High Population Density Research Articles

Ecohydrological risk assessment model for the Pra River Basin using GIS and multi-criteria decision making

ABSTRACT The Pra River Basin in Ghana is a major source of ecological, cultural, and economic benefits. However, it has been experiencing degradation, and logistical constraints have limited the implementation of Integrated Water Resources Management. This study presents a GIS-based ecohydrological risk model that identifies ecohydrological units with the highest degradation risk. First, the PRB was divided into 25 eco-hydrological units. Second, seven drivers of degradation were identified and mapped. The drivers were reclassified into five categories with risk scores of 1–5, with 5 indicating higher risk scores. The variables were ranked using the Analytical Hierarchy Process, the degradation risk model was calculated using the weighted sum method, and the multi-criteria decision tool was used to identify the ecohydrological units with the highest degradation risk. Of the 25 ecohydrological units delineated, the Buama, Lower Offin, Ayensu, and Oda ecohydrological units were found to be at the highest risk of degradation due to high artisanal small-scale gold mining, high population density, low forest/vegetation cover, and high encroachment in waterways. The results can be used as a guide to prioritize management intervention, starting with the areas classified as high risk and moving down to those classified as moderate risk.

Groundwater geochemistry using modified integrated water quality index (IWQI) and health indices with special emphasis on nitrates and heavy metals in southern parts of Tirupati, South India.

Groundwater is particularly vulnerable to pollution in places with a high population density and extensive human usage of the land, especially in southern parts of Tirupati, India. To assess this, 60 bore-well samples were obtained and assessed for physical specifications, ion chemistry, and heavy metals during the pre- and post-monsoon seasons 2022. The current investigation employed a modified integrated water quality index (IWQI), conventional graphical and human health risk assessment (HHRA) of nitrates and heavy metals to know the groundwater chemistry and its detrimental health effects on humans. The major ions were analyzed using American public health association (APHA)standards, whereas heavy metals were analyzed using inductively coupled plasma optical emission spectrometry(ICP-OES). Additionally, pH Redox Equilibrium and C (PHREEQC),a geochemical model written in C programming language was employed to determine the saturation indices of mineral facies and ArcGIS 10.3.1 was used for spatial distribution patterns of IWQI. Then, the HHRA of nitrates and heavy metals was performed using United States environmental protection agency (USEPA)guidelines. The noteworthy outcomes include elevated levels of Ca2+, Mg2+, Cl-, NO3-, Cu,Fe, Mn, and Pb, demonstrating rock-water interaction, silicate weathering, Ca-Mg-HCO3 followed by mixed water facies, dissolution/precipitation, reverse exchange, and anthropogenic contamination are the major controlling processes in groundwater of southern Tirupati, India. The modified IWQI reveals that most groundwater samples (38%) fall under the bad quality class, with (47%) in the poor quality class and only (15%) classified as medium qualityclass in pre- and post-monsoon seasons. Elevated IWQI were observed in all directions except in the east, which is suitable for drinking. Moreover, the major hazard quotient (HQ) and hazard index (HI)for nitrates (NO3-) and heavy metals like copper(Cu), iron (Fe), manganese (Mn), lead (Pb) and zinc (Zn) are above the critical value of 1, revealing potential risk to humans, especially infants, followed by children and adults, entailing the instantaneous implementation of proper remedial measures and stringent policies to reduce the risk associated with groundwater pollution in the southern parts of Tirupati.

Global stability of coexistence equilibria for [formula omitted]-species models of facultative mutualism

We further pursue an investigation on an abstract model characterizing the dynamics of a general class of n-species facultative mutualisms that was initiated in Georgescu et al. (2017), establishing biologically relevant sufficient conditions for the global asymptotic stability of the coexistence equilibria. These conditions are given in terms of per-species limits of growth-to-loss ratios computed at higher population densities, complemented by either monotonicity or sublinearity inequalities, and are observed to hold for n-species versions of mutualistic models in current use. The specific modeling details that require either of these conditions being satisfied are outlined and discussed. As mutualisms can enhance species diversification and facilitate stable coexistence via a plethora of mechanisms, it is then important to understand the stability of speciose mutualisms, our results being of potential interest to theoretical ecologists studying the coexistence of many interacting species and to conservationists aiming for rare species preservation.

Dengue outbreak 2023 in Bangladesh: From a local concern to a global public health issue.

