Early detection that results in early warning of forest fires occurrences in Indonesia, which are strongly related to land management practices (including peatlands), is necessary to mitigate land and forest fires in Indonesia. Riau has been chosen in this study because of its vulnerability to forest fires. The remoteness of this region is one reason for developing alternative warning tools using meteorological and social media information. This study identified tweets related to fires using carefully selected keywords, geoparsed to select messages relevant to fire occurrences, and binned within several Indonesian sub-regions in Riau Province. Content analysis was performed for 31 related online local newspapers. Assessment to study the correlation between meteorological and Twitter information with the forest fires was conducted. Existing approaches that the BMKG and other Indonesian agencies use to detect fire activities are reviewed, and a novel approach based on crowdsourcing of tweets is proposed. The results show a correlation between meteorological information and Twitter activity with satellites derived hotspot information. The policy implications of these results suggest that information should be included in the fire management system in Indonesia to support fire early detection as part of fire disaster mitigation efforts.

Animals living in the wild are exposed to numerous challenges, such as fires, that can lead to animal suffering. The impacts of fire have been studied in different branches of ecology, but studies of its effects on the welfare of individual animals remain scarce. The current review aims to synthesize a sample of relevant aspects regarding fire’s negative effects on wild animals. This review provides a better understanding of how fire compromises animal welfare, providing an example of how to use the knowledge gathered in ecology studies to examine the welfare of wild animals. It can help raise concern for the situation of wild animals as individuals, and to develop the field of welfare biology, by identifying promising future lines of research. The fundamentals of carrying out future work to design protocols for rescuing animals or preventing the harms they can suffer in fires is also explored.

In response to the complex social, environmental and economic situation caused by the "Terra dei Fuochi" phenomenon, the IZSM collaborated closely with the Terra dei Fuochi working group, carrying out additional monitoring surveys both on food (QR Code Campania project[30]), and on the environment (Campania Trasparente project[31]). This model was developed in the context of the experience accumulated in the field of environmental and food monitoring, and represents an innovative tool aimed at increasing knowledge of the environmental context of the Campania Region through an objective, integrated and organic synthesis of complex environmental phe-nomena and territorial dynamics. The model proposed here is useful for the global and synthetic assessment of environmental pressure on a municipal basis. As shown, it can also be applied to aggregations of municipalities. Furthermore, it can be used in the context of institutional actions for the planning and monitoring of improvements on a local or regional scale. Finally, the pro-posed municipality-based environmental pressure index represents the basis for geo-stratification of the sample in the context of population biomonitoring studies on a regional scale, as in the described biomonitoring study design applicable to the Campania Region.

Weather surveillance radars routinely detect smoke of various origin. Of particular significance to the meteorological community are wildfires in forests and/or prairies. For example, one responsibility of the National Weather Service in the USA is to forecast fire outlooks as well as to monitor wild fire evolution. Polarimetric variables have enabled relatively easy recognitions of smoke plumes in data fields of weather radars. Presented here are the fields of these variables from smoke plumes caused by grass fire, brush fire, and forest fire. Histograms of polarimetric data from plumes contrast these three cases. Most of the data are from the polarimetric Weather Surveillance Radar 1988 Doppler (WSR-88D aka Nexrad, 10 cm wavelength) hence the wavelength does not influence these comparisons. Nevertheless, in one case simultaneous observations of a plume by the operational Terminal Doppler Weather Radar (TDWR, 5 cm wavelength) and a WSR-88D is used to infer backscattering characteristic and hence sizes of dominant contributors to the returns. In addition, comparisons with observations by other investigators of plumes from urban area but at a 5 cm wavelength are made. To interpret some measurements Computational Electromagnetics (CEM) tools are applied.

Gas flaring is commonly used by industrial plants for processing oil and natural gases in the atmosphere, and hence is an important anthropogenic source for various pollutants including CO₂, CO, and aerosols. This study evaluates the feasibility of using satellite data to characterize gas flaring form space by focusing on the Khanty Mansiysk Autonomous Okrug in Russia, a region that is well known for its dominatingly gas flaring activities. Multiple satellite-based thermal anomaly data products at night are inter-compared and analyzed, including MODIS (Moderate Resolution Imaging Spectroradiometer) Terra level-2 Thermal Anomalies product (MOD14), MODIS Aqua level-2 Thermal Anomalies product (MYD14), VIIRS (Visible Infrared Imaging Radiometer Suite) Active Fires Applications Related Product (VAFP), and VIIRS level-2 data based Nightfire product (VNF). The analysis compares and contrasts the efficacy of these sensor products in detecting small, hot sources like flares on the ground in extremely cold environments such as Russia. We found that the VNF algorithm recently launched by NOAA has the unprecedented accuracy and efficiency in characterizing gas flares in the region owing primarily to the use of Shortwave Infrared (SWIR) bands. Reconciliation of VNF’s differences and similarities with other nighttime fire products is also conducted, indicating that MOD14/MYD14 and VAFP data are only effective in detecting those gas flaring pixels that are among the hottest in the region. Validation of VNF product of gas flaring location with Google Earth images are made. It is shown that that VNF’s estimates of gas flaring area (the area of gas flaming) agree well the counterparts from Google images with a linear correlation of 0.91, highlighting its potential use for routinely monitoring emissions of gas flaring from space.

