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Multifunctionality of urban agriculture can support the resolve of many urban challenges. Therefore, it is vital to understand the contribution of academic studies on urban agriculture practices as scientific information. The present study followed a systematic literature review based on the PRISMA method. Finally, 54 identified articles were analyzed. The review study mainly examined the contribution of academic literature on urban agriculture under four dimensions: the socio-economic context of the country, type of agriculture model, opportunities, and challenges. The results revealed the focus of academic literature on urban agriculture to show favoritism toward developed countries’ community gardens. Moreover, the leading academic focus on this discipline identifies multifunctionality. People’s motivations in developed countries tend to favor social, health-related, and educational benefits of urban agriculture; however, in developing countries, urban agriculture is more related to economic and ecological needs. Challenges for urban agriculture are also different among developed and developing countries. Nevertheless, existing academic studies have given comparatively less attention to identifying challenges, benefit groups of urban agriculture, and government support. Since urban agriculture is highly reliant on local factors, studying more about opportunities and challenges for urban agriculture under different socio-economic contexts and different agriculture models could be more beneficial to connect farming practices in cities with urban planning. Therefore, to make an adequate academic contribution to urban sustainability, future urban agriculture studies need to be more holistic.

Purpose – This paper aims to explore the process by which four store environment (music, light, employee, and layout) and two individual characteristics (shopping enjoyment tendency (SET) and impulse buying tendency (IBT)) influence impulse buying behavior through positive and negative affect, and urge to buy impulsively. Design/methodology/approach – The data were obtained using a structured questionnaire from 733 respondents in a mall survey conducted in Chennai, South India. Findings – In the structural model tested with AMOS, the authors found that store environment drove impulse buying (IB) through positive affect and urge. Results also showed that the personality variables (SET and IBT) influenced IB through positive affect and urge. This paper did not find support for the relationship between negative affect and urge. Research limitations/implications – Theoretically, the authors add to the list of antecedents of impulse buying, and to the outcomes of store environment. From a managerial viewpoint, the authors suggest that retail managers invest in improving the store environment to increase the level of impulse buying in their stores. Specifically, they need to focus on enhancing friendliness of store employees, playing appropriate music, designing proper layouts and having well-lit stores to encourage impulse buying. Originality/value – Prior research studied the elements of the store independently and also its long-term impact. To the best of the authors' knowledge, their research is the first to study the impact of store environment (in conjunction with trait variables) on impulse buying.

Water plays a vital role in human socioeconomic development and overall well-being, making its effective management essential in achieving the Sustainable Development Goals. The close interlinkage between water, other environmental resources, and socioeconomic development have prompted the emergence and adoption of holistic and trans-sectoral concepts such as integrated water resources management and, more recently, the resource nexus. However, even such holistic approaches often exclude the one health approach, particularly at the transboundary water basins (TWBs), which not only dominate 40% of the earth but are vital in environmental and human sustainability. This review aimed to understand, evaluate, and compare assessment tools for water, energy, food, and one health (WEF + H) nexus management in TWBs. The review applied the systematic review guidelines for articles published in the Scopus database. The inclusion criteria encompassed English-language articles featuring case studies, meta-studies, or review articles with no less than three nexus resources. The review categorized the article based on criteria that focused on identifying tools capable of analyzing scenarios and policies for WEF + H in TWBs and their accessibility and easiness of implementation in case studies. Of the eighteen analyzed tools, 13 (72%) had limitations in their application at various geographical scales. Additionally, they could not integrate one health into the nexus or analyze policies through running scenarios. On the contrary, the Bayesian networks, system dynamics, agent-based models, life-cycle assessments, and input-output tools were highly accessible for efficiently conducting scenario-based WEF + H nexus assessments in TWBs.

This paper undertakes a systematic review of the literature to understand current trends in the food–energy–water (FEW) nexus for development-oriented policy support. The paper follows three steps: (a) a bibliometric analysis of FEW nexus research, (b) a content analysis of FEW nexus research, and (c) development of a framework that fills existing gaps in FEW nexus research. The review found that FEW nexus approaches have gained ground in academia as a resource management tool and policy guide; however, the process does not have a robust conceptualization. The current FEW nexus approaches focus on national, regional, and international scales of analysis to understand the three sectors’ interactions. Further, these approaches underline the nexus processes, which have been researched in detail, including synergies and tradeoffs. However, research on the FEW nexus has not adequately explored the social factors that form part of the nexus, especially at the local household scale. Factors such as the gender dynamics of resource ownership, work roles at different scales, household incomes, and culture are essential components that are yet to be explored in FEW nexus research. Most of the existing frameworks on the FEW nexus overemphasize models and the quantitative measurement of processes while paying limited attention to social aspects. Still, these social aspects are crucial, especially on the household scale; therefore, to overcome these gaps, this paper proposes a FEW nexus framework at the local household scale that includes socio-economic determinants.

