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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

Postal Subscription Code 80-973

2018 Impact Factor: 3.883

Front Envir Sci Eng    2012, Vol. 6 Issue (5) : 734-742    https://doi.org/10.1007/s11783-012-0451-6
RESEARCH ARTICLE
Forecasting industrial emissions: a monetary approach vs. a physical approach
Yang DONG1, Yi LIU1(), Jining CHEN1, Yebin DONG2, Benliang QU2
1. School of Environment, Tsinghua University, Beijing 100084, China; 2. Center for Strategic Environmental Assessment, Dalian Municipal Design and Research Institute of Environmental Science, Dalian 116002, China
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Abstract

Forecasts of industrial emissions provide a basis for impact assessment and development planning. To date, most studies have assumed that industrial emissions are simply coupled to production value at a given stage of technical progress. It has been argued that the monetary method tends to overestimate pollution loads because it is highly influenced by market prices and fails to address spatial development schemes. This article develops a land use-based environmental performance index (L-EPI) that treats the industrial land areas as a dependent variable for pollution emissions. The basic assumption of the method is that at a planning level, industrial land use change can represent the change in industrial structure and production yield. This physical metric provides a connection between the state-of-the-art and potential impacts of future development and thus avoids the intrinsic pitfalls of the industrial Gross Domestic Product-based approach. Both methods were applied to examine future industrial emissions at the planning area of Dalian Municipality, North-west China, under a development scheme provided by the urban master plan. The results suggested that the L-EPI method is highly reliable and applicable for the estimation and explanation of the spatial variation associated with industrial emissions.

Keywords industrial emissions      environmental performance index      spatial planning      industrial land use     
Corresponding Author(s): LIU Yi,Email:yi.liu@tsinghua.edu.cn   
Issue Date: 01 October 2012
 Cite this article:   
Yang DONG,Yi LIU,Jining CHEN, et al. Forecasting industrial emissions: a monetary approach vs. a physical approach[J]. Front Envir Sci Eng, 2012, 6(5): 734-742.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-012-0451-6
https://academic.hep.com.cn/fese/EN/Y2012/V6/I5/734
industrial sectorsNo.E-EPI based on the census(wastewater/(kg·(103 CNY)-1); the others/(kg·(106 CNY))-1)
wastewaterCODammoniaSO2NOx
PFAP110254.84172.126.4583.4724.93
MF331522.36467.669.20325.5298.85
MB9740.2484.5515.92103.4247.31
MTWFC89.621.460.00157.9446.84
MPP811871.271364.130.84934.92296.40
PPCPNF52839.1735.952.11130.3062.38
MRCMCP394110.33667.899.82221.45466.15
MM101713.45267.6717.78108.89106.53
MR4110.6653.320.55163.3247.91
MP574.3037.142.663.051.57
MNMP4649.378.711.25736.032747.48
SPFM14222.2153.921.6295.0328.83
SPNM558.5525.820.00426.98111.15
MMP5090.9016.490.748.833.30
MGPM904.190.830.070.580.13
MSPM120.070.010.000.010.01
MTE22162.3017.110.0712.374.52
MCECEE1654.6013.080.840.760.83
PSEPHP133279.3512.600.006084.566788.84
total61973.442.370.1016.0916.85
Tab.1  E-EPI of the key industrial sectors in 2009
industrial sectorsNo.L-EPI based on the investigation(wastewater/(103 t·km-2·a-1); the others/(t·km-2·a-1)class
wastewaterCODammoniaSO2NOx
PFAP76607.54213.0013.17142.6244.25II
