Peat Forest Fires Research Articles

The Impact of Atmospheric Stability Affected by Peat Forest Fire on Surface PM2.5 Concentration in Pontianak Urban Area during La Nina Events 2022

The Impact of Atmospheric Stability Affected by Peat Forest Fire on Surface PM2.5 Concentration in Pontianak Urban Area during La Nina Events 2022

AN ANALYSIS OF FOREST AND LAND FIRE EXTINGUISHING IN INDONESIA INFLUENCED BY THE EL NINO PHENOMENON USING THE WATER BOMBING METHOD

Land and peat forest fires in Indonesia are a serious environmental problem, especially in the years that experience the El Nino phenomenon. El Nino causes dry and hot conditions that trigger fires. One of the methods used to extinguish fires is water bombing, which is spraying water from the air using planes or helicopters. The purpose of this study is to analyze the effectiveness and efficiency of the water bombing method in dealing with land and peat forest fires in Indonesia. This study uses secondary data from various sources, such as government reports, research institutions, mass media, and non-governmental organizations. The data is then analyzed using descriptive, comparative, and evaluative methods. The results of the study show that the water bombing method has some advantages, such as fast, flexible, and able to reach areas that are difficult to access. However, this method also has some disadvantages, such as expensive, risky, and less effective in extinguishing fire in the peat soil. Therefore, this study recommends that the water bombing method should be used as one part of a comprehensive fire control strategy, which involves prevention, detection, and recovery. This study also suggests the need for improved coordination, regulation, and innovation in the use of the water bombing method in Indonesia.

Fitsbot (Fire Detection Smart Robot) Innovation in the Development of Drone Technology in Mitigation of Peat Forest Fire

Indonesia's forests continue to shrink due to forest fires. Indonesia's deforestation rate for 2019-2020 is 115.5 thousand hectares. The use of manual methods for forest monitoring is considered less effective because it requires a long time and a lot of resources. Natural and weather conditions affect the implementation of forest monitoring to prevent forest fires. Based on these problems, the author offers an innovation in FITSBOT (Fire Smart Robot) technology. The research method used is Research and Development (R&D) with the stages of Analysis, Design, Development, Implementation and Evaluation. The result of this research is a quadcopter with integrated artificial intelligence based on YOLO for forest monitoring. This technology is expected to facilitate forest monitoring in order to take preventive measures and early detection of forest fires.

Water level and soil moisture monitoring for peatland fire risk indicator

Peatland forest conversion into cultivated land often creates environmental issues in the form of increasing greenhouse gas (GHG) emissions caused by the decomposition of organic matter that eventually increase the risk of peat forest fires. This paper presents the results of a study of the peatland water table dynamics based on certain peatland characteristics (depth and maturity) and water management techniques (canal blocking), as well as an analysis of water level and soil moisture data for the peatland fire early warning model. This study was conducted in April-December 2018 at a palm oil plantation in Pangkalan Pisang Village, Riau Province. Peatland water table observations were carried out using a water level logger at each of the midpoints of three oil palm blocks measuring 30 ha each. Meanwhile, soil moisture contents were observed using a logger with two humidity sensors at two depths. The recorded observation data showed that the water table level was very dynamic and fluctuating, both temporally and spatially. The temporal observation data indicates that the water table levels after the rain had stopped in the three observed blocks decreased at the rates of 10.3, 10.6, and 13.6 mm/day, respectively. This research shows a significant correlation between soil moisture dry weight percent and the risk level of peatland fires. Soil moisture content was less than 100% dry weight and highly flammable.

