An Empirical Emission Analysis Model for Hebei Provincial Industries in China

Transcription

1 An Empirical Emission Analysis Model for Provincial Industries in China Dezhi Liu Shijiazhuang University Economics, China, Hong Wu 1, Haibiao Cai 2 Abstract - With a population 67 million people, is one largest provinces in China, with a rapid growth in economy. The 25 provincial GDP and value creation increased respectively 3.2 and 1.8 times over the 2 level, which indicates a fantastic developing speed. However, there is an environmental challenge also has accompanied with economic growth. This challenge is nowadays an urgent issue to deal for further economic development. According to the national 25 statistics in China, the provincial s for wasting gas, CO2, dusts and soot are placed as number 1, 5, 6 and 2 respectively in a national ranking. These ranks indicate a fact the total level is much higher in province than the rest China. This paper introduces an empirical analysis model for static s for industries. The model consists a number measurable variables, such as GDP, value creation, coefficient and probability deviations. Based on the available data sourced by provincial and national statistics for outcome, the model is used to analyze the basic structure, mainstream and correlations total s, types industries and return investments for control and treatment, as well as environmental projects. The analysis model provides also the fundamental information for decision making process in further investments for industries, macro-level governing structures, restructuring the provincial sectors and better utilizing natural resources. The study analysis concluded there is still a need for limitation for total s for the provincial industries and the ways for realizing is upgrading total productivities and efficiencies. Our analysis also recommends more investments for s control and treatment projects, as well as restructuring provincial industries from heavy production based into new innovation based. Key words - Emission, Empirical analysis, Industrial Waste Gas, Treatment GENERAL SITUATION OF EMISSION OF INDUSTRIAL WASTE GAS AND OUTPUTS IN HEIBEI PROVINCE As rest China, the industry economy Heibei province has been developed in a very fast speed for the last decades. In 25, the provincial Gross Industrial Output Value was calculated as 1,1 billion RMB (equal to 143 billion USD) and the Value-added Industry Creation was calculated as 322 billion RMB (equal to 42 billion USD). Both indicators were approximately 3.2 times and 1.8 times respectively than the 2 levels. At the same time, this high speed growth has also brought the environment issues companied with the achievement. As environment becomes a global issue for debates and it has huge impact to climate, sustainability, ethics and even legal consequence [1]. The pollution issue is a severe focus and there is indeed a need to reduce the pollutions and in a long term view, eliminate it. To start with, it is necessary to define the measurable variables and standards for pollution measurement. According to the National Bureau statistics China s standard criterion, a most common pollution source is defined as waste gas, which includes: 1) Industrial SO 2, measured in cubic meters; 2) Industrial soot, measured in ton; 3) Industrial dust, measured in ton The total waste gas in China for 25 was measured as billion cubic meters, the volume SO 2 was amounted to million tons, the volume soot was amounted to.56 million tons and the volume dust amount to.713 million tons. Among these measurements, provincial industries have occupies national ranking in 1st, 5th, 5th and 2 nd places, respectively, see details in Figure 1, 2, 3, 4. According to 24 Chinese environment statistic annuals, the SO 2 intensity is.274 ton/1 RMB, the soot is.122 ton/1 RMB, the dust intensity is ton/1 RMB, respectively higher than the national average 29.9%, 23.2% and 61.4%. The data above indicated that province is still in the stage extensive mode industry economy growth. The eleventh five-year plan province indicated that should protect environment, build a resource conservation and environment friendly society, insist sustainable development and new ization path. In order to realize this object, there is a practical significance to 1 Hong Wu, Østfold Univeristy College, Norway, hong.wu@hi.no 2 Haibiao Cai, Shijiazhuang University Economics, China, chb @sohu.com Coimbra, Portugal September 3 7, 27 International Conference on Engineering Education ICEE 27

