Humid Tropical Regions Research Articles

Survey on the Prevalence of Buruli Ulcer in Patients with Chronic Wounds in Pointe-Noire

Background & objective: Buruli Ulcer (BU) is a human skin infection caused by Mycobacterium ulcerans, an environmental mycobacterium. This pathology is most prevalent in humid tropical regions, particularly near swampy or flood-prone areas. In Pointe-Noire, a coastal city in the Republic of Congo, Buruli ulcer is a health threat requiring ongoing surveillance and awareness-raising efforts to control its spread. The aim of this study was to determine the prevalence of Buruli ulcers in patients consulting for chronic wounds in Pointe-Noire. Methods: This was a descriptive cross-sectional study conducted from June 10, 2023 to September 18, 2024. We recruited 69 patients with chronic wounds consulted at the Adolphe Sicé General Hospital, the Tié Tié Referral Hospital, and the Pointe Noire Operational Sector. Mycobacterium ulcerans was systematically detected using the qPCR technique targeting the M. ulcerans IS 2404 specific insertion element on swab samples. Results: 69 patients with suspected BU were enrolled, with 57% (39) male and 43% (30) female subjects. The mean age was 47.7 ± 18.5, ranging from 6 to 94 years, and the most represented age group was [30-60] (66.7%). The wounds observed in our patients were mainly ulcerative in 94.2% (65) and localized to the lower limbs in 97.1% (67). The overall prevalence of Mycobacterium ulcerans infection was 2.89%. The age group affected was < 15 years, with 01 positive male case and [30-60], with 1 positive female case. Conclusion: The study carried out in Pointe-Noire revealed a Buruli ulcer prevalence of 2.86% among the 69 patients with chronic wounds tested, with 02 positive cases.

Molecular identification of Fusarium species in commercial vanilla and crop wild relatives in Colombia.

Vanilla is an economically important crop for low-lying humid tropical regions, but cultivated plants face serious phytosanitary problems. Fusarium wilt is a devastating disease affecting vanilla crops, caused by the fungal pathogens Fusarium oxysporum f. sp. vanillae (Fov) and F. oxysporum f. sp. radicis-vanillae (Forv), part of the F. oxysporum species complex (FOSC). We characterized 29 fungal isolates from a vanilla crop and crop wild relatives (CWR) using molecular (EF1-α and ITS-rRNA loci) and morphological traits. Fusarium was the predominant genus, followed by Colletotrichum and Clonostachys. Four Fusarium species were identified: F. oxysporum (37.9%), Fusarium solani (20.7%), Fusarium pseudocircinatum (13.8%) and Fusarium concentricum (10.3%). The latter three species were isolated only from CWR and may represent latent pathogens. Fov was isolated from both the crop and CWR, while a Forv-affiliated isolate was also found in a vanilla crop, marking the first report in the neotropical region. The EF1-α locus provided greater genotype resolution, as well as having reference sequences for Forv. However, the fungal barcode ITS locus is widely applied. We recommend the continued use of both loci for Fusarium diagnosis in vanilla to facilitate early detection and the development of effective integrated crop management strategies.

Application of the NRCS-curve number method in humid tropical basins of southeastern Nigeria: a statistical analysis

In the south-eastern region of Nigeria, the application of rainfall (P) and runoff (Q) data directly into the Natural Resources Conservation Service Curve Number (NRCS-CN) method hasn’t been thoroughly studied. This research aimed to determine representative values of the initial abstraction ratio (λ) and corresponding curve number (CN), fit the P and Q data using theoretical probability distributions, and establish confidence intervals for CN. The least squares minimization method and Kolmogorov-Smirnov test were employed on data from 129 sub-basins across 4 major basins. Findings revealed optimal initial abstraction ratio (λopt) = 0.24 and optimal CN (CNopt) = 80, with rainfall best fitted by Gamma, runoff by Weibull, and CN by Normal distributions. However, the study was limited to the available 8-year record period with 96 storm events. The 96 storm events over an 8-year period may seem limited for a humid tropical region, the available data were the most comprehensive and reliable dataset for this study area. Additional data collection over a longer time frame could enhance future studies. The localized CN value and associated confidence intervals can enhance runoff prediction accuracy for flood mitigation and water resources management in this humid tropical region, though further validation is recommended.

