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京津冀地区钢铁行业典型减污降碳技术协同效益分析

Analysis of the synergistic benefits of typical technologies for pollution reduction and carbon reduction in the iron and steel industry in the Beijing-Tianjin-Hebei region.

作者信息

Wen Wei, Deng Zifan, Ma Xin, Xing Yi, Pan Chongchao, Liu Yusong, Zhang Han, Tharaka W A N D, Hua Tongxin, Shen Liyao

机构信息

School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China.

CMA Earth System Modeling and Prediction Centre (CEMC), Beijing, 100081, China.

出版信息

Sci Rep. 2024 May 30;14(1):12413. doi: 10.1038/s41598-024-63338-8.

DOI:10.1038/s41598-024-63338-8
PMID:38816563
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11139909/
Abstract

With its high energy consumption and pollutant emissions, the iron and steel industry is a significant source of air pollution and carbon emissions in the Beijing-Tianjin-Hebei (BTH) region. To improve air quality and reduce greenhouse gas emissions, a series of policies involving ultra-low emission, synergistic reduction of pollution, and carbon application have been implemented in the region. This study has assessed air pollutant and CO emission patterns in the iron and steel industry of the region by employing co-control effects coordinate system, marginal abatement cost curve, and numerical modeling, along with the synergistic benefits of typical technologies. The results have demonstrated that: (1) the intensive production activities pertinent to iron and steel enterprises has contributed greatly to the emission in Tangshan and Handan, where the sintering process is the main source of SO, NOx, PM, and CO, accounting for 64.86%, 55.15%, 29.98%, and 46.43% of the total emissions, respectively. (2) Among the typical pollution control and reduction measures, industrial restructuring and adjustment of the energy-resource structure have led to the greatest effects on emission reduction. Technologies exhibiting great potential in emission reduction and high-cost efficiency such as Blast Furnace Top Gas Recovery Turbine Unit (TRT) need to be promoted. (3) In Tangshan city with the highest level of steel production, the iron and steel production activities contributed to the concentration of 30.51% of PM, 50.67% of SO, and 42.54% of NO during the non-heating period. During the heating period, pollutants pertinent to the combustion of fossil energy for heating have increased, while iron and steel induced emissions have decreased to 23.7%, 34.32%, and 29.13%, respectively. By 2030, it is speculated that the contribution of the iron and steel industry to air quality will be significantly decreased as result of successful implementation of ultra-low emission policies and typical synergistic reduction technologies.

摘要

钢铁行业能源消耗高、污染物排放量大,是京津冀地区空气污染和碳排放的重要来源。为改善空气质量、减少温室气体排放,该地区实施了一系列涉及超低排放、污染协同减排和碳应用的政策。本研究通过采用协同控制效应坐标系、边际减排成本曲线和数值模拟,以及典型技术的协同效益,评估了该地区钢铁行业的空气污染物和一氧化碳排放模式。结果表明:(1)钢铁企业的密集生产活动对唐山和邯郸的排放贡献巨大,其中烧结过程是二氧化硫、氮氧化物、颗粒物和一氧化碳的主要来源,分别占总排放量的64.86%、55.15%、29.98%和46.43%。(2)在典型的污染控制和减排措施中,产业结构调整和能源资源结构调整对减排的影响最大。需要推广诸如高炉煤气余压透平发电装置(TRT)等具有巨大减排潜力和高成本效益的技术。(3)在钢铁产量最高的唐山市,钢铁生产活动在非供暖期对颗粒物浓度的贡献为30.51%,对二氧化硫浓度的贡献为50.67%,对氮氧化物浓度的贡献为42.54%。在供暖期,用于供暖的化石能源燃烧产生的污染物增加,而钢铁行业产生的排放分别降至23.7%、34.32%和29.13%。据推测,到2030年,由于超低排放政策和典型协同减排技术的成功实施,钢铁行业对空气质量的贡献将显著降低。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad90/11139909/a184f9926b1c/41598_2024_63338_Fig12_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad90/11139909/a184f9926b1c/41598_2024_63338_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad90/11139909/6913df48295b/41598_2024_63338_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad90/11139909/8848056a4d48/41598_2024_63338_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad90/11139909/27f7a6f78d31/41598_2024_63338_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad90/11139909/4b3d211edd0a/41598_2024_63338_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad90/11139909/0099cb9f3eb8/41598_2024_63338_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad90/11139909/02dd4a06bc3a/41598_2024_63338_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad90/11139909/0f0ef5497c76/41598_2024_63338_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad90/11139909/a184f9926b1c/41598_2024_63338_Fig12_HTML.jpg

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