2 do empirical Analysis Emission and Treatment Waste Gas province. (1 million cu.m) 1 tons 1 tons 1 tons Aarrangement the total volume waste gas in Chinese province (region, city) in 25 FIGURE 1 FIGURE 2 Aarrangement volume SO2 in Chinese province (region, city) in 25 Aarrangement volume soot in Chinese province (region, city) in 25 FIGURE 3 Aarrangement volume dust in Chinese province (region, city) in 25 FIGURE 4 EMPIRICAL ANALYSIS OF EMISSION OF INDUSTRIAL WASTE GAS IN HEBEI PROVINCE Static econometrical model analysis waste gas If technical level is constant, the volume waste gas is in direct ratio to Gross Industrial Output Value or Value-added Industry. So below model waste gas can be established as: Y=β +β 1X1+ε 1 Y=β 2+β 3X2+ε 2 Among: Y expresses total volume waste gas. X 1 expresses Gross Industrial Output Value. X 2 expresses Value-added Industry. ε 1 andε 2 express disturbance. β 1 is direct intensity, it expresses the volume waste gas per industry product produced, reflects the direct intensity in industry department producing its products. It is direct-viewing and its physical significance is specific, it is supposed to be a invariable under invariable technical level. β 3 is Value-added intensity, it expresses the volume waste gas per Value-added created. Compare with direct intensity, it can reflect the economy benefit waste gas industry department better. In situation taking GDP Value-added caliber as the goal economy development, there is more pertinence to use Value-added intensity to study new ization path and environment friendly society. In itself, Value-added intensity is direct intensity. Its physical significance is less clear than direct intensity, which takes Gross Industrial Output Value as foundation, but its economical significance is more important. It is supposed to be a invariable under invariable technical level too. TABLE I DATA OF HEBEI PROVINCE INDUSTRIAL OUTPUT VALUE AND THE VOLUME OF INDUSTRIAL WASTE GAS EMISSION Year Gross Industrial Output Value X 1 (1 million RMB) Valueadded Industry X 2 (1 million RMB) total volume waste gas Y (1 million cu.m) volume SO 2 Y 1 (1 ton) volume soot Y 2 (1 ton) volume Y 3 (1 ton) Data source: Economy annals province, National Bureau statistics China. According to data Gross Industrial Output Value, Value-added Industry, the total volume waste gas, SO 2, soot and dust in province (Table 1), we used Eviews3.1 to regression analysis, the output result can be seen in Table 2 and Table 3. So we can establish below regression models respectively: Y = *X (1) Coimbra, Portugal September 3 7, 27 International Conference on Engineering Education ICEE 27

3 Y = *X (2) TABLE 2 EVIEWS3.1 OUTPUT RESULT Variable Coefficient Std. Error t-statistic Prob. X C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic). TABLE 3 EVIEWS3.1 OUTPUT RESULT Variable Coefficient Std. Error t-statistic Prob. X C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic). We test the sample regression equation (1), (2): Test Economical significance: β ) 1= >, β ) 3= >, they express the volume waste gas is in direct ratio to Gross Industrial Output Value or Value-added Industry, so the expression regression coefficient accords with economy theory and experience expectation. Test goodness fit: according to Table 2 and Table 3, R-squared 1 = , R-squared 2 = , Static econometrical models waste gas reflects the relation between total volume waste gas and Gross Industrial Output Value, the relation between total volume waste gas and Value-added Industry. Direct intensity and Value-added intensity both have significance, and β ) 3> β ) 1, they indicate that the treatment level total volume waste gas hasn t been improved essentially from 1995 to 25 in province,that economical benefit waste gas is low. Dynamic econometrical model analysis waste gas If technical level is variable, direct intensity and Value-added intensity will change. According to Table 1, we can calculate annual direct intensity SO 2, soot and dust from 1995 to 2 (Figure 