Dengue, a viral infection transmitted by mosquitoes, has become a substantial public health issue in Bangladesh. The high population density and subtropical-tropical climate of the nation create conducive environments for the transmission of the virus. The recent increase in dengue cases in Bangladesh prompts an inquiry into the potential for the virus to progress into an epidemic manifestation. Bangladesh is prone to dengue outbreaks due to a multitude of contributing factors. To commence, the virus is endemic to tropical and subtropical regions, and climate change is contributing to the expansion of its range. Additionally, the high population density in Bangladesh amplifies the vulnerability to dengue transmission. Intimate human proximity elevates the probability of contracting mosquito stings and transmitting viruses. The escalating incidence of dengue in Bangladesh is substantiated by the growing count of documented cases. The emergence of severe dengue is a contributing aspect that raises concerns about the potential worldwide consequences of the disease. It could potentially head from Bangladesh to neighboring nations via an infected individual. There exist apprehensions due to the substantial employment of Bangladeshi laborers overseas, compounded by the presence of foreign laborers within Bangladesh. The endeavor to control dengue in Bangladesh continues to face ongoing challenges. This review addresses the complexities of dengue transmission, assesses Bangladesh's readiness for managing epidemics, analyzes risk factors associated with dengue, and suggests preventive measures to mitigate the possibility of worldwide consequences of dengue originating within the nation.

The Potentials of Strong Earthquakes in Sub-Sahara Africa and the Neighbouring Regions: A Concept Study

This review article provides an overview of the potential locations of strong earthquakes in Sub-Saharan Africa and its neighboring regions. The study examines the geological factors contributing to seismic activity in the region and discusses the potential impact of earthquakes on the local population and infrastructure. Statistical analysis shows that the East African Rift Zone has experienced the highest seismic activity over the last two decades, with an average earthquake magnitude of 5.2 and 350 recorded seismic events of magnitude greater than 4, leading to an estimated economic loss of $850 million. Cities like Nairobi and Dar es Salaam, with urban infrastructure preparedness indices of 4.2 and 5.1 respectively, are at high risk due to their proximity to seismic zones and high population densities. The paper highlights the need for further research and preparedness measures to mitigate these risks and foster seismic resilience in Sub-Saharan Africa.

High temperatures and traffic accident crimes: Evidence from more than 470,000 offenses in China

How does climate change affect road safety? This study examines the impacts of high temperatures on the crime of causing traffic casualties based on comprehensive data covering more than 470,000 offenses from verdicts published by Chinese courts. Using 2014–2018 city-level daily panel data, we find that a day with a daily maximum temperature above 100 °F leads to a significant 11.9 % increase in traffic accident crime compared with days with a mild temperature. Heterogeneity analyses reveal that people aged 45 and above, samples on weekdays, and samples in regions with high population densities are more vulnerable to the effects of extreme heat. More importantly, we find no lagged or cumulative effects and little evidence of adaptation. Finally, by using traffic congestion index data, we observe that drivers can engage in avoidance behavior on hot days, suggesting that our estimates may provide a lower bound on the effect of extreme heat on traffic accident crime.

Technological and financial development as drivers of Latin America's energy transition

Transitioning to clean energy is a challenge for Latin American countries whose socio-economic realities require economic development and environmental sustainability to be carefully balanced. To drive this energy transition, it is essential that funding and technological innovation align with local contexts. This study aims to assess the implementation of the energy transition in Latin America from 2015 to 2020. To do this a performance indicator is developed that uses Data Envelopment Analysis (DEA) and employs data on areas such as patents and financial development as inputs. Subsequently, a Fractional Regression Model (FRM) is used to explore the socio-economic factors influencing this performance and examine its determinants. The results demonstrate significant variations in energy transition outcomes across the sample, with Brazil and Peru consistently achieving maximum DEA scores. Financial development was found to attract capital for the energy transition, with Brazil leading in the Financial Markets Development Index during the period studied. High population density was found to negatively impact energy transition across all FRM model specifications. Negative correlations between gross fixed capital formation and the level of energy transition suggest that there is lower investment in renewable energy in countries with less efficient transitions. Additionally, investment in R&D was only positively and statistically significant in efficient countries.