Negative Asymmetric Response of Pantropical Gross Primary Productivity to Precipitation Anomalies

AbstractThe carbon sink in pantropical biomes play a crucial role in modulating the inter‐annual variations of global terrestrial carbon balance and is threatened by extreme climate events. However, it has not been carefully examined whether an increase in tropical gross primary productivity (GPP) can compensate the decrease during precipitation anomalies. Using the asymmetry index (AI) and multiple GPP products, we assessed responses of pantropical GPP to precipitation anomalies during 2001–2022. Positive AI indicates that GPP increases are greater than GPP decreases during precipitation anomalies, and vice versa. Our results showed an average negative pantropical GPP asymmetry, that is, GPP decreases exceeded the GPP increases during precipitation anomalies. In addition, a positive AI was found in tropical hyper‐arid and arid regions, which is opposite to the negative AI observed in tropical semi‐arid, sub‐humid, and humid regions. This suggest that tropical GPP asymmetry changes from positive to negative as the moisture increases. Notably, a significant decreasing trend of negative AI was observed over the entire tropical region, indicating that the negative effect of inter‐annual precipitation variations on pantropical vegetation productivity has enhanced. Considering the model predicted increasing climate variability and extremes, the negative impact of precipitation variability on tropical carbon cycle may continue to intensify. Lastly, the divergence in AI estimates among multiple GPP products highlight the need to further improve our understanding of the response of tropical carbon cycle to climate changes, especially for the tropical humid regions.

Analysis of environmental variables and deforestation in the amazon using logistical regression models.

In this study, we applied a multivariate logistic regression model to identify deforested areas and evaluate the current effects on environmental variables in the Brazilian state of Rondônia, located in the southwestern Amazon region using data from the MODIS/Terra sensor. The variables albedo, temperature, evapotranspiration, vegetation index, and gross primary productivity were analyzed from 2000 to 2022, with surface type data from the PRODES project as the dependent variable. The accuracy of the models was evaluated by the parameters area under the curve (AUC), pseudo R2, and Akaike information criterion, in addition to statistical tests. The results indicated that deforested areas had higher albedo (25%) and higher surface temperatures (3.2°C) compared to forested areas. There was a significant reduction of the EVI (16%), indicating water stress, and a decrease in GPP (18%) and ETr (23%) due to the loss of plant biomass. The most precise model (91.6%) included only surface temperature and albedo, providing important information about the environmental impacts of deforestation in humid tropical regions.

The adaptability of Garut sheep grazing on oil palm and rubber plantations in tropical conditions of Indonesia.

The productivity of sheep in humid tropical plantation areas relies on their ability to adapt. Oil palm plantations serve as potential grazing lands for livestock. This study aimed to identify Garut sheep adaptations in oil palm and rubber plantations of the Garut district, West Java, Indonesia. The total number of sheep used was 103 as the object of this study. Each individual of sheep was used for several different observations, including: Physiological assessment using 24 sheep of various ages, molecular analysis of heat stress using 31 sheep, worm egg count using 59 sheep, and for morphological assessment using 98 sheep. A general linear model was employed to analyze rectal temperature (RT), heart rate (HR), respiratory rate, number of eggs in each gram of sample feces, body weight (BW), body condition score, and morphometric measurements according to age and sex. Forage was compared between oil palm and rubber plantations during the vegetation analysis. RT, HR, and panting frequency were significantly (p < 0.05) affected by the age and sex of the sheep. The mutation was found in the coding region of the HSP70 gene, which is approximately 232 bp long. Fecal eggs were found in 99% of the fecal samples, consisting of 100% Strongyle eggs and 1.75% Moniezia eggs. BW, body condition score, shoulder height, body length, pelvic height, chest circumference, and number of eggs were significantly affected (p < 0.05) by the age and sex of the sheep. The average fresh matter of vegetation under the plantation was 248.69 ± 120.94 g/m2 and 718.15 ± 249.93 g/m2 for oil palm and rubber plantations, respectively. Garut sheep were adapted to oil palm and rubber plantations in the humid tropical region. Plantations are potential sources of sheep grazing and roughage. Further research is needed regarding the consumption of forages in oil palm and rubber plantations.

