The novel coronavirus (2019-nCoV) originated in China has now covered around 213 countries globally. It has posed health calamities which have threatened the world with the emergence. Owing to the number of confirmed cases still rising every day, it has now become a phase of an international health emergency. Sudden outbreak of coronavirus disease 2019 (COVID-19) has brought global declines in the commodity process. This has majorly affected the demand as well as supply of the commodities. The oil market has been severely affected due to the outrageous collapse in the demand majorly due to travel restrictions which has also caused the steepest decline in oil prices. The prices of both precious and industrial metals have also fallen, although the price drop is less than that of oil prices. The agriculture industry is one of the least affected so far by this pandemic due to its indirect relation with economic activities. However, the ultimate impact of COVID-19 pandemic will greatly depend on the severity and duration of its outspread, but it is expected to have long-lasting implications.

Land use modifications associated with urbanization, such as clearance of vegetation, replacement of previously pervious areas with impervious surfaces and drainage channel modifications, result in increased runoff volumes, which often create flooding hazards and increase pollutant transport. An attempt has been made in the present study to investigate stormwater quality from five different urban sub-watersheds (that differ in land use and development activities) in the city of Patiala, India. The five sub-watersheds have similar geological, topographical and climatic conditions and were chosen to minimize the effect of these characteristics on stormwater quality and quantity. Stormwater samples were collected during six storm events between April 2010 and March 2011 and analyzed for BOD₅, COD, TSS, TDS, Oil and Grease, TKN, Total P, Coliforms and Heavy Metals (Zn, Cd, Ni, Pb, Fe and Cu). Results of the investigation indicate a strong correlation between land use and development activities and the resulting stormwater quality. TSS, COD and Oil and Grease were found to be major pollutants in surface runoff generated from commercial and urbanized catchments (all exceeded the surface water quality standards developed by Central Pollution Control Board, India). The water quality of the smaller residential catchment was better as compared to other catchments. Principal component analysis was investigated to identify linkages between stormwater quality and urban surface types. It was also confirmed through regression analysis that both antecedent dry period and rainfall intensity have telling influence on stormwater quality. Results obtained can provide practical information for improved stormwater management.

Eco-efficient anaerobic ammonium oxidation (ANAMMOX) can eliminate toxic nutrients from wastewater and has been used in several nutrient removal technologies. However, its implementation for robust operation remains challenging because of process nonlinearity and time-variant characteristic, higher energy consumption, excess sludge produced, and biomass loss during sludge pumping. Also, sensor failure, process startup, and shut down present additional difficulties. In this article, an intelligent human–machine interface using an advanced numerical solution for a knowledge-based system (called ANKSys) was developed by integrating the fully optimized-functionality (soft sensing, decision making, and simulating model) data driven by supervisory control. This control consists of advanced algorithms (artificial neural network, Kalman filter, principal component analysis, least-square technique/renowned root-mean-squared error) using commercial software (MATLAB R2018a, Microsoft Visual Studio IDE 2016, Microsoft SQL Server 2014, OPC Automation with XGT series programmable logic controller). The developed ANKSys can help in online monitoring and optimal process operation by assessing risk and failure occurrences, acquiring data for data analysis, and managing operating expenditure. In real-time implementation, ANKSys enhanced the energy efficiency, i.e., 16% of a pilot-scale “LEAOX” wastewater treatment plant located at Daegu, Republic of Korea. Using this strategy, an optimal and sustainable operation for the removal of biological nitrogen was achieved.