scholarly journals Development of a Smoke Dispersion Forecast System for Korean Forest Fires

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 219 ◽  
Author(s):  
Boknam Lee ◽  
Seungwan Cho ◽  
Seung-Kii Lee ◽  
Choongshik Woo ◽  
Joowon Park
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Regional Scale ◽  
Ground Level ◽  
Fuel Loading ◽  
Forecast System ◽  
Ground Level Concentration ◽  
Smoke Dispersion ◽  
Pm2.5 And Pm10 ◽  
Grid Based

Smoke from forest fires is a growing concern in Korea as forest structures have changed and become more vulnerable to fires associated with climate change. In this study, we developed a Korean forest fire smoke dispersion prediction (KFSDP) system to support smoke management in Korea. The KFSDP system integrates modules from different models, including a Korean forest fire growth prediction model, grid-based geographic information system (GIS) fuel loading and consumption maps generated by national forest fuel inventory data, and the Korean Weather Research and Forecasting Model, into a Gaussian plume model to simulate local- and regional-scale smoke dispersion. The forecast system is operated using grid-based fires and simulates a cumulative smoke dispersion of carbon monoxide (CO) and <2.5 µm and <10 µm particulate matter (PM2.5 and PM10, respectively) ground-level concentration contours at 30-min intervals during the fire in concert with weather forecasts. The simulated smoke dispersions were evaluated and agreed well with observed smoke spreads obtained from real forest fires in Korea, and the performance of the KFSDP system was also analyzed using “what-if” scenarios. This is the first study to develop an integrated model for predicting smoke dispersion from forest fires in Korea.

scholarly journals Particulate Matter Pollution around a Cement Industry and its Potential Effect

2020 ◽  
pp. 130-140
Author(s):  
Victor Emeka Amah ◽  
Ngozi Udeh ◽  
Bassey Otuekong Effiong
Keyword(s):  
Particulate Matter ◽  
Pollution Index ◽  
Ground Level ◽  
Potential Effect ◽  
Cement Industry ◽  
Pm10 And Pm2.5 ◽  
Ground Level Concentration ◽  
Level Of Significance ◽  
Pm2.5 And Pm10 ◽  
Rivers State

Analysis of particulate matter (PM) PM2.5 and PM10 was done around a cement company in Rivers State, Nigeria. Measurements were taken for the concentration of PM2.5 and PM10 and other atmospheric parameters at intervals of 100 m up to 1000 m and field observation was carried out for two days. The temperature of the area varied between 26.6 degrees and 33.3 degrees, relative humidity was between 70.2 and 98.2% and the wind speed ranged from 0.2 to 3.6 m/s. The minimum PM10 and PM2.5 values were 38 and 18 µg/m3 respectively and the maximum PM10 and PM2.5 values were 616 and 298 µg/m3 respectively. A two way analysis of variance was done at 5 % level of significance to determine the influence the time the measurement was taken and the distance from the stack have on the particulate matter concentration. P values were lower than P = .05 therefore, the null hypothesis was rejected. The pollution index for PM10 was determined and about 86% of the pollution index are above 100, 80% are above 150 and about 21% is above 400. About 96% of the pollution index for PM2.5 is above 100, 87% are above 150 and about 21% are above 300. As shown on Air quality index charts, values between 100 and 150 are unhealthy for sensitive groups, values above 150 are unhealthy, and values above 300 are hazardous while values above 400 are very hazardous. It is concluded that the ground level concentration of PM10 and PM2.5 up to 1200 m from the stack is generally unhealthy for the receptors.

scholarly journals Californian wildfire plumes over Southwestern British Columbia: <i>lidar</i>, sunphotometry, and mountaintop chemistry observations

