摘要
为探究山东半岛在长时间序列上的臭氧(O_(3))时空分布特征及潜在来源,在分析山东半岛2005~2020年O_(3)浓度时空变化的基础上,运用小波分析、熵权法和相关性分析对O_(3)及其影响因素进行了探讨,并对山东半岛O_(3)的潜在来源进行研究.结果表明:(1)时间格局上,山东半岛地区近地面臭氧2005~2020年间呈现出“三峰型”趋势,2010年达到最大值[(40.48±7.64)μg·m^(-3)],2013年为最小值[(36.63±5.61)μg·m^(-3)].季节表现为:夏季[(42.49±1.7)μg·m^(-3)]>春季[(40.65±0.6)μg·m^(-3)]>秋季[(36.47±0.7)μg·m^(-3)]>冬季[(36.46±0.3)μg·m^(-3)].(2)空间格局上,2005~2020年山东半岛O_(3)浓度随着纬度的升高而逐渐升高,呈现出东西部高,中部低的特征,O_(3)浓度16 a的演化过程中存在着1.5 a的主振荡周期.(3)气象条件分析发现,O_(3)浓度与气温、降水、相对湿度和日照时数呈正相关关系、与气压和风速呈负相关关系.社会因素分析中,烟粉(尘)排放量为第三指标影响最为明显的因素,所占权重达到了0.25.(4)通过对不同地区(济南和青岛)模拟受点气流输送轨迹发现,海洋气流对济南贡献10.69%,对青岛贡献48.94%.远距离气团传输路径64.04%来自西北方向,近距离气团传输路径43.69%来自渤海和黄海,其次是山东本省地区占21.01%.(5)O_(3)潜在源解析表明:济南潜在源主要分布在辽宁省锦州地区、江苏省北部、湖北省和安徽省交界处,其WPSCF值>0.6,青岛WPSCF值>0.6地区主要分布黄海地区.济宁市、临沂市、徐州市、淮北市和连云港市的O_(3)贡献>40μg·m^(-3).青岛的O_(3)贡献>45μg·m^(-3)的地区主要在黄海.通过对山东半岛潜在源解析,要尤其重视周边地区的工业源供给和海洋大气污染提供的海洋源.
The purpose of this study was to explore the temporal and spatial distribution characteristics and potential sources of ozone(O_(3))in the Shandong Peninsula over a long period of time based on the analysis of the temporal and spatial changes in O_(3) concentration in Shandong Peninsula from 2005 to 2020.We used wavelet analysis,the entropy weight method,and correlation analysis to discuss O_(3) and its influencing factors and researched the potential sources of O_(3) in Shandong Peninsula.The results showed that:(1)in terms of the time pattern,the near-surface O_(3) in Shandong Peninsula showed a“triple peak”trend from 2005 to 2020,reaching the maximum value of[(40.48±7.64)μg·m^(-3)]in 2010 and a minimum value of[(36.63±5.61)μg·m^(-3)]in 2013.The season was expressed as:summer[(42.49±1.7)μg·m^(-3)]>spring[(40.65±0.6)μg·m^(-3)]>autumn[(36.47±0.7)μg·m^(-3)]>winter[(36.46±0.3)μg·m^(-3)].(2)In terms of the spatial pattern,the O_(3) concentration of Shandong Peninsula gradually increased with the increase in latitude from 2005 to 2020,showing the characteristics of high concentrations in the east and west and low in the middle region.During the 16-year evolution of the O_(3) concentration,there was a 1.5 a main oscillation period.(3)The analysis of meteorological conditions revealed that O_(3) concentration was positively correlated with temperature,precipitation,relative humidity,and sunshine hours,whereas pressure and wind speed were negatively correlated.In the analysis of social factors,soot(dust)emissions were the most obvious factor affecting the third indicator,with a weight of 0.25.(4)Through simulating the trajectory of airflow from different regions(Ji’nan and Qingdao),it was found that the ocean airflow contributed 10.69%to Jinan and 48.94%to Qingdao.There was 64.04%of the long-distance air mass transmission path coming from the northwest,and 43.69%of the short-distance air mass transmission path was from the Bohai Sea and the Yellow Sea,followed by Shandong Province with 21.01%.(5)The analysis of potential sources of O_(3) showed that the potential sources of Ji’nan were mainly distributed in Jinzhou,Liaoning Province,northern Jiangsu Province,Hubei Province,and Anhui Province,with a WPSCF value>0.6,and Qingdao’s WPSCF value of>0.6 was mainly distributed in the Yellow Sea area.The O_(3) contribution of Jining City,Linyi City,Xuzhou City,Huaibei City,and Lianyungang City was>40μg·m^(-3).The area with>45μg·m^(-3) in Qingdao was mainly in the Yellow Sea.Through the analysis of potential sources in the Shandong Peninsula,particular attention should be paid to the supply of industrial sources in the surrounding areas and the marine sources provided by marine air pollution.
作者
李乐
刘旻霞
肖仕锐
王思远
米佳乐
LI Le;LIU Min-xia;XIAO Shi-rui;WANG Si-yuan;MI Jia-le(College of Geography and Environmental Science,Northwest Normal University,Lanzhou 730070,China)
出处
《环境科学》
EI
CAS
CSCD
北大核心
2022年第3期1256-1267,共12页
Environmental Science
基金
国家自然科学基金项目(31760135)
甘肃省自然科学基金项目(20JR10RA089)。
