Firefighting protective clothing is a crucial protective equipment for firefighters to minimize skin burn and ensure safety firefighting operation and rescue mission.A recent increasing concern is to develop self-powe...Firefighting protective clothing is a crucial protective equipment for firefighters to minimize skin burn and ensure safety firefighting operation and rescue mission.A recent increasing concern is to develop self-powered fire warning materials that can be incorporated into the firefighting clothing to achieve active fire protection for firefighters before the protective clothing catches fire on fireground.However,it is still a challenge to facilely design and manufacture thermoelectric(TE)textile(TET)-based fire warning electronics with dynamic surface conformability and breathability.Here,we develop an alternate coaxial wet-spinning strategy to continuously produce alternating p/n-type TE aerogel fibers involving n-type Ti_(3)C_(2)T_(x)MXene and p-type MXene/SWCNT-COOH as core materials,and tough aramid nanofiber as protective shell,which simultaneously ensure the flexibility and high-efficiency TE power generation.With such alternating p/n-type TE fibers,TET-based self-powered fire warning sensors with high mechanical stability and wearability are successfully fabricated through stitching the alternating p-n segment TE fibers into aramid fabric.The results indicate that TET-based fire warning electronics containing 50 p-n pairs produce the open-circuit voltage of 7.5 mV with a power density of 119.79 nW cm-2 at a temperature difference of 300℃.The output voltage signal is then calculated as corresponding surface temperature of firefighting clothing based on a linear relationship between TE voltage and temperature.The fire alarm response time and flame-retardant properties are further displayed.Such self-powered fire warning electronics are true textiles that offer breathability and compatibility with body movement,demonstrating their potential application in firefighting clothing.展开更多
Active organic carbon in soil has high biological activity and plays an important role in forest soil ecosystem structure and function. Fire is an important disturbance factor in many forest ecosystems and occurs freq...Active organic carbon in soil has high biological activity and plays an important role in forest soil ecosystem structure and function. Fire is an important disturbance factor in many forest ecosystems and occurs frequently over forested soils. However, little is known about its impact on soil active organic carbon (SAOC), which is important to the global carbon cycle. To investigate this issue, we studied the active organic carbon in soils in the Larix gmelinii forests of the Da Xing'an Mountains (Greater Xing'an Mountains) in Northeastern China, which had been burned by high-intensity wildfire in two different years (2002 and 2008). Soil samples were collected monthly during the 2011 growing season from over 12 sample plots in burned and unburned soils and then analyzed to examine the dynamics of SAOC. Our results showed that active organic carbon content changed greatly after fire disturbance in relation to the amount of time elapsed since the fire. There were significant differences in microbial biomass carbon, dissolved organic carbon, light fraction organic carbon, particulate organic carbon between burned and unburned sample plots in 2002 and 2008 (p < 0.05). The correlations between active organic carbon and environmental factors such as water content, pH value and temperature of soils, and correlations between each carbon component changed after fire disturbance, also in relation to time since the fire. The seasonal dynamics of SAOC in all of the sample plots changed after fire disturbance; peak values appeared during the growing season. In plots burned in 2002 and 2008, the magnitude and occurrence time of peak values differed. Our findings provide basic data regarding the impact of fire disturbance on boreal forest soil-carbon cycling, carbon-balance mechanisms, and carbon contributions of forest ecosystem after wildfire disturbance.展开更多
Physical inactivity has been identified as one of the leading causes of many chronic diseases such as cardiovascular disease,type 2 diabetes,and obesity.Technology such as video games plays a complicated role in physi...Physical inactivity has been identified as one of the leading causes of many chronic diseases such as cardiovascular disease,type 2 diabetes,and obesity.Technology such as video games plays a complicated role in physical inactivity—much like a double-edged sword.Traditionally,video games have contributed to the epidemic of physical inactivity and have展开更多
基于火灾信息资源管理系统(Fire Information for Resource Management System,FIRMS)MODIS(Moderate-resolution Imaging Spectroradiometer)与VIIRS(Visible Infrared Imaging Radiometer)的活跃火位置数据,按照2000—2018年不同时间...基于火灾信息资源管理系统(Fire Information for Resource Management System,FIRMS)MODIS(Moderate-resolution Imaging Spectroradiometer)与VIIRS(Visible Infrared Imaging Radiometer)的活跃火位置数据,按照2000—2018年不同时间(年、月、时)和空间(国家)尺度分析了北极地区活跃火动态变化,旨在为活跃火的预测和管理提供依据。研究结果表明:(1)2012—2018年,MODIS C6(MODIS Near Real-time 1 km active fire products,MCD14DL)与VIIRS V1(VIIRS Near Real-time 375 m active fire products,VNP14-IMGTDL_NRT)活跃火频次趋势一致,最大值与最小值分别出现在2013年与2015年;(2)北极地区活跃火频次累计最多的国家是俄罗斯,最少的国家是挪威,两套产品年际变化在不同国家特征颇为相似;(3)北极地区7国(俄罗斯、美国、加拿大、丹麦、挪威、瑞典和芬兰)活跃火现象主要集中在6—8月,活跃火观测时段主要集中在各国当地时间12时左右。展开更多
