Fire Accidents Research Articles

Mechanical Properties of Austenitic Stainless Steel After Exposure to Elevated Temperature

Stainless steel has been widely used in the building industry as load-bearing elements such as beams and columns. Many fire accidents in stainless steel buildings were recorded, but only a few have collapsed entirely. These buildings can be rehabilitated and the undamaged parts can be reused, which reduces the economic losses in buildings exposed to fire. The residual mechanical properties of stainless steel after the fire, are the primary determinant of the validity of the stainless steel structure. In this paper, the effect of high temperatures and the time of exposure and cooling method on the mechanical properties of S304 stainless steel was studied. The specimens were heated to 800°C and 1000°C for different heating times (30, 60,90 and 120 minutes) and cooling methods (air-cooled and water-cooled). Results showed that the post-fire yield stress was reduced by 24% and 18% after heating to 800°C for 120minutes and cooled in water and air respectively. However, heating to 1000°C showed a marginal effect on the yield stress of air-cooled specimens and a clear reduction (29%) in the water-cooled specimens. Elongation capacity increased with heating time for 1000oC specimens but decreased for 800oC specimens in both cooling methods.

Fire Extinguisher Robot: A Smart and Autonomous System for Fire Hazard Mitigation

The rapid growth of the human population and technological advancements have led to an increased occurrence of fire accidents and hazards in various settings. The challenging and demanding nature of fire extinguishing tasks, coupled with the physical limitations of human responders, necessitates innovative solutions to mitigate these risks effectively. One such solution is the development of fire extinguishing robots, which offer the potential to safeguard both human lives and the surrounding environment. This research introduces a hardware model of a fire extinguishing robot designed to address the complexities associated with fire suppression tasks. The robot's primary objective is to detect and extinguish fires swiftly, ideally before they can escalate and cause significant damage. By assuming the role of fire suppression, these robots can significantly reduce errors and overcome the limitations faced by human responders. Our designed fire extinguishing robot possesses several key functionalities. It autonomously explores the area, identifies the location of the fire, and efficiently extinguishes the flames, preventing uncontrolled fire outbreaks. Moreover, this robot demonstrates versatility by effectively handling various types of fires across diverse geographical locations. It navigates through structures while actively scanning for signs of fire, ensuring comprehensive coverage. Additionally, the robot is equipped with an array of sensors capable of monitoring critical parameters such as temperature, humidity, obstacles, and distances. These parameters are displayed in real-time on an LCD interface, providing essential data to operators. The robot's operation is streamlined through a user-friendly Bluetooth Terminal App, allowing remote control and providing users with real-time updates on fire status. In practical applications, our fire extinguishing robot shines in scenarios where the risk to human servicemen entering fire-prone areas is exceptionally high. Compared to existing robotic solutions, our system distinguishes itself by its ability to provide real-time data feedback, making it an invaluable tool for fire mitigation and prevention. Key Words: Fire Extinguishing Robot, Robotics, Fire Safety, Autonomous Systems, Fire Detection, Hazard Mitigation, Sensor Technology, Fire Prevention.

Fire-retardant hydroxyapatite/cellulosic triboelectric materials for energy harvesting and sensing at extreme conditions

Fire accidents pose a significant threat to public safety, property, and the environment. Traditional power-dependent rescue and sensing devices are susceptible to failure or even explosion in high-temperature and open-fire environments. This research has developed fire-retardant cellulosic triboelectric materials, offering a potential solution. Due to the protection of hydroxyapatite, the cellulose nanofibril (CNF)/hydroxyapatite composite film did not undergo obvious deformation or carbonization after burning for 60 s under a 500 °C alcohol lamp flame. The closely packed cross-sectional structure facilitated air filling, endowing it with certain heat insulation performance. The high surface roughness and special microstructure greatly enhanced the triboelectric performance, achieving an open circuit voltage of 102 V and a short circuit current of 6.18 μA under a working area of only 4 cm2, surpassing most cellulose-based triboelectric materials. The results in self-powered sensing of high-temperature and open flames indicate that fire-retardant cellulosic triboelectric materials have the potential for use in high-temperature environments. This study introduces a new idea for energy harvesting and sensing at extreme conditions, which has important significance for the development of wearable self-powered sensors and the smooth progress of fire rescue operations. Data availabilityData will be made available on request.

