安阳市典型工业源PM_(2.5)排放特征及减排潜力估算
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摘要
为探究安阳市PM_(2. 5)排放特征,通过现场调查对安阳市工业源活动水平和控制技术信息进行收集,采用合理的估算方法、排放因子,建立了安阳市2016年工业源PM_(2. 5)排放清单,并利用地理信息系统(GIS)技术进行空间分配.基于典型行业超低排放改造和煤炭压减要求设置3种情景,估算了2020年安阳市工业源PM_(2. 5)减排潜力.结果表明,安阳市2016年工业源PM_(2. 5)排放总量为81 071. 13 t;有色冶金、钢铁和建材行业是安阳市PM_(2. 5)主要贡献源,分别占总排放量的45. 43%、25. 74%和18. 00%;安阳市各乡镇排放差异突出,PM_(2. 5)排放主要集中在市区及林州市和安阳县,且以安阳市区排放量最为突出,而安阳市区的4个辖区的排放强度差异更为巨大;通过设定不同控制情景,估算2020年安阳市PM_(2. 5)减排潜力分别为398. 72、11 623. 87和14 072. 27 t,分别占2016年工业源排放总量的0. 49%、14. 34%和17. 22%.可见,安阳市PM_(2. 5)具有较大减排潜力,超低排放改造和煤炭压减对安阳市PM_(2. 5)减排具有重要意义.
To investigate the characteristics of PM_(2. 5) emissions in Anyang,the PM_(2. 5) emission inventory from industrial sources of Anyang in 2016 was established based on reasonable estimation method and emission factor. The spatial distribution analysis was carried out using Geographic Information System( GIS) technology. Based on the industry's typical ultra-low emission transformation and coal pressure reduction requirements,three scenarios were set to estimate the PM_(2. 5) emission reduction potential of industrial sources from Anyang in 2020. The results show that the total PM_(2. 5) emissions from industrial sources in Anyang was 81 071. 13 t in2016. Non-ferrous metallurgy,iron and steel,and building materials industries were the main contributing sources,accounting for45. 43%,25. 74%,and 18. 00% of the total emissions,respectively. The emission differences between towns and within Anyang were outstanding. The PM_(2. 5) emissions were mainly concentrated in urban areas,Linzhou City,and Anyang County. The emissions in Anyang City were most prominent,while the emission intensity differences between the four jurisdictions of Anyang City were even greater. In the three different control scenarios,the potential for PM_(2. 5) emission reduction in Anyang in 2020 was estimated to be398. 72,11 623. 87,and 14 072. 27 t,accounting for 0. 49%,14. 34%,and 17. 22% of the total industrial source emissions in2016,respectively. It can be concluded that Anyang has a great potential for PM_(2. 5) emission reduction. In addition,ultra-low emission reform and coal pressure reduction can be of great significance for PM_(2. 5) emission reduction in Anyang.
To investigate the characteristics of PM_(2. 5) emissions in Anyang,the PM_(2. 5) emission inventory from industrial sources of Anyang in 2016 was established based on reasonable estimation method and emission factor. The spatial distribution analysis was carried out using Geographic Information System( GIS) technology. Based on the industry's typical ultra-low emission transformation and coal pressure reduction requirements,three scenarios were set to estimate the PM_(2. 5) emission reduction potential of industrial sources from Anyang in 2020. The results show that the total PM_(2. 5) emissions from industrial sources in Anyang was 81 071. 13 t in2016. Non-ferrous metallurgy,iron and steel,and building materials industries were the main contributing sources,accounting for45. 43%,25. 74%,and 18. 00% of the total emissions,respectively. The emission differences between towns and within Anyang were outstanding. The PM_(2. 5) emissions were mainly concentrated in urban areas,Linzhou City,and Anyang County. The emissions in Anyang City were most prominent,while the emission intensity differences between the four jurisdictions of Anyang City were even greater. In the three different control scenarios,the potential for PM_(2. 5) emission reduction in Anyang in 2020 was estimated to be398. 72,11 623. 87,and 14 072. 27 t,accounting for 0. 49%,14. 34%,and 17. 22% of the total industrial source emissions in2016,respectively. It can be concluded that Anyang has a great potential for PM_(2. 5) emission reduction. In addition,ultra-low emission reform and coal pressure reduction can be of great significance for PM_(2. 5) emission reduction in Anyang.
引文
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[3]Valavanidis A,Fiotakis K,Vlachogianni T.Airborne particulate matter and human health:toxicological assessment and importance of size and composition of particles for oxidative damage and carcinogenic mechanisms[J].Journal of Environmental Science and Health,Part C,2008,26(4):339-362.
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[5]段振华,高绪芳,杜慧兰,等.成都市空气PM2.5浓度与呼吸系统疾病门诊人次的时间序列研究[J].现代预防医学,2015,42(2):611-614.Duan Z H,Gao X F,Du H L,et al.Analysis on the relationship between PM2.5concentration in ambient air and hospital outpatients with respiratory diseases in Chengdu[J].Modern Preventive Medicine,2015,42(4):611-614.
[6]国际环保组织绿色和平与上海闵行区青悦环保信息技术服务中心.2016年中国366个城市PM2.5浓度排名[EB/OL].http://www.greenpeace.org.cn/270-cities-need-air-controlregulation/,2017-01-17.
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[11]刘松华,周静,谭译,等.苏州市大气细颗粒物(PM2.5)工业源排放清单[J].环境科学学报,2017,37(2):453-459.Liu S H,Zhou J,Tan Y,et al.Emission inventory of atmospheric fine particles(PM2.5)from industrial sources in Suzhou City[J].Acta Scientiae Circumstantiae,2017,37(2):453-459.
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[21]王临清,朱法华,赵秀勇.燃煤电厂超低排放的减排潜力及其PM2.5环境效益[J].中国电力,2014,47(11):150-154.Wang L Q,Zhu F H,Zhao X Y.Potential capabilities of pollutant reduction and environmental benefits from ultra-low emissions of coal-fired power plants[J].Electric Power,2014,47(11):150-154.
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[23]薛文博,王金南,杨金田,等.国内外空气质量模型研究进展[J].环境与可持续发展,2013,38(3):14-20.Xue W B,Wang J N,Yang J T,et al.Domestic and foreign research progress of air quality model[J].Environment and Sustainable Development,2013,38(3):14-20.
[24]马洁云,易红宏,唐晓龙,等.空气质量模型的发展及研究进展[J].上海环境科学,2014,33(1):17-23.Ma J Y,Yi H H,Tang X L,et al.Development and research progress of the air quality modelling[J].Shanghai Environmental Sciences,2014,33(1):17-23.
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