Atmospheric fossil fuel CO2 traced by (CO2)-C-14 and air quality index pollutant observations in Beijing and Xiamen, China | |
Niu, Zhenchuan1,2,3; Zhou, Weijian1,2,3,4; Feng, Xue5; Feng, Tian1,2; Wu, Shugang1,2; Cheng, Peng1,2; Lu, Xuefeng1,2; Du, Hua1,2; Xiong, Xiaohu1,2; Fu, Yunchong1,2 | |
2018-06-01 | |
发表期刊 | ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH |
卷号 | 25期号:17页码:17109-17117 |
文章类型 | Article |
摘要 | Radiocarbon (C-14) is the most accurate tracer available for quantifying atmospheric CO2 derived from fossil fuel (CO2ff ), but it is expensive and time-consuming to measure. Here, we used common hourly Air Quality Index (AQI) pollutants (AQI, PM2.5, PM10, and CO) to indirectly trace diurnal CO2ff variations during certain days at the urban sites in Beijing and Xiamen, China, based on linear relationships between AQI pollutants and CO2ff traced by C-14 (CO2ff-C-14) for semimonthly samples obtained in 2014. We validated these indirectly traced CO2ff (CO2ff-in ) concentrations against CO2ff C-14 concentrations traced by simultaneous diurnal (CO2)-C-14 observations. Significant (p < 0.05) strong correlations were observed between each of the separate AQI pollutants and CO2ff-C-14 for the semimonthly samples. Diurnal variations in CO2ff traced by each of the AQI pollutants generally showed similar trends to those of CO2ff-C-14, with high agreement at the sampling site in Beijing and relatively poor agreement at the sampling site in Xiamen. AQI pollutant tracers showed high normalized root-mean-square (NRMS) errors for the summer diurnal samples due to low CO2ff-C-14 concentrations. After the removal of these summer samples, the NRMS errors for AQI pollutant tracers were in the range of 31.6-64.2%. CO generally showed a high agreement and low NRMS errors among these indirect tracers. Based on these linear relationships, monthly CO2ff averages at the sampling sites in Beijing and Xiamen were traced using CO concentration as a tracer. The monthly CO2ff averages at the Beijing site showed a shallow U-type variation. These results indicate that CO can be used to trace CO2ff variations in Chinese cities with CO2ff concentrations above 5 ppm. |
关键词 | Delta C-14 Fossil Fuel Co2 Indirect Tracer Co Pm2.5 |
WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
DOI | 10.1007/s11356-018-1616-z |
关键词[WOS] | LOS-ANGELES MEGACITY ; SOURCE APPORTIONMENT ; CARBON-DIOXIDE ; BACKGROUND SITES ; URBAN AREA ; EMISSIONS ; RADIOCARBON ; PM2.5 ; DELTA-C-14 ; EUROPE |
收录类别 | SCI |
所属项目编号 | 4177314、41573136、41730108 ; XAB2015A02 ; 2016360 |
WOS研究方向 | Environmental Sciences & Ecology |
项目资助者 | the National Natural Science Foundation of China ; CAS“Light of West China” Program ; the Youth Innovation Promotion Association CAS |
WOS类目 | Environmental Sciences |
WOS记录号 | WOS:000435961300079 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ieecas.cn/handle/361006/5102 |
专题 | 加速器质谱中心 |
作者单位 | 1.Chinese Acad Sci, Inst Earth Environm, State Key Lab Loess & Quaternary Geol, Xian, Shaanxi, Peoples R China 2.Xian AMS Ctr, Shaanxi Key Lab Accelerator Mass Spectrometry Tec, Xian, Shaanxi, Peoples R China 3.Qingdao Natl Lab Marine Sci & Technol, Open Studio Ocean Continental Climate & Environm, Qingdao, Peoples R China 4.Beijing Normal Univ, Joint Ctr Global Change Studies, Beijing, Peoples R China 5.Northwest Univ, Coll Urban & Environm Sci, Xian, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Niu, Zhenchuan,Zhou, Weijian,Feng, Xue,et al. Atmospheric fossil fuel CO2 traced by (CO2)-C-14 and air quality index pollutant observations in Beijing and Xiamen, China[J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,2018,25(17):17109-17117. |
APA | Niu, Zhenchuan.,Zhou, Weijian.,Feng, Xue.,Feng, Tian.,Wu, Shugang.,...&Fu, Yunchong.(2018).Atmospheric fossil fuel CO2 traced by (CO2)-C-14 and air quality index pollutant observations in Beijing and Xiamen, China.ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,25(17),17109-17117. |
MLA | Niu, Zhenchuan,et al."Atmospheric fossil fuel CO2 traced by (CO2)-C-14 and air quality index pollutant observations in Beijing and Xiamen, China".ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 25.17(2018):17109-17117. |
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