Resources Environment and Sustainability最新文献

Due to worsening air quality across many cities in developing countries, there is an urgent need to consider more aggressive air pollution control measures. Valuation of the benefits of clean air is crucial for establishing the rationale for such policies, but is methodologically challenging, often expensive, and therefore remains limited. This study assesses the potential for more standardized and cost-effective measurement of the demand for air quality improvements, applying a contingent valuation procedure via online surveys, in three Asian megacities facing severe but varying pollution problems — Beijing, Delhi, and Jakarta. The study’s primary contribution is to demonstrate the viability of this approach, which significantly enhances comparability of valuations and their drivers across locations, and thereby has great potential for informing policy analysis and targeting of specific interventions. A second contribution is to supply sorely needed data on the benefits of clean air in these three particular Asian cities, which collectively have a population of about 50 million people. The annual willingness-to-pay for air quality to reach national standards is estimated to be US$150 in Jakarta (where average PM${}_{\mathrm{2.5}}$ concentration, at 45 $\mu$g/m³, exceeds national standards by the smallest amount, specifically a factor of 1.3), US$1845 in Beijing (PM${}_{\mathrm{2.5}}$ at 58 $\mu$g/m³, 1.7 times the standard), and US$1760 in Delhi (PM${}_{\mathrm{2.5}}$ at 133 $\mu$g/m³, 3.3 times the standard). The methods deployed could be applied more widely to construct a worldwide database of comparable air quality valuations.

Product Lifecycle Management (PLM) plays a key role in digital transformation demanded by Industry 4.0 and life cycle assessment, including sustainability assessment. Knowledge Based Engineering (KBE) applications can support PLM by integrating heterogeneous knowledge from different stages throughout the product life. However, the integration of knowledge from different stages and teams can cause misunderstanding if not represented in a unified form. Furthermore, different forms of knowledge used by different software are neither machine-readable nor human-readable, which also sets obstacles to knowledge integration in KBE applications. Supply chain sustainability assessment is such a scenario that entails integrating knowledge from different sources. This paper firstly implements a sustainability assessment method from other scholar to calculate the supply chain sustainability performance and adapts a sustainability assessment ontology for supply chain sustainability assessment. Then, an example KBE application is developed by implementing the sustainability assessment ontology and calculation method to simulate the knowledge sharing and integration between different teams. Finally, through this example application, it is discussed that the implementation of ontology to represent knowledge in PLM application for collaborative tasks like sustainability assessment can increase the efficiency of data sharing and integration. This paper is a proof of concept for the ontology-based framework. This framework can facilitate to represent knowledge but not create new knowledge, which means it can increase the efficiency of the software development, but cannot provide a better calculation method and assessment framework for supply chain sustainability assessment.

The largest wine producers globally are located in Southern Europe and climate is a major factor in wine production. The European Union aims to complement the consumer’s choice for wine with information about environmental sustainability. The carbon footprint is a worldwide-standardized indicator that both wine producers and consumers perceive as the most important environmental indicator. So far, environmental life cycle assessment studies show variability in the system boundaries design and functional unit selection, and review papers do not include life cycle inventory data, and consider vineyards in various locations worldwide. This study aimed to investigate what are the key factors affecting the carbon footprint of red and white wine production in South European countries with the same climatic conditions, and benchmark both wine types. The results showed that the carbon footprints of white and red wines are comparable. The average carbon footprints were 1.02, 1.25, and 1.62 CO₂ eq. bottle of wine ⁻¹ for organic red wine, conventional red wine, and conventional white wine, respectively. The viticulture, winemaking, and packaging stages affect greatly the carbon footprint. Diesel consumption at the viticulture stage, electricity consumption at the viticulture and winemaking stages, and glass production at the packaging stage are the largest contributors to the carbon footprint. Wine consumption stage was omitted from most studies, even though it can increase the carbon footprint by 5%. Our results suggest that consumers should choose (conventional or organic) red wine that is produced locally.

Improved energy efficiency is a key factor in the shift towards sustainable energy systems and net zero emissions, both locally, regionally and globally. The total energy efficiency potential in industrial SMEs is high, but despite this large potential for improved energy efficiency, the full potential is not realized due to several barriers to implementation of energy efficiency measures. The barriers vary based on e.g., geographic location, company size, sector, etc., but for industrial SMEs the main barriers are other priorities, lack of time and lack of information about energy efficiency measures. Energy efficiency networks help companies with the support needed to successfully work with energy efficiency on site, such as conducting an energy audit, making an energy and implementation plan, and monitoring the results. However, there is so far a scarcity of ex-post evaluations of energy efficiency network policy programmes. The aim of this paper is to provide an ex-post impact evaluation of a Swedish regional energy efficiency network programme and propose a general method on how to evaluate energy efficiency networks. Results show that the achieved energy efficiency for the evaluated network policy programme is higher than previously evaluated stand-alone energy audit programmes, and that the majority of deployed energy efficiency measures are found among the support processes, such as space heating, ventilation and lighting.