2010 ◽  
Vol 10 (9) ◽  
pp. 21047-21075 ◽  
Author(s):  
I. McKendry ◽  
K. Strawbridge ◽  
M. L. Karumudi ◽  
N. O'Neill ◽  
A. M. Macdonald ◽  
...  
Keyword(s):  
British Columbia ◽  
Pacific Northwest ◽  
Forest Fire ◽  
Forest Fires ◽  
Regional Scale ◽  
Fire Plume ◽  
Physico Chemical ◽  
Observatory Data ◽  
The Pacific ◽  
June July

Abstract. Forest fires in Northern California and Oregon were responsible for two significant regional scale aerosol transport events observed in southern British Columbia during summer 2008. A combination of ground based (CORALNet) and satellite (CALIPSO) lidar, sunphotometry and high altitude chemistry observations permitted unprecedented characterization of forest fire plume height and mixing as well as description of optical properties and physicochemistry of the aerosol. In southwestern BC, lidar observations show the smoke to be mixed through a layer extending to 5–6 km a.g.l. where the aerosol was confined by an elevated inversion in both cases. Depolarization ratios for a trans-Pacific dust event (providing a basis for comparison) and the two smoke events were consistent with observations of dust and smoke events elsewhere and permit discrimination of aerosol events in the region. Based on sunphotometry, the Aerosol Optical Thicknesses (AOT) reached maxima of ~0.7 and ~0.4 for the two events respectively. Dubovik-retrieval values of reff,f during both the June/July and August events varied between about 0.13 and 0.15 μm and confirm the dominance of accumulation mode size particles in the forest fire plumes. Both Whistler Peak and Mount Bachelor Observatory data show that smoke events are accompanied by elevated CO and O3 concentrations as well as elevated K+/SO4 ratios. In addition to documenting the meteorology and physico-chemical characteristics of two regional scale biomass burning plumes, this study demonstrates the positive analytical synergies arising from the suite of measurements now in place in the Pacific Northwest, and complemented by satellite borne instruments.

Review of Wildland Fire Smoke Dispersion Models and Suggestion for Korean Forest-Fire Smoke Impact Forecast System

2016 ◽  
Vol 16 (6) ◽  
pp. 197-208 ◽  
Author(s):  
Joowon Park ◽  
◽  
Ho Jung Youn ◽  
Byung Doo Lee ◽  
Choong Shik Woo ◽  
...  
Keyword(s):  
Forest Fire ◽  
Wildland Fire ◽  
Dispersion Models ◽  
Forecast System ◽  
Fire Smoke ◽  
Smoke Dispersion

scholarly journals Automated construction of ground access routes for the management of regional forest fires

2020 ◽  
Vol 66 (No. 8) ◽  
pp. 329-388
Author(s):  
Ekaterina Podolskaia
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Transport Model ◽  
Hot Spot ◽  
Regional Scale ◽  
Fire Detection ◽  
Federal District ◽  
Fire Season ◽  
Gis Technology ◽  
Regional Forest

Modern geospatial technologies and permanently updated wildfire monitoring datasets are the basis of improving forest firefighting on different administrative scales. One of the tasks is to use the spatial representation of forest fire locations during the fire season and offer timely suitable technical options for accessing them. We developed a GIS technology to create forest fire ground access routes for special firefighting vehicles moving from a ground firefighting base (fire-chemical station) to the place of the forest fire detection; the technology includes a statistical and geospatial accessibility analysis of the routes. The key data are a transport model consisting of public roads and forest glades on the regional scale. We described the main principles of the transport model construction and usage, and their implementation for the Russian Federal Districts. An access routes database for the 2002–2019 fire seasons, a central part of the Siberian Federal District, was produced and analysed. By using a hot spot analysis, we confirmed that forest fires are poorly accessible away from the centre of the Siberian District. The created road accessibility maps show “a proposed ground access zone” within the key area to fight forest fires for the fire seasons to come.