Spatial based mapping of londerang peatprotected revegetation

The Londerang Peat Protected Forest is the largest protected peat forest in Jambi Province with 12, 500 hectares. In 2015 there was a peat forest fire that destroyed the existing vegetation. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite, thousands of hotspots were observed from May to October. The condition of peat damage reaches 90%. Peat plays an important role in absorbing 75%of carbon so it should not be burned, dried, and used as plantation land. The purpose of the study was to determine changes in land cover, to determine the extent of revegetation, and to determine the area of unvegetated forest in the Londerang Peat Protected Forest area. The remote sensing method used is Image Classification assisted by ArcGIS Version 10.8 software with Landsat 8 satellite imagery. The analysis is carried out by making 20 color classifications on satellite image data, then the majority or pulling the minority pixel classes into the majority of pixel colors. From each code grid in the attribute table, the data are combined according to the landcover classification.The results of the spatial analysis of land cover In 2013-2018 there was very high forest degradation. In 2013 it was 2940.1 ha, in 2018 it was 191.3ha from the initial area of 12500 ha so that the Gonderang HLG was categorized as critical. Revegeted land is 354 ha with 164, 000 planted vegetation and the type of planted vegetation is endemic vegetation (Jelutung, swamp island, Gelam). The revegetation of the Londerang Peat Protection Forest has only been carried out for only 2.8% of the total land area.

Design and Built a Prototype Kit for Fire Detection in a Peat Swamp Forest: A Preliminary Results

Peat forest fire detectors need to be developed immediately due to the frequency of peat forest fires in Malaysia during the summer is very high. This can affect the life in the forest and the health of the surrounding population. Among them is the Ayer Hitam Muar Forest Reserve, Johor which is almost 50,000 acres in size and experiences fires every year. However, fire monitoring management methods still need to be improved in terms of speed, accuracy and systematic channeling fire alerts. Apart from location and area factors, the main challenge of the early fire detection process is the lack of manpower to monitor and notify fires. The conventional method through patrols and phone calls from farmers who see a fire is less effective because of the delay in the notification received by the authorities. Initially, the work of identifying the location of the fire and measuring the signal strength of the telco service in the Forest Reserve was done with the help of rangers from the Muar district forestry department. This article proposes a prototype for detecting peat forest fires capable of monitoring and sending early fire notifications using a smartphone. The prototype uses an ESP32 microcontroller, GSM/GPRS modem and industry-standard sensors incluing smoke, temperature, humidity and motion detectors. A total of five prototype units were developed as sensor nodes (SN) 1 to 5 with unique IDs that can send information to UTHM web servers simultaneously. Data from each SN is displayed in real-time while notifications of smoke detection and motion alerts are sent to the authorities via the Telegram application. Solar panels are used as a source of electricity supply while the authorities can access information via smartphones. This prototype was tested to see its stability and operational accuracy while the data obtained were recorded. The developed system can help the authorities detect fires at an early stage and the location of the fire can be known based on the SN information received on the smartphone screen.

Peatland Fire Geotagging Photo for Investigation Tool using Smartphone

One of the ways to control tropical peat fires is to use a combination of the Global Navigation Satellite System (GNSS) and smartphones for monitoring, reporting, and verification of the location of the fires. The latest smartphones have many sensors, such as a compass, accelerometer, GPS, and a camera, to collect forest activity data from a specific target area. The collected data were then transferred to a cloud server through global mobile communication. This paper discusses a mobile and web application-based approach to collect and analyze user-generated geographical information of human activity data. The paper aims is to promote law enforcement agencies, local government, and fire patrol to consider the use of this low-cost, easy-to-use technology in controlling and reducing the risk of tropical peatland fires. Our mobile application has an easy-to-use mapping technology that allows its users to locate addresses quickly and provides cartographic maps augmented with digital information and high-resolution aerial imagery. This study proposes online citizen reporting as a new approach for law enforcement by aiding local government and fire patrols to conduct monitoring, reporting, and verification to reduce the risk of peat forest fires.

