基于SOA转化机制的沧州市重点企业秋冬季大气污染模拟
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摘要
基于沧州市2016年排放清单筛选出120家重点企业,采用重新编译代码后的CALPUFF空气质量模型,模拟了2017年秋冬季不同程度污染天气下120家重点企业PM_(2.5)、PM_(10)、SO_2、NO_2及二次生成硫酸盐、硝酸盐、二次有机气溶胶(SOA)的污染情况.结果表明,120家重点企业PM_(2.5)、PM_(10)、SO_2和NO_2秋冬季平均模拟浓度占平均观测浓度的比例分别为:3. 3%、5. 7%、5. 6%和2. 9%;一次排放的PM_(10)主要集中在沧州市西南部和东南部,二次转化的SOA、硫酸盐和硝酸盐主要集中在主城区和东南部; PM_(2.5)中SOA平均占比约为27. 3%,重污染时段比例上升为29. 0%; PM_(2.5)中烷烃气溶胶、甲苯气溶胶、二甲苯气溶胶和多环芳烃(PAH)气溶胶占比分别为:12. 1%、6. 0%、7. 0%和2. 2%. 120家重点企业精细化模拟结果显示,重污染天气以上120家重点企业的PM_(2.5)贡献浓度为3. 02μg·m~(-3),占沧州市"三年作战计划"要求2018年下降浓度(6. 00μg·m~(-3))的50%; PM_(2.5)浓度贡献较大的企业包括某石油化工股份有限公司沧州分公司(0. 41μg·m~(-3))、某碳素有限公司(0. 29μg·m~(-3))、某石化股份有限公司聚海分公司(0. 26μg·m~(-3))、沧州某肥业有限公司(0. 23μg·m~(-3))、沧州某大化有限责任公司(0. 19μg·m~(-3))等,主要位于新华区、沧县和渤海新区.本研究可为开展秋冬季每一家重点企业的错峰生产和应急减排提供科学依据.
120 main industrial installations were screened based on the emissions inventory of 2016 in Cangzhou City,and the air pollution effect of PM_(2.5),PM_(10),SO_2,NO_2,sulfates,nitrates,and secondary organic aerosol( SOA) was simulated for 2017 autumnwinter season for different levels of pollution using the CALPUFF model after code recompilation. The results showed that the ratios of the modelled and measured concentrations of PM_(2.5),PM_(10),SO_2,and NO_2 were 3. 3%,5. 7%,5. 6%,and 2. 9%,respectively. The areas most affected by pollution from primary PM_(10) were the southwest and southeast part of Cangzhou,while sulfate,nitrate,and SOA pollution mainly affected the southeast part. The proportion of SOA in the PM_(2.5) was around 27. 3%,and rose to 29. 0% during heavily polluted periods. The aerosols of alkenes,tolune,xylene,and PAH in PM_(2.5) accouted for 12. 1%,6. 0%,7. 0%,and 2. 2% of the total aerosols respectively. The result of the simulation of individual enterprises showed that their total contribution to PM_(2.5) during heavily polluted periods was 3. 02 μg·m~(-3),accounting for 50% of the requirements in the"Three-year Plan"for Cangzhou City( 6. 00μg·m~(-3)). The top 5 contributors were ① Petrochemical industry in Cangzhou( 0. 41 μg·m~(-3)),② Carbon Co. Ltd.( 0. 29μg·m~(-3)),③ Petrochemical industry in Juhai( 0. 26 μg·m~(-3)),④ Fertilizer Company( 0. 23 μg·m~(-3)),⑤ Dahua Co. Ltd.( 0. 19μg·m~(-3)). These industrial installations were mainly located in Xinhua District,Cangxian,and Bohai New District. This research can provide a scientific ground for production restrictions and limitations and emissions reduction of each industry during heavily polluted periods.
