Muir G K P, Hayward S, Tripney B G, Cook G T, Naysmith P, Herbert B M J, Garnett M H, Wilkinson M
SUERC Radiocarbon Laboratory, Scottish Universities Environmental Research Centre (SUERC), Rankine Avenue, East Kilbride G75 0QF, Scotland, UK.
Stopford Energy and Environment, The Gordon Manley Building, Lancaster University, Lancaster LA1 4YQ, England, UK.
Waste Manag. 2015 Jan;35:293-300. doi: 10.1016/j.wasman.2014.09.023. Epub 2014 Oct 13.
(14)C analysis of flue gas by accelerator mass spectrometry (AMS) and liquid scintillation counting (LSC) were used to determine the biomass fraction of mixed waste at an operational energy-from-waste (EfW) plant. Results were converted to bioenergy (% total) using mathematical algorithms and assessed against existing industry methodologies which involve manual sorting and selective dissolution (SD) of feedstock. Simultaneous determinations using flue gas showed excellent agreement: 44.8 ± 2.7% for AMS and 44.6 ± 12.3% for LSC. Comparable bioenergy results were obtained using a feedstock manual sort procedure (41.4%), whilst a procedure based on selective dissolution of representative waste material is reported as 75.5% (no errors quoted). (14)C techniques present significant advantages in data acquisition, precision and reliability for both electricity generator and industry regulator.
采用加速器质谱法（AMS）和液体闪烁计数法（LSC）对烟气进行¹⁴C分析，以确定一家运营中的垃圾能源（EfW）工厂混合废物的生物质比例。使用数学算法将结果转换为生物能源（占总量的百分比），并与现有的行业方法进行评估，现有方法涉及对原料进行人工分拣和选择性溶解（SD）。使用烟气进行的同步测定显示出极佳的一致性：AMS为44.8±2.7%，LSC为44.6±12.3%。使用原料人工分拣程序获得了可比的生物能源结果（41.4%），而基于代表性废物材料选择性溶解的程序报告为75.5%（未给出误差）。¹⁴C技术在数据采集、精度和可靠性方面对发电企业和行业监管机构都具有显著优势。
Zotero 插件