长三角PM2.5时空格局演变与特征——基于2013-2016年实时监测数据

doi:10.11821/dlyj201808013

地理研究 ›› 2018, Vol. 37 ›› Issue (8): 1641-1654.doi: 10.11821/dlyj201808013

长三角PM_2.5时空格局演变与特征——基于2013-2016年实时监测数据

宓科娜¹(), 庄汝龙², 梁龙武³, 段艳平¹, 高峻¹()

1. 上海师范大学城市发展研究院,上海 200234
2. 华东师范大学中国现代城市研究中心,上海 200062
3. 中国科学院地理科学与资源研究所,北京 100101

收稿日期:2018-02-10 修回日期:2018-05-09 出版日期:2018-08-20 发布日期:2018-08-20
作者简介:
作者简介：宓科娜（1989- ）,女,浙江慈溪人,博士研究生,研究方向为可持续发展与环境管理。E-mail: mknzrl@163.com
基金资助:
国家自然科学基金重点项目（41730642）;国家“十三五”重点研发计划专项（2016YFC0502706）

Spatio-temporal evolution and characteristics of PM_2.5 in the Yangtze River Delta based on real-time monitoring data during 2013-2016

Kena MI¹(), Rulong ZHUANG², Longwu LIANG³, Yanping DUAN¹, Jun GAO¹()

1. Institute of Urban Studis, Shanghai Normal University, Shanghai 200234, China
2.The Center for Modern Chinese City Studies, East China Normal University, Shanghai 200062, China
3. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

Received:2018-02-10 Revised:2018-05-09 Online:2018-08-20 Published:2018-08-20
About author:
Author: Shi Zhenqin (1988-), PhD, specialized in regional development and land space management in mountain areas. E-mail: kevinszq@163.com

^*Corresponding author: Deng Wei (1957-), Professor, specialized in mountain environment and regional development.

E-mail: dengwei@imde.ac.cn

摘要/Abstract

摘要：

长三角是中国空气污染较为严重的区域。基于地统计、探索性空间数据分析等方法,使用实时监测数据,探讨该区域41个地级以上城市PM_2.5在2013-2016年的时空格局演变与污染特征。结果显示：① PM_2.5表现出不同的年度、月度以及逐日特征。年均值逐年下降,月均值则体现出鲜明季节性,呈现冬高、夏低的“U型”特征,日均值有“脉冲型”波动特点。② 2013-2016年,长三角PM_2.5污染情况已经得到显著改善,但超过三分之二的地区仍存在不同程度超标现象,呈现“西北高、东南低”的污染格局。③ PM_2.5高值区从以合肥、扬州为中心向江苏、安徽北部边界地区转移,低值区逐步扩展形成东至舟山、西至黄山、北至上海、南至温州的低值集聚带。④ 趋势分析来看,PM_2.5年均值东西差异和南北差异均逐步减小,但东西向差异略大于南北向。同时,两个方向中部隆起现象得到改善,城市投影点趋于线性拟合。

关键词: PM_2.5, 时空格局, 联防联控, 长三角

Abstract:

With rapid economic growth and urbanization process of China, and energy consumption becoming huge, it has created a great impact on air pollution. PM_2.5 is one of the major pollutants contributing to air quality. In recent years, there are more and more research on PM_2.5 in the world. The Yangtze River Delta is a region with serious air pollution in China. It is located in the lower Yangtze River of eastern China, which occupies a crucial regional strategic location. This study employed the real-time monitoring data from 2013 to 2016 to explore the spatio-temporal evolution and pollution characteristics of PM_2.5 of 41 cities in the Yangtze River Delta by using the method of geo-statistics and exploratory spatial data analysis. The results showed that: (1) PM_2.5 concentration demonstrated varied annual, monthly and daily characteristics. In detail, the annual average concentrations decreased year by year, and monthly average showed obvious seasonal variations which were higher in winter and lower in summer like a “U-shaped” pattern. Daily average presented a pulse type fluctuation. (2) PM_2.5 pollution in the study area significantly improved from 2013 to 2016. But the PM_2.5 concentrations were still above the limited value in more than two-thirds of the total area, with a pollution pattern of higher in the northwest and lower in the southeast. (3) The PM_2.5 concentrations high value center area moved from Hefei, Yangzhou to northern border area of Jiangsu and Anhui. The low value area gradually expanded to form a low value agglomeration belt within Zhoushan in the east, Huangshan in the west, Shanghai in the north, and Wenzhou in the south. (4) The trend analysis indicated that the differences of PM_2.5 annual averages decreased gradually both in the east-west and the north- south, while the difference in the east- west was slightly larger than that in the north-south. Meanwhile, the central ridges in both directions became lower and the urban projection points tended to be linearly fitted. Based on the above conclusions, some policy implications are provided. The government should strengthen the emergency response cooperation of air pollution control, then improve the coordination and joint action of air pollution monitoring, early warning, information sharing, and emergency plans. Lastly, the emergency response system of multi-level linkages at the national, provincial, municipal, and county levels can be well implemented.

