A review on generation, characterization, containment, transport and treatment of fecal sludge and septage with resource recovery-oriented sanitation.

Fecal sludge and septage (FSS) are more concentrated than domestic wastewater which makes it difficult to treat and requires immediate attention otherwise, it leads towards serious environmental problems. In this review, an attempt has been made to highlight and discuss the various aspects of fecal sludge and septage management (FSSM) like its generation, characterization, containment, transportation, treatment, reuse and disposal. A comparison of existing fecal sludge treatment plants and technologies has been reviewed considering land requirement, capital cost, operation and maintenance cost, advantages and disadvantages. Based on the existing practices and review, a techno-economic treatment scheme is designed and proposed for solid-liquid separation and treatment of FSS with resource-recovery as fertilizer, material for construction, energy and treated effluent. To make FSSM, self-sustainable, a revenue generation model is also delineated for the researchers and decision-makers to evaluate its feasibility and implementation, especially in developing and underdeveloped countries.

Estimation of the generation rate of different types of plastic wastes and possible revenue recovery from informal recycling.

Plastic waste generation is an inevitable product of human activities, however its management faces challenges in many cities. Understanding the existing patterns of plastic waste generation and recycling is essential for effective management planning. The present study established a relationship between plastic waste generation rate and the identified socioeconomic groups, higher socioeconomic group (HSEG), middle socioeconomic group (MSEG), and lower socioeconomic group (LSEG) of the study area (Dhanbad, India). For identification of the socioeconomic groups, four different socioeconomic parameters were considered (total family income, education, occupation and type of houses). The information related to the identified parameters were obtained using questionnaire survey conducted in the selected households. One week plastic waste sampling was carried out in the households of all the socioeconomic groups. The plastic waste generated in the study area was 5.7% of the total municipal solid waste. In terms of total plastic waste generation rate, it was found that HSEG had maximum (51 g/c/d) and LSEG had minimum (8 g/c/d) generation rate. The present study area does not have any formal waste recycling system. Thus, the amount of plastic waste recovered and the revenue generated from recycling of plastic waste by the active informal recyclers (waste pickers, itinerant waste buyers and scrap dealers) in the study area have been evaluated. Additionally, three non-linear machine learning models i.e., artificial neural network (ANN), support vector machine (SVM) and random forest (RF) have been developed and compared for the prediction of plastic waste generation rate.