Background The Cerrado is the most biodiverse savanna and maintains other biomes.Aware of its significance,this paper evaluated the Brazilian Cerrado’s climatic,environmental,and socioeconomic aspects using remote se...Background The Cerrado is the most biodiverse savanna and maintains other biomes.Aware of its significance,this paper evaluated the Brazilian Cerrado’s climatic,environmental,and socioeconomic aspects using remote sensing data and spatial statistics(correlation analysis and principal components analysis—PCA).Following the measures of sample adequacy(MSA)and Kaiser–Meyer–Olkin(KMO)tests,seventeen variables were evaluated.Results The MSA revealed that the dataset had a good quality(0.76),and nine variables were selected:elevation,evapotranspiration,active fires,Human Development Index(HDI),land use and land cover(LULC;shrubland and cropland/rainfed),rainfall(spring and autumn),and livestock.The correlation matrix indicated a positive(negative)association between HDI and autumn rainfall(HDI and active fires)with a value of 0.77(-0.55).The PCA results determined which three principal components(PC)were adequate for extracting spatial patterns,accounting for 68.02%of the total variance with respective values of 38.59%,16.89%,and 12.5%.Due to economic development and agribusiness,Cerrado’s northern(central,western,and southern)areas had negative(positive)score HDI values,as shown in PC1.Climatic(rainfall—spring and fall)and environmental(cropland/rainfed and shrubland)aspects dominated the PC2,with negative scores in northern and western portions due to the transition zone between Amazon and Cerrado biomes caused by rainfall variability.On the other hand,environmental aspects(LULC-shrubland and elevation)influenced the PC3;areas with high altitudes(>500 m)received a higher score.Conclusion Agricultural expansion substantially affected LULC,leading to deforestation-caused suppression of native vegetation.展开更多
Relatively little is known about fire regimes in grassland and cropland in Central Asia.In this study,eleven variables of fire regimes were measured from 2001 to 2019 by utilizing the burned area and active fire produ...Relatively little is known about fire regimes in grassland and cropland in Central Asia.In this study,eleven variables of fire regimes were measured from 2001 to 2019 by utilizing the burned area and active fire product,which was obtained and processed from the GEE(Google Earth Engine)platform,to describe the incidence,inter-annual variability,peak month and size of fire in four land cover types(forest,grassland,cropland and bare land).Then all variables were clustered to define clusters of fire regimes with unique fire attributes using the K-means algorithm.Results showed that Kazakhstan(KAZ)was the most affected by fire in Central Asia.Fire regimes in cropland in KAZ had the frequent,large and intense characters,which covered large burned areas and had a long duration.Fires in grassland mainly occurred in central KAZ and had the small scale and high-intensity characters with different quarterly frequencies.Fires in forest were mainly distributed in northern KAZ and eastern KAZ.Although fires in grassland underwent a shift from more to less frequent from 2001 to 2019 in Central Asia,vigilance is needed because most fires in grassland occur suddenly and cause harm to humans and livestock.展开更多
VIIRS 375 m active fire data(VNP14IMG),the highest spatial resolution available cost-free fire product,were assessed for representing fire in typical degraded tropical peatlands in Indonesia.The results of applying th...VIIRS 375 m active fire data(VNP14IMG),the highest spatial resolution available cost-free fire product,were assessed for representing fire in typical degraded tropical peatlands in Indonesia.The results of applying the Tropical Peatland Combustion Algorithm to Landsat-8(ToPeCAl-L8)daytime imagery were utilised as the fire references.To permit the comparison of non-simultaneous VNP14IMG and ToPeCAl-L8,peatland fire propagation speeds resulting from previous study using TET-1 data in Central Kalimantan’s peatlands were utilised.Most peatland fires were still within 750 m from their source over 15 h under uniform conditions,except for very large fires.The detection rates of nighttime VNP14IMG compared with ToPeCAl-L8 showed about 80%agreement for small fire areas(<14 ha).For fires larger than 14 ha,a dissolved 375 m buffer(cluster buffer)of VNP14IMG active fires with an integration of nighttime and daytime acquisitions,produced a probability of detection up to 90%.These results generated a recommendation for implementing cluster buffer analysis and integration of nighttime and daytime analysis of VNP14IMG data for better accuracy in fire detection for ground fire management.They also demonstrate the utility of the ToPeCAl-L8 algorithm with VIIRS 375 m active fire data.展开更多
基金This work was financially supported by the Opening Project of National Local Joint Laboratory for Advanced Textile Processing and Clean Production(FX2022006)Guiding Project of Natural Science Foundation of Hubei province(2022CFC072)+2 种基金Guiding Project of Scientific Research Plan of Education Department of Hubei Province(B2022081)Shenghong Key Scientific Research Project of Emergency Support and Public Safety Fiber Materials and Products(2022-rw0101)Science and Technology Guidance Program of China National Textile and Apparel Council(2022002).
