Comparative Analysis for Quantification and Identification of Beverages Industries Effluent of Pakistan Using Advance Multivariate Clustering

Abstract

The water quality is perpetually deteriorating at an alarming rate due to industrial effluent. The treatment and disposal of wastewater, and its reutilization, remain critical concerns for the sustainable consumption of water in the food and beverage sector. In this paper, a comparative analysis of effluents from two beverage industries has been conducted using wastewater chemistry. Both industries are spatially located along the water channel (Nullah) in the industrial estate areas of two major cities (Rawalpindi and Peshawar) in Pakistan. Initial wastewater characterization was conducted through composite sampling techniques to assess compliance with National Environmental Quality Standards for industrial effluent. Descriptive statistical analysis, correlation matrix, and Multiple Linear Regression analysis were performed to identify and quantify the effluent constituents. The effluent from beverage industries exhibited high concentrations of Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD), which degrade the quality of water bodies. Treatment of wastewater in the food and beverage sector is important for water recycling, resource recovery, and environmental protection. In novel approaches to circular economy principles, the consumption and management of water can facilitate resource recovery, leading to higher sustainability and productivity in food production. In water-stressed countries like Pakistan, recycled wastewater can mitigate the adverse environmental and socio-economic impacts. The utilization of wastewater treatment plants, employing chemical, physical, and biological treatment methods to remove sugar, flavors, and color additives, can reduce BOD and COD levels. Considering the large volume of wastewater, it is highly recommended to reuse and recycle the effluent after initial treatment through efficient technologies to minimize organic pollutant loads.