Air pollutant emissions from wildfires on Indonesian peatlands lead to poor regional air quality across south-east Asia. Fine particulate matter (PM2.5) emissions are particularly high for peat fires leading to substantial population exposure to PM2.5. Despite this, air quality monitoring is limited in regions close to peat fires meaning the impacts of peatland fires on air quality is poorly understood and it is difficult to evaluate predictions from atmospheric chemistry models. To address this, we deployed a network of low-cost (Purple Air) PM2.5 sensors at 8 locations across Central Kalimantan, where peat fires are frequent. The sensors measured indoor and outdoor PM2.5 concentrations during August to December 2023. During the haze season (September 1st to October 31st), daily mean outdoor concentrations were 120 mg m-3 but peaked at >400 mg m-3. Indoor PM2.5 concentrations were only ~10% lower (mean 110 mg m-3), indicating that is difficult for the population to reduce their exposure to PM2.5 from fires. The reduction in mean PM2.5 concentrations between outdoor and indoor environments was larger in urban locations (-11%) compared with rural locations (-3%), suggesting urban housing may provide better protection from outdoor air pollution. To generate an updated assessment for the population’s exposure to peatland fire PM2.5 we combine the information from monitoring both indoor and outdoor PM2.5 concentrations with modelled ambient (outdoor) PM2.5 concentrations from the WRF-Chem atmospheric chemistry transport model. Our updated exposure assessment accounts for the population’s personal exposure to peatland fire PM2.5 for the first time.

Over the past three decades, a new 'haze season' has emerged in the public discourse in Indonesia, Malaysia, and Singapore. The semantic construction of 'haze season' signifies societal acknowledgement of recurring and hazardous air pollution episodes caused by the widespread burning of tropical peatlands. This study problematizes the underlying political ecology of the discursive framing of haze as 'seasonal.' Through a comprehensive discourse analysis of news media and government/corporate/NGO documents, this paper identifies and analyses three storylines used by divergent groups of actors seeking to attribute meaning and value to haze: (1) 'it keeps coming back'; (2) 'it will go away'; and (3) 'it is normal'. Political actors draw upon these storylines to meet their distinctive political and ecological objectives. Divergent framing of seasonality by different actors reveals some of the mechanisms influencing haze mitigation and adaptation. Our study highlights the importance of unearthing and interrogating the underlying politics involved in constructing 'seasons of the Anthropocene'. The semantic construction and popularization of 'seasonality' for anthropogenic environmental events can be a double-edged sword, with familiarity enhancing societal preparedness, while normalization can lead to desensitization and inertia towards mitigation. Untangling the divergent pathways of politicizing Anthropocene seasonalities is key to determining whether and how societies can build a 'liveable future'.

Seasons are changing in the Anthropocene. Seasons serve as temporal frameworks for communities and societies to organize their livelihoods and activities around the expectation of recurrent environmental, social, and cultural events. In this article, we make an original case that the scale and rapidity of changes to our planet's biogeochemical cycles profoundly impact the sociopolitically interpreted (re)definitions of seasonal rhythms. We propose a conceptually novel typology for collating how new and evolving interactions between human and more-than-human environmental cycles are reflected in the seemingly simple—yet widely relatable—concept of “ seasons. ” We define emergent, extinct, arrhythmic (changes to timing), and syncopated (changes to intensity) seasons through our typology, to bring together disparate literature on evolving human–nature interactions, environmental knowledge production and deployment, local realities of environmental risk and disaster management, and the uneven spatiality of socioenvironmental feedback loops. Seasonality in the Anthropocene is political as it reflects a diversity of temporal ontologies and unveils unjust manifestations of the hegemony of standardized time and timescales, while the discursive construction of “seasonality” may be deployed for political and economic gains. We set an agenda for cross-geographical research that explores seasonality from place-based, multiscalar perspectives to unravel the complexities of seasonality in the Anthropocene.

