A citizen science behavioural dataset of an urban collective-risk dilemma on air pollution mitigation under resource inequality
Abstract
This article describes a behavioural dataset from a collective-risk dilemma public experiment carried out in Barcelona, Spain, within the citizen science \textit{xAire} air quality project. Participants played a ten-round game in groups of six, each deciding every round how many monetary units to contribute from a private endowment toward a shared target; groups that fell short forfeited all remaining capital. Three endowment treatments held the group total fixed: an equal condition and two unequal conditions in which low-endowment participants formed either the minority or the majority of the group. Data were collected at two public outdoor venues using a tablet-based interface under lab-in-the-field protocols. Participants were recruited on-site from a demographically heterogeneous pool of individuals passing through the venues, mostly local residents. The dataset comprises 462 participants across 77 six-player games, 4\,620 contribution decisions in total. Each participant record links the full ten-round contribution trajectory to initial endowment, wealth treatment, venue, district of residence and its measured nitrogen-dioxide concentration, and socio-demographic and attitudinal survey items covering gender, age, education, economic and working status, air-quality perception, fairness norms, environmental-justice beliefs, residential mobility, and community participation. The release provides raw and cleaned participant tables, a variable codebook, the survey instrument, the district-pollution linkage, and the preprocessing code.
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BibTeX
@misc{sadurni2026citizen,
title = {{A citizen science behavioural dataset of an urban collective-risk dilemma on air pollution mitigation under resource inequality}},
author = {Marc Sadurní and Martín F. Díaz and Julián Vicens and Anna Cigarini and Isabelle Bonhoure and Miquel Montero and Josep Perelló},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.35417},
eprint = {2609.35417},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.35417},
note = {CC BY-NC-SA 4.0},
}
RIS
TY - UNPB
TI - A citizen science behavioural dataset of an urban collective-risk dilemma on air pollution mitigation under resource inequality
AU - Marc Sadurní
AU - Martín F. Díaz
AU - Julián Vicens
AU - Anna Cigarini
AU - Isabelle Bonhoure
AU - Miquel Montero
AU - Josep Perelló
PY - 2026
DA - 2026/09/28
PB - arXiv
DO - 10.48550/arxiv.2609.35417
UR - https://arxiv.org/abs/2609.35417
AB - This article describes a behavioural dataset from a collective-risk dilemma public experiment carried out in Barcelona, Spain, within the citizen science \textit{xAire} air quality project. Participants played a ten-round game in groups of six, each deciding every round how many monetary units to contribute from a private endowment toward a shared target; groups that fell short forfeited all remaining capital. Three endowment treatments held the group total fixed: an equal condition and two unequal conditions in which low-endowment participants formed either the minority or the majority of the group. Data were collected at two public outdoor venues using a tablet-based interface under lab-in-the-field protocols. Participants were recruited on-site from a demographically heterogeneous pool of individuals passing through the venues, mostly local residents. The dataset comprises 462 participants across 77 six-player games, 4\,620 contribution decisions in total. Each participant record links the full ten-round contribution trajectory to initial endowment, wealth treatment, venue, district of residence and its measured nitrogen-dioxide concentration, and socio-demographic and attitudinal survey items covering gender, age, education, economic and working status, air-quality perception, fairness norms, environmental-justice beliefs, residential mobility, and community participation. The release provides raw and cleaned participant tables, a variable codebook, the survey instrument, the district-pollution linkage, and the preprocessing code.
ER -