Forest Fires In China Research Articles

Disentangling the Roles of Climate Variables in Forest Fire Occurrences in China

In the context of global warming, climate strongly affects forest fires. With long-term and strict fire prevention policies, China has become a unique test arena for comprehending the role of climatic variables in affecting forest fires. Here, using GIS spatial analysis, Pearson correlation, and geographical detector, the climate drivers of forest fires in China are revealed using the 2003–2022 active fire data from the MODIS C6 and climate products from CHELSA (Climatologies at high resolution for the Earth’s land surface areas). The main conclusions are as follows: (1) In total, 82% of forest fires were prevalent in the southern and southwestern forest regions (SR and SWR) in China, especially in winter and spring. (2) Forest fires were mainly distributed in areas with a mean annual temperature and annual precipitation of 14~22 °C (subtropical) and 800~2000 mm (humid zone), respectively. (3) Incidences of forest fires were positively correlated with temperature, potential evapotranspiration, surface downwelling shortwave flux, and near-surface wind speed but negatively correlated with precipitation and near-surface relative humidity. (4) Temperature and potential evapotranspiration dominated the roles in determining spatial variations of China’s forest fires, while the combination of climate variables complicated the spatial variation. This paper not only provides new insights on the impact of climate drives on forest fires, but also offers helpful guidance for fire management, prevention, and forecasting.

The dynamic evolution characteristics of PM2.5 concentrations and health risk assessment during typical forest fires in China

The dynamic evolution characteristics of PM2.5 concentrations and health risk assessment during typical forest fires in China

Spatio-Temporal Characteristics of Ice–Snow Freezing and Its Impact on Subtropical Forest Fires in China

Ice–snow freezing may disrupt the growth condition and structure of forest vegetation, increasing combustible loads and thus triggering forest fires. China’s subtropical regions are rich in forest resources, but are often disturbed by ice–snow freezing, especially due to climate change. Clarifying the responsive areas and times of forest fires to ice-snow freezing in this region is of vital importance for local forest fire management. In this study, meteorological data from 2001 to 2019 were used to extract the precipitation and its duration during the freezing period in order to analyze the freezing condition of forest vegetation in subtropical China. To improve the accuracy of identifying forest fires, we extracted forest fire information year-by-year and month-by-month based on the moderate resolution imaging spectroradiometer (MODIS) active fire data (MOD14A2) using the enhanced vegetation index (EVI), and analyzed the forest fire clustering characteristics in the region using the Moran’s Index. Then, correlation analysis between forest fires and freezing precipitation was utilized to explore the responsive areas and periods of forest fires caused by ice–snow freezing. Our analysis shows the following: (1) during the period of 2001–2019, the ice–snow freezing of forest vegetation was more serious in Hunan, Jiangxi, Hubei, and Anhui provinces; (2) forest fires in subtropical China have shown a significant downward trend since 2008 and their degree of clustering has been reduced from 0.44 to 0.29; (3) forest fires in Hunan, Jiangxi, and Fujian provinces are greatly affected by ice–snow freezing, and their correlation coefficients are as high as 0.25, 0.25, and 0.32, respectively; and (4) heavy ice–snow freezing can increase forest combustibles and affect forest fire behavior in February and March. This research is valuable for forest fire management in subtropical China and could also provide a reference for other regions.

Hydrothermal liquefaction of pinecone kraft lignin into selective phenolic: Optimization of Ni and Mo impregnation on ceria

Hydrothermal liquefaction of pinecone kraft lignin into selective phenolic: Optimization of Ni and Mo impregnation on ceria

NPP and Carbon Emissions under Forest Fire Disturbance in Southwest and Northeast China from 2001 to 2020

