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Environmental factors may operate differently when relations are measured across different geographical locations, a phenomenon known as spatial non-stationarity. This study investigates the spatial non-stationarity effect of unhealthy food environments and green spaces on the T2DM prevalence rate at the neighborhood level in Toronto. This study also compares how the results vary between age groups, classified as all adults (20 and above), young adults (from 20 to 44), middle adulthood (from 45 to 64), and seniors (65 and above). The geographically weighted regression model is utilized to explore the impacts of spatial non-stationarity effects on the research results, which may lead to biased conclusions, which have often been ignored in past studies. The results from this study reveal that environmental variables dissimilarly affect T2DM prevalence rates among different age groups and neighborhoods in Toronto after controlling for socioeconomic factors. For example, the green space density yields positive associations with diabetes prevalence rates for elder generations but negative relationships for younger age groups in twenty-two and four neighborhoods, respectively, around Toronto East. The observed associations will provide beneficial suggestions to support government and public health authorities in designing education, prevention, and intervention programs targeting different neighborhoods to control the burden of diabetes.

This study aimed to realize Sustainable Development Goals (SDGs), i.e., no poverty, zero hunger, and sustainable cities and communities through the implementation of an intelligent cattle-monitoring system to enhance dairy production. Livestock industries in developing countries lack the technology that can directly impact meat and dairy products, where human resources are a major factor. This study proposed a novel, cost-effective, smart dairy-monitoring system by implementing intelligent wireless sensor nodes, the Internet of Things (IoT), and a Node-Micro controller Unit (Node-MCU). The proposed system comprises three modules, including an intelligent environmental parameter regularization system, a cow collar (equipped with a temperature sensor, a GPS module to locate the animal, and a stethoscope to update the heart rate), and an automatic water-filling unit for drinking water. Furthermore, a novel IoT-based front end has been developed to take data from prescribed modules and maintain a separate database for further analysis. The presented Wireless Sensor Nodes (WSNs) can intelligently determine the case of any instability in environmental parameters. Moreover, the cow collar is designed to obtain precise values of the temperature, heart rate, and accurate location of the animal. Additionally, auto-notification to the concerned party is a valuable addition developed in the cow collar design. It employed a plug-and-play design to provide ease in implementation. Moreover, automation reduces human intervention, hence labor costs are decreased when a farm has hundreds of animals. The proposed system also increases the production of dairy and meat products by improving animal health via the regularization of the environment and automated food and watering. The current study represents a comprehensive comparative analysis of the proposed implementation with the existing systems that validate the novelty of this work. This implementation can be further stretched for other applications, i.e., smart monitoring of zoo animals and poultry.

This study discusses the flooding related consequences of climate change on most populous Canadian cities and flow regulation infrastructure (FRI). The discussion is based on the aggregated results of historical and projected future flooding frequencies and flood timing as generated by Canada-wide hydrodynamic modelling in a previous study. Impact assessment on 100 most populous Canadian cities indicate that future flooding frequencies in some of the most populous cities such as Toronto and Montreal can be expected to increase from 100 (250) years to 15 (22) years by the end of the 21st century making these cities highest at risk to projected changes in flooding frequencies as a consequence of climate change. Overall 40–60% of the analyzed cities are found to be associated with future increases in flooding frequencies and associated increases in flood hazard and flood risk. The flooding related impacts of climate change on 1072 FRIs located across Canada are assessed both in terms of projected changes in future flooding frequencies and changes in flood timings. Results suggest that 40–50% of the FRIs especially those located in southern Ontario, western coastal regions, and northern regions of Canada can be expected to experience future increases in flooding frequencies. FRIs located in many of these regions are also projected to experience future changes in flood timing underlining that operating rules for those FRIs may need to be reassessed to make them resilient to changing climate.

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.

Abstract The importance of integrating resources criticality assessment into Life Cycle Assessment (LCA) under the Life Cycle Sustainability Assessment (LCSA) framework has been discussed for some time. However, the question how to proceed towards integration remain unclear. Only very few work is published on this issue and to our knowledge only Schneider et al. (2014) have developed one operational model. In this paper we review existing literature critically and explain why integration is important and how it could be done, using knowledge from outside the LCA field. The criticality assessment method proposed by Graedel et al. (2012) is identified as the best starting point. This paper shows based on a critical review why bridging towards such a method could help addressing criticality in LCSA, what are possible options and which research needs exists. It reveals that currently LCA does not adequately cover resource criticality and that methods like Graedel et al. (2012) are inspiring further development of LCA; both approaches have a complementary nature and hence could be developed towards integration within the LCSA framework. Currently resource indicators are not meaningful in LCA, wherefore there is no consensus in LCA community on what to recommend; hence the Area of Protection Natural Resources needs to be rethought. Broadening the scope of LCA towards LCSA provides a conceptual framework to keep LCA relevant for assessing sustainability challenges like access to resources.