In the recycling sector, the transition in system networks from centralization to decentralization is an emerging concept. The feasibility to decentralize the recycling of e-waste needs to be analyzed, considering the different characteristics of each municipality. We propose a distributed recycling system for obsolete alkaline batteries using microwave apparatus as a small-scale recycling technology. Firstly, the reactivity of obsolete alkaline batteries with microwave irradiation was empirically examined. In lab-based experiments, pyrometallurgical microwave-based heating successfully separated a mixed sample of Mn₃O₄ and ZnO contained in obsolete alkaline batteries and recovered MnO and Zn separately, achieving a recovery rate of 97% under an ambient atmosphere. It was also found that the recovery rate of zinc obtained by microwave-based heating is 1.5-fold that using conventional electric furnace-based heating, with less than half of the heating time required. The experimental results were then used to analytically determine the energy efficiency of the distributed recycling system for the treatment of obsolete alkaline batteries with microwave apparatus compared with the centralized recycling system. In an analytical study which considered the characteristics of 1710 municipalities in Japan, it was found that an annual energy and greenhouse gas reduction of 26,500 GJ and 1.54 Gg-CO₂eq, respectively, can be achieved at the national level by creating a well-balanced harmony between the centralized and distributed systems. The method applied in this study to determine the effectiveness based on population and intercity transport distance can be readily implemented in any city for the adoption of a distributed recycling system.

The fate of indicator bacteria and wastewater micropollutants (WWMPs) discharged from water resource recovery facilities (WRRFs) and combined sewer overflows (CSOs) needs to be understood for the protection of drinking water sources. This study investigated the partitioning behavior in wet and dry weather of Escherichia coli and 6 WWMPs including acetaminophen (ACET), caffeine (CAF), theophylline (THEO), carbamazepine (CBZ), 2-hydroxycarbamazepine (CBZ-2OH), and the artificial sweetener aspartame (ASP) between the water, suspended particulate matter (SPM), and sediments. ACET, CAF, THEO and CBZ were detected in all matrices. In contrast, CBZ-2OH and ASP were strongly associated with suspended particles, being exclusively detected in SPM and sediments. When comparing dry to wet weather concentrations, three main patterns were observed depending on the compounds and CSO locations: (i) compounds with low removal efficiency by wastewater treatment (CBZ, CBZ-2OH and ASP) are diluted with the addition of stormwater in the aqueous and SPM phases; (ii) contaminants with high removal efficiency (E. coli, ACET, CAF, THEO) saw an increase in their particle associated fraction (39 to 59% for E. coli, and from 12%–43% to 42%–91% for WWMPs); and (iii) no significant difference was observed for surficial sediment concentrations after rainfall events, although spatial variability was observed. Results highlight the importance of monitoring the SPM phase to overcome dilution effects in the dissolved phase. Analyzing SPM with regards to micropollutants and indicator bacteria may be more relevant for risk assessment and the assessment of the relative contribution of CSO bypass flows and treated wastewater effluents loads.

Major environmental and climate changes are driven by changes in socioeconomic development. The problem of food waste, its unsustainable management, and associated environmental consequences are becoming great concerns due to the rapid socioeconomic development in many Chinese provinces. This study assessed the current and future status of food waste and its management, and the associated environmental impact in all Chinese provinces from life cycle perspective. Based on result, food waste in China was estimated as 61.37 Mt in 2020 and could be as high as 100.95–139.82 Mt by 2040, under various socioeconomic pathways. Average per capita food waste has increased by 29.67% from 2016 and Tianjin was found to have the highest per capita food waste. Correspondingly, GHG emission of food waste in China was estimated as 149.25 Mt CO₂eq in 2020, and is largely influence by the varieties of food wasted in each province. The environmental burden of food waste is projected to increase by 70%–148% under different socioeconomic development pathways. Anaerobic digestion demands freshwater and may pose challenges for Chinese provinces facing water scarcity. Diverting food waste to anaerobic digestion can reduce GHG emissions of food waste by $\sim$74% by 2040. China’s transition to sustainable waste management may be impeded and unsustainable economic-wise if many Chinese provinces continue to build on their current food waste management trend. These findings could be pivotal in setting food waste reduction goals at provincial level and devising strategies to ensure active involvement of community in food waste reduction programs.

The information and communication technology (ICT) plays an important role in improving energy consumption efficiency and reducing the emission level in the urban transport sector. ICT-based mobility services like ridesourcing provide smart tools and algorithms for matching travel demand and supply and more convenient door to door services. However, there is a concern that the convenience and competitive service fares of these new mobility modes encourage people to make more car travel or shift from more sustainable mobility modes like public transport to car travels. Therefore, it is necessary to study the frequency use and modal shift to this new mobility mode, particularly in the cities (like Cairo), where the ICT-based mobility services contain more ridesourcing of fossil fuel cars than other modes like online bikes/scooter sharing. A survey was conducted in Cairo, and logit models were developed to analyze the associations of socioeconomic, travel behavior variables with the frequency use and modal shift to ridesourcing. The results of ordinal logistic regression indicate that people who live near a metro station, with higher income, and with more non-work trips per week are more likely to be high-frequent users of ridesourcing. Moreover, women are more likely to use ridesourcing frequently than men in Cairo. The findings indicate that the most replaced mode by ridesourcing is traditional taxis (by 33 %), and the second and third shifted modes are private cars and public transport by 30% and 24 %, respectively. The results of multinomial logistic regression show that the socioeconomic parameters have significant associations with the probability of modal shift from public transport, taxis, and private cars to ridesourcing services.