南昌站大气CO₂浓度变化特征

Variation Characteristics of Atmospheric CO₂ Concentration at Nanchang Station

摘要: 二氧化碳是最突出的温室气体之一，是导致全球变暖的主要原因。为研究南昌近地面CO₂浓度变化情况，通过南昌市温室气体监测站，对2019年1月到2020年12月期间，在距离地面30 m和50 m高度上的CO₂浓度值进行日变化、月变化和季节变化的特征分析，并与2019年瓦里关12个月的浓度值做比对。研究结果表明一天中CO₂浓度呈现早晚高，中午低的趋势，且冬季时CO₂变化幅度最小，春季变化幅度最大。一年中CO₂浓度呈现波动性季节分布特征：1~2月浓度较低，为434~450.4 ppm，3~5月起伏变化，但总体下降，为433.5~446.1 ppm，6~8月又呈现下降趋势，浓度值为418.2~436.9 ppm，8月时CO2浓度最低418.2 ppm，9~12月呈现上升趋势，浓度值为423.9~589.5 ppm，在12月份升至最高值589.5 ppm，总体上表现为冬季高，夏季低，春秋季CO₂浓度处于两者之间。其中植物的光合作用可吸收CO₂，大气扩散作用稀释CO₂，而化石燃料的燃烧可增加CO₂排放。

Abstract: Carbon dioxide is one of the most prominent greenhouse gases and is the main cause of global warming. In order to study the variation of CO₂ concentration near the ground in Nanchang, the characteristics of diurnal, monthly and seasonal variations of CO₂ concentration at 30 m and 50 m above the ground during January 2019 to December 2020 were analyzed by using Nanchang Greenhouse Gas Monitoring Station, and then compared with the concentration in Waliguan for 12 months in 2019. The results showed that the CO₂ concentration was higher in the morning and evening and lower at noon, and the variation range of CO₂ was the least in winter and the largest in spring. The seasonal distribution characteristics of CO₂ concentration in a year are as follows: From January to February, the concentration was low, 434~450.4 ppm; From March to May, it fluctuated, but the overall decrease was 433.5~446.1 ppm; From June to August, it showed a downward trend, the concentration was 418.2~436.9 ppm; In August, the CO₂ concentration was 418.2 ppm at its maximum, and from September to December, it showed an upward trend. The concentration was between 423.9 and 589.5 ppm, rising to the highest value of 589.5 ppm in December. Generally speaking, the concentration was high in winter and low in summer, and the CO2 concentration in spring and autumn was between the two. Plant photosynthesis can absorb CO₂, atmospheric diffusion dilutes CO₂ and fossil fuel combustion can increase CO₂ emissions.