scholarly journals THE DIVERSITY OF HERBACEOUS VEGETATION AFTER FOREST FIRE

2018 ◽  
Author(s):  
Jolita ABRAITIENĖ ◽  
Gerda ŠILINGIENĖ ◽  
Rasa VAITKEVIČIŪTĖ ◽  
Regina VASINAUSKIENĖ
Keyword(s):  
New Species ◽  
Plant Species ◽  
Forest Fire ◽  
Forest Fires ◽  
Ground Level ◽  
Herbaceous Plants ◽  
Coniferous Forests ◽  
First Year ◽  
Herbaceous Plant ◽  
Forested Areas

Forest fire is an uncontrolled combustion of flammable materials in forested and non-forested areas. In Lithuania forest fires mainly occur in late spring and summer, mostly in young coniferous forests (Forest ..., 1987). The studies of herbaceous plants in fireplaces were carried out in 2016 in Jurbarkas SFE. Ground-level forest fire increased the projection coverage of herbaceous plants and their species composition in the fireplaces. According to the average data of the survey, 18 herbaceous plant species were ascertained in the fireplace and 14 species in the control stand. During the first year after fire, 9 new species were recorded in the fireplace and 5 species have disappeared, while in the seventh year - 7 new species were recorded and 1 disappeared, as compared with the control stand. Summarizing the obtained data it can be stated that low-intensity ground-level forest fire in pine forest increased the number of herbaceous plant species, however, the number of new and extinct species has been gradually decreasing, suggesting that in the fireplaces the diversity of herbaceous plant species will be like in the control stand.

scholarly journals Is Exposure to PM2.5 and PM10, a Factor of Surge of 2nd Wave of COVID-19- A Case Study of Delhi, India?

2021 ◽  
Author(s):  
Avnish Shukla ◽  
Anirudh Mishra ◽  
Bhaven Nirmalbhai Tandel Tandel
Keyword(s):  
Particulate Matter ◽  
Death Rate ◽  
Positive Association ◽  
Ground Level ◽  
Average Concentration ◽  
Particulate Matter Concentration ◽  
Ground Level Concentration ◽  
Pm2.5 And Pm10 ◽  
Second Wave ◽  
Matter Concentration

Abstract Exposure to air pollutants cause severe health issues. Restriction onmajor activities induced by government improves the air quality during the lockdown due to Covid-19 pandemic. Investigation of correlation of high level of Severe Acute Respiratory Syndrome Coronavirus2 and its mortality rate with ground level particulate matter concentration was carried out in this study during the second wave of covid-19 in the megacity Delhi, India. Daily average concentration of major two fractions of particulate matter PM2.5 and PM10 were analyzed for the period of 22 March 2021 to 15 May 2021 that grouped into two categories before lockdown and during lockdown. Results revealed that overall reduction of 1.6% in PM2.5 concentration and 15% in PM10 concentration was observed on imposing the lockdown and significant reduction in Particulate Matter concentration was observed for most of the locations for the lockdown period as compared to before lockdown period. Furthermore daily new Covid-19 cases and its death rate was found negatively associated (very weak correlation) with the ground level concentration of PM2.5 and PM10 i.e. before lockdown period while positive association (moderately correlated) was noticed among the daily new Covid-19 cases, its death rate, ground level concentration of PM2.5 and PM10 in time period of lockdown. This Study revealed that the high degree of atmospheric contamination in Northern India can be deemed an external co-factor in the area's high mortality and high positivity rate during the second wave Covid19 pandemic.

scholarly journals Californian forest fire plumes over Southwestern British Columbia: lidar, sunphotometry, and mountaintop chemistry observations

2011 ◽  
Vol 11 (2) ◽  
pp. 465-477 ◽  
Author(s):  
I. McKendry ◽  
K. Strawbridge ◽  
M. L. Karumudi ◽  
N. O'Neill ◽  
A. M. Macdonald ◽  
...  
Keyword(s):  
British Columbia ◽  
Pacific Northwest ◽  
Forest Fire ◽  
Forest Fires ◽  
Regional Scale ◽  
Fire Plume ◽  
Fire Plumes ◽  
Observatory Data ◽  
The Pacific ◽  
June July

