Achieving air pollutant emission reduction targets with minimum abatement costs: An enterprise-level allocation method with constraints of fairness and feasibility

doi:10.1007/s11783-021-1459-6

Front. Environ. Sci. Eng.

2022, Vol. 16

Issue (2) : 25 https://doi.org/10.1007/s11783-021-1459-6

RESEARCH ARTICLE

Achieving air pollutant emission reduction targets with minimum abatement costs: An enterprise-level allocation method with constraints of fairness and feasibility

Yanfei Chen¹, Ji Zheng¹, Miao Chang¹(

), Qing Chen¹(

), Cuicui Xiao²

¹. School of Environment, Tsinghua University, Beijing 100084, China
². School of Humanities and Social Sciences, University of Science and Technology Beijing, Beijing 100083, China

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Abstract

• Quantification of efficiency and fairness of abatement allocation are optimized.

• Allocation results are refined to the different abatement measures of enterprises.

• Optimized allocation results reduce abatement costs and tap the abatement space.

• Abatement suggestions are given to enterprises with different abatement quotas.

For achieving air pollutant emission reduction targets, total pollutant amount control is being continuously promoted in China. However, the traditional pattern of pollutant emission reduction allocation regardless of economic cost often results in unreasonable emission reduction pathways, and industrial enterprises as the main implementers have to pay excessively high costs. Therefore, this study adopted economic efficiency as its main consideration, used specific emission reduction measures (ERMs) of industrial enterprises as minimum allocation units, and constructed an enterprise-level pollutant emission reduction allocation (EPERA) model with minimization of the total abatement cost (TAC) as the objective function, and fairness and feasibility as constraints for emission reduction allocation. Taking City M in China as an example, the EPERA model was used to construct a Pareto optimal frontier and obtain the optimal trade-off result. Results showed that under basic and strict emission reduction regulations, the TAC of the optimal trade-off point was reduced by 46.40% and 45.77%, respectively, in comparison with that achieved when only considering fairness, and the Gini coefficient was 0.26 and 0.31, respectively. The abatement target was attained with controllable cost and relatively fair and reasonable allocation. In addition, enterprises allocated different emission reduction quotas under different ERMs had specific characteristics that required targeted optimization of technology and equipment to enable them to achieve optimal emission reduction effects for the same abatement cost.

Keywords Pollutant emission reduction allocation Emission reduction measures Total abatement cost Economic efficiency Abatement space

Corresponding Author(s): Miao Chang,Qing Chen

Issue Date: 13 July 2021

Cite this article:

Yanfei Chen,Ji Zheng,Miao Chang, et al. Achieving air pollutant emission reduction targets with minimum abatement costs: An enterprise-level allocation method with constraints of fairness and feasibility[J]. Front. Environ. Sci. Eng., 2022, 16(2): 25.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-021-1459-6
https://academic.hep.com.cn/fese/EN/Y2022/V16/I2/25

Fig.1 GCAC-TAC scatter plot (a) under basic emission reduction regulation and (b) strict emission reduction regulation.

Scenarios		TAC (million RMB)	GCAC	Emission reduction in PEER (t)	Emission reduction in ESA (t)
Basic regulation	$λ$ = 0	68.21	0	7087	4685
	$λ$ = 0.37	36.56	0.26	6452	5083
	$λ$ = 1	28.60	0.53	8254	3281
Strict regulation	$λ$ = 0	89.46	0	9294	6144
	$λ$ = 0.47	48.52	0.31	8255	6873
	$λ$ = 1	43.97	0.51	9606	5522

Tab.1 Results of optimal trade-off, considering only fairness and only economic efficiency

Fig.2 Planned emission reduction allocation of ERMs at the industry statistics dimension under (a) basic and (b) strict emission reduction regulation. (Note 1: Listed are the top seven industrial-level ERMs, which accounted for 97.94% (97.68%) of total planned emission reduction under basic (strict) emission reduction regulation. Note 2: The meaning of the abscissa “x-x”: before the “-” is the abbreviation of the industries and after the “-” is the abbreviation of the emission reduction measures (e.g., ME-ESA means energy structure adjustment in Manufacture of Electricity industry).

Fig.3 (a) Unit abatement cost and (b) Abatement contribution coefficient of ERMs at the industry statistics dimension.

Tab.2 Specific allocation result of industrial enterprises under strict emission reduction regulation

Fig.4 Enterprise division from the regional perspective (ME: Manufacture of Electricity; SPFM: Smelting & Pressing of Ferrous Metals; MNMG: Manufacture of Non-metallic Mineral Goods; MPPP: Manufacture of Paper & Paper Products; PF: Processing of Foods; PPCF: Processing of Petroleum, Coking, &Fuel; MM: Manufacture of Medicines; MA: Manufacture of Automobile).

Fig.5 Enterprise division from the individual perspective.

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