the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Jun 2026
ENSO Modulation of PM2.5 air pollution in Central Kalimantan, Indonesia revealed by a dense network of Purple Air sensors
Abstract. Peatland fires in Indonesia drive severe air pollution. Studies have focused on El Niño years, therefore neutral and La Niña years remain uncharacterised. We deploy a dense network of PM2.5 sensors across Central Kalimantan peatlands between August 2023 and October 2025 to quantify how El Niño–Southern Oscillation (ENSO) modulates the magnitude and spatial variability in dry season PM2.5 concentrations. Sensors were installed at urban, rural, and remote locations, spanning El Niño (2023), neutral (2024), and La Niña (2025) dry seasons. During the 2023 El Niño dry season, low rainfall and deep water tables enhanced peatland flammability and supported extensive peat fires. Urban and rural sites exceeded the WHO 24‑hour PM2.5 guideline on 99 % and 97 % of days. A remote site exceeded these guidelines on 85 % and 24 % of days, with fire smoke influence confirmed by low spatial variability and a dual‑peak diurnal cycle across sites, indicating regional pollution rather than local sources. As ENSO conditions shifted to neutral (2024) and La Niña (2025), increased rainfall and shallower water tables reduced fire activity and PM2.5 concentrations. In 2024, WHO guideline exceedances fell to 41 % and 12 % at urban and rural sites. Our results indicate that even across non-El Niño years, dry season PM2.5 is influenced by regional fire emissions, but the magnitude and spatial variability is modulated by ENSO-phase. Our results demonstrate that dense sensor networks can distinguish regional fire smoke from local pollution, enabling early detection of fire‑driven air quality degradation. Reducing peatland fires through restoration and fire management would deliver consistent air quality benefits.
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Status: final response (author comments only)
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CC1: 'Comment on egusphere-2026-2746', Nima Zafarmomen, 05 Jul 2026
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CC2: 'Reply on CC1', Zhiheng Liao, 06 Jul 2026
Dear Editor and Authors:
I have serious doubts about the true purpose of Nima Zafarmomen's eponymous community comments on multiple ACPD articles (including this article). Nima Zafarmomen has recently posted numerous comments on papers covering very different topics (see attached comments), and in all of them, he strongly recommends citing his own article, "Comprehensive spatiotemporal analysis of long-term mobile monitoring for traffic-related particles in a complex urban environment," which is scheduled to appear in Atmospheric Pollution Research only in May 2026. In my humble opinion, that paper has no essential relevance to the articles he comments on. Moreover, Nima Zafarmomen's academic background (hydrometeorology) is far removed from the research directions relevant to the articles he comments on. Given these circumstances, I question the genuine intent behind Nima Zafarmomen's submitted eponymous community comments, and I would kindly ask the handling editor and the manuscript authors to give full consideration to the reliability of his comments.
Zhiheng Liao
Institute of Urban Meteorology, China Meteorological Administration, Beijing, China
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CC3: 'Reply on CC2', Nima Zafarmomen, 06 Jul 2026
Thank you for sharing your opinion. However, your comment appears to be based on assumptions about my background and motivations rather than on the scientific content of my community comment. Like you, I participated in the discussion by providing my scientific opinion. Whether any suggested reference is relevant is entirely for the authors and the handling editor to decide. If you believe there are scientific flaws in my comments, I would be happy to discuss those specific points.
Otherwise, I believe it is more constructive to focus on the science rather than on personal assumptions about other contributors.
Citation: https://doi.org/10.5194/egusphere-2026-2746-CC3 -
CC4: 'Reply on CC3', Zhiheng Liao, 06 Jul 2026
I have no right to decide; I am only offering my opinion to the handling editor and the authors. They will make the final judgment on the scientific soundness and reliability of your comments.
Citation: https://doi.org/10.5194/egusphere-2026-2746-CC4 -
CC5: 'Reply on CC4', Nima Zafarmomen, 06 Jul 2026
Exactly. Then I believe the discussion should focus on the scientific merits of my comment, not on assumptions about my background or intentions. The handling editor and the authors will decide its relevance.