MF30314.8481.421.9472.1521.85II
MB132218.73335.8538.96375.42174.64III
MTWFC18360.35120.3812.53340.76105.03II
MPP1310471.91529.421.261009.14311.58III
PPCPNF590539.361257.3473.884217.312678.22III
MRCMCP259171.66459.8882.26920.43851.58III
MM121862.42292.8112.71139.94123.92III
MR5208.3751.250.89203.5073.04II
MP960.7825.842.443.330.97I
MNMP18183.4320.821.79235.721903.62II
SPFM10574.3394.253.18116.17134.40II
SPNM3133.5517.211.5765.6419.85I
MMP6231.6055.753.393.931.28I
MGPM46403.0059.375.2752.3718.83II
MSPM14210.1423.280.8173.4031.35I
MTE11975.0594.621.1430.0130.07II
MCECEE131103.05168.1615.666.5211.44II
PSEPHP31628.0535.460.1439121.3321781.91III
total3307993.75232.0219.731791.351199.13
Tab.2  L-EPI of the key industrial sectors in 2009
methodoutput value /(109 CNY)emissions of the study area in 2020
wastewater/(106 t)COD/(103 t)ammonia/(103 t)SO2/(103 t)NOx/(103 t)
grey prediction8730.40641.1020.700.90140.50147.10
trend extrapolation6068.70445.7014.400.6097.70102.30
Tab.3  Industrial pollution emissions of the study area in 2020 based on E-EPI
classland use area in 2020 /hapollutant emissions in the study area in 2020 based on the Master Plan for Dalian Municipality (2009-2020)
wastewater/(106 t)COD/(103 t)ammonia/tSO2/(103 t)NOx/(103 t)
I30833.700.8062.600.800.30
II14398.301.5072.501.504.10
III428114.602.50246.4025.8015.30
total4950126.604.80381.5028.1019.70
Tab.4  Industrial pollution emissions in the study area in 2020 based on L-EPI
Fig.1  Spatial distribution of industrial COD emissions based on (a) E-EPI and (b) L-EPI methods
Fig.2  Comparison of the ranking of industrial environmental performance of (a) wastewater, (b) COD, (c) ammonia, (d) SO, (e) NO, and (f) integrated
1 M?rtberg U M, Balfors B, Knol W C. Landscape ecological assessment: a tool for integrating biodiversity issues in strategic environmental assessment and planning. Journal of Environmental Management , 2007, 82(4): 457–470
doi: 10.1016/j.jenvman.2006.01.005 pmid:16574306
2 Chávez-Zichinelli C A, MacGregor-Fors I, Rohana P T, Valdéz R, Romano M C, Schondube J E. Stress responses of the House Sparrow (Passer domesticus) to different urban land uses. Landscape and Urban Planning , 2010, 98(3-4): 183–189
doi: 10.1016/j.landurbplan.2010.08.001
3 Che X Z, Shang J C, Wang J H. Strategic environmental assessment and its development in China. Environmental Impact Assessment Review , 2002, 22(2): 101–109
doi: 10.1016/S0195-9255(01)00096-8
4 K?rn?v L. Strategic environmental assessment as catalyst of healthier spatial planning: the Danish guidance and practice. Environmental Impact Assessment Review , 2009, 29(1): 60–65
doi: 10.1016/j.eiar.2008.04.003
5 Liu Y, Chen J N, He W, Tong Q, Li W. Application of an uncertainty analysis approach to strategic environmental assessment for urban planning. Environmental Science and Technology , 2010, 44(8): 3136–3141
doi: 10.1021/es902850q pmid:20199065
6 Tao T, Tan Z, He X. Integrating environment into land-use planning through strategic environmental assessment in China: towards legal frameworks and operational procedures. Environmental Impact Assessment Review , 2007, 27(3): 243–265
doi: 10.1016/j.eiar.2006.10.002
7 Therivel R. Strategic environmental assessment of development plans in Great Britain. Environmental Impact Assessment Review , 1998, 18(1): 39–57
doi: 10.1016/S0195-9255(97)00048-6
8 Zhao N, Liu Y, Chen J N. Regional industrial production’s spatial distribution and water pollution control: a plant-level aggregation method for the case of a small region in China. Science of the Total Environment , 2009, 407(17): 4946–4953
