气象与环境学报2024，Vol.40Issue(3)：37-45,9.DOI:10.3969/j.issn.1673-503X.2024.03.005
基于AQCI的辽宁省空气质量时空分布特征
Spatio-temporal characteristics of air quality in Liaoning province based on the Air Quality Composite Index
摘要
Abstract
Based on the air quality monitoring data in Liaoning province from 2015 to 2022,the Air Quality Com-posite Index(AQCI)was used as the characterization index to analyze the temporal variation of air quality,and the ArcGIS spatial autocorrelation tool was used to explore the spatial distribution characteristics of AQCI at differ-ent time scales.The results show that AQCI in Liaoning province shows a downtrend over the past 8 years,decrea-sing from 5.64 in 2015 to 3.55 in 2022.The excellent air quality rate steadily increased,with a 24.7%improve-ment in 2022 compared to 2015.The proportion of O3,PM2.5,and PM10 as primary pollutants increased from 93.1%to 99.0%.The seasonal mean value of AQCI follows the distribution pattern of summer<autumn<spring<winter.The excellent air quality rate is highest in summer or autumn,followed by spring,and winter is lowest.The primary pollutants show seasonal fluctuations,with PM2.5 and PM10 being the main pollutants in spring,au-tumn,and winter,while O3 pollution mainly occurs in summer.The monthly variation in AQCI is significant,which varies largely in different cities,with the highest values in January and the lowest values in July or August.The ex-cellent air quality rate is lowest in January and highest in August.PM2.5,PM10,and O3 account for more than 90%of the primary pollutants each month.The spatial aggregation characteristics of AQCI in Liaoning province are evi-dent,with variations over time.The high-value aggregation characteristics of the central urban agglomeration are particularly significant.关键词
AQCI/首要污染物/空气质量优良率/空间自相关Key words
Air Quality Composite Index(AQCI)/Primary pollutants/Excellent air quality rate/Spatial autocorrela-tion分类
资源环境引用本文复制引用
于文革,梁铁军,王玉琦,张浩楠,张倩怡,丁桦..基于AQCI的辽宁省空气质量时空分布特征[J].气象与环境学报,2024,40(3):37-45,9.基金项目
辽宁省气象局科技项目(202109)资助. （202109）
