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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 evaluated the efficacy of enzyme induced calcite precipitation (EICP) in restricting the mobility of heavy metals in soils. EICP is an environmentally friendly method that has wide ranging applications in the sustainable development of civil infrastructure. The study examined the desorption of three heavy metals from treated and untreated soils using ethylene diamine tetra-acetic acid (EDTA) and citric acid (C6H8O7) extractants under harsh conditions. Two natural soils spiked with cadmium (Cd), nickel (Ni), and lead (Pb) were studied in this research. The soils were treated with three types of enzyme solutions (ESs) to achieve EICP. A combination of urea of one molarity (M), 0.67 M calcium chloride, and urease enzyme (3 g/L) was mixed in deionized (DI) water to prepare enzyme solution 1 (ES1); non-fat milk powder (4 g/L) was added to ES1 to prepare enzyme solution 2 (ES2); and 0.37 M urea, 0.25 M calcium chloride, 0.85 g/L urease enzyme, and 4 g/L non-fat milk powder were mixed in DI water to prepare enzyme solution 3 (ES3). Ni, Cd, and Pb were added with load ratios of 50 and 100 mg/kg to both untreated and treated soils to study the effect of EICP on desorption rates of the heavy metals from soil. Desorption studies were performed after a curing period of 40 days. The curing period started after the soil samples were spiked with heavy metals. Soils treated with ESs were spiked with heavy metals after a curing period of 21 days and then further cured for 40 days. The amount of CaCO3 precipitated in the soil by the ESs was quantified using a gravimetric acid digestion test, which related the desorption of heavy metals to the amount of precipitated CaCO3. The order of desorption was as follows: Cd > Ni > Pb. It was observed that the average maximum removal efficiency of the untreated soil samples (irrespective of the load ratio and contaminants) was approximately 48% when extracted by EDTA and 46% when extracted by citric acid. The soil samples treated with ES2 exhibited average maximum removal efficiencies of 19% and 10% when extracted by EDTA and citric acid, respectively. It was observed that ES2 precipitated a maximum amount of calcium carbonate (CaCO3) when compared to ES1 and ES3 and retained the maximum amount of heavy metals in the soil by forming a CaCO3 shield on the heavy metals, thus decreasing their mobility. An approximate improvement of 30% in the retention of heavy metal ions was observed in soils treated with ESs when compared to untreated soil samples. Therefore, the study suggests that ESs can be an effective alternative in the remediation of soils contaminated with heavy metal ions.

The United Nations’ Sustainable Development Goals (SDGs) rest on a set of broadly accepted values within a human rights framework. The SDGs seek to improve human lives, improve the planet, and foster prosperity. This paper examines the human rights framework and the principles of social justice and shows that, while the SDGs do not specifically state that there is human right to food, the SDGs do envision a better, more just, world which rests upon the sufficiency of the global food supply, on environmental sustainability, and on food security for all. Then the paper examines the interrelationships between the SDGs, food access and waste, and human rights within a framework of social justice. Finally, it looks at the potential pandemic of hunger wrought by COVID-19, showing that COVID-19 serves as an example of a crisis that has raised unprecedented challenges to food loss and waste in the global food supply system and tests our commitment to the principles espoused by the SDGs.

Life cycle sustainability assessment (LCSA) is a still relatively new technique. One of its main application challenges is interpreting the three dimensions of its results in combined fashion. This paper presents the first attempt at an integrated solution-oriented approach in the LCSA, while simultaneously interpreting the results of the three assessments in a combined fashion toward improving the sustainability performance of product systems. It is based on a case study of high-density polyethylene (HDPE) production in Alberta, Canada. The methodology is characterized by five steps: (1) goal and scope definition; (2) inventory analysis; (3) impact assessment; (4) interpretation where the results of the three tools of LCSA are presented and an integrated analysis of the sustainability results following the strong sustainability model and using the Driver–Pressure–State–Impact–Response (DPSIR) framework, is conducted to propose sustainability improvements for the case study product; (5) discussion and conclusion. The integrated approach developed was able to propose some sustainability improvement proposals along the life cycle of HDPE. Yet, challenges exist in interpreting the interrelationships between the three assessment results. Moving from comparative integrated assessment approach in LCSA to solution-oriented approach still faces challenges. This work highlighted some of the research tasks that need more focus from the LCSA community to demonstrate how LCSA can contribute to sustainable development by improving the sustainability performance of product systems.