Detection of Electric Bicycle Indoor Charging for Electrical Safety: A NILM Approach

The increasing fire accidents caused by electric bicycle (EB) indoor charging have raised great concerns. To ensure residential electrical safety, EB is prohibited from charging indoors by regulations, but efficient monitoring of EB indoor charging behaviour in pratice still remains as a challenging problem. From the perspective of non-intrusive load monitoring (NILM), this paper proposes a holistic approach to detect the EB indoor charging behaviour. Our approach utilizes four key elements: (i) a multi-window based cumulative sum algorithm to capture the turning-on event from aggregate power; (ii) a twostage feature selection method to determine the optimal features to form an effective appliance signature for load identification; (iii) a one-class support vector machine classifier to identify whether the turned-on appliance is EB or other appliances in a semi-supervised way; (iv) a Raspberry-Pi based edge device to implement the overall NILM algorithm. The experiment results verify the effectiveness of our NILM based approach, which can obtain a high detection performance with a lowdimensional feature space, thus providing a cost-effective and high-performance solution for EB indoor charging detection.

Experimental study on the buoyant turbulent diffusion flame height of various intermittent levels

This work studies the buoyant turbulent diffusion flame characteristics considering various flame intermittent levels and mean flame projection area. Although many investigations have been carried to reveal the mean flame height evolution of the buoyant turbulent diffusion flame, the turbulent diffusion flame height of various intermittent levels, occurs in the un-controllable (unplanned) fire accident (such as the gas fuel pipeline/tank leakage). The underlying evolutions of the buoyant turbulent diffusion flame with the heat release rate and intermittent levels have not been fully elucidated. Experiments are conducted by various burner dimensions under varied heat release rates. The flame geometries/heights at various intermittent levels are measured and quantified comprehensively by two cameras from the front- and side- view. It shows that the mean flame height declines as burner area/dimension increases. All experimental data for mean flame height in the present work and previous work are well correlated by the modified normalized heat release rate derived from the new characteristic length. Results also show that the flame height at various intermittent levels decreases with the intermittent level. A model of the flame heights at various intermittent levels is proposed considering the intermittent level and mean flame height to predict the experimental data in this work and previous work well. Finally, a flame projection area model is proposed based on the assumption of the isosceles triangle flame projection geometry. This work provides huge amount experimental data and prediction models to describe buoyant turbulent diffusion flame behaviours, which is meaningful for evaluating thermal failure probability and laying of gaseous fuel transportation pipelines.

(Digital Presentation) Experimental Investigation of Thermal Runaway of Single 21700 Li-Ion Cell and Runaway Propagation in a Battery Module

Li-ion battery is an integral part for the electric or hybrid electric vehicles, as they provide high energy density and power density with extended cycle-life compared to their closest rivals, Ni-MH batteries [1]. As the Li-ion batteries gained significant success in the automotive sector, safety issues, pertaining to the fire and explosion accidents caused by thermal runaway (TR) have become a critical issue obstructing their applications. Therefore, the Li-ion battery thermal runaway has attracted an increasing attention of the research community worldwide. Thermal runaway is a self-accelerated degradation process of Li-ion batteries, [2] it can be brought by abuse [3] or internal cell failure due to defects [4]. During the TR, a significant amount of burnable and harmful gas and a large amount of heat are generated, which substantially increase the temperature of batteries [5]. Currently, most of the research work on the TR characteristics are conducted under different triggering modes at the cell level. However, the research on the large lithium battery pack is quite scarce. Therefore, several important issues need to be identified to reveal the critical conditions of the fire propagation, and precisely predict the fire risk of Li-ion battery pack fire.In this work, thermal failure experiments were performed using commercial cylindrical 21700 Li-ion single cell and a module by external heating, to analyze the casing rupture and the TR propagation behaviors in the pack based on the fire test apparatus. The critical parameters including the temperature, and heat release rate will be carefully analyzed to reveal the fire propagation hazards of battery packs.

