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It is now recognized that analytical chemistry must also be a target for green principles, in particular chromatographic methods which typically use relatively large volumes of hazardous organic solvents. More generally, high performance liquid chromatography (HPLC) is employed routinely for quality control of complex mixtures in various industries. Acetonitrile and methanol are the most commonly used organic solvents in HPLC, but they generate an impact on the environment and can have a negative effect on the health of analysts. Ethanol offers an exciting alternative as a less toxic, biodegradable solvent for HPLC. In this work we demonstrate that replacement of acetonitrile with ethanol as the organic modifier for HPLC can be achieved without significantly compromising analytical performance. This general approach is demonstrated through the specific example analysis of a complex plant extract. A benchmark method employing acetonitrile for the analysis of Bidens pilosa extract was statistically optimized using the Green Chromatographic Fingerprinting Response (GCFR) which includes factors relating to separation performance and environmental parameters. Methods employing ethanol at 30 and 80°C were developed and compared with the reference method regarding their performance of separation (GCFR) as well as by a new metric, Comprehensive Metric to Compare Liquid Chromatography Methods (CM). The fingerprint with ethanol at 80°C was similar to or better than that with MeCN according to GCFR and CM. This demonstrates that temperature may be used to replace harmful solvents with greener ones in HPLC, including for solvents with significantly different physiochemical properties and without loss in separation performance. This work offers a general approach for the chromatographic analysis of complex samples without compromising green analytical chemistry principles.

Bromine and chlorine are almost ubiquitous in waste of electrical and electronic equipment (WEEE) and the knowledge of their content in the plastic fraction is an essential step for proper end of life management. The aim of this study is to compare the following analytical methods: energy dispersive X-ray fluorescence spectroscopy (ED-XRF), ion chromatography (IC), ion-selective electrodes (ISEs), and elemental analysis for the quantitative determination of chlorine and bromine in four real samples taken from different WEEE treatment plants, identifying the best analytical technique for waste management workers. Home-made plastic standard materials with known concentrations of chlorine or bromine have been used for calibration of ED-XRF and to test the techniques before the sample analysis. Results showed that IC and ISEs, based upon dissolution of the products of the sample combustion, have not always achieved a quantitative absorption of the analytes in the basic solutions and that bromine could be underestimated since several oxidation states occur after combustion. Elemental analysis designed for chlorine determination is subjected to strong interference from bromine and required frequent regeneration and recalibration of the measurement cell. The most reliable method seemed to be the non-destructive ED-XRF. Calibration with home-made standards, having a similar plastic matrix of the samples, enabled us to carry out quantitative determinations, which have been revealed to be satisfactorily accurate and precise. In all the analyzed samples a total concentration of chlorine and/or bromine between 0.6 and 4 w/w% was detected, compromising the feasibility of a mechanical recycling and suggesting the exploration of an alternative route for managing these plastic wastes.

ispartof: ACS SUSTAINABLE CHEMISTRY & ENGINEERING vol:9 issue:29 pages:9604-9624 status: published

Co-generation of energy derived from human movement is not new. Intentionally accumulating energy, from mass urban-mobility, provides opportunities to re-purpose power. However, when mass-mobility is predictable, yet not harnessed, this highlights critical gaps in application of interdisciplinary knowledge. This research highlights a novel application of geostatistical modelling for the built environment with the purpose of understanding where energy harvesting infrastructure should be located. The work presented argues that advanced Geostatistical methods can be implemented as an appropriate method to predict probability distribution, density, clustering of populations and mass-population mobility patterns from large-scale online distributed and heterogeneous data sets published by the Australian Urban Research Infrastructure Network. Where clear urban spatio-behavioural relationships of density and movement can be predicted – understanding such patterns supports cross-disciplinary city planning and decision-making. A data-informed – predictive spatial decision-making framework is proposed – facilitating the endeavour of cogenerating kinetic human energy within a prescribed space. This novel proposition could further sustainability strategies for compact living for cities such as in Perth, Western Australia which is increasingly economically and geographically pressured to densify. This research argues that surveillance data elucidate a capacity to interpret and understand impacts of densification strategies, efficacy of CCTV networks in existing and emerging cities.

SummaryMicrobially generated or supported nanocatalysts have potential applications in green chemistry and environmental application. However, precious (and base) metals biorefined from wastes may be useful for making cheap, low‐grade catalysts for clean energy production. The concept of bionanomaterials for energy applications is reviewed with respect to potential fuel cell applications, bio‐catalytic upgrading of oils and manufacturing ‘drop‐in fuel’ precursors. Cheap, effective biomaterials would facilitate progress towards dual development goals of sustainable consumption and production patterns and help to ensure access to affordable, reliable, sustainable and modern energy.

The joint impact of human activities and climate change on natural resources lead to biodiversity loss. Therefore, it is important to select protected areas through systematic conservation planning. The present study assessed how representative natural habitats are protected under the nature conservation network, and to identify new—but so far insufficiently—protected areas containing these habitats for sustainable management. We used the Marxan model to select the most valuable insufficiently protected natural habitats in the Czech Republic as a representative example for a conservation strategy for Central–Eastern European environments. We set three conservation targets (25%, 50%, and 75%), defining how much percent area of valuable representative natural habitats should be added to the area of the habitats already included in the Nature Protection Network. To implement these conservation targets it is necessary to preserve 22,932 ha, 72,429, ha and 124,363 ha respectively of the conservation targets occurring in the insufficiently protected areas, and 17,255 ha, 51,620 ha, and 84,993 ha respectively of the conservation features in the areas without protection status. Marxan was revealed to be an appropriate tool to select the most valuable and insufficiently protected natural habitats for sustainable management.

SummaryEnvironmentally extended multiregional input‐output (EE MRIO) tables have emerged as a key framework to provide a comprehensive description of the global economy and analyze its effects on the environment. Of the available EE MRIO databases, EXIOBASE stands out as a database compatible with the System of Environmental‐Economic Accounting (SEEA) with a high sectorial detail matched with multiple social and environmental satellite accounts. In this paper, we present the latest developments realized with EXIOBASE 3—a time series of EE MRIO tables ranging from 1995 to 2011 for 44 countries (28 EU member plus 16 major economies) and five rest of the world regions. EXIOBASE 3 builds upon the previous versions of EXIOBASE by using rectangular supply‐use tables (SUTs) in a 163 industry by 200 products classification as the main building blocks. In order to capture structural changes, economic developments, as reported by national statistical agencies, were imposed on the available, disaggregated SUTs from EXIOBASE 2. These initial estimates were further refined by incorporating detailed data on energy, agricultural production, resource extraction, and bilateral trade. EXIOBASE 3 inherits the high level of environmental stressor detail from its precursor, with further improvement in the level of detail for resource extraction. To account for the expansion of the European Union (EU), EXIOBASE 3 was developed with the full EU28 country set (including the new member state Croatia). EXIOBASE 3 provides a unique tool for analyzing the dynamics of environmental pressures of economic activities over time.