissions. The emission factor is the coefficient corresponding to the activity data. 3.2. Carbon Emission Calculation Formula Calculate CO2 emissions from fossil fuels according to the IPCC National Greenhouse Gas Guidelines. i i i Y E C B=   (2) Y represents carbon emissions, iE represents the energy consumption of i energy, iC represents the standard coal conversion factor of i energy, iB represents the carbon emission conversion factor of i energy. According to the China Energy Statistical Yearbook can be known all kinds of energy conversion standard coal coefficient, detailed data see Table 2. Table 2. Conversion Factors of Various Types of Energy Conversion Factor Raw Coal Coke Crude Oil Gasoline Kerosene Diesel Fuel Oil Natural Gas Coefficient of standard coal 0.7413 0.9714 1.4286 1.4714 1.4714 1.4571 1.4286 1.3300 Carbon emission factor 0.7476 0.1128 0.5854 0.5532 0.3416 0.5913 0.6176 0.4479 3.3. Carbon Emissions from Fossil Fuels Through the calculation method of IPCC carbon emissions, the data of fossil energy carbon emissions in Henan province from 2005 to 2022 are obtained, see Table 3. From 2005 to 2022, the total fossil energy consumption in Henan province was 557,235.54 million tons, of which the total carbon emissions from coal energy was 267,013.36 million tons, accounting for 86.83% of the total energy carbon emissions. The two least consumed types of energy were kerosene (5,006,100 tonnes) and fuel oil (5,797,600 tonnes), accounting for 0.187% and 0.217% respectively. The change trend of carbon emissions of all kinds of fossil energy is roughly consistent with the change of their consumption. The carbon emissions of raw coal, Coke and crude oil increased first and then decreased, while those of gasoline, diesel and natural gas continued to increase. The carbon emissions of fuel oil fluctuated greatly, but increased significantly in 2022, while the carbon emissions of kerosene showed a fluctuating upward trend. 166 Table 3. carbon emissions from fossil fuels in Henan province from 2005 to 2022.Unit: in tons Year Raw Coal Coke Crude Oil Gasoline Kerosene Diesel Fuel Oil Natural Gas Carbon Emissions 2005 11202.35 108.78 558.61 190.15 6.99 283.03 67.63 141.33 12558.87 2006 13164.48 130.78 583.03 202.03 8.05 298.75 61.19 181.77 14630.09 2007 14732.16 157.58 598.29 172.32 8.57 396.24 54.75 197.43 16317.34 2008 14849.48 163.18 589.13 157.46 9.17 468.57 41.87 217.43 16496.30 2009 16526.40 160.38 665.45 163.41 12.84 459.14 22.54 260.92 18271.07 2010 16752.95 192.77 708.18 246.59 16.51 490.59 16.10 282.66 18706.36 2011 18761.61 227.97 741.76 297.10 25.68 578.64 38.64 326.15 20997.56 2012 17072.56 243.57 845.54 347.61 27.52 635.25 12.88 434.87 19619.79 2013 15579.72 199.17 805.86 454.57 23.85 669.84 28.98 456.61 18218.60 2014 14926.35 295.96 708.18 430.80 25.68 688.71 45.09 456.61 17577.38 2015 15769.87 154.78 506.72 555.58 34.86 742.17 35.42 519.67 18319.06 2016 15341.03 147.18 573.87 570.44 36.69 798.77 35.42 524.01 18027.42 2017 15326.87 135.18 543.35 603.12 36.69 839.66 25.76 587.07 18097.69 2018 13372.83 155.98 692.92 620.94 40.36 855.38 28.98 630.56 16397.95 2019 12320.97 156.78 668.50 626.89 45.87 867.96 9.66 630.56 15327.17 2020 12327.03 162.38 744.81 620.94 47.70 883.68 3.22 630.56 15420.33 2021 12426.15 173.18 772.28 632.83 45.87 965.45 6.44 695.79 15717.98 2022 13421.38 173.58 732.60 650.65 47.70 1009.47 45.09 739.27 16819.74 4. LMDI Factor Decomposition Process 4.1. LMDI Decomposition The LMDI method is based on the logarithmic mean method, which decomposes the contribution of each factor to the total change by logarithmic subtraction. Compared with the traditional arithmetic average method, the logarithmic mean method can capture the relative influence of factors more accurately. In addition, the decomposition results provided by the LMDI method are not only quantitative, but also have clear economic meaning. The contribution of each factor represents the influence of different economic phenomena or social activities on the change of total carbon emissions. We let Y be the total amount of carbon emissions and convert it. ( / ) ( / ) ( / )Y Y E E G G P P=    (3) Among them, E for energy consumption, G for the province's