Evaluating Environmental Equity in Valencia Using High‑Resolution Data

Urban environmental equity is a growing concern for policymakers seeking to ensure sustainable and inclusive cities. This study develops a methodology to evaluate environmental equity at an urban level with high spatial resolution, integrating air quality data and socioeconomic vulnerability indicators. The case study is Valencia, Spain (project start: 2021; end: ongoing).

The methodology combines geo‑referenced economic, social and environmental variables with data from a network of NO₂ passive sensors. This approach enables the identification of vulnerable neighbourhoods where poor air quality and socioeconomic disadvantages overlap, revealing potential environmental inequities.

Four types of vulnerability were assessed:

1. Equipment vulnerability – access to transport, health, education and public services.
2. Demographic vulnerability – population density, age distribution and dependent populations.
3. Socioeconomic vulnerability – income levels, education and employment.
4. Global vulnerability – an aggregate of the three previous factors.

Air quality was monitored using 648 passive NO₂ sensors deployed across the city following EU Directive 2008/50/EC standards, with data collected across four seasonal campaigns in 2021.

The study found that neighbourhoods near major roads and city entrances exhibited the worst air quality, while highly vulnerable neighbourhoods were more dispersed across the city. Only 14.28 % of neighbourhoods were both highly vulnerable and had poor air quality, suggesting no direct correlation but highlighting specific zones of concern. This methodology provides a data‑driven tool for decision‑makers, allowing for targeted interventions to improve both air quality and urban equity.

The produced impact

The application of this methodology in Valencia has provided high‑resolution mapping of urban environmental equity, offering valuable insights for city planning.

• The study successfully identified the most vulnerable neighbourhoods, considering socioeconomic conditions, access to services and air‑pollution levels.
• It revealed that 45.7 % of Valencia’s neighbourhoods exceed the EU’s NO₂ limit (40 µg/m³), with the highest concentrations found at the city’s main road entrances.
• The findings challenge the assumption that vulnerability and pollution always overlap, emphasising the need for tailored policies rather than blanket approaches.

By integrating real‑world air‑quality data with socioeconomic analysis, this methodology allows policymakers to prioritise interventions where they are most needed. The study serves as a replicable model for other cities looking to address urban environmental equity challenges.

Key lessons learnt

1. Granular data is crucial – High‑resolution environmental and socioeconomic data provide a clearer picture of urban disparities.
2. Targeted policies are needed – Poor air quality does not always coincide with vulnerable populations, requiring location‑specific interventions.
3. Passive sensor networks work – The use of 648 NO₂ sensors enabled detailed mapping of pollution levels across neighbourhoods.
4. Urban planning must integrate multiple factors – Addressing environmental equity requires considering both social and infrastructural aspects.
5. Replicability – This methodology can be applied in other cities with minor adjustments, making it a valuable tool for sustainable urban planning.