Thermal Runaway Early Warning and Risk Estimation Based on Gas Production Characteristics of Different Types of Lithium-Ion Batteries

Gas production analysis during the thermal runaway (TR) process plays a crucial role in early fire accident detection in electric vehicles. To assess the TR behavior of lithium-ion batteries and perform early warning and risk estimation, gas production and analysis were conducted on LiNixCoyMn1-x-yO2/graphite and LiFePO4/graphite cells under various trigger conditions. The findings indicate that the unique gas signals can provide TR warnings earlier than temperature, voltage, and pressure signals, with an advanced warning time ranging from 16 to 26 min. A new parameter called the thermal runaway degree (TRD) is introduced, which is the product of the molar quantity of gas production and the square root of the maximum temperature during the TR process. TRD is proposed to evaluate the severity of TR. The research reveals that TRD is influenced by the energy density of cells and the trigger conditions of TR. This parameter allows for a quantitative assessment of the safety risk associated with different battery types and the level of harm caused by various abuse conditions. Despite the uncertainties in the TR process, TRD demonstrates good repeatability (maximum relative deviation < 5%) and can be utilized as a characteristic parameter for risk estimation in lithium-ion batteries.

IoT based Fire Detector and Automatic Extinguisher

This paper suggests creating an automatic fire detection system that makes use of the Blynk platform to notify users of fire emergencies. Sensors and image processing techniques will be used by the system to identify fires and notify users via a mobile application. Also, data on fire accidents will be gathered and analyzed by the system to spot trends and create preventative measures. The dataset will contain data on the origins of fires, how frequently they occur, and how they affect various kinds of buildings and structures. Machine learning algorithms will be used in the analysis to find potential risk variables and create fire prevention plans. This project's overall goal is to increase fire safety through the provision of early detection and alert systems as well as the use of data analysis to create efficient preventive measures

Study on Fire Prevention in Dong Traditional Villages in the Western Hunan Region: A Case Study of Gaotuan Village

Fire accidents have been reported frequently in Chinese townships over the past few years, where people’s lives and properties have been subjected to huge losses. As a result, a considerable number of traditional villages have disappeared. In this study, field surveys and on-site monitoring were used to study the village of Gao Tuan, while seven scenarios were set up in Pyrosim for simulation and analysis. As indicated by the results of this study, the hidden dangers of Dong traditional settlements in the western Hunan region were identified in terms of the construction materials, street width, and fire use. The Pyrosim simulation analysis results were as follows: scenarios 1/2 show that by utilizing the topography and layout, the wind speed was reduced layer by layer, which reduced the fire spreading disaster by nearly half; scenarios 3/4/5/6 show that, except for the 1000 mm wide street, the degree of fire spreading was negatively correlated with the width of the street, and the fire could no longer be spread to the other side of the street when it was 8000 mm; and scenario 7 shows that, in the case of a fire in a residential house, it is safer to evacuate the people in the building in a unit within 320 s. Based on the survey and Pyrosim simulation results of fire spreading, the strengths and weaknesses of Gaotuan Village in the face of fire events were analyzed, and targeted recommendations are made based on the study for the Dong traditional settlement in the western Hunan region for fire prevention.

IoT Enabled Model with Virtual Assistant for Smart Home Applications

The Internet of Things (IoT) has emerged as a prominent technological opportunity, offering numerous professional prospects. It revolves around establishing wireless communication standards between devices and appliances to enhance daily human life. This particular project aims to create a secure and automated home environment by monitoring and controlling various home appliances using Wi-Fi as the primary communication protocol. Traditionally, wireless communication techniques like Wi-Fi and Bluetooth have been utilized for home automation. However, these methods have limitations such as short range and high costs. To overcome these challenges, this paper proposes the techniques of comfy home automation involve the efficient management of appliances like lights and fans, which not only provide convenience but also save time, reduce the need for manual intervention, enhance home security, and send SMS alerts to the owner in case of fire accidents or gas leakages through a dedicated mobile application. Additionally, it aims to train the virtual assistant to engage in enjoyable interactions with the homeowner, further enhancing the user experience. To implement this, this work utilizes the "NodeMCUESP8266" module, which will serve as the foundation for our system. The integration of this technology will prove especially beneficial for individuals who are physically challenged, elderly, or frequently away from home due to their busy schedules. By leveraging the power of IoT and mobile applications, this paper suggests a smart home automation solution that caters to the specific needs and preferences of homeowners, ultimately enhancing their quality of life.

