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Sufficient production, consistent food supply, and environmental protection in urban +settings are major global concerns for future sustainable cities. Currently, sustainable food supply is under intense pressure due to exponential population growth, expanding urban dwellings, climate change, and limited natural resources. The recent novel coronavirus 2019 (COVID-19) pandemic crisis has impacted sustainable fresh food supply, and has disrupted the food supply chain and prices significantly. Under these circumstances, urban horticulture and crop cultivation have emerged as potential ways to expand to new locations through urban green infrastructure. Therefore, the objective of this study is to review the salient features of contemporary urban horticulture, in addition to illustrating traditional and innovative developments occurring in urban environments. Current urban cropping systems, such as home gardening, community gardens, edible landscape, and indoor planting systems, can be enhanced with new techniques, such as vertical gardening, hydroponics, aeroponics, aquaponics, and rooftop gardening. These modern techniques are ecofriendly, energy- saving, and promise food security through steady supplies of fresh fruits and vegetables to urban neighborhoods. There is a need, in this modern era, to integrate information technology tools in urban horticulture, which could help in maintaining consistent food supply during (and after) a pandemic, as well as make agriculture more sustainable.

Few studies on population-specific health effects of extreme temperature on cardiovascular diseases (CVDs) deaths have been conducted in the subtropical and tropical climates of China. We examined the association between extreme temperature and CVD across four cities in China. We performed a two-stage analysis; we generated city-specific estimates using a distributed lag non-linear model (DLNM) and estimated the overall effects by conducting a meta-analysis. Heat thresholds of 29 °C, 29 °C, 29 °C, and 30 °C and cold thresholds of 6 °C, 10 °C, 14 °C, and 15 °C were observed in Hefei, Changsha, Nanning, and Haikou, respectively. The lag periods for heat-related CVD mortality were observed only for 0–2 days, while those of cold-related CVD mortality were observed for 10–15 days. The meta-analysis showed that a 1 °C increase above the city-specific heat threshold was associated with average overall CVD mortality increases of 4.6% (3.0%–6.2%), 6.4% (3.4%–9.4%), and 0.2% (−4.8%–5.2%) for all ages, ≥65 years, and <65 years over a lag period of 0–2 days, respectively. Similarly, a 1 °C decrease below the city-specific cold threshold was associated with average overall CVD mortality increases of 4.2% (3.0%–5.4%), 4.9% (3.5%–6.3%), and 3.1% (1.7%–4.5%), for all ages, ≥65 years, and <65 years over a lag period of 0–15 days, respectively. This work will help to take appropriate measures to reduce temperature-mortality risk in different populations in the subtropical and tropical climates of China.

In this paper, we apply game theory to study the price competition between drugstores and hospitals in China’s pharmaceutical supply chain. Motivated by drug shortages and price disparity problems, we build a simplified model with one supplier, one hospital, and one drugstore in which the sellers sell one kind of drug and compete on price. The hospital receives a discount from the government when ordering the drug and both sellers face a price-sensitive and uncertain demand. The existence and uniqueness of a Nash equilibrium are proved and closed-form solutions are found for linear demand cases. We characterize the pricing and ordering decisions of the hospital and drugstore. The analysis shows that high ex-factory price, high price sensitivity, and a small discount are three factors contributing to drug shortages. We consider two special kinds of linear demand to obtain insights into the drug price disparity problem.

Air pollution is a major issue all over the world because of its impacts on the environment and human beings. The present review discussed the sources and impacts of pollutants on environmental and human health and the current research status on environmental pollution forecasting techniques in detail; this study presents a detailed discussion of the Artificial Intelligence methodologies and Machine learning (ML) algorithms used in environmental pollution forecasting and early-warning systems; moreover, the present work emphasizes more on Artificial Intelligence techniques (particularly Hybrid models) used for forecasting various major pollutants (e.g., PM2.5, PM10, O3, CO, SO2, NO2, CO2) in detail; moreover, focus is given to AI and ML techniques in predicting chronic airway diseases and the prediction of climate changes and heat waves. The hybrid model has better performance than single AI models and it has greater accuracy in prediction and warning systems. The performance evaluation error indexes like R2, RMSE, MAE and MAPE were highlighted in this study based on the performance of various AI models.

