Food waste collection and recycling for value-added products: potential applications and challenges in Hong Kong

About 3600 tonnes food waste are discarded in the landfills in Hong Kong daily. It is expected that the three strategic landfills in Hong Kong will be exhausted by 2020. In consideration of the food waste management environment and community needs in Hong Kong, as well as with reference to the food waste management systems in cities such as Linköping in Sweden and Oslo in Norway, a framework of food waste separation, collection, and recycling for food waste valorization is proposed in this paper. Food waste can be packed in an optic bag (i.e., a bag in green color), while the residual municipal solid waste (MSW) can be packed in a common plastic bag. All the wastes are then sent to the refuse transfer stations, in which food waste is separated from the residual MSW using an optic sensor. On the one hand, the sorted food waste can be converted into valuable materials (e.g., compost, swine feed, fish feed). On the other hand, the sorted food waste can be sent to the proposed Organic Waste Treatment Facilities and sewage treatment works for producing biogas. The biogas can be recovered to produce electricity and city gas (i.e., heating fuel for cooking purpose). Due to the challenges faced by the value-added products in Hong Kong, the biogas is recommended to be upgraded as a biogas fuel for vehicle use. Hopefully, the proposed framework will provide a simple and effective approach to food waste separation at source and promote sustainable use of waste to resource in Hong Kong.     

When experts disagree: the need to rethink indicator selection for assessing sustainability of agriculture

Sustainability indicators are well recognized for their potential to assess and monitor sustainable development of agricultural systems. A large number of indicators are proposed in various sustainability assessment frameworks, which raises concerns regarding the validity of approaches, usefulness and trust in such frameworks. Selecting indicators requires transparent and well-defined procedures to ensure the relevance and validity of sustainability assessments. The objective of this study, therefore, was to determine whether experts agree on which criteria are most important in the selection of indicators and indicator sets for robust sustainability assessments. Two groups of experts (Temperate Agriculture Research Network and New Zealand Sustainability Dashboard) were asked to rank the relative importance of eleven criteria for selecting individual indicators and of nine criteria for balancing a collective set of indicators. Both ranking surveys reveal a startling lack of consensus amongst experts about how best to measure agricultural sustainability and call for a radical rethink about how complementary approaches to sustainability assessments are used alongside each other to ensure a plurality of views and maximum collaboration and trust amongst stakeholders. To improve the transparency, relevance and robustness of sustainable assessments, the context of the sustainability assessment, including prioritizations of selection criteria for indicator selection, must be accounted for. A collaborative design process will enhance the acceptance of diverse values and prioritizations embedded in sustainability assessments. The process by which indicators and sustainability frameworks are established may be a much more important determinant of their success than the final shape of the assessment tools. Such an emphasis on process would make assessments more transparent, transformative and enduring.     

Application of fuzzy sets and cognitive maps to incorporate social science scenarios in integrated assessment modelsA case study of urbanization in Ujung Pandang, Indonesia

Decision–support systems in the field of integrated water management could benefit considerably from social science knowledge, as many environmental changes are human-induced. Unfortunately the adequate incorporation of qualitative social science concepts in a quantitative modeling framework is not straightforward. The applicability of fuzzy set theory and fuzzy cognitive maps for the integration of qualitative scenarios in a decision–support system was examined for the urbanization of the coastal city of Ujung Pandang, Indonesia. The results indicate that both techniques are useful tools for the design of integrated models based on a combination of concepts from the natural and social sciences. This revised version was published online in July 2006 with corrections to the Cover Date.     

The Need for Scale Sensitive Approaches in Spatially Explicit Land Use Change Modeling

This paper introduces some of the issues that are relevant to the spatially explicit modeling of land use systems. A short overview is given of the ways and means in which a number of different land use change models describe the land use system. Specific attention is given to the empirical modeling approach used in the CLUE (Conversion of Land Use and its Effects) modeling framework. This approach is demonstrated for three case studies in China, Ecuador and the Atlantic Zone of Costa Rica. These case-studies illustrate the methodology for multi-scale analysis of land use driving factors and their application in spatially explicit modeling exercises. Model functioning, performance and limitations are discussed. The presented case-studies indicate that empirical modeling results can contribute to a better theoretic imbedding of land use change research in scale sensitive and integrated theories.     