文摘Firefighting protective clothing is a crucial protective equipment for firefighters to minimize skin burn and ensure safety firefighting operation and rescue mission.A recent increasing concern is to develop self-powered fire warning materials that can be incorporated into the firefighting clothing to achieve active fire protection for firefighters before the protective clothing catches fire on fireground.However,it is still a challenge to facilely design and manufacture thermoelectric(TE)textile(TET)-based fire warning electronics with dynamic surface conformability and breathability.Here,we develop an alternate coaxial wet-spinning strategy to continuously produce alternating p/n-type TE aerogel fibers involving n-type Ti_(3)C_(2)T_(x)MXene and p-type MXene/SWCNT-COOH as core materials,and tough aramid nanofiber as protective shell,which simultaneously ensure the flexibility and high-efficiency TE power generation.With such alternating p/n-type TE fibers,TET-based self-powered fire warning sensors with high mechanical stability and wearability are successfully fabricated through stitching the alternating p-n segment TE fibers into aramid fabric.The results indicate that TET-based fire warning electronics containing 50 p-n pairs produce the open-circuit voltage of 7.5 mV with a power density of 119.79 nW cm-2 at a temperature difference of 300℃.The output voltage signal is then calculated as corresponding surface temperature of firefighting clothing based on a linear relationship between TE voltage and temperature.The fire alarm response time and flame-retardant properties are further displayed.Such self-powered fire warning electronics are true textiles that offer breathability and compatibility with body movement,demonstrating their potential application in firefighting clothing.
基金financially supported by the National Natural Science Foundation(No 31470657)Fundamental Research Funds for the Central Universities(No 2572015DA01)
文摘Active organic carbon in soil has high biological activity and plays an important role in forest soil ecosystem structure and function. Fire is an important disturbance factor in many forest ecosystems and occurs frequently over forested soils. However, little is known about its impact on soil active organic carbon (SAOC), which is important to the global carbon cycle. To investigate this issue, we studied the active organic carbon in soils in the Larix gmelinii forests of the Da Xing'an Mountains (Greater Xing'an Mountains) in Northeastern China, which had been burned by high-intensity wildfire in two different years (2002 and 2008). Soil samples were collected monthly during the 2011 growing season from over 12 sample plots in burned and unburned soils and then analyzed to examine the dynamics of SAOC. Our results showed that active organic carbon content changed greatly after fire disturbance in relation to the amount of time elapsed since the fire. There were significant differences in microbial biomass carbon, dissolved organic carbon, light fraction organic carbon, particulate organic carbon between burned and unburned sample plots in 2002 and 2008 (p < 0.05). The correlations between active organic carbon and environmental factors such as water content, pH value and temperature of soils, and correlations between each carbon component changed after fire disturbance, also in relation to time since the fire. The seasonal dynamics of SAOC in all of the sample plots changed after fire disturbance; peak values appeared during the growing season. In plots burned in 2002 and 2008, the magnitude and occurrence time of peak values differed. Our findings provide basic data regarding the impact of fire disturbance on boreal forest soil-carbon cycling, carbon-balance mechanisms, and carbon contributions of forest ecosystem after wildfire disturbance.
文摘Physical inactivity has been identified as one of the leading causes of many chronic diseases such as cardiovascular disease,type 2 diabetes,and obesity.Technology such as video games plays a complicated role in physical inactivity—much like a double-edged sword.Traditionally,video games have contributed to the epidemic of physical inactivity and have
文摘基于火灾信息资源管理系统(Fire Information for Resource Management System,FIRMS)MODIS(Moderate-resolution Imaging Spectroradiometer)与VIIRS(Visible Infrared Imaging Radiometer)的活跃火位置数据,按照2000—2018年不同时间(年、月、时)和空间(国家)尺度分析了北极地区活跃火动态变化,旨在为活跃火的预测和管理提供依据。研究结果表明:(1)2012—2018年,MODIS C6(MODIS Near Real-time 1 km active fire products,MCD14DL)与VIIRS V1(VIIRS Near Real-time 375 m active fire products,VNP14-IMGTDL_NRT)活跃火频次趋势一致,最大值与最小值分别出现在2013年与2015年;(2)北极地区活跃火频次累计最多的国家是俄罗斯,最少的国家是挪威,两套产品年际变化在不同国家特征颇为相似;(3)北极地区7国(俄罗斯、美国、加拿大、丹麦、挪威、瑞典和芬兰)活跃火现象主要集中在6—8月,活跃火观测时段主要集中在各国当地时间12时左右。
基金The authors thank CNPq and CAPES(Financial Code 001)for their scholarship awardsThis article was developed during the Post-Doctorate Junior scholarship of no.161023/2019-3 granted by Brazilian National Council for Scientific and Technological Development(CNPq)at the first authorThe second author thanks CNPq for granting the Research Productivity Fellowship level 2(309681/2019-7).
