What Causes the Difference in PM2.5 Emissions among Regions: The Perspective of Social Economic Factors

With the rapid development of China’s economy, the differences in economic levels among regions have been increasing. it directly affects the demand for terminal fossil energy among regions. The discharge of a large amount of particulate matter in the process of energy consumption which brings great pressure to the control of regional pollution. Therefore, it is of great theoretical and practical significance to study the affecting factors of the difference of PM2.5 emissions caused by fossil energy consumption in various regions of China. By 2010-2016 National Energy Balance Sheet data terminal sector energy consumption estimated the PM2.5 emissions of energy consumption and confirmed PM2.5 emissions mainly from coal consumption, thus further analyzed each region PM2.5 emission efficiency and status. On this basis, through the constructed LMDI model, the factors which influence PM2.5 emissions measured in this paper are decomposed into eight factors: industrial emission intensity, industrial structure, economic scale, population size, etc. The results show that: 1) Economic growth is the decisive factor. The difference between PM2.5 emissions among regions has a high single trend with economic development. Each region should improve the quality of economic development and achieve Pareto optimality for economic development and environmental governance. 2) Compared with the eastern region, the central and western regions have lower technical level, which means higher marginal PM2.5 emission reduction potential. Based on the above conclusions, it is necessary to focus on the sub-regions to reduce emissions and control the pollutant while fully reflecting the characteristics of regional emission reduction.


Introduction
With the rapid development of China's economy in recent years, the differences in the level of economic development in various regions of China are gradually increasing. The process of economic development has caused a great negative impact on the quality of the air environment. The most typical is the proliferation of haze pollution. It has become one of the most important reasons for the decline in air quality in China. However, China's haze pollution does not happen in a single regional, but in a large area in various regions, and the trend of haze pollution is increasingly regionalized, with total coverage of more than 1.3 million square kilometers. PM 2.5 is one of the most important indicators to measure the severity of haze, which refers to inhalable particles with a diameter or particle size of fewer than 2.5 microns. In haze weather, human inevitably inhale PM 2.5 particles in daily activities, which has a huge impact on human health, such as: endanger human body's respiratory system, heart system, etc.. According to the national temperament number published by the Environmental Protection Agency, The haze level of Jinan City ranks the first in the country (Shandong Environmental Protection Bureau,2015), which has become the city with the highest mortality rate due to fine particles. As for fine particulate matter pollution, there is much scientific evidence to prove that fossil energy consumption, especially coal consumption, is the main contribution to the formation of fine particulate matter.

Literature Review
The earliest research on PM 2. 5  particulate matter emitted by fossil energy consumption [14].
Second, the current literature focuses on the study of carbon emission estimation and decomposition. The literature on estimating or decomposing PM 2.5 emissions from fossil energy consumption in the economic sector is rare.
The contribution of this paper is to select the PM 2.5 emissions of fossil energy consumption as the research index. Compared with the primary source estimation in the above literature, the PM 2.5 emission factors generated by fossil energy consumption in the terminal sector will not be greatly fluctuated due to the improvement of technical efficiency, and there is a considerable degree of rationality, a convenient method, which can meet the estimation of PM 2.5 emissions from interregional terminal sectors. At the same time, the factor decomposition method is used to analyze the driving factors; the method is simple and convenient. The decomposition has no residual value, which is suitable for the research and analysis of the paper.

Accounting Formulas and Data Resources
At present, there are few studies on the PM 2.5 emissions of fossil energy consumption at home and abroad, especially the differences in the factors affecting the PM 2.5 emissions of fossil energy consumption among regions. Based on the comprehensive balance sheet of local energy statistics, the paper estimates the Among them, PM represents the emission of energy consumption, i P represents the emission factor of the i-th energy, and i l represents the consumption of i-th energy, which is expressed as coal, oil, natural gas, and electricity. In view of the data selected in this paper is relatively short, the emission factors generated by each energy consumption will not change much due to the technological advancement or energy utilization. While considering the emission factor as static, based on the research of Zhao Bin and Zheng Ming, the pollutant emissions from the energy consumption of each terminal department are obtained [14] [15] as shown in Table 1.
In order to accurately calculate the PM 2.5 emissions from energy consumption, Table 1 divides all energy into four categories: coal-based fuels, petroleum-based fuels, natural gas-based fuels, and electrical fuels. The PM 2.5 emissions per unit of energy consumption are measured by the consumption emission factor in g/kg.