Climate change is resulting in more extreme fire weather during major heatwaves. Across temperate Europe, shrub landscapes dominate the area burned, with the moisture content of fuels during these events determining the threat posed. Current controls on the moisture content of temperate fuel constituents and their response to future extreme heatwaves are not known. We took field measurements of live and dead heather (Calluna vulgaris) and organic soil moisture content across the UK over 3 years, including an intensive sampling campaign during the July 2022 heatwave. Here, we show that the fuel moisture content of live fuel is associated significantly with phenological variables, dead fuel only with weather variables, whilst organic-rich ground fuels are more associated with landscape variables. However, during the record 2022 heatwave there was a harmonisation in fuel moisture controls across different fuel constituents, with those controls being driven by weather alone. This caused synchronised extreme dryness outside of current seasonal norms across all fuel constituents at the same time and place. Future intense summer heatwaves can therefore be expected to align the most severe conditions for fire ignition, spread and impact in traditionally non-fire prone regions, producing humid temperate landscapes susceptible to extreme wildfire events.

AbstractIndonesia accounts for more than one third of the world's tropical peatlands. Much of the peatland in Indonesia has been deforested and drained, meaning it is more susceptible to fires, especially during drought and El Niño events. Fires are most common in Riau (Sumatra) and Central Kalimantan (Borneo) and lead to poor regional air quality. Measurements of air pollutant concentrations are sparse in both regions contributing to large uncertainties in both fire emissions and air quality degradation. We deployed a network of 13 low‐cost PM2.5 sensors across urban and rural locations in Central Kalimantan and measured indoor and outdoor PM2.5 concentrations during the onset of an El Niño dry season in 2023. During the dry season (September 1st to October 31st), mean outdoor PM2.5 concentrations were 136 μg m−3, with fires contributing 90 μg m−3 to concentrations. Median indoor/outdoor (I/O) ratios were 1.01 in rural areas, considerably higher than those reported during wildfires in other regions of the world (e.g., USA), indicating housing stock in the region provides little protection from outdoor PM2.5. We combined WRF‐Chem simulated PM2.5 concentrations with the median fire‐derived I/O ratio and questionnaire results pertaining to participants' time spent I/O to estimate 1.62 million people in Central Kalimantan were exposed to unhealthy, very unhealthy and dangerous air quality (>55.4 μg m−3) during the dry season. Our work provides new information on the exposure of people in Central Kalimantan to smoke from fires and highlights the need for action to help reduce peatland fires.

Background Accurate quantification of emissions from peatland wildfire is crucial for understanding their feedback to the atmospheric and Earth system. However, current knowledge on this topic is limited to a few laboratory and field studies, which report substantial variability in terms of the fire emission factors (EFs).Aims We aim to understand how emissions vary across the life cycle of a peatland fire.Methods In August/September 2018, we conducted the largest and longest to-date field-scale experimental burn on a tropical peatland in Sumatra, Indonesia. Field measurements of gas emissions from the fire experiment were conducted using an open-path Fourier transform infrared spectroscopy to retrieve mole fractions of 11 gas species.Key results For the first time, we calculated and reported EFs from 40 measurement sessions conducted over 2 weeks of burning, encompassing different fire stages (e.g. ignition, smouldering spread, and suppression) and weather events (e.g. rainfall). Our findings provide field evidence to indicate that EFs vary significantly among fire stages and weather events. We also observed that the heterogeneous physicochemical properties of peatland site (e.g. moisture content) influenced the EFs. We also found that modified combustion efficiency was highly sensitive to complex field variables and could introduce large uncertainties when determining the regimes of a peat fire.Conclusions and implications Further studies to investigate peat fire emissions are needed, and more comprehensive mapping of peatland heterogeneity and land use for emissions inventories, accounting for spatial and temporal variability in EFs since the initiation of a fire event is required. This research aims to understand how wildfires on degraded peatlands contribute to greenhouse gas emissions and haze in the atmosphere. The emissions were found to depend on the stage of the fire (from ignition to spread to suppression), the weather conditions and the properties of the peatland.

Background Fire activity in the UK and comparable regions of northwest Europe is generally out of phase with peak fire weather conditions.Aims Here, we assess the potential effect of phenology on fire occurrence patterns for the UK.Methods We examined fire occurrence and vegetation phenology in the UK for 2012-2023, mapped onto the main fire-affected vegetation cover types within distinct precipitation regions, allowing the fire occurrence for fuels in different phenological phases to be explored across distinct 'fuel' types and regions.Key results The UK's fire regime is characterised by burning in semi-natural grasslands and evergreen dwarf shrub ecosystems in early spring when vegetation is still dormant. During the high-greenness phase in late spring and summer, fire activity is reduced by a factor of 5-6 despite typically elevated fire weather conditions within that period.Conclusions and implications Semi-natural vegetation in the UK is very resistant to burning during the high-greenness phase. However, this 'fire barrier' is diminished during severe drought episodes, which are predicted to become more extreme in the coming decades. Incorporating phenology information into models therefore has great potential for improving future fire danger and behaviour predictions in the UK and comparable humid temperate regions. We examined fire activity and phenology for major vegetation types across the UK for 2012-2023 and found that phenology rather than fire weather was the main driver for fire occurrence. Fire weather dominated only in years with extreme drought and heatwave events, which are likely to become more frequent with climate change.