GDP; P for the total population. Set the /S Y E= to structural effect, indicating carbon intensity. /T E G= for technical effect, the ratio of energy consumption to GDP. GDP is per capita, economic effect. P for the total population, indicating the population effect. Carbon emission y is the function of structure effect, technology effect, economic effect and population effect. ( , , , )Y f S T A P S T A P= =    (4) The product model is logarithmically transformed into an additive model 1t t Y Y Y S T A P − − =  =  +  +  +  (5) Combined with the amount of carbon emissions between ( 1t − ) to t , then splits the logarithmic difference. 1 1 1 1 1 1 (ln ln ln ln ) ln ln t t t t t t t t t t t t Y Y S T A P Y Y Y S T A P − − − − − − −  =     − (6) 1 1 1 1 1 1 (ln ) ln ln t t t t t t t t t t t t Y Y S T A P Y Y Y S T A P − − − − − − −  =  − (7) t Y is the total carbon emissions of the period t , 1t Y − is the total carbon emissions of the period ( 1t − ); tS is the carbon emission intensity of the period t , 1tS − is the carbon emission intensity of the period ( 1t − ); tT is the ratio of energy consumption to GDP of the period t , 1tT − is the period of ( 1t − ) energy consumption and GDP value; tA is the period of t per capita GDP, 1tA − is the period of ( 1t − ) per capita GDP, tP is the period of the t total population, 1tP − is the period of the ( 1t − ) total population. LMDI decomposition formula for known fossil fuel carbon emissions [9]: 1 1 1 ( ) ln( ) ln ln t t t X t t t Y Y X Y Y Y X − − − −  =  −  (8) X represents the influencing factor, such as , , ,S T A P ; 1 ln ln t t Y Y − − represents the logarithmic difference between the carbon emissions of the current period and the previous period; 1 ln( ) t t X X − represents the logarithmic difference between the data of the current period and the data of the previous period; This shows the specific contribution of each factor to carbon emissions: 1 1 1 ( ) ln( ) ln ln t t t S t t t Y Y S Y Y Y S − − − −  =  −  (9) 1 1 1 ( ) ln( ) ln ln t t t T t t t Y Y T Y Y Y T − − − −  =  −  (10) 1 1 1 ( ) ln( ) ln ln t t t A t t t Y Y A Y Y Y A − − − −  =  −  (11) 167 1 1 1 ( ) ln( ) ln ln t t t P t t t Y Y P Y Y Y P − − − −  =  −  (12) The change in carbon emissions is the sum of the contributions: S T A P Y Y Y Y Y =  +  +  +  (13) S Y , T Y , A Y , P Y represent the effects of structure, technology, economy and population on the total carbon emissions of industrial enterprises in Henan province. 4.2. Calculating the Numbers S, T, A, P are carbon intensity, energy intensity, GDP per head and population, which can be calculated as shown in table 4. Table 4. LMDI numbers Year Carbon Intensity Energy Intensity Per capita GDP Population (CO2/Coal) (ton/$10,000) ($10,000) (billion) 2005 0.5517 2.2223 10486.7629 0.9768 2006 0.5494 2.2233 12197.4236 0.9820 2007 0.5472 2.0114 15021.2686 0.9869 2008 0.5470 1.7003 17882.5670 0.9918 2009 0.5486 1.7362 19244.5069 0.9967 2010 0.5464 1.5111 20976.8704 1.0800 2011 0.5454 1.4628 24096.9420 1.0922 2012 0.5449 1.2431 26492.7918 1.0932 2013 0.5508 1.0456 28655.2224 1.1039 2014 0.5379 0.9452 31142.8211 1.1102 2015 0.5551 0.8899 33060.6223 1.1217 2016 0.5576 0.8033 35399.5954 1.1370 2017 0.5596 0.7215 39399.5957 1.1377 2018 0.5595 0.5869 43635.0052 1.1444 2019 0.5594 0.5101 46768.0219 1.1486 2020 0.55949 0.50795 47075.68107 1.15260 2021 0.55955 0.48372 50352.40614 1.15330 2022 0.5600 0.4896 62140.4477 0.9872 4.3. LMDI Factor Decomposition Taking the data in table 4 into the LMDI model, the results of LMDI factor analysis of fossil energy carbon emissions in Henan province are obtained. Factor analysis results and total effect data for each year from 2005 to 2022 are detailed in table 5. Table 5. analysis results of carbon emission factors of fossil energy. Unit: 10000 tons Year Structure Effect Technology Effect Economic Effect Population Effect Total Effect 2006 -57.0236 5.9116 2050.2948 72.0385 2071.2213 2007 -60.7728 -1548.0105 3219.0871 76.9426 1687.2464 2008 -5.8151 -2757.1276 2860.6519 81.2582 178.9674 2009 51.0820 363.2453 1274.8419 85.5984 1774.7677 2010 -74.3211 -2567.8979 1593.5569 1483.9561 435.2939 2011 -38.0909 -643.1705 2749.7042 222.7487 2291.1916 