The impacts of economic restructuring and technology upgrade on air quality and human health in Beijing-Tianjin-Hebei region in China

doi:10.1007/s11783-019-1155-y

Front. Environ. Sci. Eng.

2019, Vol. 13

Issue (5) : 70 https://doi.org/10.1007/s11783-019-1155-y

RESEARCH ARTICLE

The impacts of economic restructuring and technology upgrade on air quality and human health in Beijing-Tianjin-Hebei region in China

Chao Liu¹, Hancheng Dai²(

), Lin Zhang³, Changchun Feng¹(

)

¹. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
². College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
³. Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China

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Abstract

Impacts of industrial restructuring and upgrade on air quality & health are assessed.

An integrated approach combining different models is used for the assessment.

Industrial technology upgrading is more effective than economic restructuring.

Ozone is much more difficult to mitigate than PM_2.5.

In this study, we have analyzed possible policy options to improve the air quality in an industrialized region—Beijing, Tianjin and Hebei (BTH) in China. A comprehensive model framework integrating GAINS-China, GEOS-Chem, and IMED/HEL is established to investigate the impacts of various policies on air pollution and health effects. The model establishes a data interface between economic input/output data and the emission inventory of atmospheric pollutants in the BTH region. Based on in-depth analyses of pollutant emission standards, industrial structure, pollution-intensive industries, and emission intensities in BTH and Pearl River Delta, several scenarios are constructed to explore the effectiveness of policy pathways in improving air quality in the BTH region. These scenarios include two categories: the category of “Industrial Technology Upgrade Policy” scenarios that focuses on reducing the emission intensity of industries vs. that of “Industrial Structure Adjustment Policy” scenarios that focuses on adjusting the proportion of industrial value-added. Our results show that the policy path of industrial technology upgrading can be effective and feasible, while economic structure adjustment shows complex and mixed effectiveness. We also find that the proposed policies and measures will be efficient to reduce pollution of primary pollutants and fine particles, but may not effectively mitigate ambient ozone pollution. Ozone pollution is projected to become increasingly severe in BTH, placing a challenge to pollution mitigation strategies that requires further adjustments to address it.

Keywords Economic restructuring Cleaner production Ambient air pollution Health benefits IMED model

Corresponding Author(s): Hancheng Dai,Changchun Feng

Issue Date: 07 August 2019

Cite this article:

Chao Liu,Hancheng Dai,Lin Zhang, et al. The impacts of economic restructuring and technology upgrade on air quality and human health in Beijing-Tianjin-Hebei region in China[J]. Front. Environ. Sci. Eng., 2019, 13(5): 70.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-019-1155-y
https://academic.hep.com.cn/fese/EN/Y2019/V13/I5/70

Fig.1 The schematic diagram of the established model framework.