BACKGROUND:Studies have linked daily pollen counts to respiratory allergic health outcomes, but few have considered allergen levels. OBJECTIVE:We sought to assess associations of grass pollen counts and grass allergen levels (Phl p 5) with respiratory allergic health symptoms in a panel of 93 adults with moderate-severe allergic rhinitis and daily asthma hospital admissions in London, United Kingdom. METHODS:Daily symptom and medication scores were collected from adult participants in an allergy clinical trial. Daily counts of asthma hospital admissions in the London general population were obtained from Hospital Episode Statistics data. Daily grass pollen counts were measured using a volumetric air sampler, and novel Phl p 5 levels were measured using a ChemVol High Volume Cascade Impactor and ELISA analyses (May through August). Associations between the 2 pollen variables and daily health scores (dichotomized based on within-person 75th percentiles) were assessed using generalized estimating equation logistic models and with asthma hospital admissions using Poisson regression models. RESULTS:Daily pollen counts and Phl p 5 levels were each positively associated with reporting a high combined symptom and medication health score in separate models. However, in mutually adjusted models including terms for both pollen counts and Phl p 5 levels, associations remained for Phl p 5 levels (odds ratio [95% CI]: 1.18 [1.12, 1.24]), but were heavily attenuated for pollen counts (odds ratio [95% CI]: 1.00 [0.93, 1.07]). Similar trends were not observed for asthma hospital admissions in London. CONCLUSIONS:Grass allergen (Phl p 5) levels are more consistently associated with allergic respiratory symptoms than grass pollen counts.

Businesses and organisations across the world are adopting various digital tools, technologies and infrastructure to support their strategic and operational objectives. The remarkable growth of market leaders, such as Amazon, Uber and Google is indicative of the global impact of digital innovation more broadly. Despite the rise and continued innovation of digital products and services, there is considerable uncertainty over how such innovations tackle sustainability issues at different scales. This is a pertinent point considering the climate emergency and the need to tackle social as well as environmental issues in both the Global North and Global South. In this chapter, we provide a high-level overview of the sustainability impacts associated with digital innovation, and offer a way forward in terms of a research agenda. The chapter is organised into three main parts. First, we define the digital innovations terminology and identify a range of existing business applications for digital technologies. Second, we critically examine the sustainability impacts of digital innovations focusing on questions of resource efficiency and the sharing economy. Third, we identify four promising research themes and propose key research methods.

Widespread burning of tropical peatlands across regions of Malaysia and Indonesia is now considered to be an annual event in equatorial Southeast Asia. The fires cause poor air quality (‘haze’) across the region, affecting the health of millions, and leading to transboundary disputes between places that burn and the places downwind that suffer the smoke plumes from the burning. We seek to investigate the emerging social construction of a new season in the region – the ‘haze season’. Seasons are a social construct that enables societies to organise their livelihoods around the expectation of recurring phenomena. They are not defined ‘objectively’ by observed patterns of relevant variables (e.g. satellite fire detections or air quality indices), but are instead the product of deliberation and contestation of which phenomena to observe, and how to normalise such phenomena to reflect and serve matters of concern to particular societies. The emergence of a new season may imply the normalisation of the phenomena, which may carry both positive and negative implications for progress towards adapting to and/or mitigating haze and the fires that drive the pollution crisis – a good example of a socio-environmental feedback. In this paper, we seek to answer three research questions: * When is the ‘haze season’ (onset, duration)? * How is ‘haze season’ portrayed in the media? and * What role does the haze ‘seasonality’ play in shaping people’s behaviour towards haze? Does the new season play a role in normalisation (e.g. densensitisation), adaptation (e.g. wearing masks, indoor activities) and mitigation (e.g. fighting haze, activism) behaviours? To answer these questions, we analysed news articles published in Indonesia, Malaysia and Singapore through the Factiva database. First, we identified the monthly distribution of newspaper articles mentioning ‘haze’ and ‘haze season’. Then, we identified keywords associated with ‘haze’ and ‘haze season’ by comparing the words found in the articles mentioning each concept with a corpus of words drawn from general usage in the year 2020. This is followed by a keyness analysis between two corpora of articles, namely articles that mention only ‘haze’ and articles that mention ‘haze season’. By doing so, we compare the differences between two distinct textual corpora in order to discover divergent themes. Finally, we used structural topic modelling (STM) to identify topic clusters. We find a strong distinction between the themes of articles that are written about the ‘haze season’ and articles that simply refer to the haze problem alone. Articles that mention ‘haze’, but not ‘haze season’ focus on the root causes of the haze crisis – peatland fires in Indonesia, oil palm plantations, deforestation – as well as geopolitical cooperation to prevent fires (e.g. through ASEAN). Both our keyness and STM analysis revealed that the ‘haze season’ articles have strong association with the effects of the haze crisis, particularly during the haze season months – poor air quality, pollution standards, mask-wearing, air filtration – suggesting that seasonality plays a role in adaptation behaviour. Outside of the haze season months, articles mentioning the new season focus more on haze mitigation and associated political action.