With climate change, frequent forest fires and prolonged fire period occur all over the world. Moreover, carbon emission from forest fire affects the carbon cycle of the forest ecosystem. However, this effect varies by region with no uniform conclusions, and fewer comparative studies exist on such differences between regions. In this paper, net primary productivity (NPP) data MOD17A3 were used as an important parameter of forest carbon absorption, along with MODIS fire spot data MCD14DL and burned area data MCD64A1. Forest carbon lost under forest fire interference in the northeast and southwest natural forest areas of China was studied to explore the role of forest fire in the carbon cycle process and its differences in the unlike regions of China. Here, by means of kernel density analysis and M-K trend test, the characteristics of forest fires in China’s southwest and northeast forests were calculated. Forest carbon emission under forest fire disturbance was quantified by reference to the forest fire emission factor list. We show that (1) the total number of forest fire spots in the southwest region from 2001 to 2020 was 1.06 × 105, 1.28 times that of Northeast China. However, the total burned area in the southwest was only 67.84% of that in the northeast. (2) The total carbon emissions from forest fires in the southwest from 2001 to 2020 was 37,559.94 Gg, 10.77% larger than the northeast forest, CH4 and CO2 were 13.52% and 11.29% larger respectively. Moreover, the carbon emissions of forest fire in the northeast showed a downward trend, R2 = 0.16 (p < 0.1), while it remained basically unchanged in the southwest. The contribution of carbon emissions from forest fires changed with forest types, it was shown as: evergreen needleleaf forest (14.98%) > evergreen broadleaf forest (10.81%) > deciduous needleleaf forest (6.52%) > deciduous broadleaf forest (5.22%). (3) From 2001 to 2020, under the premise that the NPP both manifested upward trends, the NPP of the burned areas showed a significant downward trend in the southwest forest, with R2 = 0.42 (p < 0.05), while it increased in the northeast forest, with R2 = 0.37 (p < 0.05). It showed negative correlation between NPP of burned areas and forest fire carbon emissions, and forest fire disturbance had no significant effect on forest NPP in Northeast China, while net carbon loss occurred in Southwest China. In general, under different forest fire characteristics, NPP, which represents forest carbon uptake, and carbon emissions from forest fires show differences. The impact of forest fire disturbance on forest carbon process varies with regions. The study can provide some ideas on the effects of forest fire disturbance on climate change.

Economic Loss Assessment and Spatial–Temporal Distribution Characteristics of Forest Fires: Empirical Evidence from China

Forest fires are a type of disaster with both human and natural factors; they differ from other forest disasters, in that they can cause significant damage not only to the ecological environments but also to the economy and society in many irreversible ways. While the risk factor of forest fires has been large, systematic studies on economic losses caused by forest fires have been lacking in recent years, and there is also a lack of analysis on forest fire economic losses in both spatial and temporal dimensions. Therefore, based on the forest fire data from 2006 to 2018, this paper establishes a forest fire economic loss evaluation system to calculate the economic losses in China and analyzes the spatial distribution characteristics and change trends of the forest fire economic losses in each province through thermal mapping. The results show the following. (1) The economic loss from forest fires in China is generally characterized by a fluctuating decline, but anomalous values due to human factors may occur. (2) The spatial heterogeneity of economic loss in China’s provinces is limited by many factors, such as the differences in resource endowments, showing the characteristics of “low in the eastern and western regions and high in the central region”. (3) Forest fires in China cause the most serious losses to forest ecological benefits. (4) Forest resources and fires are not independent of each other between regions, and areas with similar economic losses related to forest fires are often found in blocks. (5) Although the overall economic losses caused by forest fires in China are fluctuating and decreasing, some provinces are showing signs of increasing economic losses, most notably in Inner Mongolia. Therefore, this paper suggests targeted recommendations based on forest fires in different regions and with reference to the changing trends of economic loss caused by forest fires. For low-loss areas, we can further reduce the economic loss per unit area while ensuring that the losses do not increase any further. For high-loss areas, the main focus should be to find the weak points in the adaptation to forest fires. The right way to permanently reduce the damage caused by forest fires is to improve the adaptive and symbiotic capacity of the ecosystems and residential communities in relation to fires in a targeted manner and to improve the capacity for quick economic recovery after a fire.

Forest Fire Occurrence Prediction in China Based on Machine Learning Methods

Forest fires may have devastating consequences for the environment and for human lives. The prediction of forest fires is vital for preventing their occurrence. Currently, there are fewer studies on the prediction of forest fires over longer time scales in China. This is due to the difficulty of forecasting forest fires. There are many factors that have an impact on the occurrence of forest fires. The specific contribution of each factor to the occurrence of forest fires is not clear when using conventional analyses. In this study, we leveraged the excellent performance of artificial intelligence algorithms in fusing data from multiple sources (e.g., fire hotspots, meteorological conditions, terrain, vegetation, and socioeconomic data collected from 2003 to 2016). We have tested several algorithms and, finally, four algorithms were selected for formal data processing. There were an artificial neural network, a radial basis function network, a support-vector machine, and a random forest to identify thirteen major drivers of forest fires in China. The models were evaluated using the five performance indicators of accuracy, precision, recall, f1 value, and area under the curve. We obtained the probability of forest fire occurrence in each province of China using the optimal model. Moreover, the spatial distribution of high-to-low forest fire-prone areas was mapped. The results showed that the prediction accuracies of the four forest fire prediction models were between 75.8% and 89.2%, and the area under the curve (AUC) values were between 0.840 and 0.960. The random forest model had the highest accuracy (89.2%) and AUC value (0.96). It was determined as the best performance model in this study. The prediction results indicate that the areas with high incidences of forest fires are mainly concentrated in north-eastern China (Heilongjiang Province and northern Inner Mongolia Autonomous Region) and south-eastern China (including Fujian Province and Jiangxi Province). In areas at high risk of forest fire, management departments should improve forest fire prevention and control by establishing watch towers and using other monitoring equipment. This study helped in understanding the main drivers of forest fires in China over the period between 2003 and 2016, and determined the best performance model. The spatial distribution of high-to-low forest fire-prone areas maps were produced in order to depict the comprehensive views of China’s forest fire risks in each province. They were expected to form a scientific basis for helping the decision-making of China’s forest fire prevention authorities.

