Exploring complementarity of Life Cycle Thinking and Landscape & Urban Planning towards sustainable urban co-design.: Case study : Electric based tricycle technologies for last kilometer delivery
Bibliographic record
Abstract
Nowadays, sustainability is gaining importance in territorial policies. Yet, no substantial efforts have been deployed for systematically integrating environmental, social and economic aspects in early stages of urban service co-design. While Life Cycle Assessment (LCA) is a suitable method for impact assessment of products and services, Landscape-Urban Planning (LUP) provides information on how these products and services interact at the territorial scale. Our understanding of urban systems’ needs could go a step further towards better consumption patterns and resources optimization by coupling both approaches. This work explores the synergy between Life Cycle Thinking and Landscape-Urban Planning by their application to an essential urban service: logistics. The challenging metabolism of high-density urban systems is taken as an opportunity to consider emergent logistic solutions, specifically electric tricycle technologies for last kilometer delivery. Firstly, we start by applying each approach individually; following LUP perspective, we define a territorial reading grid, based on a set of criteria describing physical, socio-cultural, and economic resources of a landscape. Then, using LCA, we quantify potential impacts or benefits of electric tricycles technology compared to the existing delivery technologies. Electricity for tricycle batteries’ charging is provided by photovoltaic systems. In a second step, results from both approaches are coupled to determine local urban hotspots that describe the main aspects to meet stakeholders’ needs and improve their living conditions. Sustainability design parameters are, thus, defined to optimize the tricycle technology. Finally, the design and optimization of the electric tricycle-based delivery system is carried out. The Geographical Information System (i.e .Quantum GIS) is used to explore local data on solar energy potential spots, cycling infrastructures, potential urban logistic platforms, etc. Energy required has been computed to determine adequate charging infrastructures, taking topography and climate conditions into account. Intelligent logistic planning is performed to improve efficiency, optimize the streamline to reduce environmental impacts and simulate interaction with other urban transportation flows. Based on the current case study, the urban service co-design framework has been fully established in order to gain sustainability in a territorial management scale through LCA and LUP perspectives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".