Citation: https://doi.org/10.5194/egusphere-2026-2746-CC5
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CC5: 'Reply on CC4', Nima Zafarmomen, 06 Jul 2026
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CC4: 'Reply on CC3', Zhiheng Liao, 06 Jul 2026
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CC3: 'Reply on CC2', Nima Zafarmomen, 06 Jul 2026
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CC2: 'Reply on CC1', Zhiheng Liao, 06 Jul 2026
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RC1: 'Comment on egusphere-2026-2746', Anonymous Referee #1, 24 Jul 2026
The authors present a well-written and interesting paper highlighting the air-pollution impacts arising from the intersection of land-use change and meteorological phenomena La Niña and El Niño). I have no major comments only some minor Comments
Line 325- From August to November 2023, moderate to strong El Niño conditions (1.4–2.0 °C) (Figure 2 (d)
- Could the authors briefly clarify whether precipitation and water-table conditions leading up to August 2023 contributed to the severity of the fires? Or if this year was an outlier in terms fire emissions during El Nino. A similar point is raised later in the discussion, where the authors state that the 2019 fires produced more severe air-quality impacts. This may suggest that fire activity in 2023 was lower than average for an El Niño year.
Figure 4
- There is a small typo (“2023/34”), and the wording is slightly unclear. I was unsure whether the dashed line represents the combined mean of the 2023/24 and 2024/25 wet seasons or an overall 2023–2025 average at first. The corresponding description of the dry season is clearer.
Lines 320–325:
- Could the authors clarify whether the fine particulate matter at the remote site is transported from the urban and rural areas, or similar regional biomass burning emissions? If available, prevailing wind data or back trajectories would help clarify.
Line 326: The contrast between wet and dry season behaviour at the remote site also provides an estimate of fire contributions (red shading).
- Does the dry–wet season difference provide only a rough indication of fire influence? The authors later acknowledge the potential role of wet scavenging. Other meteorological factors may also affect the comparison. The statement could therefore be softened to reflect these confounding influences.
Line 380 –
- I initially found the line about the 2019 comparison unclear, as the preceding sentence discusses Uda et al., (2019), which covers the period 2011–2015. Please clarify that this refers to the 2019 fire season examined by Grosvenor et al. (2024) or the Uda et al., 2019 study.
Line 400 – In contrast, in 2023 a large percentage of days fall into the moderate category at Kereng 400 (39%) and Palangka Raya (32%). However
- Could this be partially due to reduced burn depth for repeat fires at the same location (Konecny et al. (2016))
Citation: https://doi.org/10.5194/egusphere-2026-2746-RC1 -
EC1: 'Comment on egusphere-2026-2746', N'Datchoh Evelyne Touré, 28 Jul 2026
After carefully considering the community comments, I have concluded that some points raised are not directly aligned with the scope or scientific content of the manuscript. As editor, my role is to ensure that authors focus their revisions on comments that contribute meaningfully to strengthening the manuscript. Therefore, I advise the authors to prioritize addressing constructive comments raised during the review process that help improve the manuscript. The suggestions provided in this community comment, including the proposed citations feeding the current discussion on this manuscript, do not meet this criterion and thus do not need to be addressed.
Citation: https://doi.org/10.5194/egusphere-2026-2746-EC1 -
RC2: 'Comment on egusphere-2026-2746', Anonymous Referee #2, 06 Sep 2026
General Comments
This is an interesting study based on a valuable multi-year dataset of PM2.5 measurements in Central Kalimantan. The relatively dense network of low-cost sensors, with measurements spanning three contrasting dry seasons, provides useful information on the spatial and temporal variability of PM2.5 in a region where ground-based observations remain limited. I found the comparison between the high-fire 2023 season and the much lower-fire conditions in 2024 and 2025 interesting, since previous studies have mainly focused on severe El Niño fire years.
I think the manuscript is suitable for ACP and can make a useful contribution. My main concern is with the interpretation of some of the results. In several places, the conclusions go beyond what can be directly supported by the analysis, particularly when observed associations are interpreted as causal relationships. My main comments are below.
The manuscript repeatedly concludes that ENSO phase controls peat hydrology, fire emissions, PM2.5 concentrations, and ultimately population exposure. It makes statements such as “ENSO-phase controls exposure risk” and “ENSO strongly modulates fire emissions”, and identifies a “climate–hydrology–fire–air quality cascade.” The proposed mechanism is reasonable and supported by previous studies. However, the dataset presented here includes one dry season for each ENSO condition: El Niño in 2023, neutral conditions in 2024, and La Niña conditions in 2025. ENSO phase therefore varies together with year, rainfall, water-table depth, fire activity, meteorology, and several other factors.