In this paper, we have examined the effects of COVID-19 on the socio-economic condition of the three-wheeled electric vehicle drivers in some selected areas of Bangladesh from the cross-sectional data (September–November 2020). The results of linear regression indicate that under COVID-19 conditions, age (p = 0.022) and hardship (p = 0.000) positively, and education (p = 0.036), driving duration (p = 0.023), COVID consciousness (p = 0.086) and easy bike vehicle (p = 0.000) negatively affects income of the respondents. The deaths of COVID in the district (p = 0.003), income (p = 0.000), age (p = 0.037), easy bike vehicle (p = 0.018), debt (p = 0.059) and sufferings of diseases (p = 0.044) positively, and property holdings (p = 0.028), residence in urban areas (p = 0.004) and COVID consciousness (p = 0.082) negatively affect the family expenditure. The results from binary logistics regressions show that diseases sufferings (adjusted p = <0.001; unadjusted p = <0.001), corona fear (unadjusted p = 0.005; adjusted p = <0.001) have positive, and income (unadjusted p = <0.001; adjusted p = <0.001), cooking fuel (unadjusted p = 0.003; adjusted p = 0.091) and easy bike vehicle (unadjusted p = <0.001; adjusted p = 0.288) have negative association with hardship or misery due to COVID-19; death of COVID-19 in the district (unadjusted p = 0.008; adjusted p = 0.037), hardship or misery (adjusted p = 0.005; adjusted p = 0.001), and urban dwelling area (unadjusted p = 0.002; adjusted p = 0.004) have positive, and access to pure drinking water (unadjusted p = 0.005; adjusted p = 0.011) has negative link with corona fear; and, family savings (unadjusted p = 0.001; adjusted p = 0.013), satisfaction in the current job (unadjusted p = <0.001; adjusted p = <0.001), and government medical service (unadjusted p = 0.065; adjusted p = 0.012) have positive affiliation, and household size (unadjusted p = 0.007; adjusted p = 0.020) has negative affiliation with the continuation desire of the current job of respondents. All the obtained results are consistent and have significant policy implications.

The COVID-19 pandemic has brought rampant changes in skill needed in the labor market. It has accentuated technological disruption leaving millions in dire need of reskilling and upskilling. In this paper, we empirically analyze the impact of the COVID-19 pandemic related lockdown on the thrust of skills upgradation among people. By analyzing the Google trends data of 13 countries, we test the effect of the lockdown implementations on the urge to upgrade the skills through online searches for skills enhancement. Using difference-in-difference estimation approach, we found a substantial hike in the frequency of search terms related to skills upgradation. Our results suggest that people are utilizing the excess time, made available due to lockdowns, by exploring avenues to enhance their skills to accumulate human capital. The online educational platforms have been proven vital. The findings of this study establish the causal link between use of online education platforms and human capital development.

The Corona Virus Disease 2019 (COVID-19) has been a tough test on companies in the global food sector supply chain, exacerbating the realities and deficiencies it presents in developing economies. This situation has been reflected in the firm’s performance (F.P.) due to the lack of business conditions to respond to the current pandemic. However, in some companies, the adverse effects of COVID-19 have been counteracted due to endowment and technological capabilities. Thus, this study examined the role of technological innovation (T.I.) and business data analytics (B.D.A.) in the F.P. of foods in Ecuador during COVID-19. A questionnaire collected the information from the food firms. Then, Covariance-Based Structural Equation Modeling processed the collected information. We found that (B.D.A.) mechanisms and different levels of T.I. within the developing market significantly shape the F.P. The results showed that the B.D.A. enables circular economy (C.E.) practices and the improvement of product delivery services, which constitutes an improvement of the F.P. The COVID-19 outbreak did not significantly affect T.I., unlike what happened with B.D.A. This study concluded that firms with the most extraordinary technological production processes have been the least affected during COVID-19. This study suggested that policy measures should boost food firms’ technological endowment to improve their resilience in uncertainty and risk scenarios.

Pollution by organic wastes and manures is an important problem in tropical and sub-tropical countries and novel solutions for their proper management and valorization are needed. Waste-derived organic manures may increase metal load in the soil–plant ecosystem and food chain, with potential risks to public health. The aim of this work was to evaluate the impact of three manures (poultry waste (PW), press mud (PM), and farmyard manure (FYM)) on heavy metals (HMs) (Cd, Co, Cr, Cu, Pb, Zn, Fe, Mn) toxicity in a soil and coriander (Coriandrum sativum L.) system and their environmental impact (bioaccumulation, pollution load) and the consequent risk to human health via consumption. Results demonstrated that HMs in coriander fluctuated from 0.40 to 0.43 for Cd, 1.84 to 3.52 for Co, 0.15 to 0.16 for Cr, 1.32 to 1.40 for Cu, 0.05 to 0.09 for Pb, 1.32 to 2.51 for Fe, 0.10 to 0.32 for Mn, and 2.01 to 8.70 mg/kg for Zn, respectively. Highest pollution load index value was 2.89 for Cd and Mn showed the lowest (0.005). Daily intake of metal was noticed to be higher for Zn (0.049 mg/kg/day) for PW and lower for Mn (0.0005) at FYM treatment. The health risk index value was <1 and in the range of 2.30–2.50 for Cd showing potential carcinogenicity. It was concluded that as the organic amendments have the widest application in vegetables, it should be prudent to avoid their contamination and mobilization in plant–soil ecosystems to protect public health perspectives.