引用本文:赵亚芳,余益军.2016—2020年常州市温室气体浓度及相关因素分析[J].环境监控与预警,2022,14(1):7-11
ZHAO Ya-fang, YU Yi-jun.Concentrations and Affecting Factors of Greenhouse Gases in Changzhou from 2016 to 2020[J].Environmental Monitoring and Forewarning,2022,14(1):7-11
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2016—2020年常州市温室气体浓度及相关因素分析
赵亚芳,余益军
江苏省常州环境监测中心,江苏 常州 213001
摘要:
基于2016—2020年常州市主要温室气体的监测数据,采用长时间序列分析和相关性分析等方法,研究了二氧化碳(CO2)和甲烷(CH4)浓度的变化趋势,分析了CO2和CH4与污染物和气象要素的相关性,初步探讨了生物源和人为源的影响。结果表明:常州市大气CO2和CH4年平均浓度分别为416.4 ppm和1635.7 ppb,上升速率均高于青海瓦里关全球大气本底站同期水平。CO2和CH4浓度整体表现为夏季低、冬季高的季节变化,CO2浓度在8月和12月分别达到最小和最大值,CH4浓度7月和10月分别达到最小和最大值。夏季光合作用、植物生长等生物源对CO2和CH4浓度影响较大,冬季人类活动、工业生产等影响增加。CO2浓度日变化呈现为早晚高、午后低的双峰结构,春季受光合作用影响有更明显的日变化规律。CH4浓度表现单峰的日变化特征,秋季CH4浓度最高,且日变化最明显,表明秋季生物源对CH4影响更明显。CO2和CH4与NO2、NOx、PM2.5和PM10均有较强的正相关性,两者与NO2和NOx相关性最强,表明受机动车影响较大;与气象参数的相关性则明显减弱,在风速增大时,扩散条件有利于CO2和CH4浓度降低。
关键词:  温室气体  二氧化碳  甲烷  浓度特征  相关性分析
DOI:
分类号:X51
基金项目:常州市科技局基金资助项目(CJ20180039);江苏省常州环境监测中心培优、培新科研基金资助项目(201808-PX,201809-PX)
Concentrations and Affecting Factors of Greenhouse Gases in Changzhou from 2016 to 2020
ZHAO Ya-fang, YU Yi-jun
Jiangsu Changzhou Environmental Monitoring Center, Changzhou,Jiangsu 213001, China
Abstract:
Based on the monitoring data of main greenhouse gases, variation characteristics of carbon dioxide (CO2) and methane (CH4) in Changzhou from 2016 to 2020 were studied by using such methods as long term sequence analysis and correlation analysis. A correlation between the concentration of CO2 and CH4 and pollutants and meteorological parameters was analyzed, and the effects of biological sources and human activities were discussed preliminary. The results showed that the annual average concentrations of CO2and CH4were 416.4ppm and 1635.7ppb in Changzhou respectively, and the increasing rates were both higher than that in Waliguan during the same period. The CO2and CH4 concentrations were lower and the biological sources such as photosynthesis and plant growth had a greater impact in summer. While the concentrations and impacts of human activities and industrial production increased in winter. The diurnal variation of CO2 concentration showed two peaks in the morning and evening. The diurnal variation of CH4 exhibited one peak and it was highest in autumn which indicated the greater impact of biological sources on CH4. CO2 and CH4 were significantly correlated with NO2, NOx, PM2.5and PM10. The correlation with meteorological parameters was obviously weakened. When the wind speed increased, the diffusion conditions were conducive to the reduction of CO2 and CH4 concentrations.
Key words:  Greenhouse gases  CO2  CH4  Concentration characteristics  Correlation analysis