5). The below dynamic econometrical model waste gas can be established: Yi=Ci+ƒ 1i(q)X1+ε i(i=1,2,3) (3) Yi=Ci+ƒ 2i(q)X2+ui(i=1,2,3) (4) Among: i=1,2,3 expresses the dynamic econometrical model SO 2, soot and dust respectively in the model. Y i expresses the volume different kind waste gas. X 1 expresses Gross Industrial Output Value. X 2 expresses Value-added Industry. ε i and u i express disturbance. ƒ 1i(q) expresses direct intensity, it is the function current year investment amount q treatment project waste gas. ƒ 2i(q) expresses Valueadded intensity, it is the function current year investment amount q treatment project waste gas too. Adjusted R-squared 1 = ,Adjusted R-squared 2 = , result indicate that 99% total sum squares are explained by sample regression line, only 1% is not explained, obviously, the goodness fit sample regression model is very high. T test: given significance levelα =.5, we check t distributing table on degrees freedomν =11-2=9, gain t.25 ( 9 ) = 2.26, according to table 2 and table 3, t = >t.25 (9),t 1 = > t.25 (9),t 2 = > ton/1 yuan,5,4,3,2, Direct intensity SO2 Direct intensity soot Direct intensity dust t.25 (9), t 3 = > t.25 (9),so regression coefficients two model have significance and are not equal to zero, model should contain absolute term, X 1 and X 2 have significant effect on Y respectively. According to above test, these two models are relatively good. FIGURE DIRECT EMISSION INTENSITY OF INDUSTRIAL WASTE GAS IN HEBEI Coimbra, Portugal September 3 7, 27 International Conference on Engineering Education ICEE 27

4 ton /1yuan,16,14,12,1,8,6,4, Value-added intensity SO2 Value-added intensity soot Value-added intensity dust Figure VALUE-ADDED EMISSION INTENSITY OF INDUSTRIAL WASTE GAS We can get differential from both sides equation (3) and equation (4): Δ Yi=ƒ 1iΔ q+ ƒ 1i(q)Δ X1 Δ Yi=ƒ 2iΔ q+ ƒ 2i(q)Δ X2 X 1 and X 2 are exogenous variables, the tendency ƒ 1i and ƒ 2i are mainly consistent as well as the tendency intensity three kind waste gas according to Figure 5 and Figure6, so we will take ƒ 11(q) for instance to analysis in following text. According to data province direct intensity SO 2 and current year investment amount q treatment project waste gas (Table 4), we can establish following model direct intensity: ƒ 11=C1+C11q+ν Among:ν expresses disturbance We used Eviews3.1 to regression analysis, the output result can be seen in Table 5, establish below regression model: ƒ 11 = e-7*q TABLE 4 HEBEI PROVINCE DIRECT EMISSION INTENSITY OF INDUSTRIAL SO2 AND CURRENT YEAR INVESTMENT COST Q OF TREATMENT PROJECT OF INDUSTRIAL WASTE GAS Year current year investment cost q treatment project waste gas (1RMB) direct intensity SO 2 ƒ 11 (ton/1rmb) TABLE 5 EVIEWS3.1 OUTPUT RESULT Variable Coefficient Std. Error t-statistic Prob. Q -3.98E E C R-squared.8385 Mean dependent var Adjusted R-squared S.D. dependent var.9673 S.E. regression.4129 Akaike info criterion Sum squared resid.136 Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic).22 Test Economical significance: C 11 = e- 7<, expresses with investment cost increase 1,RMB, technical level will be enhanced, as a result, the direct intensity SO 2 will reduce e-7. It accords with economy theory and experience expectation. Test goodness fit: R-squared =.8385, Adjusted R-squared= , indicates the goodness fit sample regression model is very high. T test: given significance level α =.5,we check t distributing table on degrees freedomν =1-2=8, t.25 (8) = 2.31,obviously, t c1 = >2.31,t c = >2.31,indicates current year investment amount q treatment project waste gas has significant effect on ƒ 11direct intensity SO 2. The same principle may result in, according to data Table 1 and Table 4, we can establish following sample regression model direct intensity soot and dust: ƒ 12= e-7*q ( ) ( ) R2= ƒ 13 = e-7*q ( ) ( ) R2= What dynamic econometrical model analysis waste gas measures are the alteration direct intensity or Value-added intensity caused by alteration treatment investment cost, the influence on the volume waste gas. According to above analysis, the investment cost treatment waste gas has significant influence on waste gas intensity. C 11 > C13 > C12, Therefore, investment cost have most influence on direct intensity SO2, have certain influence on direct intensity dust, and have less influence on direct intensity soot relatively. Structure analysis waste gas In 24, among the national industry pression, the first 5 pressions the volume SO 2 are the electric power industry, non-metallic mineral product industry, ferrous metals melting industry, chemical manufacturing industry, non-ferrous metals melting industry; the first 3 pressions the volume soot Coimbra, Portugal September 3 7, 27 International Conference on Engineering Education ICEE 27