Exposure to tropospheric ozone and NO2 in the ambient air of Tehran metropolis: Spatiotemporal distribution and inhalation health risk assessment

BackgroundAir pollution has emerged as a critical challenge in the 21st century, necessitating alert monitoring of key pollutants such as ozone and nitrogen dioxide (NO2)F. These pollutants are exacerbated by urbanization and industrialization, posing significant health risks, particularly in densely populated metropolitan areas. ObjectiveThe aim of this study was inhalation health risk assessment of NO2 and ozone in various scenarios and spatiotemporal Distribution Interpolation. MethodsData were collected from the Tehran Air Quality Control Center, encompassing 18 monitoring stations from March 2019 to February 2022. Health risk assessments (HRA) were performed for adult age groups across three different exposure scenarios (3, 8, and 12 h) And a sensitivity analysis was also conducted to determine the relative importance of each parameter in assessing the risks of each scenario. ResultsThe hazard index (HI) values for NO2 and ozone in all three scenarios were found to range from 0.24 to 1.56 and 0.04 to 0.49, respectively and body weight is a risk-lowering factor in sensitivity analyses. The interpolation results of ozone, NOx, and NO2 using the IDW approach from March 2019 to February 2022 showed that overall, the north and northeast of Tehran had the highest concentrations of NO2 and NOx, and the north and west had the highest concentrations of ozone. SignificanceThis study underscores the HRA with exposure to NO2 and ozone, particularly for individuals spending more than 8 h outdoors. Given Tehran's high population density and persistent air pollution, it is imperative to implement effective control policies to safeguard public health. The findings advocate for limiting outdoor activity to less than 8 h per day, especially for vulnerable occupational groups. Additionally, the study highlights the importance of considering body weight in health risk assessments.

The Integration of Structural and Non-Structural Mitigation Based on Collaborative Governance Process at Tanjung Mas Sub-District

Abstract Subsidence of land levels and rising sea levels are two impacts of climate change that influence human activities, causing tidal floods. 12th and 16th RW (neighbourhood) of Tanjung Mas Subdistrict is a coastal area with a high population density that experiences tidal floods yearly. Structural mitigation programs receive more attention than non-structural programs. The mitigation process requires collaboration between stakeholders to obtain optimal results. This research aims to develop a disaster collaborative governance framework that integrates structural and non-structural mitigation. The research method used is a mixed method with a quantitative primary approach. The results show that collaborative governance in disaster mitigation involves various stages, such as collaborative initiatives, commitment to the process, collaborative processes, and monitoring evaluation. Non-structural mitigation is the primary basis for the success of the disaster management stage, while structural mitigation plays a significant role in the recovery stage. Emphasizing the balance of the role of the hexa helix is needed to create a sustainable mitigation process.

Solid waste characterization in the slum areas of Bagmati River—A case of Kathmandu, Nepal

Solid waste management (SWM) is a challenging environmental issue globally, with developing nations experiencing considerable difficulties in its efficient and effective implementation. Urban slum areas within these regions, particularly, have been reported to face unique challenges in SWM due to a combination of factors, including the low socio-economic status of residents, high population density, inadequate infrastructure, and a thriving informal economy. Despite these critical concerns, most SWM research in Nepal has concentrated on major cities and tourist hotspots. As a result, the condition of SWM in urban slum areas, typically found along the banks of major rivers in Nepal, remains a critical yet neglected aspect in research and policy discussions. This study, therefore, aims to evaluate SWM in the densely populated urban slum areas situated along the Bagmati River, a key river system in Kathmandu, the capital of Nepal. Four major slum locations within the central metropolitan area of Kathmandu—Sinamangal, Thapathali, Teku, and Balkhu—were selected for the study, and systematic random sampling and characterization of household solid waste was conducted. The results reveal that the average household solid waste generation rates in the four study sites were 155.32 g capita−1 d−1, 124.69 g capita−1 d−1, 149.9 g capita−1 d−1, and 218.44 g capita−1 d−1, respectively. Organic wastes was the most prevalent type, comprising 63.34% of the total waste, followed by paper and paper products (13.72%), plastics (12.15%), dirt and construction debris (5.57%), glass (4.31%), and other wastes (0.91%). Qualitative data from the survey revealed that although municipal waste management programs exist, awareness and participation among residents were limited. As a result, many households ended up managing their waste on their own, often in an unscientific manner polluting the river water in the vicinity. The study offers critical insights for policymakers, operators, and regulators in addressing the growing challenges of SWM. Findings are expected to aid in the sustainable management of solid waste along the river basin in central urban regions of the capital city. Under Nepal's new federal governance system, provincial and local governments are recommended to collaborate with all stakeholders, including households, to develop comprehensive, multimodal SWM strategies that also address the needs of slum areas.

