One of the technical barriers to the wider use of biochar in the composting practices is the lack of accurate quantification linking biochar properties to application outcomes. To address this issue, this paper investigates the use of ammonia nitrogen adsorption capacity by biochar as a predictor of ammonia emission during composting in the presence of biochar. With this in mind, this work investigated the use of ammonia nitrogen adsorption capacity of biochar when mixed with solid digestate, and the reduction in ammonia emissions resulting from the addition of biochar during aerobic degradation of solid digestate. A biochar synthesized at 900 °C, another synthesized at 450 °C, and two derivatives of the latter biochar, one chemically modified with nitric acid and the other with potassium hydroxide, were tested. This study concluded that the chemical characteristics of the biochar, including pH and oxygen/carbon atomic ratio, had a greater influence on the adsorption of ammonia nitrogen than physical attributes such as specific surface area. In this regard, nitric acid modification had superior performance compared to hydroxide potassium modification to increase biochar chemical attributes and reduce ammonia emissions when applied to aerobic degradation. Finally, a significant linear correlation (p-value < 0.05, r = 0.79) was found between biochar ammonia nitrogen adsorption capacity and ammonia emissions along composting, showing the potential of this variable as a predictive parameter. This study provides insights for future explorations aiming to develop predictive tests for biochar performance.

中文翻译：

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生物炭氨氮吸附及其与好氧降解氨排放相关性的新见解

在堆肥实践中广泛使用生物炭的技术障碍之一是缺乏将生物炭特性与应用结果联系起来的准确量化。为了解决这个问题，本文研究了利用生物炭的氨氮吸附能力作为生物炭堆肥过程中氨排放的预测指标。考虑到这一点，本工作研究了生物炭与固体沼渣混合时的氨氮吸附能力的利用，以及在固体沼渣好氧降解过程中添加生物炭所导致的氨排放量的减少。测试了一种在 900 °C 下合成的生物炭，另一种在 450 °C 下合成的生物炭，以及后一种生物炭的两种衍生物，一种用硝酸化学改性，另一种用氢氧化钾化学改性。本研究得出的结论是，生物炭的化学特性（包括 pH 值和氧/碳原子比）对氨氮吸附的影响大于比表面积等物理特性。在这方面，硝酸改性与氢氧化钾改性相比具有优越的性能，当应用于好氧降解时，可以增加生物炭的化学属性并减少氨排放。最后，发现生物炭氨氮吸附能力和堆肥过程中氨排放量之间存在显着的线性相关性（p 值 < 0.05，r = 0.79），表明该变量作为预测参数的潜力。这项研究为未来的探索提供了见解，旨在开发生物炭性能的预测测试。