Circuit Integrity Assessment of Fire-Resistant Cables

In the electrical industry, fire accidents may happen due to overheating of electrical equipment, short circuit faults and any external source of fire. Polymeric Electrical Cables are prone to spread fire along the cable run as the insulation and sheathing materials are of flammable nature. Hence various flame retardants and low-smoke polymers are being used so that the flame spread and toxic gas release can be controlled. There are some special application cables called Fire Resistant cables which need to maintain the circuit integrity of the cable even during fire conditions. The construction of these fire-resistant cables requires fire-resistant insulation to achieve the fire-resistance property. They are such as Glass- Mica tape, Silicone Rubber, mineral insulation, metal insulation and fire retardant coating. There is various International and National standard assessing methods to assess these special cables. In this paper, the fire-resistant insulating materials and their performance during the assessment in achieving the required fire-resistant property are discussed.

Statistical analysis of heat-induced rock physics and mineralogical alteration processes of monzogranite samples from Bátaapáti, Hungary

Heat-induced physical changes of rocks, as would happen in fire accidents, have crucial importance in the long-term stability of underground openings such as tunnels or radioactive waste disposal chambers. The thermal behaviour of monzogranite from the Radioactive waste repository of Bátaapáti (Hungary) was studied in that context. Room temperature (22 °C) and a series of high temperature (250 °C, 375 °C, 500 °C, 625 °C, 750 °C) heat-treated samples were tested. P and S- ultrasound pulse velocity, bulk density, Duroskop rebound, uniaxial compressive strength, and modulus of elasticity were measured and compared, detecting temperature-related changes. Descriptive statistics and non-parametric Kruskal–Wallis and Median tests were carried out to analyze the heat-induced rock mechanical and mineralogical alteration processes. Based on these results using the data set of physical parameters, it is possible to predict the heating temperature of granitic rocks when the firing or heat stress conditions are unknown. Additionally, the data could be utilized for design and monitoring systems in underground repositories or tunnel systems constructed in granitic rock settings globally. The study demonstrated that significant alteration occurs above 500 °C; all studied rock-mechanical parameters decreased rapidly. These changes are linked to the thermal expansion, micro-cracking in micro-fabric, and volumetric increase and fragmentation of quartz inversion. Consequently, the propagation velocities of P- and S-waves also decreased significantly. Bulk density and Duroskop surface strength significantly decreased above 375 °C, while uniaxial compressive strength and modulus of elasticity dropped drastically at 750 °C after a linear decrease.

Experimental study of the burning behavior and key parameters of gasoline pool fires with different ullage heights

Pool fires with different ullage heights are a common type of fire accident. A series of gasoline pool fire experiments with two sizes (D = 40 cm, 60 cm) and six ullage heights (h = 0, 0.2D, 0.4D, 0.6D, 0.8D, 1.0D) are conducted. The burning process, axial temperature profile, radiative heat feedback, and burning rate are measured and analyzed. The result shows that the fuel vapor layer and the down-reaching flame layer are distinguished based on the axial temperature profile for the steady burning stage. Meanwhile, the down-reaching flame length (Ldown) increases more profoundly for large tank diameters under the same ullage height. Subsequently, the dimensionless down-reaching flame length (Ldown* = Ldown/D) increases exponentially with the dimensionless ullage heights (h* = h/D). Finally, based on the classical burning rate model for the low ullage height and the heat transfer process from the flame to the fuel surface, a correlation with different ullage heights is established to calculate the burning rate, which is then validated against the experimental data in the paper and literature values. The results are of importance to understand the burning rate and the radiative heat feedback to the fuel surface for pool fires with different ullage heights.

A Study to Assess Knowledge and Practices regarding Fire Safety among Health care workers in selected Hospitals of Pune City

Background: Every year, in India, about 25,000 persons die due to fires and related causes. According to India Risk Surveys 2018, outbreak of fire poses risks to business continuity and operations and ranks India at 3rd position in fire incidents, especially in Northern and Western regions of India. Past incidents show that most fire accidents take place due to three major reasons: electrical short circuit and gas cylinder/stove bursts, human negligence, and ill-formed habits. As per the ADSI-2019 report, there were 11,037 fire accidents reported across the country in 2019. The number of such reported fire accidents fell by around 16% compared to 2018. The decline was more steeped compared to the year earlier, which was around 2%. The number of persons injured in fire accidents also more than halved with 441 injured persons in 2019 compared to 1193 in 2015. Fire can happen in very severe condition and so many people and animals dying due to this. It is one of the disasters faced by India. So fire safety and fire measures are one of the important aspects. Most of the fire seen in the hospital areas is due to the gaseous and chemical substances. So, for the prevention of fire or further complications fire safety measures are must. Health care worker know about the fire safety measures and preventions. Subjects and Methods: Setting: The study was conducted at selected Hospitals of the Pune city. subject the study sample comprised 100 health care workers, three tools were used for data collection, namely: Sociodemographic data, structured knowledge questionnaire, structured practice checklist. Results: Statistically significant difference was noticed between sociodemographic variables like age, gender, profession, educational qualification, work experience with Knowledge and practices of health care workers. Conclusion: There was an appreciably good practice about fire safety but they are having poor knowledge regarding fire safety. Recommendation: The study recommended continuous observation of practices can done to evaluate practices of fire safety and interventional study can be conducted to improve knowledge of health care worker.