Abstract This study quantified CO2 emissions from tropical peat swamp soils in Brunei Darussalam. At each site, soil was collected from areas of intact and degraded peat and CO2 flux, and total organic content were measured ex situ. Soil organic content (~20–99%) was not significantly different between intact and degraded forest samples. CO2 flux was higher for intact forest samples than degraded forest samples (~1.0 vs. ~0.6 μmol CO2 m−2 s−1, respectively) but did not differ among forest locations. From our laboratory experiments, we estimated a potential emissions of ~10–20 t CO2 ha−1 y−1 which is in the lower range of values reported for other tropical peat swamps. However, our results are likely affected by unmeasured variation in root respiration and the lability of resident carbon. Overall, these findings provide experimental evidence to support that clearance of tropical peat swamp forests can increase CO2 emissions due to faster rates of decomposition.

Peat wildfires can burn over large areas of peatland, releasing ancient carbon and toxic gases into the atmosphere over prolonged periods. These emissions cause haze episodes of pollution and accelerate climate change. Peat wildfires are characterised by smouldering – the flameless, most persistent type of combustion. Mitigation strategies are needed in arctic, boreal, and tropical areas but are hindered by incomplete scientific understanding of smouldering. Here, we present GAMBUT, the largest and longest to-date field experiment of peat wildfires, conducted in a degraded peatland of Sumatra. Temperature, emission and spread of peat fire were continuously measured over 4–10 days and nights, and three major rainfalls. Measurements of temperature in the soil provide field experimental evidence of lethal fire severity to the biological system of the peat up to 30 cm depth. We report that the temperature of the deep smouldering is ~13% hotter than shallow layer during daytime. During night-time, both deep and shallow smouldering had the same level of temperature. The experiment was terminated by suppression with water. Comparison of rainfall with suppression confirms the existence of a critical water column height below which extinction is not possible. GAMBUT provides a unique understanding of peat wildfires at field conditions that can contribute to mitigation strategies.

Repeat observations underpin our understanding of environmental processes, but financial constraints often limit scientists’ ability to deploy dense networks of conventional commercial instrumentation. Rapid growth in the Internet-Of-Things (IoT) and the maker movement is paving the way for low-cost electronic sensors to transform global environmental monitoring. Accessible and inexpensive sensor construction is also fostering exciting opportunities for citizen science and participatory research. Drawing on 6 years of developmental work with Arduino-based open-source hardware and software, extensive laboratory and field testing, and incorporation of such technology into active research programmes, we outline a series of successes, failures and lessons learned in designing and deploying environmental sensors. Six case studies are presented: a water table depth probe, air and water quality sensors, multi-parameter weather stations, a time-sequencing lake sediment trap, and a sonic anemometer for monitoring sand transport. Schematics, code and purchasing guidance to reproduce our sensors are described in the paper, with detailed build instructions hosted on our King’s College London Geography Environmental Sensors Github repository and the FreeStation project website. We show in each case study that manual design and construction can produce research-grade scientific instrumentation (mean bias error for calibrated sensors –0.04 to 23%) for a fraction of the conventional cost, provided rigorous, sensor-specific calibration and field testing is conducted. In sharing our collective experiences with build-it-yourself environmental monitoring, we intend for this paper to act as a catalyst for physical geographers and the wider environmental science community to begin incorporating low-cost sensor development into their research activities. The capacity to deploy denser sensor networks should ultimately lead to superior environmental monitoring at the local to global scales.