Assessment of heat stress contributing factors in the indoor environment among vulnerable populations in Klang Valley using principal component analysis (PCA)

Rising global temperatures can lead to heat waves, which in turn can pose health risks to the community. However, a notable gap remains in highlighting the primary contributing factors that amplify heat-health risk among vulnerable populations. This study aims to evaluate the precedence of heat stress contributing factors in urban and rural vulnerable populations living in hot and humid tropical regions. A comparative cross-sectional study was conducted, involving 108 respondents from urban and rural areas in Klang Valley, Malaysia, using a face-to-face interview and a validated questionnaire. Data was analyzed using the principal component analysis, categorizing factors into exposure, sensitivity, and adaptive capacity indicators. In urban areas, five principal components (PCs) explained 64.3% of variability, with primary factors being sensitivity (health morbidity, medicine intake, increased age), adaptive capacity (outdoor occupation type, lack of ceiling, longer residency duration), and exposure (lower ceiling height, increased building age). In rural, five PCs explained 71.5% of variability, with primary factors being exposure (lack of ceiling, high thermal conductivity roof material, increased building age, shorter residency duration), sensitivity (health morbidity, medicine intake, increased age), and adaptive capacity (female, non-smoking, higher BMI). The order of heat-health vulnerability indicators was sensitivity > adaptive capacity > exposure for urban areas, and exposure > sensitivity > adaptive capacity for rural areas. This study demonstrated a different pattern of leading contributors to heat stress between urban and rural vulnerable populations.

Enhanced Biological Nitrate Removal from Groundwater in Humid Tropical Regions Using Corn Cob-Based Permeable Reactive Barriers: A Case Study from Panama

Nitrate contamination in groundwater is a global concern due to its widespread presence and consequential social, environmental, and economic ramifications. This study investigates the efficacy of biological denitrification in a humid tropical setting, utilizing corn cob in batch and column tests to assess nitrate removal under varying conditions. Batch tests demonstrated the nitrate removal efficiencies of 93.14%, 91.58%, 90.77%, and 98.74% for initial concentrations of 22.18 ± 2.82 mg/L, 27.3 mg/L, 69.1 ± 1.2 mg/L and 115.08 ± 1.88 mg/L, respectively. In the column test, the removal efficiency was 99.86%, 87.13%, and 74%, and the denitrification rate was 32.82, 53.43, and 83.53 mg NO3−-N/L d, for a hydraulic retention time (HRT) of 24 h, 16 h, and 7 h, respectively. Predominantly, nitrate removal occurred via biological denitrification, particularly favoring a 24 h HRT. The corn cob effectively removed high nitrate concentrations of up to 115 mg NO3−-N/L. Scanning electron microscopy and Fourier transform infrared spectroscopy revealed surface characteristic changes of the carbon source pre- and post-denitrification. This research sheds light on the potential of biological denitrification using corn cob in humid tropical environments, offering a promising avenue for addressing nitrate contamination challenges in groundwater systems.

