98%
921
2 minutes
20
Indonesia 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 PM sensors across urban and rural locations in Central Kalimantan and measured indoor and outdoor PM concentrations during the onset of an El Niño dry season in 2023. During the dry season (September 1st to October 31st), mean outdoor PM concentrations were 136 μg m, with fires contributing 90 μg m 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 PM We combined WRF-Chem simulated PM 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) 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.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11532237 | PMC |
http://dx.doi.org/10.1029/2024GH001125 | DOI Listing |
Environ Monit Assess
September 2025
Department of Environment and Life Science, KSKV Kachchh University, Bhuj, Gujarat, 370 001, India.
India's energy demand increased by 7.3% in 2023 compared to 2022 (5.6%), primarily met by coal-based thermal power plants (TPPs) that contribute significantly to greenhouse gas emissions.
View Article and Find Full Text PDFLight Sci Appl
September 2025
Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 230031, Hefei, China.
Marine vessels play a vital role in the global economy; however, their negative impact on the marine atmospheric environment is a growing concern. Quantifying marine vessel emissions is an essential prerequisite for controlling these emissions and improving the marine atmospheric environment. Optical imaging remote sensing is a vital technique for quantifying marine vessel emissions.
View Article and Find Full Text PDFEnviron Res
September 2025
Thrust of Sustainable Energy and Environment, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 510000, China. Electronic address:
China's aluminum-products industry, a large-scale consumer of industrial paints, is a potentially significant source of full-volatility organic compounds (F-VOCs). However, the emission characteristics of F-VOCs, including VOCs, intermediate-, semi-, and low-volatility organic compounds (I/S/LVOCs), and their role in ozone formation potentials (OFP), and secondary organic aerosol formation potentials (SOAP) remain unclear. In this study, we collected in-field samples from three industrial paints (solvent-based, water-based and powder paints) at spraying and drying processes, and treatment devices to analyze the emission characteristics of F-VOCs, OFP, SOAP.
View Article and Find Full Text PDFJ Environ Manage
September 2025
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
Dissolved oxygen (DO) is a key water quality indicator reflecting river health. Modeling and understanding the spatiotemporal dynamics of DO and its influencing factors are crucial for effective river management. Machine learning (ML) models have gained popularity in water quality prediction; however, their accuracy strongly depends on the predictor variables.
View Article and Find Full Text PDF