Predominance of clade D <Emphasis Type="Italic">Symbiodinium</Emphasis> in shallow-water reef-building corals off Kish and Larak Islands (Persian Gulf,Iran)

Scleractinian coral species harbour communities of photosynthetic taxa of the genus Symbiodinium. As many as eight genetic clades (A, B, C, D, E, F, G and H) of Symbiodinium have been discovered using molecular biology. These clades may differ from each other in their physiology, and thus influence the ecological distribution and resilience of their host corals to environmental stresses. Corals of the Persian Gulf are normally subject to extreme environmental conditions including high salinity and seasonal variation in temperature. This study is the first to use molecular techniques to identify the Symbiodinium of the Iranian coral reefs to the level of phylogenetic clades. Samples of eight coral species were collected at two different depths from the eastern part of Kish Island in the northern Persian Gulf, and Larak Island in the Strait of Hormuz. Partial 28S nuclear ribosomal (nr) DNA of Symbiodinium (D1/D2 domains) were amplified by polymerase chain reaction (PCR). PCR products were analyzed using single stranded conformational polymorphism and phylogenetic analyses of the LSU DNA sequences from a subset of the samples. The results showed that Symbiodinium populations were generally uniform among and within the populations of eight coral species studied, and there are at least two clades of Symbiodinium from Kish and Larak islands. Clade D was detected from eight of the coral species while clade C was found in two of species only (one species hosted two clades simultaneously). The dominance of clade D might be explained by high temperatures or the extreme temperature variation, typical of the Persian Gulf. Publication of this article was held up owing to technical problems. The publisher apologizes sincerely for this lengthy delay.     

Modeling Land-Use Change in a Decision-Support System for Coastal-Zone Management

RaMCo is a prototype version of a decision-support system for coastal-zone management. The model is based on the findings of a multidisiciplinary research program, conducted in Southwest Sulawesi, Indonesia. Different management strategies can be compared on the basis of the short- and long-term consequences. Land-use change has been included in RaMCo in view of the impacts of land-based human activities on the marine environment. The key aspect of the model is a combination of the temporal dynamics of land-use change on the regional (macro-level) scale and spatial dynamics on the local (micro-level) scale. Constrained cellular automata are used to integrate both scale levels. The state changes of the cells depend on the consistency with the macro-scale model, local geographical conditions, and interaction with neighboring cells. In this paper, we discuss the underlying theoretical assumptions of the macro-scale and micro-scale models, some characteristic results for land-use change in the study area, and the validation problem.     

A novel ligand for cloud point extraction to determine gold content in ore samples

Gold is a valuable metal occurring usually at very low concentrations in complex natural samples. Gold analysis thus needs preconcentration methods. Classical liquid–liquid extraction involves hazardous organic solvents. Alternatively, cloud point extraction involves non-toxic and nonvolatile surfactants. Here, we analyzed ore samples. The complex of Au(III) with sulphapyridylazo resorcin was extracted by the cloud point method. Concentrations were measured by flame atomic absorption spectrometry. We tested the effects of pH, reagent concentration, Triton X-100 surfactant concentration, equilibration temperature and time. Results show that the best detection limit of the method was 0.48 µg L^?1 for Au with a preconcentration factor of 31 times. Calibration is linear in range of 6.4–2,000 µg L^?1, and relative standard deviations are lower than 5 %. Quantum chemical computations reveal the plausible structure of the gold–ligand complex. This report represents the first determination of gold using sulphapyridylazo resorcin as a ligand.     

Environmental and Biological Assessment of Exposure to Benzene in Petroleum Workers

Occupational exposure to benzene was measured in two gasoline marketing terminals and five major refineries in Singapore. A total of 280 workers were monitored over two years. This assessment was carried out with two primary objectives: (1) To find out the extent of occupational exposure to benzene in the petroleum industry in Singapore, (2) To identify suitable biomarkers for monitoring of low levels of benzene exposure. The exposure was measured in five different categories of petroleum and petrochemical workers, i.e., truck drivers, despatch assistant, process operators, oil movements operators and laboratory technicians. The results revealed wide variations in exposure, from 0.01 to 13.6 ppm for personal time weighted average (TWA) exposure over the whole workshift. The exposure of truck drivers appeared to be the highest, with geometric mean (GM) of 1.98 ppm (ranged from 0.25 to 13.6 ppm). The average benzene exposure for process operators was relative low with a GM of 0.04 ppm. Lowest benzene exposure was found in the laboratory technicians, with a GM of 0.02 ppm. As cigarette smoking is known to affect metabolism of benzene, data analyses on the relationships with environmental exposure were conducted only on the 190 nonsmokers. The results showed that urinary trans, trans-muconic acid (ttMA), unmetabolized benzene in urine (UBZ) and benzene in blood (BBZ) were better biomarkers for low level benzene exposure as compared to urinary phenolic metabolites in urine, such as hydroquinone, phenol and catechol.