摘要
海洋源排放的二甲基硫(Dimethylsulfide, DMS)是全球大气硫循环的主要参与者。本研究利用机器学习法构建了夏季东中国海12 km×12 km分辨率海表DMS浓度清单,基于该清单和WRF-CMAQ模型模拟了2016年夏季东中国海DMS的海洋释放和DMS在大气中的物理化学过程,探究了夏季东中国海大气DMS及其氧化产物的浓度特征和主要影响因素。结果表明:海表DMS浓度随离岸距离增大而降低,平均浓度为7.66 nmol/L;与全球海表DMS浓度数据库在东中国海的结果相比,本研究计算的海表DMS浓度是其2~3倍,与观测浓度更为接近,也更好地再现了海表DMS空间分布特征。DMS海-气通量受海表DMS浓度及风速等因素影响,研究海域海洋释放DMS通量为3.0~47.2μmol/(m^(2)·d)。东中国海夏季大气DMS浓度为1.54~16.73 nmol/m^(3),渤海(7.22 nmol/m^(3))>东海(5.92 nmol/m^(3))>黄海(5.38 nmol/m^(3))。大气DMS浓度日变化呈双峰分布,在08:00和18:00左右浓度较高,午间和夜晚浓度较低,这主要与DMS的被大气中自由基的氧化等过程有关;大气DMS的氧化转化使夏季东中国海SO2、SO42-和MSA月均浓度分别升高了0.02~0.92、0.01~1.08、0.01~0.06μg/m^(3)。
Dimethylsulfide(DMS)emitted from marine sources is a major player in the global atmospheric sulfur cycle.In this study,a sea surface DMS concentration inventory(12 km×12 km)was constructed in the East China Seas in summer using a machine learning model.Based on this inventory and the WRF-CMAQ model,we simulated the marine DMS emission and the physicochemical processes of DMS in the atmosphere in the East China Seas during summer 2016 and explored the concentration characteristics and main influencing factors of atmospheric DMS and its oxidation products.The sea surface DMS concentration decreases with increasing offshore distance,and the average concentration is 7.66 nmol/L,which is 2~3 times than the global DMS datebase.The simulated sea surface DMS concentrations are very close to the observations in terms of concentration magnitude and spatial distribution.DMS emission fluxes are influenced by sea surface DMS concentrations and wind speed,and the oceanic emission of DMS fluxes in the study area ranged from^(3).0 to 47.2μmol/(m^(2)·d).Atmospheric DMS concentrations ranged from 1.54 to 16.73 nmol/m^(3) in the East China Seas in summer,with the Bohai Sea(7.22 nmol/m^(3))>East China Sea(5.92 nmol/m^(3))>Yellow Sea(5.38 nmol/m^(3)).The diurnal variation of atmospheric DMS concentrations is bimodal,with higher concentrations around 08:00 and 18:00.Due to the oxidation process of radicals in the atmosphere,atmospheric DMS concentrations are lower at midday and night.The oxidative transformation of atmospheric DMS improved the monthly average concentrations of SO 2,SO 2-4 and MSA in the East China Sea in summer by 0.02~0.92,0.01~1.08 and 0.01~0.06μg/m^(3),respectively.
作者
李恒
张洁
贺慧泽
王娇
张宜升
刘晓环
Li Heng;Zhang Jie;He Huize;Wang Jiao;Zhang Yisheng;Liu Xiaohuan(College of Environmental Science and Engineering,Ocean University of China,Qingdao 266100,China;Key Laboratory of Marine Environment and Ecology,Ministry of Education,Ocean University of China,Qingdao 266100,China;Laboratory for Marine Ecology and Environmental Science,Laoshan Laboratory,Qingdao 266237,China;School of Environment and Municipal Engineering,Qingdao University of Technology Qingdao,Qingdao 266033,China)
出处
《中国海洋大学学报(自然科学版)》
CAS
CSCD
北大核心
2024年第7期79-88,共10页
Periodical of Ocean University of China
基金
国家自然科学基金项目(42175129,U1906215)资助。
关键词
二甲基硫
CMAQ
机器学习
东中国海
dimethyl sulfide(DMS)
CMAQ
machine learning
East China Seas