The challenge
Salt was defining the future of its waste collection service at a turning point: new regulatory requirements, a need to improve source-separation results, and a need to move towards systems with more traceability, shared responsibility, and the ability to incentivise better behaviour.
The main challenge wasn’t just defining which model could get the best results. It was determining which model could actually work in Salt.
The municipality combines high urban density, a significant share of multi-family buildings, a lack of private open space, streets and pavements with constraints, small dwellings, and high social diversity. This complexity isn’t evenly distributed, which raises real questions about whether a single system could work across the whole municipality.
That’s why the study was approached as a territorial, social, environmental and operational feasibility analysis of the different possible scenarios, before any decision was made about the future model.
That’s why the study was approached as a territorial, social, environmental and operational feasibility analysis of the different possible scenarios, before any decision was made about the future model.
Project development
The study starts from a comprehensive reading of the current system and progressively builds up to a comparison of scenarios.
The work covered:
- Analysis of the European, Spanish and Catalan legal framework.
- Diagnosis of the current collection model.
- Analysis of how generation and source separation have evolved.
- Analysis of fraction quality and contamination levels.
- Analysis of how the service currently operates and is organised.
- Territorial and cartographic reading of the municipality.
- Analysis of urban planning and socioeconomic parameters.
- Building a system for weighting complexity.
- Zoning the municipality by territorial characteristics.
- Specific analysis of economic activities and facilities.
- Identifying constraints and opportunities through a SWOT-CAME analysis.
- Defining the criteria for comparing scenarios.
- Comparative analysis of different collection models by zone.
- Technical assessment of scenarios against consistent criteria.
The goal was to move from a general diagnosis of the municipality to a territorial reading able to explain where, and why, each alternative might work better or run into more difficulties.
Methodology
One of the study’s distinctive features was building its own system for weighting territorial complexity.
The analysis combined two blocks of variables: urban-planning complexity and socioeconomic complexity.
Each parameter was scored on a complexity scale, and the results from the different blocks were then aggregated. This made it possible to build a quantitative, comparable reading of the municipality’s complexity.
But the analysis didn’t stop at an overall score. The same system was applied to the municipality’s different zones to see how the constraints changed across the territory. This reading uncovered something particularly significant: complexity wasn’t evenly spread, and the zone with the most urban-planning constraints also had the highest socioeconomic complexity and the densest concentration of activity.
This analysis made it possible to identify a particularly relevant reality: complexity was not homogeneous, and the area with the greatest urban planning constraints also had greater socioeconomic complexity and a high concentration of activity.
Comparing scenarios
With the diagnosis in place, criteria were defined to allow the alternatives to be compared consistently.
Each scenario was assessed on its ability to respond, at the same time, to different dimensions:
- Regulatory compliance and effective recycling
- Capture rate and fraction quality
- Reducing the residual waste fraction
- Identification and traceability of contributions
- Ability to link the service to future behaviour-based taxation
- Compatibility with the urban reality
- Adaptation to socioeconomic characteristics
- Specific viability in each zone
- Social acceptance and ease of rollout
- Quality and use of public space
- Integration of commercial and complementary flows
- Flexibility and the system’s capacity to be adjusted
- The model’s ability to steer the service towards results
The comparison made it possible to assess what each model could do under ideal conditions, and how it would respond to Salt’s specific conditions.
Results
- Comprehensive diagnosis of Salt’s current collection system.
- Identification of the main environmental, operational, territorial and social constraints.
- Building a methodology for weighting urban-planning and socioeconomic complexity.
- Cartographic analysis of the main parameters shaping collection.
- Zoning the municipality by territorial characteristics.
- Identifying the areas with the greatest complexity and need for adaptation.
- Specific analysis of economic activities and facilities.
- Defining a set of objective criteria for comparing alternatives.
- Technical comparison of the different scenarios by zone.
- Identifying the main advantages, limitations and risks of each alternative.
- Building a technical basis to guide the definition of the future service.
Conclusions
The feasibility of a collection model cannot be determined solely by its environmental or operational potential.
The viability of a collection model can’t be determined by its environmental or operational potential alone.
In a municipality like Salt, the answer depends on the relationship between the collection model and the territory: urban planning, housing, public space, density, economic activity, social characteristics, and how well users can adapt.
The methodology developed makes it possible to move from a generic question — what’s the best model? — to a much more useful one for decision-making: which model, under what conditions and with what adaptations, can actually work in each part of the municipality?
This way of working reduces the risk of decisions based purely on theoretical comparisons, and builds a solid technical basis for defining and rolling out the service afterwards.
Lessons learned
- Complexity can be measured. Combining urban-planning and socioeconomic variables turns a complex reality into comparable information for guiding decisions.
- A municipality isn’t necessarily a single system. Zoning makes it possible to identify internal differences and assess how well each alternative fits the specific conditions of the territory.
- A model’s potential isn’t enough on its own. A system can offer great results on paper and still run into rollout problems if it doesn’t fit the housing, the public space, or the social conditions.
- Comparison has to weigh performance against viability. The most suitable alternative isn’t necessarily the one that scores best on a single variable — it’s the one that responds in a balanced way to the service’s different constraints.
Complexity isn’t a barrier: it’s information for designing better.