Fire Detection System At Labuhanbatu University Based On Internet Of Things (IoT)

Fire accidents are disasters that often occur compared to other fire disasters such as floods, landslides, earthquakes or tsunamis. Fires can occur at any time, and no one knows for sure when a fire accident will occur. The impact of a fire disaster is not only material that can disappear from human lives. The causative factors of fire disasters often occur due to human negligence and fires often occur in houses where the occupants have left them. Labuhanbatu University at night will be left by the owner and all lecturers and educational staff, only guarded by two security people with this condition, it is very dangerous when a fire occurs in one of the buildings. The purpose of this research is to focus on developing a fire detection system at Labuhanbatu University based on the Internet of Things to provide early warning of safety. The system uses three sensors, namely temperature sensor, gas sensor, and fire sensor. This research is R&D research using the ADDIE model with the following stages: analysis, design, development, implementation, and evaluation. The results of the fire sensor test were 90% successful, the results of the sensor test as soon as possible were 90% successful, and the results of the temperature sensor test were 90% successful. This fire detection system can minimize or minimize the occurrence of fire accidents and losses because it is based on the Internet of Things providing early information when a fire occurs to education staff and lecturers at Labuhanabtu University. Overall, this fire warning system can function properly.

Modified analytic hierarchy process for risk assessment of fire and explosion accidents of external floating roof tanks

AbstractTo ensure the safe operation of external floating roof (EFR) tanks, it is important to conduct risk assessments for fire and explosion accidents. In this study, we develop a modified analytic hierarchy process to overcome the subjectivity in traditional analytic hierarchy analysis, improved analytic hierarchy process, and fuzzy fault tree analysis. We propose a parameter with a correction factor: the role of the parameter in the model can be gained from further modifying the structural importance of each basic event so as to overcome the subjectivity in traditional analytic hierarchy analysis, improved analytic hierarchy process, and fuzzy fault tree analysis. The judgment matrix for the analytic hierarchy process is constructed based on the modified structural importance of each basic event in a fault tree. The weight factor for each index to the top goal, combined with the fuzzy comprehensive assessment method, is adopted to conduct risk assessments for the fire and explosion accidents of EFR tanks.

New insight into the pyrophoricity and mechanism of ironic sulfide from synergistic effect of FeS and FeS2

The pyrophoricity of ironic sulfide of sulfur corrosion products in oil tanks is a critical safety and environment concern that may trigger fire and explosion accidents. This paper focused on mixtures of FeS with FeS2 and aimed to systematically investigate their influence on the pyrophoricity of ironic sulfide. The results showed that the mixtures’ oxidation spontaneous combustion processes are generally similar, including low-temperature heating, oxidation decomposition, and burning-out stages. The more unstable molecular configuration and uneven surface morphology of FeS made it more prone to spontaneous combustion than FeS2. As the proportion of FeS2 in the sample increased, it absorbed the energy used to activate FeS during the early stages of oxidation and decomposition, causing the sample’s activation energy to increase and its pyrophoricity to weaken. When the proportion of FeS2 reached a certain level, the reaction may produce a large amount of elemental sulfur, which further oxidized and released heat, thus promoting the sample’s pyrophoricity. The study results suggest that the oxidation process of ironic sulfide involved a spontaneous, multistage exothermic reaction and produced intermediate products such as elemental sulfur, leading to a synergistic effect that influenced the reaction process.