Abstract. Forest fires in Northern California and Oregon were responsible for two significant regional scale aerosol transport events observed in southern British Columbia during summer 2008. A combination of ground based (CORALNet) and satellite (CALIPSO) lidar, sunphotometry and high altitude chemistry observations permitted unprecedented characterization of forest fire plume height and mixing as well as description of optical properties and physicochemistry of the aerosol. In southwestern BC, lidar observations show the smoke to be mixed through a layer extending to 5–6 km a.g.l. where the aerosol was confined by an elevated inversion in both cases. Depolarization ratios for a trans-Pacific dust event (providing a basis for comparison) and the two smoke events were consistent with observations of dust and smoke events elsewhere and permit discrimination of aerosol events in the region. Based on sunphotometry, the Aerosol Optical Thicknesses (AOT) reached maxima of ~0.7 and ~0.4 for the two events respectively. Dubovik-retrieval values of reff, f during both the June/July and August events varied between about 0.13 and 0.15 μm and confirm the dominance of accumulation mode size particles in the forest fire plumes. Both Whistler Peak and Mount Bachelor Observatory data show that smoke events are accompanied by elevated CO and O3 concentrations as well as elevated K+/SO4 ratios. In addition to documenting the meteorology and physic-chemical characteristics of two regional scale biomass burning plumes, this study demonstrates the positive analytical synergies arising from the suite of measurements now in place in the Pacific Northwest, and complemented by satellite borne instruments.

Satellite-based analysis of CO and Fires in the Arctic

2021 ◽  
Author(s):  
Tomi Karppinen ◽  
Anu-Maija Sundström ◽  
Hannakaisa Lindqvist ◽  
Johanna Tamminen
Keyword(s):  
Greenhouse Gases ◽  
Forest Fire ◽  
Forest Fires ◽  
Arctic Region ◽  
Ground Level ◽  
Fire Effects ◽  
Satellite Observations ◽  
The Arctic ◽  
High Latitudes ◽  
Fire Emissions

&lt;p&gt;&lt;span&gt;Climate change is proceeding fastest in the Arctic region. While human-induced emissions of long-lived greenhouse gases are the main driving factor of global warming, short-lived climate forcers or pollutants emitted from the forest fires are also playing an important role, especially in the Arctic. Forest fire emissions also affect local air quality and photochemical processes in the atmosphere. For example, CO contributes to the formation of tropospheric ozone and affects the abundance of greenhouse gases such as methane and CO2.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;During past years Arctic summers have been warmer and drier elevating the risk for extensive forest fire episodes. Satellite observations show, that during the past three summers (2018-2020) fire detections in Arctic, especially in Arctic Siberia have increased considerably, affecting also local emissions of CO. This work focuses on studying CO concentration and its variation at high latitudes and in the Arctic using satellite and ground-based observations. Satellite observations of CO from TROPOMI are analyzed for the 2018-2020 (NH) summer months. To assess the satellite retrieved columns the satellite measurements are compared to ground-based remote sensing measurements at Sodankyl&amp;#228;. Also, ground-based in-situ measurements are used to see how the total column changes mirror the ground level concentrations. The fire characteristics are analyzed using observations from MODIS instruments onboard Aqua and Terra. Fire effects on seasonal cycle and interannual variability of CO concentrations at Arctic high latitudes are analyzed.&lt;/span&gt;&lt;/p&gt;

scholarly journals A Collaborative Region Detection and Grading Framework for Forest Fire Smoke Using Weakly Supervised Fine Segmentation and Lightweight Faster-RCNN

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 768
Author(s):  
Jin Pan ◽  
Xiaoming Ou ◽  
Liang Xu
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Learning Strategy ◽  
Early Stage ◽  
Fire Detection ◽  
Surveillance Systems ◽  
Region Detection ◽  
Decision Network ◽  
Fire Smoke ◽  
Weakly Supervised