2012 -16.7038 -3303.9159 1924.2748 18.5786 -1377.7663 2013 202.4621 -3271.6212 1483.7784 184.1923 -1401.1884 2014 -424.6621 -1808.2200 1489.8132 101.8433 -641.2256 2015 566.1510 -1081.8229 1072.4176 184.9339 741.6796 2016 79.9763 -1860.0651 1242.2500 246.2025 -291.6363 2017 64.1583 -1938.6880 1933.6875 11.1169 70.2746 2018 -2.6377 -3557.9472 1759.6480 101.1938 -1699.7432 2019 -2.8659 -2225.4950 1099.4917 58.0877 -1070.7814 2020 3.3107 -64.4040 100.8033 53.4459 93.1559 2021 1.5258 -760.9393 1047.6142 9.4523 297.6530 2022 12.7536 197.1537 3420.8576 -2529.0034 1101.7615 Full-time effect 298.5269 -26823.0144 30322.7732 462.5861 4260.8719 From 2006 to 2022, the total effect of fossil energy carbon emissions in Henan province showed a fluctuating trend of first decreasing and then increasing. Specifically, the total effect of carbon emissions continued to decline between 2006 168 and 2008, rising in 2009 and then declining further in 2011. Carbon emissions fell the most in 2011, by 36.6895 million tonnes, and the total effect level remained basically unchanged until 2013. From 2015 to 2022, the total effect of carbon emissions fluctuated greatly and showed an overall upward trend. Overall, the total amount of fossil energy carbon emissions in Henan province has changed by 4.261 billion tons. 4.3.1. Structural Effects The structural effect has the lowest positive driving degree to the total effect, and its contribution to carbon emissions in the whole period is 2.9853 million tons. The structural effect was negative in most years between 2006 and 2014. The negative driving value was-4.2385 million tons, indicating that the fossil energy consumption structure effectively curbed carbon emissions during this period. From 2015 to 2022, although the overall trend shows a continuous downward trend, the value of most structural effects is always positive, and the positive driving value of this interval is 7.2237 million tons. This shows that the relevant departments have optimized and upgraded the energy consumption structure after the introduction of the policy of “Energy saving and emission reduction and low-carbon development work arrangement in Henan province in 2015”, but there is still a certain potential for carbon emission reduction. Overall, the total effect from 2006 to 2022 is positive, indicating that despite changes in energy consumption structure, there is still a potential to reduce carbon emissions from fossil fuels. 4.3.2. Technical Effects It can be seen from table 5 that the impact of technological progress on carbon emissions in Henan province fluctuates from 2006 to 2022. Specifically, in 2008,2010,2013 and 2018, the negative impact of technological progress on carbon emissions rebounded the following year, respectively. The negative driving effect in 2010 was the most significant, reaching 29.3114 million tons. Reductions in energy intensity often result from technological progress, reflecting improvements in energy efficiency [10]. Compared with the impact of other factors on the total amount of fossil carbon emissions, the technical effect has a total effect of-268230100 tons. This shows that from 2005 to 2022, the technological progress in the field of fossil energy carbon emissions in Henan province has played a positive role in reducing carbon emissions. 4.3.3. Economic Effects The economic effect has the largest positive driving force on the total effect, with a cumulative total of 30.2277 million tons of CO2. From 2005 to 2022, the economic effect is always positive and the overall trend is upward. In 2008, affected by the global financial crisis, the economic effect of a substantial decline in the 15.8581 million tons. Since then, the economic effect has gradually rebounded and declined again after reaching 27.497 million tons in 2011 until it stabilized in 2015. From 2017 to 2020, the impact of economic effects on fossil energy carbon emissions showed a downward trend. Since then, the economic effect has continued to grow and reached 34,208,600 tons in 2022. Because the economic effect has the highest positive driving degree on fossil energy carbon emissions, it shows that economic growth is the main factor to promote the