Spatial and temporal variation of air pollutant emissions from forest fires in China

Spatial and temporal variation of air pollutant emissions from forest fires in China

RETRACTED: Wu, S. The Temporal-Spatial Distribution and Information-Diffusion-Based Risk Assessment of Forest Fires in China. Sustainability 2021, 13, 13859

The author and journal retract the article (The Temporal-Spatial Distribution and Information-Diffusion-Based Risk Assessment of Forest Fires in China) [...]

An analysis of fatalities from forest fires in China, 1951–2018

The frequent occurrence of fatalities from wildfires is an ongoing problem in China, even though great improvements have been achieved in overall wildfire management in recent years. We analysed the occurrence patterns and correlative environments of fatalities from forest fires in China from 1951 to 2018. Changes in fire policies affected changes in the numbers of fires, forest area burned and number of fatalities before and after 1987, after the large Great Black Dragon Fire that burned in the Daxing’anling Mountains in northeastern China. Most fatalities occurred in the southern, southwestern and eastern forest regions of the country where population centres are concentrated, while most of the burned area was distributed in forests of northeast China with fewer population centres. Fatalities were correlated with higher values of fire weather indices, coniferous forests, coniferous and broad-leaved mixed forests, moderate–average slopes (5.1–15°), and primarily small fires of less than 100 ha in area. These results should be a first step to help improve awareness of inherent dangers during wildfires and to assist fire managers and policy-makers in strengthening safety procedures for both professional firefighters and the public to reduce wildfire fatalities in the future.

RETRACTED: The Temporal-Spatial Distribution and Information-Diffusion-Based Risk Assessment of Forest Fires in China

As forest fires are becoming a recurrent and severe issue in China, their temporal-spatial information and risk assessment are crucial for forest fire prevention and reduction. Based on provincial-level forest fire data during 1998–2017, this study adopts principal component analysis, clustering analysis, and the information diffusion theory to estimate the temporal-spatial distribution and risk of forest fires in China. Viewed from temporality, China’s forest fires reveal a trend of increasing first and then decreasing. Viewed from spatiality, provinces characterized by high population density and high coverage density are seriously affected, while eastern coastal provinces with strong fire management capabilities or western provinces with a low forest coverage rate are slightly affected. Through the principal component analysis, Hunan (1.33), Guizhou (0.74), Guangxi (0.51), Heilongjiang (0.48), and Zhejiang (0.46) are found to rank in the top five for the severity of forest fires. Further, Hunan (1089), Guizhou (659), and Guanxi (416) are the top three in the expected number of general forest fires, Fujian (4.70), Inner Mongolia (4.60), and Heilongjiang (3.73) are the top three in the expected number of large forest fires, and Heilongjiang (59,290), Inner Mongolia (20,665), and Hunan (5816) are the top three in the expected area of the burnt forest.

Temporal evolution of the hydromechanical properties of soil-root systems in a forest fire in China

Temporal evolution of the hydromechanical properties of soil-root systems in a forest fire in China