Nepal’s efforts to reduce manufacturing-related water pollution have faltered because they rely on traditional methods and regulation. We employed an environmentally extended input–output model to establish direct and indirect relations between water pollution and production in 19 Nepalese manufacturing sectors. We identify which are chief emitters of biochemical oxygen demand and total suspended solids. We categorize three sectors as pollution abatement industries (heavy polluters that portend relatively low clean-up costs) and three as pollution prevention industries (polluters responsible for accelerating pollution by inducing the release of pollutants from other linked sectors). We then draw upon statistical analysis to recommend appropriate pollution-reducing incentives or penalties for both categories. We find that incentives to meet discharge standards are effective for pollution abatement industries and that penalties (e.g., polluter pay) are effective in pollution prevention industries because they underpin Nepal’s economy. If these policies do not succeed as desired, emission control policies are warranted.

Cropping intensity is one of the most important decisions made independently by farmers in Vietnam. It is a crucial variable of various economic and process-based models. Rice is grown under irrigated triple- and double-rice cropping systems and a rainfed single-rice cropping system in the Vietnamese Mekong Delta (VMD). These rice cropping systems are adopted according to the geographical location and water infrastructure. However, little work has been done to map triple-cropping of rice using Sentinel-1 along with the effects of water infrastructure on the rice cropping intensity decision. This study is focused on monitoring rice cropping patterns in the An Giang province of the VMD from March 2017 to March 2018. The fieldwork was carried out on the dates close to the Sentinel-1A acquisition. The results of dual-polarized (VV and VH) Sentinel-1A data show a strong correlation with the spatial patterns of various rice growth stages and their association with the water infrastructure. The VH backscatter (σ°) is strongly correlated with the three rice growth stages, especially the reproductive stage when the backscatter is less affected by soil moisture and water in the rice fields. In all three cropping patterns, σ°VV and σ°VH show the highest value in the maturity stage, often appearing 10 to 12 days before the harvesting of the rice. A rice cropping pattern map was generated using the Support Vector Machine (SVM) classification of Sentinel-1A data. The overall accuracy of the classification was 80.7% with a 0.78 Kappa coefficient. Therefore, Sentinel-1A can be used to understand rice phenological changes as well as rice cropping systems using radar backscattering.

Wastewater-based epidemiology (WBE) is an approach that can be used to estimate COVID-19 prevalence in the population by detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. As the WBE approach uses pooled samples from the study population, it is an inexpensive and non-invasive mass surveillance method compared to individual testing. Thus, it offers a good complement in low- and middle-income countries (LMICs) facing high costs of testing or social stigmatization, and it has a huge potential to monitor SARS-CoV-2 and its variants to curb the global COVID-19 pandemic. The aim of this review is to systematize the current evidence about the application of the WBE approach in mass surveillance of COVID-19 infection in LMICs, as well as its future potential. Among other parameters, population size contributing the fecal input to wastewater is an important parameter for COVID-19 prevalence estimation. It is easier to back-calculate COVID-19 prevalence in the community with centralized wastewater systems, because there can be more accurate estimates about the size of contributing population in the catchment. However, centralized wastewater management systems are often of low quality (or even non-existent) in LMICs, which raises a major concern about the ability to implement the WBE approach. However, it is possible to mobilize the WBE approach, if large areas are divided into sub-areas, corresponding to the existing wastewater management systems. In addition, a strong coordination between stakeholders is required for estimating population size respective to wastewater management systems. Nevertheless, further international efforts should be leveraged to strengthen the sanitation infrastructures in LMICs, using the lessons gathered from the current COVID-19 pandemic to be prepared for future pandemics.