Confidence Analysis of Hotspot as Peat Forest Fire Indicator

Indonesia has recorded 14.9 million hectares of peat forest that continue to be deforested due to fire across Sumatra and Kalimantan. To operate a successful firefight, fast detection is a key element. Hotspot that appeared consecutively in more than two days is a strong indicator of fire existence. As the interest in data mining arose, an advanced technique can be implemented toward hotspot dataset into finding solutions. Many previous works have been carried out to mine sequence patterns and succeeded in determining as well as predicting areas with high occurrence of fire. However, none of the studies analyses the outliers, such as several hotspots which confidence decrease significantly in an adjacent interval of time. Confidence determines the quality of hotspot, with a value above 70% strongly indicates that fire spot exist. This study generated sequence patterns using the SPADE algorithm and analyses 21 hotspots considered as outliers using the Landsat-8 image. The result shows that 85.71% of hotspots have decreased confidence due to haze cover.

Identifying and addressing knowledge gaps for improving greenhouse gas emissions estimates from tropical peat forest fires

Tropical peatlands are areas of high carbon density that are important in biosphere-atmosphere interactions. Drainage and burning of tropical peatlands releases about 5% of global greenhouse gas (GHG) emissions, yet there is great uncertainty in these estimates. Our comprehensive literature review of parameters required to calculate GHG emissions from burnt peat forests, following the international guidelines, revealed many gaps in knowledge of carbon pools and few recent supporting studies. To improve future estimates of the total ecosystem carbon balance and peatfire emissions this study aimed to account for all carbon pools: aboveground, deadwood, pyrogenic carbon (PyC) and peat of single and repeatedly burnt peat forests. A further aim was to identify the minimum sampling intensity required to detect with 80% power significant differences in these carbon pools among long unburnt, recently burnt and repeatedly burnt peat swamp forests.About 90 Mg C ha−1 remains aboveground as deadwood after a single fire and half of this remains after a second fire. One fire produces 4.5 ± 0.6 Mg C ha−1 of PyC, with a second fire increasing this to 7.1 ± 0.8 Mg C ha−1. For peat swamp forests these aboveground carbon pools are rarely accounted in estimates of emissions following multiple fires, while PyC has not been included in the total peat carbon mass balance. Peat bulk density and peat carbon content change with fire frequency, yet these parameters often remain constant in the published emission estimates following a single and multiple fires. Our power analysis indicated that as few as 12 plots are required to detect meaningful differences between fire treatments for the major carbon pools. Further field studies directed at improving the parameters for calculating carbon balance of disturbed peat forest ecosystems are required to better constrain peatfire GHG emission estimates.

Environmental Communication Model of Farmer Community in Peatlands Ecotourism Development

This study aims to find out the environmental communication model of farmer communities in overcoming the problem of peatland fires through ecotourism management in Bukit Batu sub-district, Bengkalis-Indonensia. This research uses the study of communication ethnoecology, by understanding the problem directly and participating. The results of this study indicate that environmental communication through community-based tourism can preserve the peatland environment in a sustainable manner. Communities have their own interpretations and awareness of the meaning of environmental symbols that are around them. Community environmental communication for the development of peat arboretum ecotourism was built in conjunction with Pertamina's CSR through community empowerment in overcoming forest fires with the Kampung Gambut Berdikari program. Pertamina's CSR strengthens community understanding in increasing public awareness of the problem of peat forest fires and the land managment. Peat arboretum as ecotourism and educational tour is useful to convey messages to change understanding, perspective, and influence people's behavior as well as visitors. The model of environmental communication for the development of peat ecotourism by the community is based on friendship, deliberation and mutual assistance as a form of community local wisdom.

Characterization and Impact of Peat Fires on Stabilization of Tropical Lowland Peats in Banting, Selangor, Malaysia

