天津市夏季臭氧污染特征及来源的模拟分析

doi:10.13209/j.0479-8023.2017.109

摘要/Abstract

摘要：

利用Models-3/CMAQ模式系统和高阶去耦合直接技术(HDDM-3D), 对天津市2014年7月的臭氧(O₃)污染进行模拟, 分析臭氧生成的前体物控制区分布规律, 量化天津市及周边地区排放的影响。研究结果表明, 天津市臭氧浓度分布从中心城区向外部郊区逐渐增高, 东南部临海的滨海新区浓度水平最高。天津全市7月的臭氧生成以VOCs控制为主, 中部地区(中心城区、北辰区、东丽区、滨海新区) 95%以上天数的臭氧处于VOCs控制区, 北部远郊(蓟县、宝坻区、宁河区、武清区)以及中部津南区有2/3以上天数受VOCs控制, 南部郊区(西青区、静海区、大港区)的VOCs控制区与共同控制区出现的比例相近。山东省排放是天津市夏季臭氧的主要来源, 平均贡献占比约为1/4, 对天津东南沿海地区的影响尤为突出; 河北省排放平均贡献占比约为1/6, 主要影响天津西部区县的臭氧水平; 天津排放贡献则主要分布在北部的宝坻和蓟县。

关键词: 天津, 臭氧, 前体物控制区, 来源, HDDM

Abstract:

Models-3/CMAQ and High-order Decoupled Direct Method (HDDM) was applied to simulate the ozone pollution during July 2014 in Tianjin, and then to analyze the distribution of ozone-precursor sensitivity regimes and to quantify the impact of source emissions from Tianjin and surrounding areas. The distribution of ozone concentration in Tianjin was gradually increased from the center urban areas to the suburbans areas. The concentrations in Binhai new district (in the southeast of Tianjin), was the highest. Ozone formation was mainly VOCs-sensitive in Tianjin in July, the central area (Central city, Beichen, Dongli and Binhai new district) was VOCs-sensitive over 95% days, near 2/3 of simulation days in northern suburbs (Jixian, Baodi, Ninghe and Wuqing) and Jinnan in central area was VOCs controlled, VOC-sensitive regime had similar probability of occurrence to mixed sensitive regime in southern suburbs (Xiqing, Jinghai and Dagang). Shandong Province contributed 1/4 to ozone in Tianjin, was the main source of Tianjin summer ozone, significantly influencing the level of ozone in the southeast coastal of Tianjin. The average contribute of Hebei Province was 1/6. It main effected of western area of Tianjin. Tianjin local emissions contributed in Baodi and Jixian in the north of Tianjin.

Key words: Tianjin, ozone, sensitivity regimes, source apportionment, HDDM

洪礼楠, 黄争超, 秦墨梅, 王雪松. 天津市夏季臭氧污染特征及来源的模拟分析[J]. 北京大学学报自然科学版, 2017, 53(5): 929-938.

Linan HONG, Zhengchao HUANG, Momei QIN, Xuesong WANG. Simulation of Pollution Characteristics and Source Apportionment of Ozone in Tianjin during Summer Time[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2017, 53(5): 929-938.

图/表 12

图1 两重嵌套的模拟区域(a)及天津市的部分观测站点分布(b)

Fig. 1 Two domains for the simulation (a) and the locations of some monitoring sites (b)

图2 第二重模拟区域内的NOx和VOCs排放速率分布

Fig. 2 Distributions of NOx and VOCs emission rates in the second domain

表1 天津市臭氧小时浓度模拟值与观测值的对比评估及与文献比较

Table 1 Comparison of ozone simulation performancebetween this study and previous studies

地区	时间	NMB/%	NME/%	COR	文献
天津	2014/7	3.1	34.3	0.70	本研究
珠三角	2004/10	-5.4	37.1	0.73	[29]
珠三角	2010/8	3.6	47.3	-	[30]
美国	1999/7	21.0	28.0	0.61	[31]
北京	2006/8	-28.9	-	-	[32]
长三角	2001/7	-3.1	-	0.77	[33]

图3 天津市国控站点平均臭氧模拟值与观测值对比的时间序列

Fig. 3 Comparison between simulated and observed ozone concentrations at Tianjin sites

图4 2014年7月臭氧超标日的10:00—17:00时臭氧平均浓度空间分布

Fig. 4 Spatial distribution of 10:00-17:00 average ozone concentration in ozone pollution days in July 2014

图5 2014年7月天津中心城区的风玫瑰图

Fig. 5 Wind rose of central city of Tianjin in July 2014

图6 2014年7月7, 17, 26和29日14:00近地面臭氧浓度和模拟风场空间分布

Fig. 6 Distribution of surface ozone concentration and simulated wind field at 14:00 on 7, 17, 26, and 29 July 2014

图7 污染日臭氧高值时段分别削减50%NOx排放和VOCs排放的臭氧浓度变化

Fig. 7 Ozone concentration changes of reduce the 50% NOx emissions and VOCs emissions in ozone polluted days

表2 2014年7月天津市各区县不同类型臭氧控制区的出现概率

Table 2 Frequencies of ozone-precursor sensitivity regimes of each district/county

区县	出现概率/%
区县	NOx控制	VOCs控制	共同控制
中心城区	0	100.0	0
北辰	0	96.8	3.2
东丽	0	100.0	0
西青	0	51.6	48.4
津南	0	74.2	25.8
武清	0	67.7	32.3
宁河	0	87.1	12.9
静海	0	41.9	58.1
大港	0	58.1	41.9
宝坻	0	80.6	19.4
蓟县	9.7	67.7	22.6
滨海新区	0	100.0	0

表3 各地排放对各站点在污染日高值时段影响比例

Table 3 Impact ratios of each site in polluted days

地区	影响比例/%
地区	市监测中心	蓟县环保局	团泊洼	中新生态城	平均值
天津	-52.8	8.3	2.3	5.8	-9.1
北京	4.8	2.7	3.0	1.3	2.9
河北北	1.8	1.6	1.2	0.5	1.3
河北东	0.4	1.2	1.3	2.4	1.3
河北中	18.5	9.5	13.1	6.7	11.9
河北南	3.3	1.1	2.2	2.0	2.1
内蒙古	4.5	3.0	2.7	1.3	2.9
辽宁	2.2	1.2	1.4	2.1	1.7
山西	3.6	1.7	2.6	1.3	2.3
山东	25.8	15.4	16.6	35.3	23.3
河南	7.1	2.9	5.0	1.7	4.2
其他	4.8	3.5	3.3	8.8	5.1
背景	76.0	47.9	45.4	30.8	50.0

图8 污染日高值时段(10:00—17:00)各地区50%源排放影响臭氧浓度

Fig. 8 Ozone concentration effect by 50% emissions of each area on polluted time

图9 山东省各类源排放对天津环境监测中心站点贡献比例

Fig. 9 Contribution rates of each source in Shandong emissions to environmental monitoring center site

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