摘要
海口市作为我国著名的热带滨海城市之一,地理环境特殊,气候资源独特。为深入认识海口市臭氧(O_(3))污染变化规律及污染物潜在贡献源区,也为进一步开展O_(3)污染预报预警和区域联防联控提供技术支撑,利用海口市区4个环境监测数据,结合气象观测资料,采用后向轨迹模拟、聚类分析、多元回归分析法、潜在源区贡献因子算法和权重轨迹方法分析了海口市最大8 h平均(O_(3)-8h)质量浓度年际变化、月际变化、日变化及与气象影响因子的关系,影响O_(3)-8h质量浓度的主控因子,并探讨了O_(3)传输路径和潜在贡献源区。结果表明,2013—2020年海口市区4个站点O_(3)-8h质量浓度均出现不同程度的上升,其中龙华站的趋势系数达到了0.929,通过了99.9%的信度检验;O_(3)-8h质量浓度月际变化呈“V”型分布,最大值出现在10月;日变化呈单峰型,峰值出现在15:00附近;平均气温在18—28℃之间,相对湿度位于65%—80%,太阳辐射日总量在6—23 MJ·m^(−2)之间,日照时数位于4—10 h·d^(−1),受4—6 m·s^(−1)之间的东北风影响时,海口市O_(3)-8h质量浓度容易超标。多元回归分析表明,10 m平均风速、相对湿度和大气压是主控因子;后向轨迹和潜在源区分析发现,秋季的内陆中短距离气流和沿海长距离气流,春季的沿海中短距离气流和冬季内陆短距离气流容易造成O_(3)-8h质量浓度超标,其中江西省、浙江省、福建省和广东省是O_(3)污染的主要贡献源区。
Haikou City is one of the well-known tropical coastal cities in China,which has a special geographical environment and unique climate resources.In order to have a further understanding of ozone(O_(3))pollution characteristics and potential source regions of pollutants in Haikou City,and technological support for carrying out warning,forecast,management and regional joint prevention of ozone pollution,four environmental monitoring data and meteorological observational data in Haikou City were used;interannual variation,monthly change,diurnal variation and meteorological influence of the O_(3)-8h(defined as the maximum 8 h average result)were analyzed using the backward trajectory simulation,cluster analysis,multiple regression analysis,PSCF(Potential source analysis function)and CWT(Concentration weight trajectory)methods.The results showed that the O_(3)-8h from all the four stations in Haikou City showed an upward trend from 2013 to 2020.The trend coefficient of Longhua Station reached 0.929,which passed the 99.9%significant test.The monthly variation of O_(3)-8h showed a“V”-shaped distribution,with the maximum value occurred in October.The daily variation was unimodal,with a peak value around 15:00.The exceedance probability of O_(3)-8h concentrations was relatively high when the average temperature was around 18‒28℃,relative humidity was between 65%and 80%,the total solar radiation ranged 6‒23 MJ·m^(−2),sunshine duration was between 4 h·d^(−1)and 10 h·d^(−1),and wind speed of the northeast wind was between 4 to 6 m·s^(−1).Multiple regression analysis showed that 10 m average wind speed,relative humidity and atmosphere pressure were the main dominate factors on O_(3)-8h.Backward trajectory and potential source analysis revealed that the inland short-distance air flow and coastal long-distance air flow in autumn,the medium and short-distance air flow along the coast in spring and the inland short-distance air flow in winter are likely to cause the above-normal O_(3)-8h concentration.Jiangxi,Zhejiang,Fujian and Guangdong provinces are the main sources of O_(3)pollution in Haikou City.
作者
符传博
丹利
佟金鹤
陈红
FU Chuanbo;DAN Li;TONG Jinhe;CHEN Hong(Hainan Institute of Meteorological Science,Haikou 570203,P.R.China;Key Laboratory of Regional Climate-Environment Research for Temperate East Asia,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,P.R.China;Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province,Haikou 570203,P.R.China;Hainan Meteorological Observatory,Haikou 570203,P.R.China)
出处
《生态环境学报》
CSCD
北大核心
2023年第2期331-340,共10页
Ecology and Environmental Sciences
基金
国家自然科学基金项目(42065010,42141017)
海南省重大科技计划项目(ZDKJ202007)
海南省自然科学基金项目(422RC802,421QN0967)
海南省院士创新平台科研项目(YSPTZX202143)。
关键词
臭氧(O3)
气象因子
后向轨迹
潜在源区
海口市
ozone(O3)
meteorological factor
backward trajectory
potential source
Haikou City