Framework for the Development of Thai Normalisation Factors for Life Cycle Assessment in Thailand

Life cycle assessment (LCA) has become a widely recognized method for evaluating the environmental performance of a product or system along its supply chain. Nowadays, site-dependent Life Cycle Impact Assessment (LCIA) methods have been developed and LCA results could therefore potentially reflect the local, national, and/or regional environmental conditions. In Thailand, site-dependent normalisation factors (NFs) which could support the local decision context have not been developed yet. The objectives of this study are to review underlying methodologies of the NFs in existing LCIA methods; and to establish a framework for the development of Thai NFs. Depending upon the spatial scales, four LCIA methods (ReCiPe2016, EF 3.0, CML-IA baseline, and TRACI 2.1) were selected to be reviewed and considered when designing a framework. The theoretical approach for the NFs of the four selected LCIA methods is similar but the considered impact categories are different depending upon the spatial distribution and targeted environmental impacts. NFs from each LCIA method apply different reference inventory and year depending upon its spatial scale and data availability, and apply different approaches for data source selection. The selection of an appropriate reference system and representative year for the inventory, and data gap filling are essential criteria to develop NFs for life cycle assessment in Thailand. After the reference inventory is developed for the NFs of desired spatial scale (regional or national), the robustness of the inventory should be evaluated to reflect the actual impacts from each category. The developed framework could provide the required information for the future development of NFs and satisfy the required gap specific for Thailand. Besides, this framework is potentially applicable for other regions

Carbon Footprint: Concept, Methodology and Calculation

Carbon footprint (CF) is nowadays one of the most widely used environmental indicators and calculations of CF have been recently in very high demand. Many approaches, methodologies and tools, from simplified online calculators to other more scientific and complex life-cycle based methods, have been developed and are available for estimations. CF evaluations are, in general, focused on products and organizations, but calculation approach have been developed also for specific themes/sectors, such as for instance cities, individuals, households, farms, etc. This chapter is aimed at giving an updated and comprehensive overview on the concept of CF, and also on methodologies, technical standards, protocols and tools for its calculation. Attention is focused on the two main and usual scopes of CF assessment, i.e. products and organizations, but also on other relevant specific study subjects, also discussing methodological differences and issues.5n

Life cycle inventory modeling of phosphorus substitution, losses and crop uptake after land application of organic waste products

Purpose: Life cycle assessments (LCAs) that attempt to provide advice on treatment options for phosphorus (P) containing organic waste products encounter problems related to the quantification of mineral P fertilizer substitution, P loss and crop P uptake after land application. The purpose of this study was to develop a relatively easy to use life cycle inventory model, known as PLCI, that could be used to estimate these values. Methods: A life cycle inventory model for P was developed, which estimates the effect of an application of organic waste followed by ordinary fertilizer management in the modeling period. This was compared with a simulation without the initial waste application. The difference in mineral P fertilizer application (substitution), P loss and crop P uptake was then calculated and expressed as a proportion of the amount of waste applied. As an example, the effect of an initial application of mineral fertilizer, sewage sludge and ash on two farm types was simulated. These results were applied in an LCA case study of different sewage sludge treatment options. Results and discussion: Farm type influenced the P fertilizer substitution, loss and crop uptake factors. The application on an arable farm showed a substitution of 28 to 31%, relatively low P loss and a large spread in crop P uptake for the different P sources, compared with the pig farm. Application on a pig farm showed no mineral P substitution. For substitution, mineral fertilizer outperformed waste product fertilizer with a short modeling period, due to higher immediate P availability, which was not the case with a long period. The LCA case study showed that the P substitution factor had an influence on the environmental impact categories climate change and depletion of reserve-based abiotic resources while the P loss factor influenced freshwater eutrophication. Application of the P loss and substitution factors generated from the PLCI model resulted in higher environmental burdens and lower savings than using conventional factors. Conclusions: The soil P status mainly affected P substitution and loss, with the fertilizer type only having a small influence when soils had a low P status. The PLCI model can facilitate more coherent and rigorous estimates of P substitution and loss to be used in LCA studies involving application of waste products on agricultural land. This is important since P substitution and loss can have an important influence on impact categories, such as freshwater eutrophication and resource depletion