This article reviews recent studies applying machine learning (ML) approaches to biochar applications. We first briefly introduce the general biochar production process. Various aspects are contained, including the biochar application in the elimination of heavy metals and/or organic compounds and the biochar application in environmental and economic scopes, for instance, food security, energy, and carbon emission. The utilization of ML methods, including ANN, RF, and NN, plays a vital role in evaluating and predicting the efficiency of biochar absorption. It has been proved that ML methods can validly predict the adsorption effectiveness of biochar for water heavy metals with higher accuracy. Moreover, the literature proposed a comprehensive data-driven model to forecast biochar yield and compositions under various biomass input feedstock and different pyrolysis criteria. They said a 12.7% improvement in prediction accuracy compared to the existing literature. However, it might need further optimization in this direction. In summary, this review concludes increasing studies that a well-trained ML method can sufficiently reduce the number of experiment trials and working times associated with higher prediction accuracy. Moreover, further studies on ML applications are needed to optimize the trade-off between biochar yield and its composition.

The world faces unprecedented threats from climate change and increasing variability, which severely impacts human society and the natural environment. To reduce future climate change and ensure our economies can grow in a sustainable way, sustainable energy development is considered to be an effective approach. In this context, sustainable energy development involves augmenting our energy supplies and managing demands in a fashion that societal energy needs are met with a minimal effect on greenhouse gas emissions and a nominal resultant contribution to future climate change. In this Special Issue, research papers focus on the role of sustainable energy development (while addressing important dimensions of sustainability), which mandates an inter-disciplinary perspective in all articles. We collected 11 such papers that have analyzed a broad array of topics related to bioenergy, wind power, industrial innovation, and climate change mitigation. These papers show the varied application of renewable energy and climate change energy responses, while providing meaningful decision-making information and policy implications.

Taiwan imports more than 99% of her energy and suffers from climate change effects such as rising ocean level. Therefore, energy insecurity and GHG emissions offset are two serious problems facing Taiwan. This paper examines the possibilities for domestic bioenergy production in Taiwan utilizing set-aside land. Three bioenergy alternatives are examined: Pyrolysis-based bioelectricity, conventional bioelectricity and ethanol. We examine the comparative economics and choices among these alternatives under current Taiwanese agricultural system policies and also under altered energy and greenhouse gas/carbon prices. Biochar, produced from pyrolysis, is also investigated for different uses: whether it is best used as an energy source and/or a soil amendment. The study employs modified Taiwanese Agricultural Sector Model (TASM) to simulate the effects of the alternatives in the face of energy and greenhouse gases prices. Results show that ethanol production is chosen under current conditions but that this is replaced by pyrolysis-based bioelectricity when the GHG price is high. The results also indicate that Taiwan's energy security can be enhanced by domestic bioenergy production and up to1.59% of total GHG emissions can be offset.

Pyrolysis and gasification are considered as a means of producing renewable energy and improving energy sustainability, which has become attractive renewable technologies to many countries. Unlike other studies that are conducted in small scale, this study aims to aggregate the economic and environmental effects such as agricultural benefits, energy sale, and carbon sequestration to provide more detailed information to decision-makers before these projects are widely employed. This study first employs a lifecycle assessment to investigate the feasibility, profitability, and emission reduction of four major pyrolysis and gasification technologies using crop residuals, and then conducts a sensitive analysis to examine the most influential factors. The results indicate that the intermediate pyrolysis with rice straw and slow pyrolysis from corn stover could offset the carbon dioxide the most. However, the pyrolysis value is also sensitive to production of the feedstock used. Value adding of stover-based biochar under fast pyrolysis improves profitability but other technologies do not have such patterns. Additionally, while gasification can generate considerable amount of renewable electricity, it yields almost zero percent of biochar that can be used as a soil amendment, and thus its contribution to agricultural sector is trivial.