Generic Sectors (Abbrev.)	GAINS Sectors	GDP Sectors
Mining (MIN)	Briquettes production Hard coal mining Non-ferrous metals Primary aluminum	Coal, oil, natural gas production Mining of metals and no-metals
Food (FOD)	Coke oven Cooking stoves Meat frying, food preparation, BBQ	Hotel and Restaurant
Tertiary industry (TEI)	Fireworks Other non-road machinery	Science and arts Education Banking Hospital Market Etc
Non-Metal production (NME)	Agglomeration plant – pellets Agglomeration plant – sinter Agglomeration plant – sinter (fugitive) Brick production Cement production Glass production (flat, blown, container glass) Lime production	Non-Metal production
Service (SER)	Heating stoves Residential-commercial Single house boilers (<50 kW) – manual Small industrial and business facilities – fugitive	Residential related affairs
Chemical industry (CHE)	Chemical industry (boilers) Fuel conversion – combustion Fuel conversion (pulverized bed boiler) Refineries Transformation sector (boilers)	Chemical production Refinery and coking
Construction (CON)	Construction activities Construction machinery	Construction
Traffic (TRA)	2-stroke engines (non-road) Aviation – LTO Buses Cars Heavy-duty vehicles Light duty vehicles Mopeds Motorcycles Railways Storage & handling of agricultural crops Storage & handling of coal Storage & handling of iron ore Storage & handling of N,P,K fertilizers Storage & handling of other industrial bulk products	Transport Post Storage
Metal Production (MET)	Aluminum production – secondary Basic oxygen furnace Cast iron (gray iron foundries) Cast iron (gray iron foundries) (fugitive) Electric arc furnace Pig iron, blast furnace Pig iron, blast furnace (fugitive)	Metal production Smelting and rolling of Metal products
Energy (ENE)	Diesel generator sets Modern power plants (coal: ultra and supercritical; gas: CCGT) Modern power plants (coal: ultra and supercritical; gas: CCGT) with CCS Open hearth furnace Three-stone stove	Production and supply of gases and water
Electricity (ELE)	Power & district heat plants – existing (excl. coal) Power & district heat plants – existing coal (<50 MWth) Power & district heat plants – existing coal (>50 MWth) Power & district heat plants – IGCC Power & district heat plants – IGCC with CCS Power & district heat plants – new (excl. coal) Power & district heat plants – new coal (>50 MWth)	Production and supply of power and heat
Agriculture (AGR)	Agriculture	Agriculture
Other industry (ETC)	Industrial furnaces Industry: Other combustion, pulverized Medium boilers (<1 MW) – manual Medium boilers (<50 MW) – automatic Other industry (boilers; liquid and gaseous fuels) Other industry (large coal boilers;>50 MWth) Other industry (small coal boilers;<50 MWth) Trash burning	Repair and Production of device, machine, electrical equipment, instruments, meters Recycle of the waste product
Light industry (LIG)	Cigarette smoking Paper & pulp (boilers) Paper pulp mills	Cigarette, paper, textile and wood manufacture

Tab.1 The set-up of generic sectors to synthesize the GAINS and GDP sectors

Fig.2 The variation of the emission intensity of the air pollutants in the Beijing-Tianjin-Hebei region and the Guangdong Province (2002–2012): (a) CO; (b) NO_x; (c) SO₂; (d) PM_2.5; (e) VOC.

Fig.3 The economic structure of (a) Beijing; (b) Tianjin; (c) Heibei.

Fig.4 The annual emissions of (a) CO, (b) NO_x, (c) SO₂, (d) PM_2.5, and (e) VOC under Base scenario in 2012 in Beijing, Tianjin and Hebei calculated by GAINS model.

Fig.5 Sectoral emissions of (a) CO, (b) NO_x, (c) SO₂, (d) PM_2.5, and (e) VOC under different scenarios in Hebei.

Fig.6 The emission intensities (EIs) of (a) CO, (b) NO_x, (c) SO₂, (d) PM_2.5, and (e) VOC for different sectors under two policy scenarios in Hebei.

Fig.7 Comparative analysis of the emissions of (a) CO, (b) NO_x, (c) SO₂, (d) PM_2.5and (e) VOCs between Scenario A and Scenario D with the emission reduction factor (F) set from 0.1 to 0.7. The cross over points for Scenario D and A of the emissions of CO, NO_x, and VOCs represent the reduction factor (F) equals to 0.5.

Fig.8 GEOS-Chem model simulated surface PM_2.5 concentrations in the Base scenario averaged for January (top panels) and July (bottom panels) in 2012 with surface measurements (circles) over-plotted. The right four columns show simulated changes in PM_2.5 in the four policy scenarios relative to Base. Numbers inset are mean values over the BTH region: (a) Base case for January; (b) Scenario-A for January; (c) Scenario-B for January; (d) Scenario-C for January; (e) Scenario-D for January; (f) Base case for July; (g) Scenario-A for July; (h) Scenario-B for July; (i) Scenario-C for July; (j) Scenario-D for July.

Fig.9 The same as Fig. 8, but for surface O₃ concentration: (a) Base case for January; (b) Scenario-A for January; (c) Scenario-B for January; (d) Scenario-C for January; (e) Scenario-D for January; (f) Base case for July; (g) Scenario-A for July; (h) Scenario-B for July; (i) Scenario-C for July; (j) Scenario-D for July.

Fig.10 Health impact of PM_2.5 and O₃ pollution in different policy scenarios: (a, c) PM_2.5 mortality; (b, d) O₃ mortality.

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