I believe that three contrasting years are not sufficient to demonstrate the strength of the ENSO control implied throughout the manuscript. What the observations clearly show is that PM2.5 concentrations were much higher during the dry and high-fire El Niño season of 2023 than during the wetter and lower-fire seasons of 2024 and 2025. The physical connection with ENSO is plausible, but the manuscript should separate more clearly what is demonstrated by this dataset from what is inferred from the established understanding of ENSO impacts in the region. I suggest framing some of the conclusions around three hydroclimatically contrasting dry seasons occurring under different ENSO conditions, rather than presenting the measurements as direct evidence of ENSO control.
The paper acknowledges that the number of sensors varied over the study period, but I could not find a discussion of how this may affect comparisons between years, particularly the CoV analysis. The number of outdoor sensors changes considerably, from 4 in 2023 to 42 in 2024 and 6 in 2025, and the calculated spatial variability may depend on the number and location of the sites included. The manuscript should at least discuss how these changes in the sensor network may affect the results and their interpretation.
The paper also derives one RH correction from July 2024–January 2025 and applies it to the whole 2023–2025 dataset, including the extreme 2023 fire period. This may be reasonable, but aerosol optical properties during intense peat-smoke episodes may be quite different from those during the calibration period. Since PM2.5 exceeds several hundred ug m−3 in 2023, the authors should discuss the extrapolation of the correction and show the concentration range covered by the calibration.
In the Introduction, the paper gives “25 mg m−3” as the WHO 24-hour PM2.5 limit (Lines 47–48). The current WHO 2021 24-hour guideline is 15 ug m−3, not 25 ug m−3 (I assume mg m−3 is a typo). It is not clear from the analysis which value was used to calculate the exceedances. If the analysis uses 25 ug m−3, the exceedances need to be recalculated, as this could substantially change the results and requires more than a textual correction.
I also found difficult at times to link the Discussion back to the Results. The Discussion does not follow the same order as the Results and moves between different parts of the analysis, making the paper harder to follow. I suggest either dividing the Results into subsections that match those in the Discussion, or reorganising the Discussion to follow the order in which the results are presented.
Specific comments
Introduction. The Introduction could say more about why peat fires have such a large impact on near-surface air quality. A key characteristic of Indonesian peat fires is that they are dominated by smouldering combustion, producing smoke plumes with relatively low injection heights. Much of the smoke therefore remains within the boundary layer, leading to high near-surface PM2.5 concentrations and potentially long exposure periods. This has been shown using MISR observations (Tosca et al., 2011), for example.
https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2010JD015148
Lines 71–72. Some other recent studies may be relevant here, including studies using PurpleAir sensors to investigate smoke pollution in the USA:
Green barriers: https://www.mdpi.com/1660-4601/22/2/306
Fires: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023GH000982 https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025GH001365
Lines 141–143. Grammar: “BAM instruments report mass concentrations under specific temperature and relative humidity conditions (EPA, 2016). Whereas low-cost sensors measure in ambient conditions where relative humidity is not controlled.
Line 276. Oceanic Niño Index (ONI) is already defined above. Please check acronyms throughout the manuscript and only define them when first mentioned.
Line 310. Section 3.3. Where are Sections 3.1 and 3.2?
Lines 365–366. The Results give 2024 fire counts of 479 versus 16,169 in 2023, which is about a 34-fold reduction, whereas the Discussion states “reducing fire activity by a factor of 250 and fire emissions by a factor of 33.” Where does the factor of 250 come from?
Line 406. “88% of days in Kereng and 93% of days in Kereng.” I assume the second refers to Palangka Raya?
Citation: https://doi.org/10.5194/egusphere-2026-2746-RC2
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The manuscript presents a multi-year air-quality monitoring study examining how ENSO phase modulates PM2.5 pollution from Indonesian peatland fires in Central Kalimantan. The authors use a dense PurpleAir sensor network deployed across urban, rural, and remote sites from August 2023 to October 2025, covering El Niño, neutral, and La Niña dry seasons. The study shows that the 2023 El Niño dry season produced severe peat drying, extensive fire activity, and high PM2.5 exposure, while wetter neutral and La Niña conditions in 2024 and 2025 reduced fire activity and PM2.5 concentrations. The manuscript is timely and valuable because it demonstrates how dense low-cost sensor networks can distinguish regional fire-smoke influence from local pollution sources and provide practical evidence for early-warning and peatland management strategies.