废弃生物质灰分含量与热值的差异性和相关性及其测定方法

为探究生物质能源化利用中灰分含量和热值的函数变化规律及测定方法，检索2001—2021年已发表的相关文献，获得380个不同类型的生物质样本的灰分含量和高位热值数据，并对测定方法进行分析。结果表明:1)不同热值测定标准对热值的测定结果的评价影响可以忽略不计，而根据固体矿物燃料标准测定的灰分含量结果会显著低于按照生物质燃料标准的测定结果；2)草本植物类生物质的灰分含量为7.96%~9.19%，高于木本植物的2.26%~3.37%，但其平均热值(17.45 MJ/kg)却低于木本植物(19.61 MJ/kg)；3)草本植物的高位热值与灰分含量呈负相关，相关系数(r)的绝对值为0.567~0.918，高于木本植物的0.136。高位热值与化学元素(碳、氢、氮、硫、氧)含量的决定系数(R2)为0.936 7~0.973 7，高于与灰分、挥发分和固定碳含量的决定系数0.812 0~0.971 4，前者函数的拟合效果更好；4)应用近红外光谱技术建立的生物质水分、灰分含量和热值模型的预测偏差较小，小于参考方法的重复性界限，因此该测定方法更便捷，在生物质产业中具有很大的应用潜力。

Differences and correlations between ash content and calorific value in waste biomass and their determination methods

In order to explore the expression law and determination method of ash content and calorific value in biomass energy utilization, the ash and higher calorific value data of 380 different types of biomass samples were obtained from literature published from 2001 to 2021. The determination methods were analyzed statistically. The results showed as follows: 1)The influence of different calorific value determination standards on the determination of calorific value was negligible, but the outcome of ash content determination according to solid fossil fuels standard was significantly lower than those of biomass fuels. 2)The ash content of herbaceous biomass ranged from 7. 96% to 9. 19%, which was significantly higher than that of woody biomass from 2. 26% to 3. 37%. Its average calorific value(17. 45 MJ/kg)was lower than that of woody biomass(19. 61 MJ/kg). 3)The high calorific absolute value of herbaceous plants was negatively correlated with ash content(r 0. 567-0. 918), which was higher than that of woody plants(0. 136). The coefficient(R2)of determination between high calorific value and chemical elements(carbon, hydrogen, nitrogen, sulfur, oxygen)content was 0. 936 7-0. 973 7, higher than 0. 812 0-0. 971 4 with ash, volatile, and fixed carbon. The former function had better fitting effect. 4)The deviation of biomass moisture, ash content and calorific values predicted by the model established by NIR technology was basically less than the repeatability limit of the reference method. The method established in this study was faster and had great application potential in the biomass industry.