Urbanization and concomitant challenges pose a great threat to sustainable development. Urban and rural development interacts through the flows of people, materials, energy, goods, capital, and information. Without building sound urban–rural linkages, achieving development in one area could compromise it in another area. Achieving sustainable development needs customized policy prioritization and implementation in both urban and rural areas. Much literature exists in the research field of urban–rural linkages, but little has been done via a comprehensive analysis from an interlinkage perspective in the context of the Sustainable Development Goals (SDGs). Sustainable Development Goal 11 on sustainable cities and several targets embedded under other Goals provides a good framework for analyzing the urban–rural linkages. This paper contributes to this novel research perspective using Ghana as a case. The study applied an integrated approach by combining the results from a solution-scanning exercise with an SDG interlinkage analysis to identify the challenges and priority solutions and assess the synergies and trade-offs of the identified solutions. It extends the conventional solution-scanning approach by further assessing the synergies and trade-offs of the solutions from an SDG interlinkage perspective. It also enables a more practical SDG interlinkage analysis through the contributions from the multi-stakeholder consultations conducted in Ghana. The analyses show that prioritizing gender inclusion (Goal 5) will positively affect many social and well-being outcomes, including poverty elimination (Goal 1), hunger reduction (Goal 2), health improvement (Goal 3) and access to quality education (Goal 4) and basic services, such as water (Goal 6). However, gender inclusion could have potential trade-offs in the agricultural sector (Goal 2) in the case that women who dominate agricultural value chains could move to work in other sectors. Lack of proper infrastructure (Goal 9), such as transport, will hinder wide gender inclusion. An integrated approach that considers both the synergies and trade-offs of relevant solutions is critical for effective policymaking, specifically in developing countries.

Global climate changes significantly contribute to increased frequency of hydrologic extremes. This significantly underestimates the hydrologic design parameters, bringing of hydro systems to increased failure risk. In order to address this concern, the current practice of development of hydrologic frequency tools need to be updated accounting for non-stationarity. This study first considered a diverse set of statistical tests to examine the trend, change points, non-stationarity and randomness of streamflow, rainfall and temperature time series of scales ranging from daily to annual. The annual maxima time series indicated non stationarity against the stationary behaviour of daily series of hydro-meteorological datasets of the basin. Subsequently, this study developed the Temperature Duration Frequency (TDF), Rainfall Intensity Duration Frequency (IDF) and Flood Frequency (FF) curves of Greater Pamba river basin in Kerala India, the part of which was most severely affected by the near century return period flood event of 2018. The analysis was performed for a multitude of combinations of variations in distribution parameters with time and climatic drivers as physical covariates in the extreme value formulations. The study proposed a novel wavelet coherence (WC) based driver selection of most dominant combination of climatic precursors in developing FF and IDF relations of three locations of Kalloopara, Malakkara and Thumpamon and TDF curve of Kuttanad region in the basin, considering data of 1985–2015 period. The proposed WC framework considers bi-multi-and partial effects of climatic oscillations (COs) like El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO) in identifying potential drivers. The different WC formulations captured in-phase relationships of streamflows and rainfall with COs at intra-annual, annual and inter annual scales up to 4 years. The methods showed that addition of climatic precursors improved the NS estimates of flood and rainfall quantiles by more accurately capturing the magnitudes of extreme streamflows and rainfalls of 2018, 2021 than the time covariate formulations. However, the role of COs on extreme temperature is not found to be influential in developing TDF relationships, which needs further investigation.

For countries in Southeast Asia that mainly rely on surface water as their water resource, changes in weather patterns and hydrological systems due to climate change will cause severely decreased water resource availability. Warm weather triggers more water use and exacerbates the extraction of water resources, which will change the operation patterns of water usage and increase demand, resulting in water scarcity. The occurrence of prolonged drought upsets the balance between water supply and demand, significantly increasing the vulnerability of regions to damaging impacts. The objectives of this study are to identify trends and determine the impacts of extreme drought events on water levels for the major important water dams in the northern part of Borneo, and to assess the risk of water insecurity for the dams. In this context, remote sensing images are used to determine the degree of risk of water insecurity in the regions. Statistical methods are used in the analysis of daily water levels and rainfall data. The findings show that water levels in dams on the North and Northeast Coasts of Borneo are greatly affected by the extreme drought climate caused by the Northeast Monsoon, with mild to the high risk recorded in terms of water insecurity, with only two of the water dams being water-secure. This study shows how climate change has affected water availability throughout the regions.