5 are the electric power industry, the non-metallic mineral product industry, ferrous metal smelting and the rolling processing industry; the first 2 pressions volume dust are non-metallic mineral product industry, ferrous metal smelting industry. In 24, the data gross value output in province and the first 5 pressions situation can be seen in table 6, obviously, industry structure Province by the high pollution pression primarily, the gross value output high pollution pressions account for the total output value entire province industry 47.2%. Industry structure Province determines the waste gas volume and composing proportion on certain degree. TABLE 6 24 GROSS VALUE OF TOTAL PROVINCE INDUSTRIAL OUTPUT AND THE FIRST 5 INDUSTRY PROFESSIONS IN HEBEI Grouped by Sector Gross value output (1 Million) Province total Smelting and Pressing Ferrous Metals Manufacture chemical industry Production and Distribution Electric Power and Heat Power Processing Food from Agricultural Products Manufacture Non-metallic Mineral Products Style waste gas SO 2, soot, dust 46.5 SO 2, SO 2, soot, SO 2, soot, dust EMPIRICAL ANALYSIS OF TREATMENT OF INDUSTRIAL WASTE GAS IN HEBEI PROVINCE Analysis Industrial waste gas treatment efficiency in province Take 24 as the example, in Province, the data treatment efficiency waste gas comparing with the national top and average treatment efficiency can be seen in Figure 7, obviously, in, the rate soot meeting discharge standard has achieved the domestic advanced level, the rate SO2 and dust meeting discharge standard is higher than the national average level, but still exists 15.6%and 11.4% disparities with the domestic advanced level respectively. % SO2 99,9 99,9 96,8 1 84,3 75,6 soot 8,2 dust 88,6 FIGURE 7 24 THE COMPRAISON OF INDUSTRIAL WASTE GAS MEETING DISCHARGE STANDARD 71,1 The rate domestic advanced level Domestic advanced level The rate average level Analysis investment waste gas treatment in province In 24, the data investment source treatment project waste gas in Province can be seen Figure 8, investment source by the enterprise self-provides and the environmental protection special fund primarily, enterprise self-provides fund is 971 billion RMB (equal to 126 billion USD), which accounts for 74% in total sources, environmental protection special fund is 231 billion RMB (3 billion USD), accounts for 18% in total sources. 24 INVESTMENT SOURCE OF TREATMENT PROJECT OF INDUSTRIAL WASTE GAS IN 4% 1% 74% 3% % 18% State budget fund HEBEI Environmental protection special fund Enterprise self-provides fund Domestic loan Foreign capital using Others FIGURE 8 24 INVESTMENT SOURCE OF TREATMENT PROJECT OF INDUSTRIAL WASTE GAS IN HEBEI From 1995 to24, the tendency proportion that investment cost treatment industry waste gas investment occupies total investment pollution treatment in province can be seen in Figure 9. In 24, its proportion increases approximately 28- percentage points comparing to Obviously, it increases the cost proportion waste gas treatment investment in the general tendency. This has reflecting in the investment cost, which representing a changeable and dynamic econometrical model analysis waste gas.,8,6,4, FIGURE THE TENDENCY OF PROPORTION THAT INVESTMENT COST OF TREATMENT OF INDUSTRY WASTE GAS INVESTMENT OCCUPIES TOTAL INVESTMENT OF POLLUTION TREATMENT IN HEBEI CONCLUSION AND MEASURES According to the static and dynamic econometrical model analysis waste gas, the structure analysis waste gas and the analysis efficiency and investment treatment, we can get to draw a conclusion as follow: Coimbra, Portugal September 3 7, 27 International Conference on Engineering Education ICEE 27