Key words: PM_2.5, spatio-temporal pattern, joint prevention and control, Yangtze River Delta

宓科娜, 庄汝龙, 梁龙武, 段艳平, 高峻. 长三角PM_2.5时空格局演变与特征——基于2013-2016年实时监测数据[J]. 地理研究, 2018, 37(8): 1641-1654.

Kena MI, Rulong ZHUANG, Longwu LIANG, Yanping DUAN, Jun GAO. Spatio-temporal evolution and characteristics of PM_2.5 in the Yangtze River Delta based on real-time monitoring data during 2013-2016[J]. GEOGRAPHICAL RESEARCH, 2018, 37(8): 1641-1654.

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	2013年	2014年	2015年	2016年		2013年	2014年	2015年	2016年
上海	77.03	49.63	53.17	27.23	衢州	87.29	63.11	22.11	19.31
南京	116.14	110.89	61.66	36.6	舟山	-10.49	-15.4	-16	-27.91
无锡	114.23	92.26	74.89	50.83	台州	51	32.49	19.4	2.11
徐州	115.6	91.94	82.6	72.46	丽水	34.23	25.54	17.49	-6.14
常州	115.06	90.11	71.26	51.49	合肥	145.74	128.46	86.2	63.51
苏州	96.03	88.54	63.8	32.37	淮北	-	-	77.69	57.54
南通	105.94	75.94	62.74	43.2	亳州	-	-	72.54	66
连云港	97.94	76.69	55.2	39.2	宿州	-	-	79.23	84.49
淮安	131	96	65.11	52.54	蚌埠	-	-	81.77	72.57
盐城	88.77	66.71	40.31	23.11	阜阳	-	-	45.86	75.29
扬州	99.83	88.46	55.4	44.63	淮南	-	-	42.17	51.49
镇江	104.66	92.34	69.03	43.83	滁州	-	-	77.83	68.91
泰州	123.71	106.54	73.03	55.66	六安	-	-	61.77	32.29
宿迁	110.8	96.29	73.34	60.63	马鞍山	-	101.83	73.2	40.14
杭州	83.66	75.49	58.34	39.63	芜湖	-	93.14	63.8	52.14
宁波	47.69	30.6	27.54	13.69	宣城	-	-	38.29	46
温州	47	30.17	24.34	9.86	铜陵	-	-	65.77	45.14
嘉兴	90.54	60.86	50.97	26.26	池州	-	-	-1.06	26.83
湖州	103.09	80.43	58.37	31.66	安庆	-	-	49.06	53.69
绍兴	97.31	79.71	55.83	30.8	黄山	-	-	-3.11	-19.54
金华	98.49	83.63	55.43	32.37	平均值	91.24	74.73	53.33	39.56

长三角PM_2.5时空格局演变与特征——基于2013-2016年实时监测数据

Spatio-temporal evolution and characteristics of PM_2.5 in the Yangtze River Delta based on real-time monitoring data during 2013-2016

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长三角PM2.5时空格局演变与特征——基于2013-2016年实时监测数据

Spatio-temporal evolution and characteristics of PM2.5 in the Yangtze River Delta based on real-time monitoring data during 2013-2016

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长三角PM_2.5时空格局演变与特征——基于2013-2016年实时监测数据

Spatio-temporal evolution and characteristics of PM_2.5 in the Yangtze River Delta based on real-time monitoring data during 2013-2016