Determining the quality of wood charcoals as a bioenergy source in humid tropical regions of Central Africa: the effect of carbonized wood and storage time

Determining the quality of wood charcoals as a bioenergy source in humid tropical regions of Central Africa: the effect of carbonized wood and storage time

Association of SERPING1 gene single nucleotide polymorphism with resistance to natural strongyle infection among native goats in humid tropical Kerala

Strongylosis poses a significant threat to goat populations, particularly in humid tropical regions like Kerala, a southern peninsular state in India. This study aimed to compare breed differences in host resistance and resilience to natural strongyle infection between Attappady Black and Malabari goats reared under semi-intensive systems. Additionally, we analyzed the association of a potential single nucleotide polymorphism (SNP) in the Serine Proteinase Inhibitor Clade G member 1 (SERPING1) gene with these traits. Faecal egg count (FEC) and volume of packed red cells (VPRC) were employed as indicators of host resistance and resilience, respectively. Over the course of one year, fortnightly phenotypic data on FEC and VPRC were collected from 109 native goats, including 58 Malabari and 51 Attappady Black goats. The Malabari goats exhibited greater resistance and resilience to strongylosis, evidenced by significantly lower FEC (p≤0.01) and higher VPRC (p≤0.05) compared to Attappady Black goats. Pearson correlation analysis revealed a highly significant negative correlation between FEC and VPRC (r= −0.41, p<0.01). Genotyping of the −312-C>T SNP in SERPING1 gene was conducted using modified bidirectional PCR amplification of specific alleles (Bi-PASA). While the association between SERPING1 genotypes and FEC was not significant, a significant association was observed between SERPING1 genotypes and VPRC (p<0.05). These findings underscore the importance of breed-specific differences in goat resilience to strongyle infection and highlight the potential role of SERPING1 gene polymorphism in modulating host resilience traits.

Vegetation changes through recurrent fire affect soil water behavior and enhance landslides in the mountainous region of Rio de Janeiro state, southeast Brazil

The role of fire in vegetation-soil–water interactions and its implications for soil stability and slope failures is poorly documented in humid tropical regions. This paper focuses on the relationships between vegetation change through recurrent fire and its effects on hydraulic conductivity and soil suction. Two monitoring sites were chosen on steep slopes in the mountainous domain of the Atlantic rainforest: the first is representative of degraded secondary rainforest (DRf) 25–30 years after slash and burn agriculture; the other represents herbaceous-shrubby vegetation (HS) resulting from wildfires in short-time intervals (<5 years). Two fires had previously occurred on the HS slope, one in December 2014 and the other in September 2019. Continuous records of rainfall and soil suction at depths of 10, 20, 50, 100, 150, and 220 cm provided a 6-year data collection from January 2015 to December 2020. Hydraulic conductivity (Ksat) field tests were conducted around the two monitoring sites before and after the September 2019 fire. The main results include: a) soil suction in the topsoil of both vegetation covers follow the rainfall inputs with high values of Ksat (DRf = 195 mm/h; HS = 203 mm/h); b) while quick rainfall-suction responses prevail within the DRf soil profile, soil suction at HS maintains a mean suction value around -27 kPa below 100 cm deep; c) field observations attest to the occurrence of hydrophobicity after the 2019 fire; d) Ksat tests just after this fire indicated a decreasing mean value from 203 mm/h to 46 mm/h; and e) by the end of the dry season after fire, there is a delayed increase in soil suction reaching -143 kPa at a depth of 100 cm and in smaller proportions at 220 cm deep. These results indicate that post-fire soil changes tend to favor the sudden loss of soil stability and slope failure during extreme rainfall events.

