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.     

Electrospun and functionalized PVDF/PAN nanocatalyst-loaded composite for dechlorination and photodegradation of pesticides in contaminated water

A novel approach for the electrospinning and functionalization of nanocatalyst-loaded polyvinylidene fluoride/polyacrylonitrile (PVDF/PAN) composite grafted with acrylic acid (AA; which form polyacrylic acid (PAA) brush) and decorated with silver (Ag/PAN/PVDF-g-PAA-TiO₂/Fe–Pd) designed for the dechlorination and photodegradation of pesticides was carried out. PAN was used both as a nitrogen dopant as well as a co-polymer. Smooth nanofibers were obtained by electrospinning a solution of 12:2 wt.% PVDF/PAN blend using dimethylformamide (DMF) as solvent. The nanofibers were grafted with AA by free-radical polymerization using 2,2′azobis(2-methylpropionitrile) (AIBN) as initiator. Both bimetallic iron–palladium (Fe–Pd) and titania (TiO₂) nanoparticles (NP) were anchored on the grafted nanofibers via the carboxylate groups by in situ and ex situ synthesis. The Fe–Pd and nitrogen-doped TiO₂ nanoparticles were subsequently used for dechlorination and oxidation of target pollutants (dieldrin, chlorpyrifos, diuron, and fipronil) to benign products. Structural and chemical characterizations of the composites were done using various techniques. These include surface area and porosity analyzer (ASAP) using the technique by Brunner Emmett Teller (BET), Fourier transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscope (TEM) analyses were done. After dechlorination, the transformation products (TPs) for dieldrin, chlorpyrifos, diuron, and fipronil were obtained and identified using two-dimensional gas chromatography (time-of-flight) with a mass spectrometer detector (GCxGC-TOFMS). Analysis of total organic carbon (TOC) was carried out and used to extrapolate percentage mineralization. Experimental results showed that dechlorination efficiencies of 96, 93, 96, and 90 % for 1, 2, 2, and 3 h treatment period were respectively achieved for 5 ppm solutions of dieldrin, chlorpyrifos, diuron, and fipronil. The dechlorination of dieldrin, diuron, and fipronil follows first-order kinetics while that of chlorpyrifos followed pseudo-first order. Mineralization performance of 34 to 45 % were recorded when Fe–Pd was used, however upon electrospinning, doping, and grafting (Ag/PAN/PVDF-g-PAA-TiO₂/Fe–Pd composite); it significantly increased to 99.9999 %. This composite reveals great potential for dechlorination and mineralization of pesticides in contaminated water.     

Release of PCBs from Silvretta glacier (Switzerland) investigated in lake sediments and meltwater

This study is part of our investigations about the release of persistent organic pollutants from melting Alpine glaciers and the relevance of the glaciers as secondary sources of legacy pollutants. Here, we studied the melt-related release of polychlorinated biphenyls (PCBs) in proglacial lakes and glacier streams of the catchment of the Silvretta glacier, located in the Swiss Alps. To explore a spatial and temporal distribution of chemicals in glacier melt, we combined two approaches: (1) analysing a sediment record as an archive of past remobilization and (2) passive water sampling to capture the current release of PCBs during melt period. In addition, we determined PCBs in a non-glacier-fed stream as a reference for the background pollutant level in the area. The PCBs in the sediment core from the Silvretta lake generally complied with trends of PCB emissions into the environment. Elevated concentrations during the most recent ten years, comparable in level with times of the highest atmospheric input, were attributed to accelerated melting of the glacier. This interpretation is supported by the detected PCB fractionation pattern towards heavier, less volatile congeners, and by increased activity concentrations of the radioactive tracer ¹³⁷Cs in this part of the sediment core. In contrast, PCB concentrations were not elevated in the stream water, since no significant difference between pollutant concentrations in the glacier-fed and the non-glacier-fed streams was detected. In stream water, no current decrease of the PCBs with distance from the glacier was observed. Thus, according to our data, an influence of PCBs release due to accelerated glacier melt was only detected in the proglacial lake, but not in the other compartments of the Silvretta catchment.     

Mean Vehicle Speed Distributions for the Spatiotemporal Estimation of Exhaust Emissions

Link Emissions Models estimate traffic-related air pollution emissions at the individual road link level and inform governmental policies for air quality management. The current South Australian Link Emissions Model (CLEM) assumes constant spatiotemporal traffic flow at a single fixed mean speed, a potential limitation as the variability of exhaust emissions with vehicle speed has been established in the literature.We extend CLEM to eliminate the assumption of constant traffic flow, through the derivation of mean Australian vehicle speed distributions for different road types. Specifically, we successfully model the vehicle speed profile data from the second National In-Service Emissions study using Nearest Neighbour Kernel Density Estimation. We propose a mean speed Distribution Link Emissions Model (DLEM) for exhaust emission estimation based on the derived mean speed distributions. DLEM is an augmented, enhanced version of CLEM, accommodating a range of vehicle speeds and road types. The performance of the extended model, DLEM, is analysed in comparison to the current model, CLEM, through a case study analysis of vehicle exhaust emissions on a typical arterial road in Adelaide, South Australia. Results indicate use of DLEM and, by extension, mean vehicle speed distributions, has a strong impact on emission estimation. In particular, the fixed speed model, CLEM, may be substantially underestimating exhaust emissions of carbon monoxide, non-methane volatile organic compounds and particulate matter less than 2.5 μm in diameter. These are common exhaust pollutants that have been extensively linked with adverse health effects including respiratory morbidity and premature mortality.     