Spatio-temporal characteristics of forest fires in China between 2001 and 2017

The remotely sensed burned area (BA) products can provide continuous and spatiotemporally explicit characteristics of fire patches, which are critical data sources for understanding regional fire regimes. However, their accuracy remains to be improved. In this study, a global BA product (i.e., CCI_Fire) at 250 m resolution was integrated with global forest change (GFC) product at 30 m to generate a refined BA product, named CCI_GFC product, whose accuracy was evaluated through comparing the BA with pre-existing fire patches data. To reveal the characteristics of forest fire in China between 2001 and 2017, we conducted a grid analysis at 0.05°×0.05° spatial resolution based on the refined BA product and the spatial pattern of eco-regions at the macro scale. The results showed that the accuracy metrics including the recognition rate (RR), variance explained (R2), root mean squared error (RMSE), mean absolute percentage error (MAPE) of the CCI_GFC product (i.e., 83%, 0.91, 0.28, and 8.5% respectively) were all superior to the CCI_Fire product (i.e., 74%, 0.86, 0.36, and 11.8% respectively) and the MCD64A1 product (i.e., 35%, 0.78, 0.48, and 17.3% respectively). The total burned area of forest was approximately 12.11 million hm2 for the whole country from 2001 to 2017, while the annual burned area temporally decreased. Forest fires in China were dominated by the low-frequency [0<burned forests rate (BFR)≤40%] burns which occupied 79% of the total burned area. The medium-frequency (40%<BFR≤80%) and high-frequency (80%<BFR≤120%) burns accounted for 11% and 10% of the total burned area, respectively. The seasonality of forest fires differed substantially among eco-regions. The primary fire season of the temperate eco-region was spring (May) and autumn (October). Fire season in the tropical-subtropical eco-region started from the winter to the next spring which included the months from November to next March.

A Probabilistic Method Predicting Forest Fire Occurrence Combining Firebrands and the Weather-Fuel Complex in the Northern Part of the Daxinganling Region, China

The fire danger rating method currently used in the northern part of the Daxinganling Region with the most severe forest fires in China only uses weather variables without considering firebrands. The discrepancy between fire occurrence and fire risk by FFDWR (Forest Fire-Danger Weather Rating, a method issued by the National Meteorological Bureau, that is used to predict forest fire probability through links between forest fire occurrence and weather variables) in the northern part is more obvious than that in the southern part. Great discrepancy has emerged between fire danger predicted by the method and actual fire occurrence in recent years since a strict firebrand prohibition policy has significantly reduced firebrands in the region. A probabilistic method predicting fire probability by introducing an Ignition Component (IC) in the National Fire Danger Rating System (NFDRS) adopted in the United States to depict effects of both firebrand and weather-fuel complex on fire occurrence is developed to solve the problem. The suitability and accuracy of the new method in the region were assessed. Results show that the method is suitable in the region. IC or the modified IC can be adopted to depict the effect of the weather-fuel complex on fire occurrence and to rate fire danger for periods with fewer firebrands. Fire risk classes and corresponding preparedness level can be determined from IC in the region. Methods of the same principle could be established to diminish similar discrepancy between actual fire occurrence and fire danger in other countries.

Forest fire characteristics in China: Spatial patterns and determinants with thresholds

Forest fire characteristics in China: Spatial patterns and determinants with thresholds

Historical trends of forest fires and carbon emissions in China from 1988 to 2012

AbstractA larger amount of carbon is stored in forest ecosystems than in the entire atmosphere. Thus, relatively small changes in forest carbon stocks can significantly impact net carbon exchange between the biosphere and atmosphere. Changes in forest stocks can result from various disturbances, such as insect pests, windstorms, flooding, and especially forest fires. Globally, the impact of forest fires has been enhanced due to ongoing warming of the climate. The current study reported an evaluation of carbon emissions from historical forest fires in China during 1988–2012 with observational data collected from national agriculture statistics. Historical fire trends and fire‐induced carbon emissions were described over space and time at both national and regional levels. The results indicated that no significant increases in fire occurrence and carbon emissions were observed during the study period at the national level. However, at the regional level, there was a significant increasing trend in fire occurrence, and drought severity was a major driver of fire activity. Most carbon emissions were from north and northeast China, and these emissions contributed significantly to total carbon emissions. The results also showed that annual fire‐induced emissions ranged from 0.04 Tg C to 7.22 Tg C, with an average of 1.03 Tg C. Large interannual and spatial variabilities of carbon emissions were also indicated, and these were attributed to spatial and temporal variations in fire regimes. The results improve understanding of fire characteristics and provide significant information for reducing model‐related uncertainty of fire‐induced carbon emissions.

Ergonomic evaluation of the operating characteristics of the 6MF-30 portable pneumatic extinguisher

Ergonomic evaluation of the operating characteristics of the 6MF-30 portable pneumatic extinguisher

Forest fire prevention management legal regime between China and the United States

Precautions against forest fires, a significant element in the prevention and reduction of natural disasters in China, are very important to the development of public emergency systems, as well as to the safety of forest resources, ecology, people’s lives and properties. The USA has extensive experience in forest fire management, which has been widely accepted and used by other countries. The precautions taken by China and the USA to prevent forest fires have been compared in a great number of previous studies. However, most of the studies have focused merely on fire extinguishing technologies and management methods; they have lacked a comparative study on the legal aspects of management. This paper will consider five distinct aspects related to forest fire management between China and the USA and will analyze the similarities and differences as well as study other features to facilitate work related to precautions against forest fires in China.

