Owing to environmental pollution and increasingly strict regulations, heavy metals have attracted the attention of many researchers in various disciplines. Alginate and chitosan derivatives have gained popularity as biosorbents for water treatment. An increase in the number of publications on modified biosorbents for the biosorption of toxic compounds reveals widespread interest in examining the requirements and positive contribution of each modification type. This paper reviews the advantages and disadvantages of using alginate and chitosan for adsorption. Well-known modifications based on chitosan and alginate, namely, grafting, functionalization, copolymerization and cross-linking, as well as applications in the field of adsorption processes, especially amino acid functionalization, are reviewed. The selection criteria for the best biosorbents and their effectiveness and proposed mechanism of adsorption are discussed critically. In the conclusion, the question of why these adsorbents need modification before use is addressed.

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.

Pakistan is facing a severe energy crisis due to its heavy dependency on the import of costly fossil fuels, which ultimately leads to expansive electricity generation, a low power supply, and interruptive load shedding. In this regard, the utilization of available renewable energy resources within the country for production of electricity can lessen this energy crisis. Livestock waste/manure is considered the most renewable and abundant material for biogas generation. Pakistan is primarily an agricultural country, and livestock is widely kept by the farming community, in order to meet their needs. According to the 2016–2018 data on the livestock population, poultry held the largest share at 45.8%, followed by buffaloes (20.6%), cattle (12.7%), goats (10.8%), sheep (8.4%), asses (1.3%), camels (0.25%), horses (0.1%), and mules (0.05%). Different animals produce different amounts of manure, based upon their size, weight, age, feed, and type. The most manure is produced by cattle (10–20 kg/day), while poultry produce the least (0.08–0.1 kg/day). Large quantities of livestock manure are produced from each province of Pakistan; Punjab province was the highest contributor (51%) of livestock manure in 2018. The potential livestock manure production in Pakistan was 417.3 million tons (Mt) in 2018, from which 26,871.35 million m³ of biogas could be generated—with a production potential of 492.6 petajoules (PJ) of heat energy and 5521.5 MW of electricity. Due to its favorable conditions for biodigester technologies, and through the appropriate development of anaerobic digestion, the currently prevailing energy crises in Pakistan could be eliminated.