Decadal changes in microplastic accumulation in freshwater sediments: Evaluating influencing factors

Microplastics are small plastic particles with sizes ranging between 1 μm and 5 mm. Microplastics can originate from macro plastics and degrade to a smaller size or be produced directly by manufacturers. Few studies have examined microplastic contamination in freshwater sediment cores to estimate changes in microplastic contamination over time. We present the results of a study that examined sediment cores from four watersheds, Kiskiminetas River, Blacklick Creek, Raystown Lake, and Darby Creek, in Pennsylvania, USA to reveal the history of microplastic accumulation and factors that contribute to microplastic distribution. The abundance and morphology of microplastics varied over time and between these four locations. The highest microplastic abundance was found in Raystown Lake, ranging from 704 to 5397 particles kg−1 with fiber as the dominant microplastic type, while Darby Creek (0–3000 particles kg−1), Kiskiminetas River (0–448 particles kg−1), and Blacklick Creek (0–156 particles kg−1) had lower microplastic concentration. Moreover, Darby Creek had the most diverse microplastic morphology and a trend of decreasing concentration with depth. Although the Darby Creek watershed has the most developed area and highest population density, it did not have the highest microplastic concentration. Averaged over the four cores, microplastic abundance increased as global plastics production increased from the 1950s–2010s. Our findings provide insights into the fate and transport of microplastic contamination in freshwater environments, which is vital to establishing sustainable mitigation strategies.

Two decades of land cover change and anthropogenic pressure around Bontioli Nature Reserve in Burkina Faso

Protected areas (PAs) are critical for ecosystem maintenance and providing services that benefit both wildlife and people. Nevertheless, climate change and anthropogenic pressures are posing an increasing challenge. Surrounded by high human population densities, there is still a paucity of information on how the land cover in Burkina Faso's PAs is changing, and what kinds of human activities are the main drivers. In this study, we examined the change in land use and land cover (LULC) in the Bontioli Nature Reserve (NR), one of Burkina Faso's most important protected areas, and assessed anthropogenic pressure within and around. Landsat imagery (ETM+ and OLI-TIRS) is used to categorise and estimate the change in LULC in 2000, 2010, and 2022 with the Random Forest algorithm on the Google Earth Engine platform. Regression analysis was applied to examine the relationship between the LULC categories and population increase. We found significant changes and correlations in LULC trends and population growth over time. From 2000 to 2022, wooded savanna, tree savanna, and shrub savanna decreased by 20.8 %, 6.8 %, and 4.5 %, respectively, while cropland increased by 26.3 %, along with grass savanna by 5 %. Population growth correlated with increased agriculture and decreased vegetative area with R2 of 0.903 and 0.793, respectively. Efforts should be made to create harmony between humans and nature through various approaches such as nature-based solutions to enable efforts for the reserve sustainable management (SDG15).

Pinpointing sources of pollution using citizen science and hyperlocal low-cost mobile source apportionment

Currently, methodologies for the identification and apportionment of air pollution sources are not widely applied due to their high cost. We present a new approach, combining mobile measurements from multiple sensors collected from the daily walks of citizen scientists, in a high population density area of Birmingham, UK. The methodology successfully pinpoints the different sources affecting the local air quality in the area using only a handful of measurements. It was found that regional sources of pollution were mostly responsible for the PM2.5 and PM1 concentrations. In contrast, PM10 was mostly associated with local sources. The total particle number and the lung deposited surface area of PM were almost solely associated with traffic, while black carbon was associated with both the sources from the urban background and local traffic. Our analysis showed that while the effect of the hyperlocal sources, such as emissions from construction works or traffic, do not exceed the distance of a couple of hundred meters, they can influence the health of thousands of people in densely populated areas. Thus, using this novel approach we illustrate the limitations of the present measurement network paradigm and offer an alternative and versatile approach to understanding the hyperlocal factors that affect urban air quality. Mobile monitoring by citizen scientists is shown to have huge potential to enhance spatiotemporal resolution of air quality data without the need of extensive and expensive campaigns.