Assessing agricultural land-use change in the Midlands region of KwaZulu-Natal,South Africa: application of mixed multinomial logit

On-farm tree cultivation is considered an important strategy to mitigate detrimental environmental impacts of agricultural land-use change (ALUC). In South Africa, however, little is known about farm-level incentives and constraints that govern ALUC decisions among small-scale farmers. To address this knowledge gap, this study employs a mixed multinomial logit model by using a combination of revealed and stated preference data. After correcting for endogeneity, the estimated results show that decisions about ALUC are rationally derived and driven by clear but heterogeneous preferences and trade-offs between crop productivity, food security and labour saving. The results further show that the decision to plant sugarcane is constrained by landholding, whilst farmland afforestation is negatively influenced by household size. Decisions to convert land use are also driven by the behaviour of peer groups and agro-ecological conditions. Based on these findings, important policy implications for sustainable land use are outlined.     

Hunting Selectivity and Its Influence on the Structure of Sable Populations in the Cis-Ural Region

The structure of commercial sable samples from the Cis-Ural region was studied taking into account hunting method (shooting or trapping). The proportion of adult animals was found to be significantly lower in samples taken during the first half of the hunting season, compared to the second half, indicating predominant harvesting of young animals. To estimate the degree of hunting selectivity (I), the ratios of demographic groups among shot and trapped animals were calculated. The results confirmed the fact of selective hunting for underyearlings both by shooting (I = 1.49–1.60 for the Cis-Ural region and I = 2.46–3.37 for the Western Sayan Mountains) and by trapping (I = 2.80–4.37), especially during the first half of winter. Samples taken during the second half of the season were characterized by prevalence of adult animals making up the reproductive core of the population (I = 1.43–2.07). It is considered that the process of reproduction in Cis-Ural sable populations in the 1960s to 1980s was stimulated by intensive commercial hunting. To maintain reproduction of sable populations at a safe level, it is necessary to reduce the period of hunting in the first quarter of the year. It is proposed to use the phenomenon of hunting selectivity for managing sable populations, regulating their exploitation, and improving the economic productivity of habitats. Commercial hunting in terms of its impact on the population can act as a factor of conscious or unconscious artificial selection.     

A Mathematical Model for the Effects of Fertilization on Nitrogen Concentrations in Unsaturated Soil on Blueberry Farms in Southern New Jersey

Nitrogen is commonly known as a food source for crops. However, the nitrogen compounds used in crop fertilizers, most commonly nitrate (NO₃) and ammonium (NH₄), are not widely understood. Blueberry plants do not take up these compounds as efficiently as organic nitrogen so varying amounts of leaching into the soil and groundwater will occur. A biogeochemical model consisting of ordinary and partial differential equations is implemented to computationally predict the concentrations of nitrate and ammonium in unsaturated soil of blueberry plants, specifically in the southern region of New Jersey. The model takes into account the type of soil of the region, the nitrate uptake of the plant, the water content in the roots region, the pressure heads in the soil pores, and the application rates of fertilizers containing nitrate, ammonium, and organic nitrogen. Computational simulations demonstrate that the model accounts for natural processes and, in addition, show that commonly used fertilizer application rates cause unnecessarily high concentrations of both nitrate and ammonium in the unsaturated soil level. Further, simulations show that decreasing nitrate fertilizer applications by 85.7% in annual and 91.8% in bi-annual schedules provides an optimal system for safe reapplication.     

Development and implementation of eco-genomic tools for aquatic ecosystem biomonitoring: the SYNAQUA French-Swiss program

The effectiveness of environmental protection measures is based on the early identification and diagnosis of anthropogenic pressures. Similarly, restoration actions require precise monitoring of changes in the ecological quality of ecosystems, in order to highlight their effectiveness. Monitoring the ecological quality relies on bioindicators, which are organisms revealing the pressures exerted on the environment through the composition of their communities. Their implementation, based on the morphological identification of species, is expensive because it requires time and experts in taxonomy. Recent genomic tools should provide access to reliable and high-throughput environmental monitoring by directly inferring the composition of bioindicators’ communities from their DNA (metabarcoding). The French-Swiss program SYNAQUA (INTERREG France-Switzerland 2017–2019) proposes to use and validate the tools of environmental genomic for biomonitoring and aims ultimately at their implementation in the regulatory bio-surveillance. SYNAQUA will test the metabarcoding approach focusing on two bioindicators, diatoms, and aquatic oligochaetes, which are used in freshwater biomonitoring in France and Switzerland. To go towards the renewal of current biomonitoring practices, SYNAQUA will (1) bring together different actors: scientists, environmental managers, consulting firms, and biotechnological companies, (2) apply this approach on a large scale to demonstrate its relevance, (3) propose robust and reliable tools, and (4) raise public awareness and train the various actors likely to use these new tools. Biomonitoring approaches based on such environmental genomic tools should address the European need for reliable, higher-throughput monitoring to improve the protection of aquatic environments under multiple pressures, guide their restoration, and follow their evolution.