Forest fires are serious disasters that affect countries all over the world. With the progress of image processing, numerous image-based surveillance systems for fires have been installed in forests. The rapid and accurate detection and grading of fire smoke can provide useful information, which helps humans to quickly control and reduce forest losses. Currently, convolutional neural networks (CNN) have yielded excellent performance in image recognition. Previous studies mostly paid attention to CNN-based image classification for fire detection. However, the research of CNN-based region detection and grading of fire is extremely scarce due to a challenging task which locates and segments fire regions using image-level annotations instead of inaccessible pixel-level labels. This paper presents a novel collaborative region detection and grading framework for fire smoke using a weakly supervised fine segmentation and a lightweight Faster R-CNN. The multi-task framework can simultaneously implement the early-stage alarm, region detection, classification, and grading of fire smoke. To provide an accurate segmentation on image-level, we propose the weakly supervised fine segmentation method, which consists of a segmentation network and a decision network. We aggregate image-level information, instead of expensive pixel-level labels, from all training images into the segmentation network, which simultaneously locates and segments fire smoke regions. To train the segmentation network using only image-level annotations, we propose a two-stage weakly supervised learning strategy, in which a novel weakly supervised loss is proposed to roughly detect the region of fire smoke, and a new region-refining segmentation algorithm is further used to accurately identify this region. The decision network incorporating a residual spatial attention module is utilized to predict the category of forest fire smoke. To reduce the complexity of the Faster R-CNN, we first introduced a knowledge distillation technique to compress the structure of this model. To grade forest fire smoke, we used a 3-input/1-output fuzzy system to evaluate the severity level. We evaluated the proposed approach using a developed fire smoke dataset, which included five different scenes varying by the fire smoke level. The proposed method exhibited competitive performance compared to state-of-the-art methods.

scholarly journals Short-Term Effects of Fire Severity on Vegetation Based on Sentinel-2 Satellite Data

2021 ◽  
Vol 13 (1) ◽  
pp. 432
Author(s):  
Aru Han ◽  
Song Qing ◽  
Yongbin Bao ◽  
Li Na ◽  
Yuhai Bao ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Vegetation Change ◽  
Fire Severity ◽  
Dynamic Change ◽  
Burned Area ◽  
Fire Event ◽  
Vegetation Dynamic ◽  
Area Index ◽  
Sentinel 2

An important component in improving the quality of forests is to study the interference intensity of forest fires, in order to describe the intensity of the forest fire and the vegetation recovery, and to improve the monitoring ability of the dynamic change of the forest. Using a forest fire event in Bilahe, Inner Monglia in 2017 as a case study, this study extracted the burned area based on the BAIS2 index of Sentinel-2 data for 2016–2018. The leaf area index (LAI) and fractional vegetation cover (FVC), which are more suitable for monitoring vegetation dynamic changes of a burned area, were calculated by comparing the biophysical and spectral indices. The results showed that patterns of change of LAI and FVC of various land cover types were similar post-fire. The LAI and FVC of forest and grassland were high during the pre-fire and post-fire years. During the fire year, from the fire month (May) through the next 4 months (September), the order of areas of different fire severity in terms of values of LAI and FVC was: low > moderate > high severity. During the post fire year, LAI and FVC increased rapidly in areas of different fire severity, and the ranking of areas of different fire severity in terms of values LAI and FVC was consistent with the trend observed during the pre-fire year. The results of this study can improve the understanding of the mechanisms involved in post-fire vegetation change. By using quantitative inversion, the health trajectory of the ecosystem can be rapidly determined, and therefore this method can play an irreplaceable role in the realization of sustainable development in the study area. Therefore, it is of great scientific significance to quantitatively retrieve vegetation variables by remote sensing.

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