This paper presents an autoethnographic study which tracks the experience of routinely monitoring personal exposure to air pollution, using Plume Labs' “Flow” device. While conventional air quality data is provided by static monitoring stations, this paper seeks to understand how new intimate data from portable sensors can influence decision-making and induce behavioural change. This is explored in relation to self-tracking and the “Quantified Self” (QS) movement, recognising that the environment is intrinsically part of the self and the body. Through autoethnography and reflecting on experiences in London and Kuala Lumpur, this paper explores the practicalities of using Flow and its potential as a transformative tool to facilitate societal consciousness and change towards “the optimal self” with minimised exposure to air pollution. Through personal experience and interactions with others, this paper finds that individuals' willingness and ability to attempt to minimise exposure to air pollution is subject to a combination of factors within and beyond one's control. However, while self-tracking does not necessarily translate into attempts to minimise exposure, choosing to be exposed to higher levels of air pollution in certain circumstances becomes an active decision. While some maintained their scepticism of Flow's potential, and others remained apathetic towards air pollution, Flow was found to be particularly effective in cultivating curiosity and consciousness through its facilitation of conversations about air quality. Flow's provision of otherwise absent information and its potential to create a network of better-informed individuals is exciting but uncertain. This paper raises important questions about the role of the QS and such sensor devices in addressing urban air pollution and creating a sense of collective accountability to the environment, moving towards a new goal of “the optimal environment for our optimal selves.”.

Abstract This study supplements spatial panel econometrics techniques with qualitative GIS to analyse spatio-temporal changes in the distribution of integrated conservation–development projects relative to poaching activity and unauthorized resource use in Volcanoes National Park, Rwanda. Cluster and spatial regression analyses were performed on data from ranger monitoring containing > 35,000 combined observations of illegal activities in Volcanoes National Park, against tourism revenue sharing and conservation NGO funding data for 2006–2015. Results were enriched with qualitative GIS analysis from key informant interviews. We found a statistically significant negative linear effect of overall integrated conservation–development investments on unauthorized resource use in Volcanoes National Park. However, individually, funding from Rwanda's tourism revenue sharing policy did not have an effect in contrast to the significant negative effect of conservation NGO funding. In another contrast between NGO funding and tourism revenue sharing funding, spatial analysis revealed significant gaps in revenue sharing funding relative to the hotspots of illegal activities, but these gaps were not present for NGO funding. Insight from qualitative GIS analysis suggests that incongruity in prioritization by decision makers at least partly explains the differences between the effects of revenue sharing and conservation NGO investment. Although the overall results are encouraging for integrated conservation–development projects, we recommend increased spatial alignment of project funding with clusters of illegal activities, which can make investment decision-making more data-driven and projects more effective for conservation.

Although it has long been recognised that human activities affect fire regimes, the interactions between humans and fire are complex, imperfectly understood, constantly evolving, and lacking any kind of integrative global framework. Many different approaches are used to study human-fire interactions, but in general they have arisen in different disciplinary contexts to address highly specific questions. Models of human-fire interactions range from conceptual local models to numerical global models. However, given that each type of model is highly selective about which aspects of human-fire interactions to include, the insights gained from these models are often limited and contradictory, which can make them a poor basis for developing fire-related policy and management practices. Here, we first review different approaches to modelling human-fire interactions and then discuss ways in which these different approaches could be synthesised to provide a more holistic approach to understanding human-fire interactions. We argue that the theory underpinning many types of models was developed using only limited amounts of data and that, in an increasingly data-rich world, it is important to re-examine model assumptions in a more systematic way. All of the models are designed to have practical outcomes but are necessarily simplifications of reality and as a result of differences in focus, scale and complexity, frequently yield radically different assessments of what might happen. We argue that it should be possible to combine the strengths and benefits of different types of model through enchaining the different models, for example from global down to local scales or vice versa. There are also opportunities for explicit coupling of different kinds of model, for example including agent-based representation of human actions in a global fire model. Finally, we stress the need for co-production of models to ensure that the resulting products serve the widest possible community.