Creating integrated business and environmental value within the context of China’s circular economy and ecological modernization

This paper investigates the challenges and opportunities of how firms and organizations can and will be able to strike a better balance between economic growth and environmental stewardship in the context of China’s emerging ‘circular economy’ policy paradigm and based on ecological modernization theoretic approaches.Based on three company case studies in the information technology and electronic industries in China, we identify and demonstrate how a blended business and environmental value can be created from adopting a sustainable supply chain management approach. The adoption of a sustainable supply chain management approach is rapidly becoming a key business challenge and opportunity in China and other large emerging economies around the world, where our greatest environmental management challenges currently reside and will continue to exist for many years to come. The value creation framework proposed in research focuses on evaluating three case study companies who appear in various stages of an electronic industry supply chain. Value creation within a supply chain can provide the impetus for organizations to adopt circular economy, sustainable supply chain practices, for competitive reasons.In addition, we describe how a value proposition can be evaluated at two levels of analysis, a more specific micro-level and a more general meso-level of analysis. The four major business value dimensions include cost reduction, revenue generation, resiliency, and legitimacy and image.The initial findings are that a variety of opportunities exist for electronic firms in emerging and developing countries, while results from this study provide an important scholarly foundation to develop and refine sustainable supply chain management practices in emerging and developing economies.     

Atmospheric Aerosols over a Southwestern Region of Texas

Speciated samples of PM_2.5 were collected at the Big Bend site from July of 2003 to June 2006 and the McDonald Observatory site from July of 2003 to August of 2005 in southwestern Texas, respectively, by the US Environmental Protection Agency. A total of 175 samples for the Big Bend site and 105 samples for the McDonald Observatory site with 52 species were measured; however, 30 and 32 species from the Big Bend and McDonald Observatory sites, respectively, were excluded because of too much below-detection-limit data. Due to the laboratory change about November 1 of 2004 and possible analytical artifacts, phosphorous was excluded as well. Among the species excluded, 31 species are common to both sites. The two data sets were analyzed by positive matrix factorization to infer the sources of PM observed at the two sites. The analysis resolved five source-related factors for Big Bend and four for McDonald Observatory. Sulfate-rich secondary aerosol, coal burning, motor vehicle/road dust, and a mixed factor were identified as common sources to both sites. The other factor identified for Big Bend is related to soil. Sulfate mainly exists as ammonium salts. The sulfate-rich secondary aerosols account for about 62% and 66% of the PM_2.5 mass concentration at the two sites, respectively. The highest concentration of Si associated with Ca, Fe, \textSO₄^{2 -} {\text{SO}}_4^{2 - } , and organic carbon at the two sites was possibly attributed to the coal-fired power plants in the region. Basically, the factor of sulfate and coal burning at the two sites showed similar chemical composition profiles and seasonal variation that reflect the regional characteristics of these sources. The regional factors of sulfate, coal burning, and soil showed predominantly low-frequency variations; however, the area-related and/or local factors showed both high and low frequency variations. The motor vehicle/road dust and the mixed factors were likely to be area-related and/or local source.     

A shell-based magnetic field model for magnetic proximity detection systems

Several magnetic proximity detection systems have been developed for mining vehicles and mobile machinery to protect nearby workers. Magnetic field generators are often used in these systems to establish magnetic fields around the equipment. A sensor worn by a worker provides a measurement of the magnetic flux density that is used to estimate the proximity to the machine. The proximity detection systems currently available for underground mining equipment are capable of identifying whether a worker is near the machine. However, it is a challenge for these systems to accurately locate the worker. Mining machines, which have fast-moving, articulated parts, present hazards that change depending on the situation at hand as well as the specific location of the worker. In addition, the dynamic nature and confined spaces of the mining environment often demand that the workers be close to the machinery. Therefore, in many cases, simply knowing the proximity of a worker may be inadequate. To provide the most effective protection, it would be advantageous to know the worker’s exact location relative to specific parts of the machine. To lay the foundation for measuring such a location, we have developed a shell-based model of the magnetic flux density distribution for a ferrite-cored generator. This paper will present an analysis of the model along with a model construction process. Also presented are the laboratory test results of a prototype system that implements this model to determine the exact location of a magnetic sensor using the fields from two generators.     

Does the antidiabetic drug metformin affect embryo development and the health of brown trout (<Emphasis Type="Italic">Salmo trutta</Emphasis> f. <Emphasis Type="Italic">fario</Emphasis>)?

Background

Due to the rising number of type 2 diabetes patients, the antidiabetic drug, metformin is currently among those pharmaceuticals with the highest consumption rates worldwide. Via sewage-treatment plants, metformin enters surface waters where it is frequently detected in low concentrations (µg/L). Since possible adverse effects of this substance in aquatic organisms have been insufficiently explored to date, the aim of this study was to investigate the impact of metformin on health and development in brown trout (Salmo trutta f. fario) and its microbiome.

Results

Brown trout embryos were exposed to 0, 1, 10, 100 and 1000 µg/L metformin over a period from 48 days post fertilisation (dpf) until 8 weeks post-yolk sac consumption at 7 °C (156 dpf) and 11 °C (143 dpf). Chemical analyses in tissues of exposed fish showed the concentration-dependent presence of metformin in the larvae. Mortality, embryonic development, body length, liver tissue integrity, stress protein levels and swimming behaviour were not influenced. However, compared to the controls, the amount of hepatic glycogen was higher in larvae exposed to metformin, especially in fish exposed to the lowest metformin concentration of 1 µg/L, which is environmentally relevant. At higher metformin concentrations, the glycogen content in the liver showed a high variability, especially for larvae exposed to 1000 µg/L metformin. Furthermore, the body weight of fish exposed to 10 and 100 µg/L metformin at 7 °C and to 1 µg/L metformin at 11 °C was decreased compared with the respective controls. The results of the microbiome analyses indicated a shift in the bacteria distribution in fish exposed to 1 and 10 µg/L metformin at 7 °C and to 100 µg/L metformin at 11 °C, leading to an increase of Proteobacteria and a reduction of Firmicutes and Actinobacteria.

Conclusions

Overall, weight reduction and the increased glycogen content belong to the described pharmaceutical effects of the drug in humans, but this study showed that they also occur in brown trout larvae. The impact of a shift in the intestinal microbiome caused by metformin on the immune system and vitality of the host organism should be the subject of further research before assessing the environmental relevance of the pharmaceutical.