120 main industrial installations were screened based on the emissions inventory of 2016 in Cangzhou City,and the air pollution effect of PM_(2.5),PM_(10),SO_2,NO_2,sulfates,nitrates,and secondary organic aerosol( SOA) was simulated for 2017 autumnwinter season for different levels of pollution using the CALPUFF model after code recompilation. The results showed that the ratios of the modelled and measured concentrations of PM_(2.5),PM_(10),SO_2,and NO_2 were 3. 3%,5. 7%,5. 6%,and 2. 9%,respectively. The areas most affected by pollution from primary PM_(10) were the southwest and southeast part of Cangzhou,while sulfate,nitrate,and SOA pollution mainly affected the southeast part. The proportion of SOA in the PM_(2.5) was around 27. 3%,and rose to 29. 0% during heavily polluted periods. The aerosols of alkenes,tolune,xylene,and PAH in PM_(2.5) accouted for 12. 1%,6. 0%,7. 0%,and 2. 2% of the total aerosols respectively. The result of the simulation of individual enterprises showed that their total contribution to PM_(2.5) during heavily polluted periods was 3. 02 μg·m~(-3),accounting for 50% of the requirements in the"Three-year Plan"for Cangzhou City( 6. 00μg·m~(-3)). The top 5 contributors were ① Petrochemical industry in Cangzhou( 0. 41 μg·m~(-3)),② Carbon Co. Ltd.( 0. 29μg·m~(-3)),③ Petrochemical industry in Juhai( 0. 26 μg·m~(-3)),④ Fertilizer Company( 0. 23 μg·m~(-3)),⑤ Dahua Co. Ltd.( 0. 19μg·m~(-3)). These industrial installations were mainly located in Xinhua District,Cangxian,and Bohai New District. This research can provide a scientific ground for production restrictions and limitations and emissions reduction of each industry during heavily polluted periods.
引文
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[21]伯鑫. CALPUFF模型技术方法与应用[M].北京:中国环境出版社,2016.
[22]伯鑫,丁峰,徐鹤,等.大气扩散CALPUFF模型技术综述[J].环境监测管理与技术,2009,21(3):9-13,47.Bo X,Ding F,Xu H,et al. Review of atmospheric diffusion spersion model CALPUFF technology[J]. The Administration and Technique of Environmental Monitoring,2009,21(3):9-13,47.
[23]伯鑫,马继,李时蓓,等. CALPUFF大气模型多线程计算及业务系统[A]. 2016中国环境科学学会学术年会论文集(第二卷)[C].海口:中国环境科学学会,2016.
[24] Tartakovsky D,Broday D M,Stern E. Evaluation of AERMOD and CALPUFF for predicting ambient concentrations of total suspended particulate matter(TSP)emissions from a quarry in complex terrain[J]. Environmental Pollution,2013,179:138-145.
[25] Rood A S. Performance evaluation of AERMOD,CALPUFF,and legacy air dispersion models using the Winter Validation Tracer Study dataset[J]. Atmospheric Environment,2014,89:707-720.
[26] Macintosh D L,Stewart J H,Myatt T A,et al. Use of CALPUFF for exposure assessment in a near-field,complex terrain setting[J]. Atmospheric Environment,2010,44(2):262-270.
[27]王刚,吴成志.美国大气许可中PM2. 5评估方法及对中国的启示[J].环境影响评价,2015,37(6):48-51,78.Wang G,Wu C Z. Overview of PM2. 5assessment methods in US air permitting and reference to China thereof[J]. Environmental Impact Assessment,2015,37(6):48-51,78.
[28]伯鑫,王刚,田军,等. AERMOD模型地表参数标准化集成系统研究[J].中国环境科学,2015,35(9):2570-2575.Bo X,Wang G,Tian J,et al. Standard systems of surface parameters in AERMOD[J]. China Environmental Science,2015,35(9):2570-2575.
[29]田谧.京津冀地区霾污染过程大气PM2. 5及前体物变化特征研究[D].北京:北京化工大学,2013.Tian M. Characteristics of PM2. 5and its precursor pollutants during haze in Beijing-Tianjin-Hebei region[D]. Beijing:Beijing University of Chemical Technology,2013.
[30]伯鑫,吴忠祥,王刚,等. CALPUFF模式的标准化应用技术研究[J].环境科学与技术,2014,37(120):530-534.
[31]虢俊龙.石家庄霾污染过程大气颗粒物化学组分分析及来源解析[D].北京:北京化工大学,2015.Guo J L. Study of chemical composition features and sources apportionment of atmospheric particulate matter during haze in Shijiazhuang[D]. Beijing:Beijing University of Chemical Technology,2015.