In supply chain operation practices, lead time uncertainty is a common management issue. Uncertain lead time can lead to increased inventory costs and unstable service levels, which will directly affect the overall operation performance of the supply chain. While considering environmental performance in supply chain, it is important to understand how an uncertain lead time will affect sustainable performance. In this paper, we constructed a supply chain model with stochastic lead time and explored the relationship between uncertain lead time and supply chain performance. We considered carbon cost, inventory cost, and service level as a supply chain performance. System dynamics methodology was employed to observe and explore the dynamic change trend of the overall performance in the complicated supply chain model. This was done under both different levels of lead time standard deviation and different order policies. The results demonstrate how stochastic lead times can significantly increase inventory costs and carbon costs. Therefore, we propose appropriate ordering policies which mitigate the negative impacts of stochastic lead times.

At present, there are myriad concerns about tourism and sustainability at cultural and natural world heritage sites. Based on an analysis of 811 evaluations written between 1980 and 2010 by two official advisory bodies to the World Heritage Committee, this paper charts the timing and extent to which such concerns have become central to assessing the value of heritage sites. We find that, over time, issues related to tourism and sustainability expanded considerably in quantity and variety, and recommendations for managing and developing sustainable tourism became a routine feature of site evaluations. Despite the growing prevalence of such concerns, the conceptualization of sustainable tourism and related recommendations provided by the advisory experts remain somewhat ambiguous. Furthermore, our findings reveal regional disparities in the degree to which tourism is seen as a threat to the sustainability of heritage sites and in the likelihood that a state is considered a model of sustainable tourism.

The sustainable use of clean and safe sources of energy is indeed a global challenge. Traditional and unsafe forms of energy use is predominant among households in sub-Saharan Africa. This is not only a threat to the environment, but also constitutes health risk to the population. In the Nigeria context, this study provides the first attempt to estimate household energy poverty status and also investigate the driving factors of household energy poverty status using the National Demographic Health Survey (NDHS) dataset. The analytical techniques adopted in this study are based on Multidimensional Energy Poverty Index (MEPI) and Tobit regression model. Our results show that national average MEPI was 0.38, suggesting that majority of the households are energy poor. Energy poverty is however found to be higher in rural areas than in urban areas. We also found that male-headed households, age, rural sector and northeast residents are found to be the energy poverty enhancing factors, while household income and credit access are energy poverty inhibiting factors. The study concludes that income smoothening among other energy poverty reduction interventions should be prioritized, especially among rural households in order to help them exit energy poverty trap.

China’s rapid urbanization has caused dramatically increasing energy consumption in the district heating systems of the building sector in the Jing-Jin-Ji urban agglomeration, and this change has led to enormous air pollution issues in this region. However, the drivers and the sustainable development process of the district heating system of the building sector have not been investigated to understand the management of energy conservation and emissions reduction in the Jing-Jin-Ji urban agglomeration. This study investigates the drivers of the district heating energy consumption of the building sector (DHEB) in the Jing-Jin-Ji urban agglomeration between 2004 and 2016 by developing a decomposition framework. The decoupling status between the DHEB and gross domestic product (GDP) is then analyzed based on the Tapio decoupling index. The results show that a weak decoupling effect is mainly found between the DHEB and GDP in the Jing-Jin-Ji urban agglomeration from 2004 to 2016. The increase in the DHEB in 2004–2016 is largely driven by the growth of the district heating area and population, while the heating energy intensity negatively contributes to the increase. Significant differences in the effects of the share of the energy mix and share of heat production technology were found between subregions in response to government policy, which impacted levels in Beijing, Tianjin, and Hebei in decreasing order.