Peat soil is a representative material of soil and well known as rich in organic matters, high compressibility, high porosity and low shear strength. During dry seasons, peat lands will lose lots of water and potentially turn into a tinderbox bringing in fires. When peat forest fires happen, it prompts degradation of humic-rich organic matter eventually reduce the stability of peat soil. The impacts of peat fire on peat soil from degraded area in Banting, Selangor, Peninsular Malaysia, were investigated through the field identification, physical and engineering properties through burnt peat site. The Unconfined Compressive Strength (UCS) result shows the burnt peat soil gained in strength that strongly related to the binder and filler dosage, moisture content of peat and curing time. The value of UCS strength increased with the gain of moisture content of peat samples but the strength tends to decrease when the moisture content exceeds certain point. The organic material changed its physical and chemical structure resulting from the fire event, thus, the capability of the soil to hold water particles is reducing and yielded higher UCS strength of cement-peat-stabilization. The most important geotechnical aspects of peat that have effect on stabilization process are natural water content, humification grade, ash content, and pH value. The results also suggested that lateral variation within the peat basin indirectly affects the strength of cement-peat-stabilization. The strength of burnt peat can be considerably improved by stabilization and support the concept of Air Curing Technique.

Chemical Composition of Fine Particulate Matter from Peat Forest Fires at Palangka Raya and Its Dispersion using HYSPLIT

An air quality monitoring was conducted to investigate the chemical characteristics of particulate emissions in peat forest fires at Palangka Raya, Indonesia during 2012 where a peat forest fire episode occurred. Aerosol samples were collected at Palangka Raya where represents a sub urban site downwind of the peat forest fires. The samples were collected using Gent stacked filter unit sampler. The sampler provides two size fractions: coarse (2.5-10 μm equivalent aerodynamic diameters EAD) and fine (<2.5 μm EAD). Black carbon (BC) was measured using Smoke Stain Reflectometer, and elemental compositions were analyzed using X-ray Fluorescence (XRF). The concentrations of PM2.5 during a haze episode were significantly different about seven to eight times higher when compared to the concentrations in non-haze conditions. The major components of PM2.5 in peat smoke haze consist of sulphur, biomass burning component (BC, K), and crustal components (Al, Fe, Si). The sulphur mainly comes from the peat as it is the earliest stage of transition from compressed plant growth to the formation of coal. The dispersion pattern to show the effect of wind direction using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) simulation was also applied.

Prediction of Peat Forest Fires Using Wavelet and Backpropagation

One of the causes of smog as well as climate damage, particularly in Palangka Raya, Center Kalimantan, are peat forest fires. There are a lot of losses inflicted by the smog including the increasing number of people who suffer respiratory infection (ARI) due to polluted air and any other related aspects. Peat fires are problematic to overcome because the locations of fires are difficult to be accessed. This paper focuses on building the system to predict the distribution of peat forest fire hotspots by utilizing satellite imagery. In designing the system for predicting the fire hotspots distribution, wavelet orthogonal was used as the initial processing of mapping the distribution of peat forest fire hotspots. Meanwhile, backpropagation method was used to identify the fire hotspot distribution patterns of peat forest fire in this system. From the result of the data tested which had been done for predicting the peat forest fire hotspots, the decomposition image obtained using Haar wavelet had the highest percentage of accuracy to recognize the fire hotspots, which is 90%. The recency of this system was its ability to predict the peat forest fire hotspots distribution which can be used as peat forest fires prevention, especially in Palangka Raya, Central Kalimantan.

A quantitative assessment of distributions and sources of tropospheric halocarbons measured in Singapore