Projection of climate change effects on flood inundation in the Gin River basin, Sri Lanka

Abstract. Human-induced climate change has altered the frequency and severity of heavy precipitation, droughts, and floods worldwide. Sri Lanka, a developing country in the Indian Ocean, has suffered frequent floods, affecting over 64 % of the population in the past decade. The Gin River, the primary drinking water source of the densely populated Galle district with over 1 million residents, faces recurrent flood disasters. Therefore, this study employed a multi-model ensemble to simultaneously simulate the impact of climate change on both river flow and inundation extent in the frequently flooded Gin River basin located in humid tropical monsoon region. Bias-corrected climate projections of an ensemble of five General Circulation Models (GCMs) from the Coupled Model Inter-comparison Project Phase 5 (CMIP5) under Representative Concentration Pathway (RCP) 4.5 emission scenario were used to project future river flow and flood inundation in the Gin River basin, Sri Lanka. The validated Rainfall–Runoff–Inundation (RRI) model projected a 5 % increase in high flows (flows exceeding a 5 % probability of exceedance (&lt;Q5)) at the downstream (Baddegama) gauging station and a 16 % increase at the upstream (Thawalma) gauging station in the future (2040–2060) in comparison to the past (1980–2000), which can be attributed to the elevated rainfall projected during the two monsoon seasons (southwest monsoon (May–September) and northeast monsoon (December–February)) by the GCM ensemble. In addition to the projected changes in high flows revealed by the RRI simulations, the model also yielded critical information about the expansion of annual maximum inundated extent in the basin by 3.5 % that will aid flood risk projection and sustainable management in the basin.

Blue Urbanism

Coastal cities are most at risk to rising sea levels and increased precipitation. This is however the Climate Change Scenario forecasted for the humid tropical region in the IPCC’s Sixth Assessment report. As standard engineering (grey) solutions are prohibitive in many developing countries due to financial and technical limitations, this paper proposes an adaptive blue approach. It shares insights from Brunei, where the old capital was a city built over water. It also presents findings from a preliminary survey to gauge the public’s views on a set of blue urbanism proposals. The study found positive support for the proposals in general. In particular, there was strong support for: (i) incorporating ‘green’ features into the urban complex; (ii) more public spaces where people could learn about their cultural heritage; and (iii) participation in the life and management of the city. There is however (iv) less enthusiastic response to blue features. The paper discusses viability of the blue urbanism approach vis-à-vis cultural and contextual changes. The insights presented could be useful to other coastal cities in the region.

Spatial phylogenetics of grasses in the Southern Cone provides insights into ecology and evolution of the family in South America

AbstractIn this study, we explored the distributions of grass genera in the Southern Cone (SC) of South America, applying several phylogenetic diversity (PD) metrics and randomization tests. Grasses appear to have been present in South America since their early evolution as tropical understory species more than 60 Ma. During the course of evolution, grasses have adapted to all terrestrial biomes and become one of the most successful plant families on earth. At present, the SC contains nearly all terrestrial biomes and a wide range of humid to arid ecoregions. Analyzing 126.514 point occurrences and four plastid markers for 148 genera (91% of the native grass genera), we found that tropical humid regions hold the highest PD, with no observed bias in branch lengths. These results indicate that niche conservatism dominates the diversity pattern of grasses in the SC. We found significantly low PD in the Dry Chaco and in the Patagonian Steppe, which suggest ecological filtering in both warm and cold arid regions. The Patagonian Steppe also holds significantly longer branches than expected by chance, as the native grass flora is mainly composed of distantly related Pooideae genera with a northern hemisphere origin. Short branches are found in the Uruguayan Savanna, suggesting that these grasslands could be a cradle for grass diversity within the SC. The dated phylogeny supported the current view of a relatively recent evolution of the family within the SC, with most diversification taking place from the middle Miocene and onwards.