doi: 10.1016/j.scitotenv.2009.05.023 pmid:19505711
9 Pauleit S, Duhme F. Assessing the environmental performance of land cover types for urban planning. Landscape and Urban Planning , 2000, 52(1): 1–20
doi: 10.1016/S0169-2046(00)00109-2
10 Peng B, Zhou S.Study on Land-Use Planning. Nanjing: Southeast University Press, 2003
11 Sadler B, Verheem R. Strategic Environmental Assessment: Status, Challenges and Future Direction. The Hague: Ministry of Housing, Spatial Planning and the Environment, the EIA Commission of the Netherlands , 1996
12 Standing Committee of the National People’s Congress. The Law of the People’s Republic of China on Environmental Impact Assessment. Beijing: China Law Press, 2002
13 Stinchcombe K, Gibson R B. Strategic environmental assessment as a means of pursuing sustainability: ten advantages and ten challenges. Journal of Environmental Assessment Policy and Management , 2001, 3(3): 343–372
doi: 10.1142/S1464333201000741
14 Wu C F. Land-Use Planning. Beijing: Geological Press, 2000
15 Yan J.Land-Use Planning in China: Theory, Methodology and Strategy. Beijing: Economic Management Press, 2001
16 Zhu D, Ru J. Strategic environmental assessment in China: motivations, politics, and effectiveness. Journal of Environmental Management , 2008, 88(4): 615–626
doi: 10.1016/j.jenvman.2007.03.040 pmid:17524553
17 Malcolm A, Zhang L, Linninger A A. Optimal regulations for sustainable chemical manufacturing. International Journal of Environment Pollution , 2007, 29(1/2/3): 144–164
doi: 10.1504/IJEP.2007.012801
18 Malcolm A, Zhang L, Linninger A A. Design of environmental regulatory policies for sustainable emission reduction. AlChE Journal , 2006, 52(8): 2792–2804
doi: 10.1002/aic.10861
19 Lee D S, Pacyna J M. An industrial emissions inventory of calcium for Europe. Atmospheric Environment , 1999, 33(11): 1687–1697
doi: 10.1016/S1352-2310(98)00286-6
20 dos Santos Lucon O, Moutinho dos Santos E. The HORUS model—inventory of atmospheric pollutant emissions from industrial combustion in Sao Paulo, Brazil. Environmental Impact Assessment Review , 2005, 25(2): 197–214
doi: 10.1016/j.eiar.2004.06.010
21 Pham T B T, Manomaiphiboon K, Vongmahadlek C. Development of an inventory and temporal allocation profiles of emissions from power plants and industrial facilities in Thailand. Science of the Total Environment , 2008, 397(1-3): 103–118
doi: 10.1016/j.scitotenv.2008.01.066 pmid:18405943
22 Akashi O, Hanaoka T, Matsuoka Y, Kainuma M. A projection for global CO2 emissions from the industrial sector through 2030 based on activity level and technology changes. 2011, Energy, 36(4): 1855–1867
doi: 10.1016/j.energy.2010.08.016
23 Mingsheng C, Yulu G. The mechanism and measures of adjustment of industrial organization structure: the perspective of energy saving and emission reduction. Energy Procedia , 2011, 5: 2562–2567
doi: 10.1016/j.egypro.2011.03.440
24 Hasanuzzaman M, Rahim N A, Saidur R, Kazi S N. Energy savings and emissions reductions for rewinding and replacement of industrial motor. Energy , 2011, 36(1): 233–240
doi: 10.1016/j.energy.2010.10.046
25 Liu L C, Fan Y, Wu G, Wei Y M. Using LMDI method to analyze the change of China’s industrial CO2 emissions from final fuel use: an empirical analysis. Energy Policy , 2007, 35(11): 5892–5900
doi: 10.1016/j.enpol.2007.07.010
26 Henriques J M FDantas F, Schaeffer R. Potential for reduction of CO2 emissions and a low-carbon scenario for the Brazilian industrial sector. Energy Policy , 2010, 38(4): 1946–1961