We use the third version of the Canadian Local Climate Model as a diagnostic tool to study the climatology of observed CG lightning activity at Maniwaki (latitude: 46,23°N; Longitude: 75,58°W). We examine the dependence between the hourly lightning activity and the related atmospheric variables during the warm season of sixteen years (between 1984 and 2004). The goal of this research is: a) to evaluate the atmospheric static state evolution and its moisture contents for conditions having generated lightning occurrence, b) to develop a CG lightning parameterization, and c) to verify this CG lightning parameterization on other Canadian areas. The freezing level altitude and the precipitable water content are used to estimate the static air instability and its moisture content respectively. These two parameters are served to develop the CG lightning parameterization. A comparison between the observations and simulations CG lightning occurrence and frequency at Maniwaki showed a mean absolute error rate of 27% and 55% respectively. We apply this parameterization at four Canadian regions, distributed from west to east. The simulated CG lightning results are comparable to observed CG lightning at Maniwaki and tested regions. The application of the CG lightning parameterization to the daily data enabled us to find the monthly results. This application represents a preliminary stage for validation this parameterization in regional numerical models in Canada during the historic period.

Biomass burning is an important and changing component of the global and hemispheric carbon cycles. Boreal forest fires in Russia and Canada are significant sources of greenhouse gases carbon dioxide (CO2) and methane (CH4). The influence of carbon monoxide (CO) on the greenhouse effect is practically absent: its main absorption bands of 4.6 and 2.3 μm are far away from the climatically important spectral regions. Meanwhile, CO concentrations in fire plumes are closely related to CO2 and CH4 emissions from fires. On the other hand, satellite measurements of CO are much simpler than those for the aforementioned gases. The Atmospheric Infrared Sounder (AIRS) provides a satellite-based CO data set since October, 2002 up to now. This communication presents estimates of CO emissions from biomass burning north of 30° N using a simple two-box mass-balance model. These results correlate closely with independently estimated CO emissions from the GFED4 bottom-up data base. Both ones reported record high emissions in 2021 throughout two decades, double the annual emissions comparing to the previous years. There have been two years with extremely high emissions (2003 and 2021), but for the rest of data upward trend with a rate of 3.6 ± 2.2 Tg CO yr-2 (4.8 ± 2.7% yr-1), was found. A similar rate of CO emission follows from the GFED4 data.

Biomass burning is an important and changing component of the global and hemispheric carbon cycles. In particular, boreal forest fires in Russia and Canada are important sources of greenhouse gases carbon dioxide (CO2) and methane (CH4). The influence of carbon monoxide (CO) on the climate is insignificant: its main absorption bands of 4.6 and 2.3 μm are far away from the climatically important regions of the spectrum. Meanwhile, CO concentrations in fire plumes are closely related to CO2 and CH4 emissions from fires. On the other hand, satellite measurements of CO are much simpler than those for the aforementioned gases. The Atmospheric Infrared Sounder (AIRS) provides a long satellite-based CO data set. This article presents estimates of CO emissions from biomass burning north of 30° N using a simple two-box model. These results correlate closely with independently estimated CO emissions from the GFED4 bottom-up data base. Both ones reported record high emissions in 2021 throughout two decades, double the annual emissions comparing to the previous a few years. There have been several years with extreme emissions, but for the rest of data upward trend with a rate of 3.7 ± 2.3 Tg CO yr-2 (4.4 ± 2.8% per year), was found.

Extraordinary high aerosol contamination observed in the atmosphere over Kyiv city, Ukraine, during the March – April 2020 period. The source of contamination was the large grass and forest fires in the northern part of Ukraine and the Kyiv region. The level of PM2.5 load investigated using newly established AirVisual sensors mini-network in five areas of the city. The aerosol data from the Kyiv AERONET sun-photometer site analyzed for that period. Aerosol optical depth, Angstrom exponent, and the aerosol particles properties (particles size distribution, single-scattering albedo, and complex refractive index) were analyzed using AERONET sun-photometer observations. The smoke particles observed at Kyiv site during the fires in general correspond to aerosol with optical properties of biomass burning particles. The variability of the optical properties and chemical composition indicates that the aerosol particles in the smoke plumes over Kyiv were produced by different burning material and phases of vegetation fires at different time. The case of enormous PM2.5 aerosol contamination in Kyiv city reveals the need to accept strong measures for forest fire control and prevention in Kyiv region, especially in the north-west region where radioactive contamination from Chornobyl disaster is still significant.