Regional-Scale Assessment of Burn Scar Mapping in Southwestern Amazonia Using Burned Area Products and CBERS/WFI Data Cubes

Fires are one of the main sources of disturbance in fire-sensitive ecosystems such as the Amazon. Any attempt to characterize their impacts and establish actions aimed at combating these events presupposes the correct identification of the affected areas. However, accurate mapping of burned areas in humid tropical forest regions remains a challenging task. In this paper, we evaluate the performance of four operational BA products (MCD64A1, Fire_cci, GABAM and MapBiomas Fogo) on a regional scale in the southwestern Amazon and propose a new approach to BA mapping using fraction images extracted from data cubes of the Brazilian orbital sensors CBERS-4/WFI and CBERS-4A/WFI. The methodology for detecting burned areas consisted of applying the Linear Spectral Mixture Model to the images from the CBERS-4/WFI and CBERS-4A/WFI data cubes to generate shadow fraction images, which were then segmented and classified using the ISOSEG non-supervised algorithm. Regression and similarity analyses based on regular grid cells were carried out to compare the BA mappings. The results showed large discrepancies between the mappings in terms of total area burned, land use and land cover affected (forest and non-forest) and spatial location of the burned area. The global products MCD64A1, GABAM and Fire_cci tended to underestimate the area burned in the region, with Fire_cci underestimating BA by 88%, while the regional product MapBiomas Fogo was the closest to the reference, underestimating by only 7%. The burned area estimated by the method proposed in this work (337.5 km2) was 12% higher than the reference and showed a small difference in relation to the MapBiomas Fogo product (18% more BA). These differences can be explained by the different datasets and methods used to detect burned areas. The adoption of global products in regional studies can be critical in underestimating the total area burned in sensitive regions. Our study highlights the need to develop approaches aimed at improving the accuracy of current global products, and the development of regional burned area products may be more suitable for this purpose. Our proposed approach based on WFI data cubes has shown high potential for generating more accurate regional burned area maps, which can refine BA estimates in the Amazon.

Diverse spatiotemporal patterns of vapor pressure deficit and soil moisture across China

Study regionChina and the different climatic zones. Study focusVapor pressure deficit (VPD) and soil moisture (SM) are vital for the land-atmosphere hydrological cycle and vegetation growth. Understanding the spatiotemporal variations of VPD and SM is essential for exploring vegetation dynamics and ecosystem changes. However, our current understanding of the simultaneous variations of VPD and SM within specific regions remains limited. This study utilized Empirical Orthogonal Function (EOF) methods to analyze the spatiotemporal variability of VPD, surface SM (SMsurf), and root-zone SM (SMroot), respectively. We then investigated the synchronous and asynchronous variations of VPD and SM and examined their relationships with climatic factors. New hydrologic insights for the regionFrom 1980–2020, VPD exhibited a significant upward trend across China and in various climate zones, indicating an increase in atmospheric dryness. However, the trends of SMsurf and SMroot showed a slight upward trend across China but divergent patterns in different climate zones. In summary, approximately 43% of China experiences a significant simultaneous increase in both VPD and SM, mainly in semi-arid and arid regions. Conversely, about 4% of China shows contrasting changes in VPD and SM, primarily in humid tropical and subtropical regions. These findings enhance our understanding of VPD and SM patterns in various climates, emphasizing the significance of soil drought in humid and semi-humid regions.

Land suitability analysis for turmeric crop for humid tropical Kerala, India, under current and future climate scenarios using advanced geospatial techniques.

