Camille Fournier de Lauriere

Air pollution is a leading health risk, especially in large cities of the Majority World. In these emerging markets and developing economies, it remains unclear whether residents will demand mitigation, perceive it as a threat or view poor air quality as a necessary part of development. Competing theories predict either strong or weak support and cross-national evidence is scarce, particularly for measures of policy support. Here we surveyed 11,417 adults in 4 severely polluted cities—Accra, Delhi, Jakarta and Johannesburg. Air quality was a highly prioritized issue and overall levels of concern are very high. Majorities support six mitigation proposals, including cost-salient measures such as stricter industrial limits, increasing household electrification and expanding public transport. Concern, trust and low perceived behavioral control were the strongest correlates of support. People see air pollution, feel its effects and want governments to act, even when action entails economic costs, challenging views of limited environmental demand in highly exposed, economically developing settings.

Air pollution is a global health crisis, but evidence on public perceptions of pollution exposure and mitigation demands remains fragmented. We first map "what research covers" by reviewing the survey-based literature on public views of air pollution, coding 456 studies through a transparent, LLM-assisted screening and classification workflow. Then, we map "what surveys offer" by cataloging 112 air-quality survey items in cross-national survey programs, coding them manually using the same classification framework. We find persistent geographic and exposure-level biases: survey-based research focuses on high-income countries, China and India, while cross-national item coverage is more clustered in Europe. Thematically, both domains emphasize perceptions, with gaps in behavior, policy preferences, and health—particularly in high-exposure regions. These findings highlight that where mitigation is most needed, research coverage is most limited and accessible survey data most scarce. Methodologically, the paper develops a validated LLM-assisted workflow to facilitate future large-scale literature mapping and classification.

Air pollution is a leading health risk, especially in emerging markets and developing economies. Yet, it remains unclear whether citizens will demand mitigation, perceive it as a threat, or view poor air quality as a necessary part of development. Competing theories predict either strong or weak support, and cross-national evidence is scarce, particularly for measures of policy support. We surveyed 11,562 adults in four severely polluted cities — Accra, Delhi, Jakarta, and Johannesburg. Air quality was a highly prioritised issue, and overall levels of concern are very high. Majorities back six different mitigation proposals, including cost-salient measures such as stricter industrial limits, increasing household electrification, and expanding public transport. Concern, trust, and low behavioural control were the strongest predictors of support. People see air pollution, feel its effects, and want governments to act, even when action entails economic costs, challenging views of limited environmental demand in highly exposed, economically developing settings.

Air pollution is a global health crisis that disproportionately affects lower- and middle-income countries. We examine global air quality monitoring data, highlighting persistent inequalities in high-exposure regions, and assess the potential of emerging technologies to improve data utility for mitigation. Improving air quality, however, does not need to wait for more data, nor will monitoring alone drive action. Immediate mitigation measures with broad cobenefits are needed now to reduce pollution, even in data-scarce settings.

Outdoor air pollution is responsible for more than 4 million premature deaths annually, with disproportionate impacts in low- and middle-income countries. Despite the human and economic cost of air pollution, many cities worldwide lack reliable air pollution data, even in regions suspected of having the highest levels of pollution. The publication of air quality information has been widely advocated as a critical step towards reducing pollution and improving public health, as it can raise awareness, drive regulatory action, and empower citizens to demand effective policies.In practice, China’s extensive Air Quality Monitoring (AQM) campaigns have successfully raised public attention and awareness while reducing pollution levels. Similarly, it is documented that reference-grade monitors at U.S. embassies have led to significant pollution reductions. Despite these examples, we lack a systematic understanding of how AQM campaigns translate into pollution reductions. Notably, the role of ‘low-cost’ sensors -that are cheaper, easier to deploy and maintain and show increasing accuracy to measure air pollution levels- is not yet broadly documented.This research is a quantitative evaluation of the extent to which reference-grade monitors and low-cost sensors might be associated with reductions in pollution levels. We also explore how socio-economic and political contexts may mediate the effectiveness of AQM, particularly in developing regions where regulatory enforcement and public responsiveness vary. Understanding how AQM in different developing contexts may or may not lead to improved air quality could prove invaluable in designing new successful campaigns without hindering economic development.