This work reports the first ground-based atmospheric measurements of 26 halocarbons in Singapore, an urban-industrial city-state in Southeast (SE) Asia. A total of 166 whole air canister samples collected during two intensive 7 Southeast Asian Studies (7SEAS) campaigns (August–October 2011 and 2012) were analyzed for C1-C2 halocarbons using gas chromatography-electron capture/mass spectrometric detection. The halocarbon dataset was supplemented with measurements of selected non-methane hydrocarbons (NMHCs), C1-C5 alkyl nitrates, sulfur gases and carbon monoxide to better understand sources and atmospheric processes. The median observed atmospheric mixing ratios of CFCs, halons, CCl4 and CH3CCl3 were close to global tropospheric background levels, with enhancements in the 1–17% range. This provided the first measurement evidence from SE Asia of the effectiveness of Montreal Protocol and related national-scale regulations instituted in the 1990s to phase-out ozone depleting substances (ODS). First- and second-generation CFC replacements (HCFCs and HFCs) dominated the atmospheric halocarbon burden with HFC-134a, HCFC-22 and HCFC-141b exhibiting enhancements of 39–67%. By combining near-source measurements in Indonesia with receptor data in Singapore, regionally transported peat-forest burning smoke was found to impact levels of several NMHCs (ethane, ethyne, benzene, and propane) and short-lived halocarbons (CH3I, CH3Cl, and CH3Br) in a subset of the receptor samples. The strong signatures of these species near peat-forest fires were potentially affected by atmospheric dilution/mixing during transport and by mixing with substantial urban/regional backgrounds at the receptor. Quantitative source apportionment was carried out using positive matrix factorization (PMF), which identified industrial emissions related to refrigeration, foam blowing, and solvent use in chemical, pharmaceutical and electronics industries as the major source of halocarbons (34%) in Singapore. This was followed by marine and terrestrial biogenic activity (28%), residual levels of ODS from pre-Montreal Protocol operations (16%), seasonal incidences of peat-forest smoke (13%), and fumigation related to quarantine and pre-shipment (QPS) applications (7%).

Effects of peat fires on the characteristics of humic acid extracted from peat soil in Central Kalimantan, Indonesia.

When peat forest fires happen, it leads to burn soil and also humic acids as a dominant organic matter contained in peat soil as well as the forest. The structure and properties of humic acids vary depending on their origin and environment, therefore the transformation of humic acid is also diverse. The impacts of the peat fires on peat soil from Central Kalimantan, Indonesia were investigated through the characterization of humic acids, extracted from soil in burnt and unburnt sites. The characterization of humic acids was performed by elemental composition, functional groups, molecular weight by HPSEC, pyrolysate compounds by pyrolysis-GC/MS, fluorescence spectrum by 3DEEM spectrofluorometer, and thermogravimetry. The elemental composition of each humic substance indicated that the value of H/C and O/C of humic acids from burnt sites were lower than that from unburnt sites. The molecular weight of humic acids from burnt sites was also lower than that from unburnt sites. Pyrolysate compounds of humic acids from unburnt sites differed from those of humic acids from burnt soil. The heating experiment showed that burning process caused the significant change in the properties of humic acids such as increasing the aromaticity and decreasing the molecular weight.

Peat Moisture and Water Level Relationship in a Tropical Peat Swamp Forest

Forest fire occurring in the tropical peat swamp forest has been a major concern and has been on the increase at an alarming rate during the past decades. This problem is further compounded by the fact that some of the affected areas have burned twice or more. If left unabated, peat areas that will be at risk to frequent fires will be on the increase. Peat soils when dry, posed a high risk of combustibility. It is therefore essential to understand the moisture characteristic of the peat soil in order to develop forest fire management programme. The objective of this study was to monitor peat moisture and water level relationship. A study has been conducted to investigate the temporal characteristics of the peat water level and to understand the relationship between water table and peat moisture. The study was conducted at Compartment 101, Raja Musa Forest Reserve, Selangor, Malaysia. This area was on fire in 1998, early June 1999 and 9 March 2000. A 180 m long transect starting from the edge of the canal into the forest was established. Twenty peizometers of 2 m length each, were installed along the established transect. Water table and peat samples were taken weekly beginning at 24 October to 20 December 2000. Peat soils were analyzed for soil moisture on oven-dry basis. The result showed that there was a systematic rise and fall of the water table. The maximum and minimum water table recorded were at 22.6 cm above ground and 31.5 cm below ground, respectively. In the forested area, results showed that the changes in water level had a smaller range (16.9 cm) compared to the open area (25.1 cm). Mean peat moisture sample at depths 0 cm (surface), 50 and 100 cm were 577,891 and 1070%, respectively. ANOVA analysis showed that lower depth has significantly higher moisture (at 95% confidence level) compared to higher layers. The study shows the temporal variations of water level in peat swamp forest. This variations can be used as a basis for early warning indicator of peat forest fire. © 2006 Asian Network for Scientific Information.