Plastic waste production around the world is increasing, which leads to global plastic waste pollution. The need for an innovative solution to reduce this pollution is inevitable. Increased recycling of plastic waste alone is not a comprehensive solution. Furthermore, decreasing fossil-based plastic usage is an important aspect of sustainability. As an alternative to fossil-based plastics in the market, bio-based plastics are gaining in popularity. According to the studies conducted, products with similar performance characteristics can be obtained using biological feedstocks instead of fossil-based sources. In particular, bioplastic production from microalgae is a new opportunity to be explored and further improved. The aim of this study is to determine the current state of bioplastic production technologies from microalgae species and reveal possible optimization opportunities in the process and application areas. Therefore, the species used as resources for bioplastic production, the microalgae cultivation methods and bioplastic material production methods from microalgae were summarized.

The biogas production technology has improved over the last years for the aim of reducing the costs of the process, increasing the biogas yields, and minimizing the greenhouse gas emissions. To obtain a stable and efficient biogas production, there are several design considerations and operational parameters to be taken into account. Besides, adapting the process to unanticipated conditions can be achieved by adequate monitoring of various operational parameters. This paper reviews the research that has been conducted over the last years. This review paper summarizes the developments in biogas design and operation, while highlighting the main factors that affect the efficiency of the anaerobic digestion process. The study’s outcomes revealed that the optimum operational values of the main parameters may vary from one biogas plant to another. Additionally, the negative conditions that should be avoided while operating a biogas plant were identified.

In the biogas plants, organic material is converted to biogas under anaerobic conditions through physical and biochemical processes. From supply of the raw material to the arrival of the products to customers, there are serial processes which should be sufficiently monitored for optimizing the efficiency of the whole process. In particular, the anaerobic digestion process, which consists of sequential complex biological reactions, requires improved monitoring to prevent inhibition. Conventional implemented methods at the biogas plants are not adequate for monitoring the operational parameters and finding the correlation between them. As Artificial Intelligence has been integrated in different areas of life, the integration of it into the biogas production process will be inevitable for the future of the biogas plant operation. This review paper first examines the need for monitoring at the biogas plants with giving details about the process and process monitoring as well. In the following sections, the current situation of implementations of Artificial Intelligence in the biogas plant operation and in the similar industries will be represented. Moreover, considering that all the information gathered from literature and operational needs, an implementation model will be presented.

Process optimization is no longer an option for processes, but an obligation to survive in the market in any industry. This argument also applies to anaerobic digestion in biogas plants. The contribution of biogas plants to renewable energy can be increased through more productive systems with less waste, which brings the common goal of minimizing costs and maximizing yields in processes. With the help of data science and predictive analytics, it is possible to take conventional process optimization and operational excellence methods, such as statistical process control and Six Sigma, to the next level. The more advanced the process optimization aspect, the more transparent and responsive the systems. In this study, seven different machine learning algorithms—linear regression, logistic regression, K-NN, decision trees, random forest, support vector machine (SVM) and XGBoost—were compared with laboratory results to define and predict the possible impacts of wide range temperature fluctuations on process stability. SVM provided the best accuracy with 0.93 according to the metric precision of the models calculated using the confusion matrix.

This work aimed to estimate the annual methane production from the municipal solid waste disposal sites in Pakistan. In this study, the Intergovernmental Panel on Climate Change (IPCC) default methodology was used to estimate theoretical methane formation potential of the waste disposal sites in major cities of Pakistan. The estimates of this study are based on the last population census conducted in the year 2017 and latest available data regarding the waste generation and management practices in the cities considered in the study. Results showed that 31.18 million tonnes of municipal solid waste (MSW) is generated annually. The top 10 major populated cities in Pakistan (with 20% share in country’s population) contributing 31% share in the total quantity of MSW generated in overall country. On average 50–60% of the MSW generated is collected and openly dumped at the designated waste disposal sites. After analyzing the data, we estimate that annually 12.8 MtCO₂-eq of methane is emitted from the waste disposal sites in major cities considered in this study. The methane produced from the waste disposal sites can be sustainably utilized as a source of energy through transforming MSW disposal sites (open dumps) to sanitary landfills with methane capturing and utilization facilities. In the present scenario of waste management and methane formation potential, sanitary landfills would generate 62.35 MWh of electric power if 25% of the methane was recovered and utilized in power generation.

Sustainable management of municipal solid waste is one of the major challenges for authorities in developing countries. Current waste disposal methods in Pakistan and other developing countries are not meeting standards of any proper waste management system opted for in the developed world. This mismanagement of waste is leading to serious environmental problems at local as well as global levels. This study aims to investigate the methane emissions from waste dumpsites in the city of Karachi, Pakistan, and to propose an effective approach to enhance their environmental sustainability. The methane emissions from waste disposal sites were assessed by simulating four different landfill situations during the landfill simulation reactor experiment. The residual methane reduction potential of each waste disposal approach was assessed by a biochemical methane test of waste after the experiment. It is estimated that in the present situation, about 11,500 tons of CO₂-eq methane is released annually from waste disposal sites in Karachi. The convectional anaerobic landfill with methane capturing facilities and post-aeration operation was found to be the most environmentally sustainable approach with controlling 65% of residual methane emissions in comparison with the present scenario. For the development of new landfill sites, we recommend the bioreactor landfill approach with methane recovery and post-care (in-situ aeration).