Model Construction
The paper constructs a comprehensive and improved LMDI model to decompose and analyze the growth of PM 2.5 emissions in China, and decomposes the total emissions from China's terminal energy consumption into 30 provinces, the sum of the driving contribution effects of three economic sectors (industrial, In formula (2), the amount of emissions from the j-th sector of the i-th province due to energy consumption is expressed as ij PM (unit: ton), ij Y indicates the nominal value added by the j-th department of the i-th province (unit: 100 million yuan), i Y indicates the nominal GDP of the i-th province (unit: 100 million yuan), P indicates the population size of the i-th province (unit: 10,000 people), ij I indicates the emission intensity of the j-th economic sector in the i-th province, ij K indicates the structure proportion of the j-th department of the i-th province, i S represents the per capita living standard of the i-th province.
According to the LMDI I decomposition method, the decomposition of each province's PM 2.5 emissions can be expressed as: In formula (3), PM I , PM J , PM S , and PM P respectively represent changes in emissions that result from economic sector emission intensity effects, industrial structure effects, economic scale effects, and population size effects.

Analysis of the Current Situation of China's Three Major Regional PM2.5 Emissions from 2010 to 2016
Energy consumption refers to the number of various energy sources produced and consumed by the terminal department for a certain period of time after deducting the consumption and loss of the secondary energy used for processing.
The data of emissions in this paper are collected from the energy consumption of the terminal department. In order to ensure the accuracy of the emissions statistics, the paper selects the provincial energy balance table and the database of CNKI to estimate the emissions, whose results are relatively close to reality.  Table 2 and Figure 4 show that economic growth is the main positive factor of   has a negative effect, which indicates that there is significant progress in the governance of regional structure, whose essence is that the economic development mode has been effectively transformed. The most significant contribution to the industrial structure is the industrial structure effect, and its contributions among  (Table 3).

Analysis of Factors Affecting Interregional PM2.5 Emissions
During the period of research, China has been implementing policy control over regional emissions. The Chinese Environmental Protection Agency put forward a series of guidance opinions on controlling regional air quality in 2010, which emphasizes that particulate matter is a key pollutant, and it is required  strong, the emission intensity effect and total effect are more obvious for emission reduction. The central and western regions are rich in resources, whose economic development mainly depends on high energy-consuming and labor-intensive industries, thus has a lower reduction for emissions. According to national statistics, the proportion of agricultural added value is less than 15% from 2010 to 2014, and the proportion of agricultural labor is less than 30%, showing that China is in the stage of industrial economy, and the effect of industrial structure on this period is not obvious to the emission reduction. After 2014, China was in the transition period from the industrial economy to a service economy. By 2015, the value-added ratio of China's service industry exceeded 50%, and the proportion of service labor force exceeded 40%. During this period of time, the industrial structure has been continuously upgraded and modernized, and the proportion of industrial labor has been continuously reduced. In this year, the industrial structure effect is particularly obvious for emission reduction. It is pointed out that when social-economic development reaches a certain level, the population growth rate will decrease accordingly. In addition, China has implemented the family planning policy for nearly 30 years.
Under the dual effect, the fertility rate has continued to decline, which shows that the population effect of China has not changed much during the "Twelfth Five-Year Plan" period.

Conclusions and Suggestions
Using which is mainly high-energy-consuming products. Therefore, we can reduce the proportion of exports of high-energy-consuming products through taxation, subsidize and support the export of technology products and reduce emissions.