Early detection of wildfires has been limited using the sun-synchronous orbit satellites due to their low temporal resolution and wildfires’ fast spread in the early stage. NOAA’s geostationary weather satellites GOES-R can acquire images every 15 minutes at 2km spatial resolution, and have been used for early fire detection. However, advanced processing algorithms are needed to provide timely and reliable detection of wildfires. In this research, a deep learning framework, based on Gated Recurrent Units (GRU), is proposed to detect wildfires at early stage using GOES-R dense time series data. GRU model maintains good performance on temporal modelling while keep a simple architecture, makes it suitable to efficiently process time-series data. 36 different wildfires in North and South America under the coverage of GOES-R satellites are selected to assess the effectiveness of the GRU method. The detection times based on GOES-R are compared with VIIRS active fire products at 375m resolution in NASA’s Fire Information for Resource Management System (FIRMS). The results show that GRU-based GOES-R detections of the wildfires are earlier than that of the VIIRS active fire products in most of the study areas. Also, results from proposed method offer more precise location on the active fire at early stage than GOES-R Active Fire Product in mid-latitude and low-latitude regions.

Historical analysis of Australian bushfire data spanning 170 years addresses whether the strength of recent fire events has been exacerbated by human-induced climate change. The question of “cause” looks at the characteristics of a wider range of natural hazards. Fire characteristics are compared with earthquake hazard characteristics: (1) energy – termed “magnitude”; (2) severity – termed “intensity”; and (3) resultant damage to people and structures – termed “impact”.Published global, Northern and Southern hemisphere temperature data are shown to vary consistently in phase over 170 years, but vary in amplitude with statistical significance. CO₂ levels north and south of the Equator have tracked quite consistently. Thus, Southern Hemisphere bushfire magnitude and intensity is compared with the Southern Hemisphere climate record, rather than a global data set.28 major bushfires and associated droughts since 1850 show neither apparent drought extent, nor area burned, nor bushfire intensity, correlates with changes in Southern Hemisphere climate. Average rainfall from 1900 shows a wetter, rather than drier trend. Cyclone energy shows no significant trend with climate. Planet-wide “greening”, through CO₂ fertilisation, is an insignificant contributor to bushfire magnitude. Combustion theory shows recorded “global warming” could have had no significant influence on bushfire magnitude or intensity. Any increase in Australian bushfire impact, as judged by lives lost, similarly, shows no correlation with bushfire magnitude, nor indeed, any observed Southern Hemisphere global warming.Thus, bushfire magnitude seems much more likely driven by fuel load and any anomalous bushfire intensity is likely driven by anomalous ground level fuel load. The evidence suggests that any CO₂ emissions reduction will have no impact on future bushfire “severity.

In order to assess the human exposure risks from the release of contaminants from water pipes made of polyvinyl chloride (PVC), experiments were carried out by subjecting the PVC pipe material to burning and leaching conditions followed by analysis of the emission and leachate samples. The emissions of burning pipes were analyzed by both infrared spectrometry and gas chromatography-mass spectrometry (GC-MS). The emission results indicate the presence of chlorinated components including chlorine dioxide, methyl chloride, methylene chloride, allyl chloride, vinyl chloride, ethyl chloride, 1-chlorobutane, tetrachloroethylene, chlorobenzene, and hydrogen chloride were detected in the emissions of burning PVC pipes. Furthermore, the concentrations of benzene, 1,3-butadiene, methyl methacrylate, carbon monoxide, acrolein, and formaldehyde were found at levels capable of affecting human health adversely. The analysis of PVC pipe leachates using GC-MS shows that there are 40-60 tentatively identified compounds, mostly long-chain hydrocarbons such as tetradecane, hexadecane, octadecane, and docosane, were released when the burned PVC materials were soaked in deionized water for one week. Quantitative analysis shows that 2-butoxyethanol, 2-ethyl-1-hexanol, and diethyl phthalate were found in the burned PVC polymer at the average levels of 2.7, 14.0, and 3.1 micrograms per gram (g/g) of pipe material. This study has significant implications for understanding the benzene contamination of drinking water in the aftermath of wildfires that burned polymer pipes in California.