Rivers are significant sources of greenhouse gases (GHGs; e.g., CH4 and CO2); however, our understanding of the large-scale longitudinal patterns of GHG emissions from rivers remains incomplete, representing a major challenge in upscaling. Local hotspots and moderate heterogeneities may be overlooked by conventional sampling schemes. In August 2020 and for the first time, we performed continuous (once per minute) CH4 measurements of surface water during a 584-km-long river cruise along the German Elbe to explore heterogeneities in CH4 concentration at different spatial scales and identify CH4 hotspots along the river. The median concentration of dissolved CH4 in the Elbe was 112 nmol L−1, ranging from 40 to 1,456 nmol L−1 The highest CH4 concentrations were recorded at known potential hotspots, such as weirs and harbors. These hotspots were also notable in terms of atmospheric CH4 concentrations, indicating that measurements in the atmosphere above the water are useful for hotspot detection. The median atmospheric CH4 concentration was 2,033 ppb, ranging from 1,821 to 2,796 ppb. We observed only moderate changes and fluctuations in values along the river. Tributaries did not obviously affect CH4 concentrations in the main river. The median CH4 emission was 251 μmol m−2 d−1, resulting in a total of 28,640 mol d−1 from the entire German Elbe. Similar numbers were obtained using a conventional sampling approach, indicating that continuous measurements are not essential for a large-scale budget. However, we observed considerable lateral heterogeneity, with significantly higher concentrations near the shore only in reaches with groins. Sedimentation and organic matter mineralization in groin fields evidently increase CH4 concentrations in the river, leading to considerable lateral heterogeneity. Thus, river morphology and structures determine the variability of dissolved CH4 in large rivers, resulting in smooth concentrations at the beginning of the Elbe versus a strong variability in its lower parts. In conclusion, groin construction is an additional anthropogenic modification following dam building that can significantly increase GHG emissions from rivers.

In the past 10 years, the implementation of grassland ecological compensation policy has played an important role in the sustainable development of the pastoral economy. How much impact on herders will delineating the ecological conservation redline have? Such delineation is significant for the smooth implementation of the ecological conservation redline. Based on this, taking the three banner counties with a large area under the control area of the ecological redline of the Xilin Gol as examples, OLS and quantile regression were used to analyze the impact of a grassland ecological compensation policy on herdsmen’s income level, and the ordered Probit model was used to analyze the influencing factors of herdsmen’s satisfaction with the policy. The results show that: (1) grassland ecological compensation has a significant positive impact on low-income herders in ecological protection redline areas; (2) grassland ecological compensation, income and the implementation of current policy have a positive impact on the satisfaction of herders in the redline area; (3) herdsmen are highly satisfied with the grassland ecological compensation policy, but there is still a lot of room for improvement in the compensation policy after the redline is delineated. In this regard, we should increase compensation for areas with a high proportion of ecological conservation redlines, and explore ways to increase income from animal husbandry products. At the same time, we should strengthen the publicity of ecological protection redline policies and promote the timely disbursement of funds, reconstruct the grassland ecological compensation mechanism by strengthening policy incentives and hardening regulatory constraints, and effectively improve the policy efficiency of ecological protection redlines.

Although traditional agriculture carried out by ethnic groups is considered for its high biodiversity and important for food security and sovereignty, few studies have investigated the potential of these systems in the interest of promoting a sustainable agricultural development policy according to United Nations Sustainable Development Goals. Using the FAO's Sustainability Assessment of Food and Agriculture (SAFA) methodology, this study analyzed the sustainability of four traditional agricultural systems, three indigenous (Waorani, Shuar, and Kichwa) and one migrant settler populations in the Yasuní Biosphere Reserve (YBR) and identified synergies and trade-offs among the dimensions of sustainability. The results showed different dynamics in all dimensions of sustainability-specifically, trade-offs in the dimensions of good governance with environmental integrity and social well-being, economic resilience, and social well-being. It was identified that the differences in terms of sustainability are narrowing between the indigenous Shuar people's traditional agricultural systems and those of migrant settlers, which provides policymakers with specific information to design sustainable development policies and rescue traditional agricultural systems in the Amazon region.