Smoke Detection of Marine Engine Room Based on a Machine Vision Model (CWC-Yolov5s)

According to statistics, about 70% of ship fire accidents occur in the engine room, due to the complex internal structure and various combustible materials. Once a fire occurs, it is difficult to extinguish and significantly impacts the crew’s life and property. Therefore, it is urgent to design a method to detect the fire phenomenon in the engine room in real time. To address this problem, a machine vision model (CWC-YOLOv5s) is proposed, which can identify early fires through smoke detection methods. Firstly, a coordinate attention mechanism is added to the backbone of the baseline model (YOLOv5s) to enhance the perception of image feature information. The loss function of the baseline model is optimized by wise intersection over union, which speeds up the convergence and improves the effect of model checking. Then, the coordconv coordinate convolution layer replaces the standard convolution layer of the baseline model, which enhances the boundary information and improves the model regression accuracy. Finally, the proposed machine vision model is verified by using the ship video system and the laboratory smoke simulation bench. The results show that the proposed model has a detection precision of 91.8% and a recall rate of 88.1%, which are 2.2% and 4.6% higher than those of the baseline model.

Risk Analysis of Laboratory Fire Accidents in Chinese Universities by Combining Association Rule Learning and Fuzzy Bayesian Networks

Targeting the challenges in the risk analysis of laboratory fire accidents, particularly considering fire accidents in Chinese universities, an integrated approach is proposed with the combination of association rule learning, a Bayesian network (BN), and fuzzy set theory in this study. The proposed approach has the main advantages of deriving conditional probabilities of BN nodes based on historical accident data and association rules (ARs) and making good use of expert elicitation by using an augmented fuzzy set method. In the proposed approach, prior probabilities of the cause nodes are determined based on expert elicitation with the help of an augmented fuzzy set method. The augmented fuzzy set method enables the effective aggregation of expert opinions and helps to reduce subjective bias in expert elicitations. Additionally, an AR algorithm is applied to determine the probabilistic dependency between the BN nodes based on the historical accident data of Chinese universities and further derive conditional probability tables. Finally, the developed fuzzy Bayesian network (FBN) model was employed to identify critical causal factors with respect to laboratory fire accidents in Chinese universities. The obtained results show that H4 (bad safety awareness), O1 (improper storage of hazardous chemicals), E1 (environment with hazardous materials), and M4 (inadequate safety checks) are the four most critical factors inducing laboratory fire accidents.

Comparative Analysis of the Impact of Two Common Residue Burning Parameters on Urban Air Quality Indicators

Crop residue burning produces a lot of polluting gases and fine particles, endangering human health, damaging soil structure, and causing fire accidents. In addition to the impact of residue burning on the local environment, pollutants can spread with the wind to more distant areas and impact their air quality. Nevertheless, a comparative analysis of the impact of two common residue burning parameters, the number of residue fire points, and residue burned area on urban air quality indicators has not been reported. In this study, the correlation between these two different residue burning parameters on air quality in Daqing City (Western Heilongjiang Province, China) was investigated comparatively using the Visible Infrared Imaging Radiometer Suite (VIIRS) fire point product, the Moderate-resolution Imaging Spectroradiometer (MODIS) burned area product, and buffer zone analysis. The association between MODIS burned area products and air quality index (AQI) was found to be around 0.8. Meanwhile, it was found that the correlation between the number of residue fire points extracted from the VIIRS active fire products and air quality was above 0.6, again with a maximum of 0.75 at a buffer radius of 50 km. Within other levels of buffer zones, the correlation between residue burned area and AQI was consistently higher than that between residue fire points and AQI. By comparing the correlation between VIIRS fire points, MODIS burned area, and the concentration of each AQI pollutant, it can be found that the correlation between the concentration of each AQI pollutant and the residue burned area was higher than that and the fire points number. MODIS burned area monitoring, on the other hand, detects changes in the time series of images taken by satellite at two transit moments to obtain a new burned area and cumulative burned area during this period, allowing the monitoring of fire traces caused by fire points at non-transit moments. From analyzing the correlation between residue fire points, residue burned area, and the concentration of each pollutant (PM2.5, PM10, CO, NO2, SO2, and O3), we found significant correlations between residue burning and PM2.5, PM10, CO, and NO2 concentrations, with the highest correlation (R2) of 0.81 for PM2.5. Moreover, the correlation between residue burned area and PM2.5, PM10, CO, and NO2 concentrations was significantly higher than that between the number of residue fire points and their concentrations.