文摘Background The Cerrado is the most biodiverse savanna and maintains other biomes.Aware of its significance,this paper evaluated the Brazilian Cerrado’s climatic,environmental,and socioeconomic aspects using remote sensing data and spatial statistics(correlation analysis and principal components analysis—PCA).Following the measures of sample adequacy(MSA)and Kaiser–Meyer–Olkin(KMO)tests,seventeen variables were evaluated.Results The MSA revealed that the dataset had a good quality(0.76),and nine variables were selected:elevation,evapotranspiration,active fires,Human Development Index(HDI),land use and land cover(LULC;shrubland and cropland/rainfed),rainfall(spring and autumn),and livestock.The correlation matrix indicated a positive(negative)association between HDI and autumn rainfall(HDI and active fires)with a value of 0.77(-0.55).The PCA results determined which three principal components(PC)were adequate for extracting spatial patterns,accounting for 68.02%of the total variance with respective values of 38.59%,16.89%,and 12.5%.Due to economic development and agribusiness,Cerrado’s northern(central,western,and southern)areas had negative(positive)score HDI values,as shown in PC1.Climatic(rainfall—spring and fall)and environmental(cropland/rainfed and shrubland)aspects dominated the PC2,with negative scores in northern and western portions due to the transition zone between Amazon and Cerrado biomes caused by rainfall variability.On the other hand,environmental aspects(LULC-shrubland and elevation)influenced the PC3;areas with high altitudes(>500 m)received a higher score.Conclusion Agricultural expansion substantially affected LULC,leading to deforestation-caused suppression of native vegetation.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences(XDA19030301)。
文摘Relatively little is known about fire regimes in grassland and cropland in Central Asia.In this study,eleven variables of fire regimes were measured from 2001 to 2019 by utilizing the burned area and active fire product,which was obtained and processed from the GEE(Google Earth Engine)platform,to describe the incidence,inter-annual variability,peak month and size of fire in four land cover types(forest,grassland,cropland and bare land).Then all variables were clustered to define clusters of fire regimes with unique fire attributes using the K-means algorithm.Results showed that Kazakhstan(KAZ)was the most affected by fire in Central Asia.Fire regimes in cropland in KAZ had the frequent,large and intense characters,which covered large burned areas and had a long duration.Fires in grassland mainly occurred in central KAZ and had the small scale and high-intensity characters with different quarterly frequencies.Fires in forest were mainly distributed in northern KAZ and eastern KAZ.Although fires in grassland underwent a shift from more to less frequent from 2001 to 2019 in Central Asia,vigilance is needed because most fires in grassland occur suddenly and cause harm to humans and livestock.
基金This research was funded by STEM-University of South Australia under scholarship programme of Research and Innovation in Science and Technology Project(RISET-Pro)in Ministry of Research,Technology and Higher Edu-cation of the Republic of Indonesia(Kemenristekdikti)with World Bank Loan No.8245-ID.
文摘VIIRS 375 m active fire data(VNP14IMG),the highest spatial resolution available cost-free fire product,were assessed for representing fire in typical degraded tropical peatlands in Indonesia.The results of applying the Tropical Peatland Combustion Algorithm to Landsat-8(ToPeCAl-L8)daytime imagery were utilised as the fire references.To permit the comparison of non-simultaneous VNP14IMG and ToPeCAl-L8,peatland fire propagation speeds resulting from previous study using TET-1 data in Central Kalimantan’s peatlands were utilised.Most peatland fires were still within 750 m from their source over 15 h under uniform conditions,except for very large fires.The detection rates of nighttime VNP14IMG compared with ToPeCAl-L8 showed about 80%agreement for small fire areas(<14 ha).For fires larger than 14 ha,a dissolved 375 m buffer(cluster buffer)of VNP14IMG active fires with an integration of nighttime and daytime acquisitions,produced a probability of detection up to 90%.These results generated a recommendation for implementing cluster buffer analysis and integration of nighttime and daytime analysis of VNP14IMG data for better accuracy in fire detection for ground fire management.They also demonstrate the utility of the ToPeCAl-L8 algorithm with VIIRS 375 m active fire data.