Predicting hourly litter moisture content of larch stands in Daxinganling Region, China using three vapour-exchange methods

Fuel moisture affects fuel ignition potential and fire behaviour. To accurately model fire behaviour, predict fuel ignition potential and plan fuel reduction, fuel moisture content must be assessed regularly and often. To establish models for Daxinganling Region, which has the most severe forest fires in China, hourly measurements were taken of moisture content in litter beds of larch stands sampled under different shading and slope conditions. Models were established using three vapour-exchange methods. The Nelson and Simard methods employed a direct timelag method using a timelag concept and the Nelson and Simard equilibrium moisture content (EMC) functions and estimating model parameters directly from fuel moisture and weather observation data in the field. The direct regression method used equations directly derived from linear regression of fuel moisture and field weather variation. The mean absolute error and mean relative error were determined for the Nelson (0.78%, 4.98%), Simard (1.04%, 5.57%) and direct regression (1.48%, 9.01%) methods. Only the models established using the direct timelag methods met the 1% accuracy requirement using either the Nelson or Simard EMC function, confirming the suitability and robustness of the direct timelag methods. The Simard and Nelson methods had similar accuracy, but Simard was more robust and only needed estimation of one parameter and hence is recommended for predicting litter moisture in this region.

黑龙江省温带森林火灾碳排放的计量估算研究

As global climate change continues to accelerate,the frequency and intensity of forest fires continue to grow.Forest fires,which play an important ecological role in forest ecosystems,have a very significant effect on carbon emissions and carbon sinks,and also play an important role in the carbon cycle. Although the impact of forest fires on carbon emissions has been analyzed in detail,studies that scientifically and accurately measure carbon and carbonaceous gas emissions from forest fires are lacking. Carbon dioxide( CO2) emissions from temperate forest fires are usually calculated based on Intergovernmental Panel on Climate Change guidelines( IPCC 1997) and only include direct effects of burning.Forest fires have been shown to release significant amounts of carbon into the atmosphere and play a significant role in theglobal carbon cycle and carbon balance. In this study,we estimated the level of emissions from forest fires for carbon and carbonaceous gases including CO2,carbon monoxide( CO),methane( CH4),and non-methane hydrocarbons( NMHC)from 1953 to 2012 in Heilongjiang Province,China. We used a geographic information system based modeling approach to simulate emissions using a two-step procedure. First,we calculated total carbon released from forest fires in Heilongjiang for selected years between 1953 and 2012 by merging and analyzing measurements of several parameters. Second,we calculated the amounts of four carbonaceous gases released during the burn,CO2,CO,CH4,and NMHC,using several different experimentally derived emission factors. The origin of each of the inputs used in our models was based on a combination of analysis of forest fire inventory,forest resources inventory,field research,and laboratory experiments.Direct total carbon emissions from forest fires in Heilongjiang during 1953—2012 were about 5. 88×107t,and mean annual carbon emissions were about 9. 80 ×105t per year,accounting for 8. 66% of the direct total carbon emissions from forest fires in China. Carbon emissions of four trace gases,CO2,CO,CH4and NMHC,from forest fires were 1. 89×108,1.06×107,6.33×105and 4. 43×105t,respectively; mean annual emissions of CO2,CO,CH4and NMHC were 3. 15×106,1.77×105,1.05×104and 7. 38×103t,respectively,accounting for 7. 74%,6. 52%,9. 42% and 6. 53% of the amounts of CO2,CO,CH4and NMHC released from forest fires in China,respectively,during that period. Our results indicate that combustion efficiency of coniferous broad-leaved mixed forest is lower than other forest types. The mean annual burned area for this type of forest accounts for 57. 54% of China's total burn area,while this area's fires account for only 38. 57% of carbon total emissions from forest fires. We propose the following forest fire management strategy. First,our studies show that the area's mean annual forest fire carbon emissions have an important impact on the regional carbon balance. So,we suggest strengthening the management of forest fuels( fine fuels,heavy fuels,etc.) as part of the regional forest fire management strategy. Fuels on the ground do not decompose easily in Heilongjiang's cold and dry temperate forests. Land managers should implement a reasonable prescribed burning plan designed to reduce the accumulation of combustible fuels.A policy for conducting periodic prescribed burning will reduce the incidence of forest fires. Prescribed burning should help land managers to control and limit the incidence and intensity of wildfires while allowing them to improve the condition of the ecosystem. Finally,we should give full consideration to the role of forest fires in maintaining the ecological balance of forest ecosystems.