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This study focuses on the embryonic stages of the COVID‐19 pandemic in China, where most people affected opted to abide by the Chinese government’s national self‐quarantine campaign. This resulted in major disruptions to one of the most common market processes in retail: food retailing. The research adopts the theory of planned behaviour to provide early empirical insights into changes in consumer behaviour related to food purchases during the initial stages of the COVID‐19 outbreak in China. Data from the online survey carried out suggest that the outbreak triggered considerable levels of switching behaviours among customers, with farmers’ markets losing most of their customers, while local small independent retailers experienced the highest levels of resilience in terms of customer retention. This study suggests avenues for further scholarly research and policy making related to the impact this behaviour may be having around the world on society’s more vulnerable groups, particularly the elderly.

Nitrous oxide (N 2 O) emissions show large variability among dam reservoirs, which makes it difficult to estimate N 2 O contributions to global greenhouse gases (GHGs). Because river damming alters hydraulic residence time and water depth, the hydraulic load (i.e., the ratio of the mean water depth to the residence time) was hypothesized to control N 2 O emissions from dam reservoirs. To test this hypothesis, we investigated N 2 O fluxes and related parameters in the cascade reservoirs along the Wujiang River in Southwest China. The N 2 O fluxes showed obvious temporal and spatial variations, ranging from −7.86 to 337.22 μmol m −2 d −1 , with an average of 12.76 μmol m −2 d −1 . Nitrification was the main pathway of N 2 O production in these reservoirs, and seasonal dissolved oxygen (DO) stratification played an important role in regulating the N 2 O production. The reservoir N 2 O flux had a significant negative logarithmic relationship with the hydraulic load, suggesting its control of the N 2 O emission. This was because the hydraulic load was a prerequisite for regulating the nitrification−denitrification and the DO stratification in the dam reservoirs. This empirical relationship will help to estimate the contribution of reservoir N 2 O emissions to global GHGs.

Stepwise power tariff (SPT), which has been put into practice, is a crucial way for energy saving and environment protecting. In this paper, a new optimal model of SPT based on residential demand response model is presented. The optimal decision is proposed to restrain high electricity consumption as well as safeguard benefits of both supply and demand sides. As a result, the objective is designed to minimize electricity consumption and constraints are taken into consideration thoroughly, including acceptable index of consumers, average price, sales profit of power providers and basic electricity demand, which serves as a foundation for smooth implement of SPT. To solve the constrained optimal problem, genetic algorithm (GA) is employed. The effectiveness of the model and algorithm is investigated and demonstrated based on real data of 300 residents by a numerical example. The study shows that the method can reduce power consumption obviously with little sacrifice of the benefits of consumers and power providers.Index Terms-Electricity markets, energy saving, stepwise power tariff. NOMENCLATUREElectricity quantity of the step .Upper limit of electricity quantity.Single price before implementing SPT.Unit price of the step after implementation of SPT.Upper limit of price.Clearing price per month.Steps of SPT.