Turmeric cultivation primarily thrives in India, followed by Bangladesh, Cambodia, Thailand, China, Malaysia, Indonesia and the Philippines. India leads globally in both area and production of turmeric. Despite this, there is a recognized gap in research regarding the impact of climate change on site suitability of turmeric. The primary objective of the present study was to evaluate both the present and future suitability of turmeric cultivation within the humid tropical region of Kerala, India, by employing advanced geospatial techniques. The research utilized meteorological data from the Indian Meteorological Department for the period of 1986-2020 as historical data and projected future data from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Four climatic scenarios of shared socioeconomic pathway (SSP) from the Intergovernmental Panel on Climate Change AR6 model of MIROC6 for the year 2050 (SSP 1-2.6, SSP 2-4.5, SSP 3-7.0 and SSP 5-8.5) were used. The results showed that suitable area for turmeric cultivation is declining in future scenario and this decline can be primarily attributed to fluctuations in temperature and an anticipated increase in rainfall in the year 2050. Notable changes in the spatial distribution of suitable areas over time were observed through the application of geographic information system (GIS) techniques. Importantly, as per the suitability criteria provided by ICAR-National Bureau of Soil Survey and Land Use Planning (ICAR-NBSS & LUP), all the districts in Kerala exhibited moderately suitable conditions for turmeric cultivation. With the GIS tools, the study identified highly suitable, moderately suitable, marginally suitable and not suitable areas of turmeric cultivation in Kerala. Presently 28% of area falls under highly suitable, 41% of area falls under moderately suitable and 11% falls under not suitable for turmeric cultivation. However, considering the projected scenarios for 2050 under the SSP framework, there will be a significant decrease in highly suitable area by 19% under SSP 5-8.5. This reduction in area will have an impact on the productivity of the crop as a result of changes in temperature and rainfall patterns. The outcome of the present research suggests that the state of Kerala needs to implement suitable climate change adaptation and management strategies for sustaining the turmeric cultivation. Additionally, the present study includes a discussion on potential management strategies to address the challenges posed by changing climatic conditions for optimizing turmeric production in the region. © 2024 Society of Chemical Industry.

Heat tolerance of goats to increased daily maximum temperature and low salinity of drinking water in tropical humid regions.

The daily maximum temperature and seawater level continuously increase as global warming continues. We examined the adaptability and production performance of heat-stressed goats with a supply of low-saline drinking water. Twelve Kacang and Kacang Etawah cross goats were exposed to two climatic conditions (control, 25°C to 33°C, 83% relative humidity [RH], temperature humidity index [THI]: 76 to 86; and hot environment, 26°C to 39°C, 81% RH, THI: 77 to 94) and two salt levels in drinking water (0% and 0.4% NaCl). The experimental design was a Latin Square (4×4) with four treatments and four periods (28 days each). Temperature of the rectal, skin, and udder, and respiration rate rose, reached a maximum level on the first day of heat exposures, and then recovered. Plasma sodium rose at 0.4% NaCl level, while the hot environment and salinity treatments increased the drinking water to dry matter (DM) intake ratio. Water excretion was elevated in the hot environment but lowered by the increase in salinity. Total lying time increased, whereas change position frequency decreased in the hot condition. Lying and ruminating and total ruminating time increased and explained the enhanced DM digestibility in the hot conditions. The goats exhibited a high level of plasma sodium as salinity increased, and they demonstrated physiological and behavioral alterations while maintaining their production performances under increasing daily maximum temperatures.

Climate variability impacts on methane recovery in a municipal solid waste landfill: A case study in a humid tropical climate region

Climate variability impacts on methane recovery in a municipal solid waste landfill: A case study in a humid tropical climate region

Investigation of Outdoor Thermal Comfort for Campus Pedestrian Walkways in Thailand

Thermal comfort is an important subject to evaluate the quality of outdoor environments. This study investigated outdoor thermal conditions and the thermal comfort perception of pedestrians using walkways within a university campus in Thailand, located in the hot and humid tropical region. In this field study, microclimate measurements were conducted to assess the physiological equivalent temperature (PET) of walkways, and on-site questionnaire surveys (n = 400) were used to evaluate the thermal sensation votes of pedestrians in different walkway conditions. The results revealed that the neutral PET was 25.2 °C and its acceptable range was 24.6–32.0 °C. Most pedestrians accept the thermal conditions of all walkway types but at different levels of acceptability, albeit in a slightly warm sensation. Among different walkway types, the cantilever-covered walkway with sparse trees yields the closest PET to the neutral PET. The most comfortable and favorable walkway is that with a lower air temperature, less sunlight, and higher wind ventilation. The studies on the outdoor thermal comfort of pedestrian walkways could benefit urban planners and engineers in designing physical and environmental conditions of walkways as well as promoting non-motorized transport and green university campuses.