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.

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The outbreak of novel and recent coronavirus disease 2019, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, has made an emergency throughout the world. In India, the outspread of the pandemic was observed on 3 March 2020, and after that exponential growth in the cases was observed in the country. Owing to the widespread transmission, high population density, high testing capacity and ineffective treatment, a continuous rise in cases was observed due to the pandemic in India. In this paper, we have discussed the trend and spread of COVID-19 spread in India with time, history of initial confirmed cases, the impact of phased manner lockdown, age- and gender-wise trend of cases and comparison of cases with the other most affected countries. The study uses exploratory data analysis to describe the current situation of COVID-19 cases in India till 16 August 2020, with the help of data from the Ministry of Health and Family Welfare, Government of India (GOI) and the World Health Organization (WHO). As of August 16, the total number of confirmed cases in India crossed 2.5 million marks with over 50,000 causalities. With more patients recovering and being discharged from hospitals and home isolation (in case of mild and moderate cases), the total recoveries have crossed the 1.8 million mark with a recovery rate of more than 70% and case fatality rate of 1.94% which is maintained below the global average and is on a continuous positive slide. The study also enlightens the preventive and stringent measures taken by India to combat the COVID-19 situation along with the future prospects. The GOI is following its proactive and preemptive approach for management, prevention and containment of COVID-19 in collaboration with the WHO. Electronic supplementary material The online version of this article (10.1007/s10668-020-00963-z) contains supplementary material, which is available to authorized users.

The outbreak of severe acute respiratory syndrome coronavirus 2 is regarded as a highly contagious disease that has challenged the healthcare systems worldwide with confirmed cases approaching 12 million and more than 50,000 deaths. Considering the worldwide cases of novel coronavirus disease (COVID-19), it remains a pandemic and the vaccines and therapeutic agents have yet to be developed to stop the spread of this outbreak. Due to the unavailability of specific treatment for the COVID-19, it can be viewed that the risk of cluster infection will continue to be present within the intermittent and small-scale outbreaks. Though the COVID-19 has been identified as a communicable disease, the preventive measures and response policies in South Korea are effectively serving the purpose and gained the confidence to overcome the COVID-19 crisis. This paper includes the exploratory data analysis of COVID-19 cases in South Korea till July 8, 2020. South Korea has reported the lowest death rate with the majority of the deaths, associated with persons with underlying health conditions or elderly infected individuals. Currently the infected patients (total 989) remaining in South Korea are mild cases owing to its robust health care system and quarantine inspection procedures followed by the Ministry of Health and Welfare of South Korea to flatten the COVID-19 curve. Although the COVID-19 countermeasures taken by the South Korean government may not be conclusive or universal for all, but its exemplary approach to tackle COVID-19 can aid countries across the globe to strengthen their response system for the future outbreak of such an infectious disease. Electronic supplementary material The online version of this article (10.1007/s10668-020-00883-y) contains supplementary material, which is available to authorized users.

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Stormwater management at urban sub-watershed level has been envisioned to include stormwater collection, treatment, and disposal of treated stormwater through groundwater recharging. Sizing, operation and control of the stormwater management systems require information on the quantities and characteristics of the stormwater generated. Stormwater characteristics depend upon dry spell between two successive rainfall events, intensity of rainfall and watershed characteristics. However, sampling and analysis of stormwater, spanning only few rainfall events, provides insufficient information on the characteristics. An attempt has been made in the present study to assess the stormwater characteristics through regression modeling. Stormwater of five sub-watersheds of Patiala city were sampled and analyzed. The results obtained were related with the antecedent dry periods and with the intensity of the rainfall event through regression modeling. Obtained regression models were used to assess the stormwater quality for various antecedent dry periods and rainfall event intensities.

Precise control of biological wastewater treatment for nitrogen removal is difficult because of the nonlinearity, time-varying, and time-consuming nature of the process. With due emphasis on addressing the challenges involved in its effective implementation, this study developed an artificial neural network (ANN) based soft sensor (SS) with a set of proposed thumb rules for online forecasting of the concentrations of hard-to-measure parameters (NH4 + and NO2 −) from secondary easy-to-measure variables, (reactor volume, dissolved oxygen, suspended solids, pH, temperature, and ORP) in an Anammox based pilot plant. Four hybrid neural networks (PCA-Kalman NN, PCA NN, Kalman NN, and Non NN) were applied to identify net optimum input vectors for the SS, using an appropriate quantity of samples from the set of secondary variables. The proposed hybrid SS was tested on a sewage wastewater treatment plant operated using a Matlab R2018a framework and validated using operational plant data. The results showed that the PCA-Kalman neural network with R 2 values of 0.9985 and 0.9263 for NH4 + and NO2 –, respectively, is potentially a valuable tool for plant operators in the selection of operational states to minimize cost and to efficiently predict important parameters that are prone to errors due to a failure in online sensors.