doi: 10.1016/j.enpol.2009.11.076
27 Zhao M, Tan L R, Zhang W, Ji M, Liu Y, Yu L. Decomposing the influencing factors of industrial carbon emissions in Shanghai using the LMDI method. Energy , 2010, 35(6): 2505–2510
doi: 10.1016/j.energy.2010.02.049
28 Du B, Zheng M H, Tian H, Liu A, Huang Y, Li L, Ba T, Li N, Ren Y, Li Y, Dong S, Su G. Occurrence and characteristics of polybrominated dibenzo-p-dioxins and dibenzofurans in stack gas emissions from industrial thermal processes. Chemosphere , 2010, 80(10): 1227–1233
doi: 10.1016/j.chemosphere.2010.05.044 pmid:20646736
29 Jin G Z, Lee S J, Park H, Lee J E, Shin S K, Chang Y S. Characteristics and emission factors of PCDD/Fs in various industrial wastes in South Korea. Chemosphere , 2009, 75(9): 1226–1231
doi: 10.1016/j.chemosphere.2009.01.070 pmid:19254805
30 Kim K H, Hong Y J, Pal R, Jeon E C, Koo Y S, Sunwoo Y. Investigation of carbonyl compounds in air from various industrial emission sources. Chemosphere , 2008, 70(5): 807–820
doi: 10.1016/j.chemosphere.2007.07.025 pmid:17765288
31 El-Fadel M, Zeinati M, Ghaddar N, Mezher T. Uncertainty in estimating and mitigating industrial related GHG emissions. Energy Policy , 2001, 29(12): 1031–1043
doi: 10.1016/S0301-4215(01)00033-7
32 Bhanarkar A D, Rao P S, Gajghate D G, Nema P. Inventory of SO2, PM and toxic metals emissions from industrial sources in Greater Mumbai, India. Atmospheric Environment , 2005, 39(21): 3851–3864
doi: 10.1016/j.atmosenv.2005.02.052
33 Li Y F, Zhang Y J, Cao G L, Liu J H, Barrie L A. Distribution of seasonal SO2 emissions from fuel combustion and industrial activities in Shanxi province, China, with 1/6°×1/4° longitude/latitude resolution. Atmospheric Environment , 1999, 33(2): 257–265
doi: 10.1016/S1352-2310(98)00157-5
34 Tolmasquim M T, Cohen C, Szklo A S. CO2 emissions in the Brazilian industrial sector according to the integrated energy planning model (IEPM). Energy Policy , 2001, 29(8): 641–651
doi: 10.1016/S0301-4215(00)00141-5
35 Ministry of Housing and Urban-Rural Development of the Republic of China. The Guidelines for Urban Planning Drawing Up. Beijing: China Legal Publishing House, 2005
36 Standing Committee of the National People's Congress. Urban and Rural Planning Law of the People’s Republic of China. Beijing: China Legal Publishing House, 2007
37 China’s Ministry of Construction. GB50137-2011: Standards for Urban Land Use Classification and Planning Construction. Beijing: China Building Industry Press, 2011
38 National Bureau of Statistics of China. GB/T4754-2002: Industrial Classification and Codes for National Economic Activities. Beijing: China Standard Press, 2002
39 Li D C, Yeh C W, Chang C J. An improved grey-based approach for early manufacturing data forecasting. Computer and Industrial Engineering , 2009, 57(4): 1161–1167
doi: 10.1016/j.cie.2009.05.005
40 Lin C T, Yang S Y. Forecast of the output value of Taiwan’s optoelectronics industry using the grey forecasting model. Technological Forecasting and Social Change , 2003, 70(2): 177–186
doi: 10.1016/S0040-1625(01)00191-3
41 Mao M, Chirwa E C. Application of grey model GM (1,1) to vehicle fatality risk estimation. Technological Forecasting and Social Change , 2006, 73(5): 588–605
doi: 10.1016/j.techfore.2004.08.004
42 Xie D, Liu Y, Chen J N. Mapping urban environmental noise: a land use regression method. Environmental Science and Technology , 2011, 45(17): 7358–7364
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