Viganda Varabuntoonvit

The research conducted a life cycle impact assessment (LCIA) of single-use food packaging made from PP, PLA, and Paper/PLA materials using the ReCiPe method. The assessment covered 18 environmental impacts from box processing to end-of-life treatment, with a functional unit (FU) specified as 1,000 units of single-use food container boxes. The dimensions of the boxes were standardized to reflect the average size from the Thailand market and food-delivery boxes. When focused on production stage, PP box shows the greatest impact on overall especially human non-carcinogenic toxicity (285.11 kg 1, 4-DCB). However, when focused on cradle-to-grave life cycle, the PP emerged as the optimal choice of food box due to its comparable environmental impact to biodegradable alternatives, when applying recycling processes. It recycles significantly reduces the total impact up to 73% from their waste-to-energy treatment option. To achieve environmental goals necessitates policy interventions such as extended producer responsibility laws and refund schemes to incentivize responsible disposal. In country lacking waste management infrastructure and collection system, the sensitivity analysis of this research show that biodegradable PLA material emerges as the most suitable choice, particularly over Paper/PLA, offering lower overall environmental impact due to less overall emission in landfill and composting process.

Bangkok, the capital of Thailand, is confronting critical traffic congestion caused by the large number of private vehicles. In 2019, the city was ranked eleventh highest on the global traffic index. Public transport was proposed as the key to alleviating the problem. Nonetheless, the sustainability of public transportation should be evaluated from environmental, economic, and social perspectives to support policy decision‐makers and monitor the improvement. This research developed a sustainability indicator and used a case study to assess the sustainability of public transportation in Bangkok, by comparing the public bus to the rapid transit (electric rail transportation) service due to their high use rates in Bangkok. A sustainable efficiency indicator (SEI) was developed using the concept of eco‐efficiency and the negative impacts were extended to cover environmental, economic, and social aspects. The results showed that the environmental impact of the bus was greatest during the operational phase, whereas for rail transport, it was greatest during the construction phase. In terms of the economy, because the railway system had been designed to service a large population, an increase in passenger numbers for rail transportation could increase its sustainable efficiency. The social impact was assessed based on a satisfaction survey for each of the two types of transportation. All the impacts were converted into monetary values to calculate the SEI. The SEI could also be used to monitor the enhancement of sustainability effectiveness as a tracking performance indicator.

As a decision support tool, life cycle assessment (LCA) is prone to multiple uncertainties associated with the data, model structures, and options offered to practitioners. Therefore, to make the results reliable, consideration of these uncertainties is imperative. Among the various classifications, parameter, scenario, and model uncertainty are widely reported and well-acknowledged uncertainty types in LCA. There are several techniques available to deal with these uncertainties; however, each strategy has its own pros and cons. Furthermore, just a few of the methods have been included in LCA software, which restricts their potential for wider application in LCA research. This paper offers a comprehensive framework that concurrently considers parameter, scenario, and model uncertainty. Moreover, practitioners may select multiple alternatives depending on their needs and available resources. Based on the availability of time, resources, and technical expertise three levels—basic, intermediate, and advanced—are suggested for uncertainty treatment. A qualitative method, including local sensitivity analysis, is part of the basic approach. Monte Carlo sampling and local sensitivity analysis, both of which are accessible in LCA software, are suggested at the intermediate level. Advanced sampling methods (such as Latin hypercube or Quasi-Monte Carlo sampling) with global sensitivity analysis are proposed for the advanced level.

Emerging strategies to respond to public awareness of the environment include carbon emission reporting and labelling. In Thailand, however, only a small proportion of manufacturers have implemented carbon footprint programmes, and some have decided not to continue the programme after their labels expired. This situation mirrors that of many developing countries. This study aims to investigate the factors that drive the implementation of the footprint programme and obstacles that may hinder its long-term implementation. Benefits gained from this programme are also explored. A questionnaire was sent to companies that were or have been certified for the Thai carbon footprint label. Interviews with experts were also conducted to supplement the survey data. According to the statistical analysis, companies expected the carbon footprint programme to enhance their green image, increase their sales and reduce costs. However, benefits derived only in terms of the company’s image, employee development and satisfaction, and production costs returned, while no sales and marketing benefits were evident. The lack of social awareness of the label and of the climate change issue was the most significant challenge the implementers faced, as its rating scores were significantly higher than those of other barriers. Small companies also encountered difficulties due to the required initial investment. This study provides insight into the reasons many developing countries fail to pursue carbon labelling programmes. These issues have not yet been clarified by previous studies. The findings can help prospective companies overcome potential barriers and facilitate their strategic decision making. They can also help governments to develop appropriate policies to promote the carbon footprint label and enhance national sustainability.