Report on high density population of a Cladoceran, Moina macrocopa and their gut microbes in anoxic sewage water: a potential bio-indicator of aquatic pollution

Report on high density population of a Cladoceran, Moina macrocopa and their gut microbes in anoxic sewage water: a potential bio-indicator of aquatic pollution

Hydraulic Design Concept of 6.60MLD Water Treatment Plant

Abstract: The design and construction of a 6.6 million liters per day (MLD) water treatment plant (WTP) in Belpada Village, Odisha, aim to meet the increasing water demand while ensuring public health through effective water treatment processes. The plant, which sources raw water from the Tel River, follows a well-structured treatment process that includes aeration, sedimentation, filtration, and disinfection. This journal outlines the hydraulic design, treatment schemes, and structural components of the WTP. Design calculations, based on CPHEEO standards, are also discussed, focusing on the hydraulic detention times, surface loading, filtration rates, and sludge management techniques.The design of water treatment plants (WTPs) plays a crucial role in delivering safe drinking water, especially in areas with high population density and industrial growth. The 6.6 MLD WTP designed for Belpada Village in Balangir District draws water from Tel River and utilizes a cascade aeration system for the removal of contaminants. This paper discusses the hydraulic and process design, focusing on flow rates, detention times, and surface loading parameters that meet the Central Public Health and Environmental Engineering Organization (CPHEEO) standards.

Quantifying the relative importance of agricultural land use as a predictor of catchment nitrogen and phosphorus concentrations

Agriculture is a major source of nitrogen (N) and phosphorus (P) in freshwater ecosystems, and different management strategies exist to reduce farmland nutrient losses and thus mitigate freshwater eutrophication. The importance of agricultural sources of N and P as drivers of water quality is known to vary spatially, but quantification of the relative importance of the nutrient sources shaping this variability remains challenging, especially with reference to inputs from waste water treatment works. Addressing this knowledge gap is key for targeting management strategies to where they are likely to have the greatest effect. To advance our understanding in this area, this study assesses the impact of population density as a driver of the relative importance of agricultural land use for predicting mean Total Oxidised Nitrogen (TON) and Reactive Phosphorus (RP) concentrations in rivers in England, using two different data-driven, statistical approaches: a generalised linear model and random forest. Our results show that agricultural N and P sources dominate in catchments with low population density, where stream water concentrations are lower and waste water treatment works are numerous, but smaller in terms of the population equivalent served. Agricultural N and P sources are not important predictors of N and P in catchments with high population density, where contributions from waste water treatment works dominate. These results require cautious interpretation, as model validation outcomes show that high TON and RP concentrations are consistently underpredicted. Altogether, our results suggest that the relative contribution of agricultural sources may be overestimated in densely populated catchments, relative to point sources from waste water treatment works, and that management strategies to reduce the contribution of agriculture to N and P in rivers may be better targeted towards catchments with lower population density, as this is where agricultural land use is the primary source of N and P.

Utilizing Digital Mapping Technologies to Analyze the Characteristics of the Population of Ramadi City: Patterns and Trends

This study aims to employ digital mapping technologies to analyze the characteristics of the population of Ramadi city. Demographic data were collected from official sources and analyzed using digital mapping tools to provide a comprehensive overview of population distribution, population density, and growth rates in the city. The population of Ramadi city in 2022 was approximately 25,770, with the Othman bin Affan district being the most populous, with 31,703 residents. Population distribution was represented using dot maps to illustrate the numerical distribution of the population across different neighborhoods. The population density in the city was 55.3 persons per hectare, with Al-Khansaa district having the highest population density at 210.1 persons per hectare. Population density was represented using choropleth maps to highlight differences between neighborhoods. The population growth rate was 3.1% for the city of Ramadi. The western neighborhoods of the city, which experienced the highest growth rates of 8% and 7.5%, were the main destination for internal migration from other neighborhoods, significantly affecting population distribution and density. The study concluded that the use of digital mapping technologies provides effective tools for analyzing and interpreting demographic patterns, contributing to improved urban planning and equitable distribution of services across neighborhoods.

Sex-Specific Associations between Social Behavior, Its Predictability, and Fitness in a Wild Lizard.