increase of fossil energy carbon emissions in Henan province 4.3.4. Population Effect The positive impact of population on fossil fuel carbon emissions is relatively small, at 4,625,860 tons. From 2006 to 2021, the impact factors of population effect on fossil energy carbon emissions were all positive, and the impact degree was 29.9159 million tons of CO2. In 2022, the impact of population effect on carbon emissions has a negative driving force, which is-25.2 million tons of CO2. From 2006 to 2022, the population effect has increased carbon emissions by 4.6259 million tons, indicating that population growth has a positive driving effect on fossil energy carbon emissions. 5. Carbon Emission Reduction Measures 5.1. Optimizing the Energy Consumption Structure Optimizing energy consumption structure is an important way to improve energy efficiency [11]. Optimizing the energy consumption structure, that is, reducing the dependence on traditional high-carbon energy, can reduce the growth of carbon emissions caused by structural changes. To achieve this goal requires the joint efforts of the government and enterprises. The government can gradually reduce the proportion of fossil energy consumption by increasing clean energy investment, strengthening carbon emission regulation and promoting green finance Enterprises can reduce energy waste and improve energy efficiency by introducing energy- saving technologies, improving equipment efficiency and developing energy-saving products. The two work together to promote the optimization of the energy structure. 5.2. Promoting Innovation in Green Technologies Green technology innovation is an important way to promote technology upgrading, which can fundamentally reduce carbon emissions [12]. The key to promoting green technology innovation is to increase support for research and development of core technologies, especially in cutting-edge areas such as carbon capture and storage (CCUS) and battery storage in addition, the government can encourage enterprises to increase r & D investment in green technology through fiscal subsidies, green credit and other policy means. With the continuous improvement of technology, the application effect of green technology is enhanced, thus further reducing carbon emissions. 5.3. Strengthening Energy Management Strengthening energy consumption management can reduce the correlation between energy consumption and carbon emissions in economic activities, and help to reduce the impact of economic factors on carbon emissions. Strengthening energy consumption management can achieve this goal by building an intelligent energy consumption management platform, implementing energy consumption restrictions, promoting renewable energy and other measures. The construction of intelligent energy consumption management platform can improve energy efficiency by reducing energy loss [13]. The implementation of energy consumption restriction policy can gradually phase out high carbon emission energy by regulating carbon emission quota and adjusting market mechanism. The promotion of renewable energy can guide enterprises and residents to transform the use of fossil energy to clean energy by constructing supporting facilities and issuing green subsidies. 169 6. Conclusion This study aims to calculate the carbon emissions of fossil fuels in Henan province, analyze the impact of relevant factors on them, and provide suggestions for carbon emission reduction in Henan province. Through the decomposition of LMDI factors, the carbon emissions caused by fossil energy consumption are divided into four factors: Structure, technology, economy and population. The contribution of each factor to the total effect of carbon emissions was 2.9853 million tons, -268.2301 million tons, 303.2277 million tons and 4.6259 million tons, respectively. The results show that: economic growth and technological progress significantly affect carbon emissions; energy structure change, economic development and population growth positively drive carbon emissions of fossil energy in Henan province; The improvement of technology has a negative impact on carbon emissions. 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