State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an 710061, China.
State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Xi'an 710061, China; Xi'an Jiaotong University, Xi'an 710049, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an 710061, China; Open Studio for Oceanic-Continental Climate and Environment Changes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China.
Sci Total Environ. 2020 May 1;715:136669. doi: 10.1016/j.scitotenv.2020.136669. Epub 2020 Jan 13.
Fossil fuel-derived CO (CO) time series are critical to understanding urban carbon emissions, and to devise strategies to mitigate emission reduction. Using tree ring C archives, we reconstruct an historical CO time series from 1991 to 2015 in the greater Xi'an region, China. CO concentrations from the urban sites reached 22.5 ppm, with an average of 14.0 ppm, while average values from rural and mountain sites averaged about 6.0 ppm. These values provide a good measure of the distribution of anthropogenic CO emissions in the region. We also observed CO concentration increases from both urban and rural sites during the study period, with more significant increases among urban sites. The persistent rise in CO was attributed to increasing energy consumption caused by regional socio-economic development, which are corroborated by strong correlations between CO and socioeconomic parameters.
化石燃料衍生的 CO（CO）时间序列对于理解城市碳排放以及制定减排策略至关重要。我们利用树木年轮 C 档案，重建了中国西安地区 1991 年至 2015 年的历史 CO 时间序列。城市站点的 CO 浓度达到 22.5 ppm，平均值为 14.0 ppm，而农村和山区站点的平均值约为 6.0 ppm。这些值很好地衡量了该地区人为 CO 排放的分布。我们还观察到研究期间城市和农村站点的 CO 浓度均有所增加，城市站点的增加更为明显。CO 的持续上升归因于区域社会经济发展导致的能源消耗增加，这与 CO 与社会经济参数之间的强烈相关性相符。