AbstractSocial environments impose a number of constraints on individuals' behavior. These constraints have been hypothesized to generate behavioral variation among individuals, social responsiveness, and within-individual behavioral consistency (also termed "predictability"). In particular, the social niche specialization hypothesis posits that higher levels of competition associated with higher population density should increase among-individual behavioral variation and individual predictability as a way to reduce conflicts. Being predictable should hence have fitness benefits in group-living animals. However, to date empirical studies of the fitness consequences of behavioral predictability remain scarce. In this study, we investigated the associations between social behavior, its predictability, and fitness in the eastern water dragon (Intellagama lesueurii), a wild gregarious lizard. Since this species is sexually dimorphic, we examined these patterns both between sexes and among individuals. Although females were more sociable than males, there was no evidence for sex differences in among-individual variation or predictability. However, females exhibited positive associations between social behavior, its predictability, and survival, while males exhibited only a positive association between mean social behavior and fitness. These findings hence partly support predictions from the social niche specialization hypothesis and suggest that the function of social predictability may be sex dependent.

Online Utilization of the Nominal Group Technique to Gather Consensus Opinion Across Geographically Disparate Locations

Introduction: The nominal group technique (NGT) is a structured focus group that gathers opinion and generates consensus from groups on topics of interest. Previous studies using online NGTs (ONGTs) in health have been conducted in regions of high population density and internet connectivity. This activity aimed to determine the feasibility and utility of ONGTs in gathering opinion and reaching consensus on curriculum topics for a continuing research education program for health professionals dispersed across various locations in Southern Queensland. Methods: Fifteen clinical education academics from a range of health professions participated in 1-hour ONGT sessions from 2 University Department of Rural Health sites or their home offices. The traditional NGT was adapted for online use, using two free online platforms (Zoom for videoconferencing and Wooclap for voting and response collation). Results: The chosen platforms were effective in presenting ONGTs, allowing active and effective contributions to research topic ideas from all participants, including those with low internet connectivity. Silent generation enabled sharing, open discussion, and clarification of generated ideas. Wooclap was effective in reviewing and voting on generated responses and providing real-time feedback on voting outcomes. Outcomes were consistent with group consensus and useful in prioritizing research training topics. Discussion: The modified ONGT is effective in gathering opinion and gaining consensus from a geographically dispersed health workforce with varied levels of internet connectivity and experience with online platforms. It represents a cost-effective and time-effective alternative to face-to-face NGTs that is less likely to be affected by workforce disruptions.

Prediction of Forest-Fire Occurrence in Eastern China Utilizing Deep Learning and Spatial Analysis

Forest fires are a major natural calamity that inflict substantial harm on forest resources and the socio-economic landscape. The eastern region of China is particularly susceptible to frequent forest fires, characterized by high population density and vibrant economic activities. Precise forecasting in this area is essential for devising effective prevention strategies. This research utilizes a blend of kernel density analysis, autocorrelation analysis, and the standard deviation ellipse method, augmented by geographic information systems (GISs) and deep-learning techniques, to develop an accurate prediction system for forest-fire occurrences. The deep-learning model incorporates data on meteorological conditions, topography, vegetation, infrastructure, and socio-cultural factors to produce monthly forecasts and assessments. This approach enables the identification of spatial patterns and temporal trends in fire occurrences, enhancing both the precision and breadth of the predictions. The results show that global and local autocorrelation analyses reveal high-incidence areas mainly concentrated in Guangdong, Fujian, and Zhejiang provinces, with cities like Jiangmen exhibiting distinct concentration characteristics and a varied spatial distribution of fire occurrences. Kernel density analysis further pinpoints high-density fire zones primarily in Meizhou, Qingyuan, and Jiangmen in Guangdong Province, and Dongfang City in Hainan Province. Standard deviation ellipse and centroid shift analysis indicate a significant northward shift in the fire-occurrence centroid over the past 20 years, with an expanding spatial distribution range, decreasing flattening, and relatively stable fire-occurrence direction. The model performs effectively on the validation set, achieving an accuracy of 80.6%, an F1 score of 81.6%, and an AUC of 88.2%, demonstrating its practical applicability. Moreover, monthly fire zoning analysis reveals that high-incidence areas in spring and winter are mainly concentrated in Guangdong, Fujian, Zhejiang, and Hainan, while autumn shows widespread medium-incidence areas, and summer presents lower fire occurrences in most regions. These findings illustrate the influence of seasonal climate variations on fire occurrences and highlight the necessity for enhanced fire monitoring and prevention measures tailored to different seasons.