[32]杨孝文,周颖,程水源,等.北京冬季一次重污染过程的污染特征及成因分析[J].中国环境科学,2016,36(3):679-686.Yang X W,Zhou Y,Cheng S Y,et al. Characteristics and formation mechanism of a heavy winter air pollution event in Beijing[J]. China Environmental Science,2016,36(3):679-686.
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[2] Bressi M,Sciare J,Ghersi V,et al. Sources and geographical origins of fine aerosols in Paris(France)[J]. Atmospheric Chemistry and Physics,2014,14(16):8813-8839.
[3] Waked A,Favez O,Alleman L Y,et al. Source apportionment of PM10in a north-western Europe regional urban background site(Lens,France)using positive matrix factorization and including primary biogenic emissions[J]. Atmospheric Chemistry and Physics,2014,14(7):3325-3346.
[4] Zhao M F,Qiao T,Huang Z S,et al. Comparison of ionic and carbonaceous compositions of PM2. 5in 2009 and 2012 in Shanghai,China[J]. Science of the Total Environment,2015,536:695-703.
[5]唐孝炎,张远航,邵敏.大气环境化学[M].(第二版).北京:高等教育出版社,2006.Tang X Y,Zhang Y H,Shao M. Atmosphere environmental chemistry(2nd ed.)[M]. Beijing:Higher Education Press,2006.
[6] Liu T Y,Li Z J,Chan M N,et al. Formation of secondary organic aerosols from gas-phase emissions of heated cooking oils[J]. Atmospheric Chemistry and Physics,2017,17(12):7333-7344.
[7] Tuet W Y,Chen Y L,Fok S,et al. Inflammatory responses to secondary organic aerosols(SOA)generated from biogenic and anthropogenic precursors[J]. Atmospheric Chemistry and Physics,2017,17(18):11423-11440.
[8]陈文泰,邵敏,袁斌,等.大气中挥发性有机物(VOCs)对二次有机气溶胶(SOA)生成贡献的参数化估算[J].环境科学学报,2013,33(1):163-172.Chen W T, Shao M, Yuan B, et al. Parameterization of contribution to secondary organic aerosol(SOA)formation from ambient volatile organic compounds(VOCs)[J]. Acta Scientiae Circumstantiae,2013,33(1):163-172.
[9]王永宏,胡波,王跃思,等.沧州市大气污染特征观测研究[J].环境科学,2012,33(11):3705-3711.Wang Y H, Hu B, Wang Y S, et al. Characteristics of atmospheric pollutants in Cangzhou[J]. Environmental Science,2012,33(11):3705-3711.
[10]叶霞,王剑,刘伟,等.沧州市郊大气PM10浓度变化特征分析[J].环境化学,2013,32(8):1588-1589.
[11]段菁春,周雪明,张鹤丰,等.沧州市春季NMHCs空间分布特征[J].环境科学,2017,38(5):1769-1774.Duan J C,Zhou X M,Zhang H F,et al. Spatial distribution characteristics of NMHCs in Spring in Cangzhou City[J].Environmental Science,2017,38(5):1769-1774.
[12]任妙春,宋博,王琼.沧州市冬季一次大范围强浓雾天气过程分析[A].见:第31届中国气象学会年会S11第三届城市气象论坛——城市与环境气象[C].北京:中国气象学会,2014.
[13] Lee H D, Yoo J W, Kang M K, et al. Evaluation of concentrations and source contribution of PM10and SO2emitted from industrial complexes in Ulsan,Korea:Interfacing of the WRF-CALPUFF modeling tools[J]. Atmospheric Pollution Research,2014,5(4):664-676.
[14] Holnicki P,Kaluszko A,Trapp W. An urban scale application and validation of the CALPUFF model[J]. Atmospheric Pollution Research,2016,7(3):393-402.
[15] Ghannam K, El-Fadel M. Emissions characterization and regulatory compliance at an industrial complex:An integrated MM5/CALPUFF approach[J]. Atmospheric Environment,2013,69:156-169.