Resilience is a key feature of ecosystem dynamics reflecting a system's ability to resist and recover from environmental perturbations. Slowing down in the rate of recovery has been used as an early‐warning signal for abrupt transitions. Recent advances in Earth observation (EO) vegetation data provide the capability to capture broad‐scale resilience patterns and identify regions experiencing resilience loss. However, the proliferation of methods for evaluating resilience using EO data has introduced significant uncertainty, leading to contradictory resilience estimates across approximately 73% of the Earth's land surface. To reconcile these perspectives, we review the range of methods and associated metrics that capture aspects of ecosystem resilience using EO data. Using a principal component analysis, we empirically test the relationships between the most widely used resilience metrics and explore emergent patterns within and among the world's biomes. Our analysis reveals that the 10 resilience metrics aggregate into four core components of ecosystem dynamics, highlighting the multidimensional nature of ecosystem resilience. We also find that ecosystems with slower recovery are more resistant to drought extremes. Furthermore, the relationships between resilience metrics vary across the world's biomes and vegetation types. These results illustrate the inherent differences in the dynamics of natural systems and highlight the need for careful consideration when evaluating broad‐scale resilience patterns across biomes. Our findings provide valuable insights for identifying global resilience patterns, which are critically needed to inform policy decisions and guide conservation efforts globally.

1) Context: The resilience of the Earth's vegetation is changing heterogeneously, making it a challenge to unveil what causes these resilience changes. Understanding the driving forces of these changes can help us make informed management decisions to protect and restore ecosystems. Here, we address this gap by identifying the drivers that have caused the resilience of ecosystems to change during the last two decades.2) Methods: We globally measured two complementary aspects of resilience, namely sensitivity and autocorrelation, which are respectively associated with the resisting and recovering ability of ecosystems. We used a machine learning approach to identify the main environmental, climatic, and anthropogenic drivers of changes in resilience between two periods (the period 2000-2010 vs. that of 2010-2020).3) Results: We found that in 26% of regions worldwide, vegetation exhibits signs of resilience loss. Moreover, ecosystem’s properties (aridity, elevation, anthropization) affect the way vegetation resilience has changed over time. When controlling for these properties, different biomes (forest, grasslands, and savannas) will exhibit similar responses to changes in climate conditions. Regions experiencing intense warming (>0.2ºC/decade) have shown a major loss in vegetation resilience. Decreasing productivity is associated with reduced resilience and interacts with warming, exacerbating resilience loss of less productive lands (potentially showing signs of degradation). 4) Conclusions: Warming and degradation appear as major drivers of losses in vegetation resilience across vegetation types. These results raise concerns about the persistence of ecosystems under continued climate change and expected intensification of human activities which, highlights the importance of maintaining the resilience of ecosystems under changing environmental conditions.

Quantifying biodiversity across the globe is critical for transparent reporting and assessment under the Kunming-Montreal Global Biodiversity Framework. Understanding the full complexity of biodiversity requires consideration of the variation of life across genetic, species and ecosystem levels. Achieving this in a globally-standardized way remains a key international challenge for biodiversity monitoring efforts. Here, we present the Sustainable Ecology and Economic Development (SEED) framework, which consolidates multiple dimensions of biodiversity into a single measure of biocomplexity as a holistic estimate of the current state of nature at a given location. The SEED framework continuously integrates state-of-the-art datasets and maps of the biological variation in plants, microbes, animals, and ecosystems to estimate the local biocomplexity across the planet relative to a comparable, minimally-disturbed ‘reference’ ecosystem. The SEED framework allows an assessment of ecological health in response to positive and negative human impacts, and informs decision makers who strive to improve the global state of nature.