6 1. The current study can be developed and used as a case study for a part higher education syllabus, such as course in environment management. The definitions in SO 2, measured in cubic meters, versus soot, and dust, both measured in ton can still be an open debate issue for university students, as these definitions and they converting applications toward international standards. 2. The mathematic calculations and modeling waste s are important decision making reasoning and this reasoning has structure and determinism based approach. The good thing with this approach is clear and simple view, the disadvantage is lack qualitative analysis, so the combination both is recommended. 3. The treatment level total volume waste gas hasn t been improved essentially in province. From now on, controlling total volume should be focused on. In this aspect, the institution pollution right trade that has been tried out in other province can exert positive effect. So institution pollution right trade should be pushed in province. 4. Economical benefit waste gas is low, so we should speed our steps to reform technique then lower the Value-added intensity. 5. The level waste gas is higher than most other province, but with investment cost increasing, the direct intensity waste gas has been reduced obviously. In order to reduce intensity pollution more, we should insist new ization mode low pollution and increase more investment cost. 6. The structure province is structure high pollution. During and after the eleventh five-year plan, the structure should be adjust gradually, break away from extensive mode industry economy growth. 7. The total efficiency treatment waste gas province is better than that national average efficiency, but hasn t come up with the national advanced treatment efficiency yet. The source investment pollution treatment is too centralized. REFERENCES [1] Christina Voigt, From climate change to sustainability: An essay on sustainable development, legal and ethical choice. Worldviews 25. 9, Koninklijke Brill NV, Leiden, Also available online [2] Dallas Burtraw, David A. Evans, Alan Krupnick, Karen Palmer, and Russell Toth, Economics pollution trading for SO2 and NOx. Annual Review Environmental Resource : [3] David Pearce, An intellectual history environmental economics. Annual Review Energy Environment : [4] Economy annals province [5] Edi Medilanski, Liang Chuan, Hans-Joachim Mosler, Roland Schertenleib and Tove A Larsen, Wastewater management in Kunming, China: a stakeholder perspective on measures at the source. Environment and Urbanization 26; 18; 353. The online version this article can be found at: [6] Gao Xue ming, Xu Jian etc., Resources and environmental statistics [M], China Statistics Press, April in 24, 1st edition [7] Jeffrey M. Wooldridge, Introductory Econometrics A Modern Approach [M], Chinese people university press, March in 23, 1 st edition [8] National environmental protection bureau China, Chinese environment statistics annual report in 24 [M], China environmental science press, August in 25, 1 st edition [9] Noel de Nevers, Air pollution control engineering, Tsinghua University Press, 22. [1] Swee Chua, Economic growth, liberalization and the environment: A review the economic evidence. Annual Review Energy Environment : [11] Vaclav Smil., China's environmental crisis An inquiry into the limits national development [M], M.E.Sharpe,Inc [12] Xu Jian, Input-Occupancy-Output Analysis Water Consumption Coefficients and Establishment Water-saving National Economic System [J], Selected paper on analytical purposes I-O techniques in China [M], China statistics press, May in 24, 1 st edition Seen from the tendency proportion that investment cost treatment industry waste gas investment accounted for total investment pollution treatment, province realizes importance treatment waste gas more and more. In order to achieve better treatment efficiency, local government should open up the source investment pollution treatment, should increase the quantity and proportion state budget fund, domestic loan and foreign capital using. It is also worth to investigate the international experiences, both in pollution trading [2] and environmental economics [3] so the new economic development is based on environmental thinking. Coimbra, Portugal September 3 7, 27 International Conference on Engineering Education ICEE 27