[16]孙博飞,伯鑫,张尚宣,等.钢厂烧结机烟气排放对土壤二英浓度的影响[J].中国环境科学,2017,37(11):4222-4229.Sun B F,Bo X,Zhang S X,et al. Effect of exhaust gas from sintering machines on the concentration of dioxin in soil around a steel plant[J]. China Environmental Science,2017,37(11):4222-4229.
[17]伯鑫,王刚,温柔,等.京津冀地区火电企业的大气污染影响[J].中国环境科学,2015,35(2):364-373.Bo X,Wang G,Wen R,et al. Air pollution effect of the thermal power plants in Beijing-Tianjin-Hebei region[J]. China Environmental Science,2015,35(2):364-373.
[18]陈金胜,伯鑫,徐君妃,等.我国环境影响评价VOCs模拟研究进展[J].环境工程,2018,36(3):143-147.Chen J S,Bo X,Xu J F,et al. Research progress on VOCs simulation in environmental impact assessment in China[J].Environmental Engineering,2018,36(3):143-147.
[19]崔建升,屈加豹,伯鑫,等.基于在线监测的2015年中国火电排放清单[J].中国环境科学,2018,38(6):2062-2074.Cui J S,Qu J B,Bo X,et al. High resolution power emission inventory for China based on CEMS in 2015[J]. China Environmental Science,2018,38(6):2062-2074.
[20] Cui H L,Yao R T,Xu X J,et al. A tracer experiment study to evaluate the CALPUFF real time application in a near-field complex terrain setting[J]. Atmospheric Environment,2011,45(39):7525-7532.
[21]伯鑫. CALPUFF模型技术方法与应用[M].北京:中国环境出版社,2016.
[22]伯鑫,丁峰,徐鹤,等.大气扩散CALPUFF模型技术综述[J].环境监测管理与技术,2009,21(3):9-13,47.Bo X,Ding F,Xu H,et al. Review of atmospheric diffusion spersion model CALPUFF technology[J]. The Administration and Technique of Environmental Monitoring,2009,21(3):9-13,47.
[23]伯鑫,马继,李时蓓,等. CALPUFF大气模型多线程计算及业务系统[A]. 2016中国环境科学学会学术年会论文集(第二卷)[C].海口:中国环境科学学会,2016.
[24] Tartakovsky D,Broday D M,Stern E. Evaluation of AERMOD and CALPUFF for predicting ambient concentrations of total suspended particulate matter(TSP)emissions from a quarry in complex terrain[J]. Environmental Pollution,2013,179:138-145.
[25] Rood A S. Performance evaluation of AERMOD,CALPUFF,and legacy air dispersion models using the Winter Validation Tracer Study dataset[J]. Atmospheric Environment,2014,89:707-720.
[26] Macintosh D L,Stewart J H,Myatt T A,et al. Use of CALPUFF for exposure assessment in a near-field,complex terrain setting[J]. Atmospheric Environment,2010,44(2):262-270.
[27]王刚,吴成志.美国大气许可中PM2. 5评估方法及对中国的启示[J].环境影响评价,2015,37(6):48-51,78.Wang G,Wu C Z. Overview of PM2. 5assessment methods in US air permitting and reference to China thereof[J]. Environmental Impact Assessment,2015,37(6):48-51,78.
[28]伯鑫,王刚,田军,等. AERMOD模型地表参数标准化集成系统研究[J].中国环境科学,2015,35(9):2570-2575.Bo X,Wang G,Tian J,et al. Standard systems of surface parameters in AERMOD[J]. China Environmental Science,2015,35(9):2570-2575.
[29]田谧.京津冀地区霾污染过程大气PM2. 5及前体物变化特征研究[D].北京:北京化工大学,2013.Tian M. Characteristics of PM2. 5and its precursor pollutants during haze in Beijing-Tianjin-Hebei region[D]. Beijing:Beijing University of Chemical Technology,2013.
[30]伯鑫,吴忠祥,王刚,等. CALPUFF模式的标准化应用技术研究[J].环境科学与技术,2014,37(120):530-534.
[31]虢俊龙.石家庄霾污染过程大气颗粒物化学组分分析及来源解析[D].北京:北京化工大学,2015.Guo J L. Study of chemical composition features and sources apportionment of atmospheric particulate matter during haze in Shijiazhuang[D]. Beijing:Beijing University of Chemical Technology,2015.
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