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• A coupled humid-mechanical-damage model was utilized. • The influence of humidity on the stability of Longyou Grottoes was investigated. • The cave roof is the most dangerous position under humidity variation. • Fissures act as shortcuts for humidity diffusion and stress generation. • Waterproof measurements contribute to the stability and durability of the grottoes. Silty sandstone grottoes are suffered climate changes. The Longyou Grottoes are typical argillaceous siltstone. This paper utilized the coupled humid-mechanical-damage model to investigate the influence of environmental humidity change on the deformation and stability of Cave 4 and Cave 5 in Longyou Grottoes. It is found that the change in environmental humidity significantly influences the stability of caves in Longyou Grottoes. The water saturation of surrounding rock changes with the increase or decrease of ambient humidity. The water swelling and dry shrinkage processes greatly affect the stress state and mechanical properties of the surrounding rock, resulting in micro-cracks which may form fractures that disturb the structural integrity and aggravate the geological hazard of weathering. The cave roof is the most dangerous position during the humidity variation. Pre-existing fissures act as shortcuts for humidity diffusion and stress generation. In turn, the fast diffusion rate and high stress cause further propagation of the fissures. Repairing pre-existing fissures and applying waterproof measurements on the inner wall of caves contributes to the stability and durability of the grottoes. This study improves the understanding of the relationship between the changes in environmental humidity and the weathering of grottoes and provides theoretical support for the subsequent disaster risk management and preservation of Longyou Grottoes. [ABSTRACT FROM AUTHOR]

• CatBoost regression model for prediction of surface chloride level. • The regression model has MAE and RMSE scores of 0.11 and 0.16 respectively. • Increase in chloride ingress with the increase in temperature and humidity. • Exposure zone has a significant effect on chloride ingress. • Temperature and humidity of RCP 2.6 and RCP 8.5 considered for analysis. This paper presents the effect of climate change on the long-term reliability of concrete structures due to chloride ingress. The impact has been demonstrated for three regions across the globe for the best and worst-case climate change scenarios. The methodology adopted here can be divided into three main steps. The first one is the development of a machine learning regression model using CatBoost for estimation of surface chloride levels, which is a function of temperature, concrete material properties, exposure conditions, and chloride levels in the seawater. The CatBoost model fitted over the experimental data has a mean absolute error (MAE) and root mean square error (RMSE) value of 0.11 and 0.16, respectively, and a high R2 value of 0.82. The second step is solving the coupled non-linear partial differential equation for temperature, humidity, and chloride ingress in concrete with time. A parametric study considering the effect of external parameters (temperature, humidity, exposure condition, and chloride levels in water) reveals the complexity and the dependencies of the chloride ingress process on external parameters. The final step involves the reliability analysis to estimate the time for chlorides to reach threshold levels at the rebar level using the numerical model. The input for the numerical model is temperature and humidity condition for different representative concentration pathways (RCP) scenarios, the material properties of concrete, and the exposure conditions. The reliability analysis shows that, for the concrete structure located in Dubai, UAE, and Cascais, Portugal, the mean time to corrosion initiation decreases due to climate change and it increases for the structure located in Tasmania, Australia. Further, the structures that are built in the future may have lower service life compared to the structures that were built in the past. Based on the study it concluded that it is necessary to consider the impact of climate change on service life to design resilient structures. [ABSTRACT FROM AUTHOR]

This paper studies the impact of climate change on the nutritional status of very young children between the ages of 0–3 years by using weather data from the last half century merged with rich information on child, mother, and household characteristics in rural coastal Bangladesh. We evaluate the health consequences of rising temperature and relative humidity and varying rainfall jointly employing alternate functional forms. Leveraging models that control for annual trends and location-specific seasonality, and that allow the impacts of temperature to vary non-parametrically while rainfall and humidity have flexible non-linear forms, we find that temperatures that exceed 25 °C (the "comfortable" benchmark) in the month of birth exert negative effects on children's nutritional status as measured by mid upper arm circumference. Humidity has a positive impact which persists when child, mother and household controls are included. We find that exposure to changing climate in utero also matters. Explanations for these results include consequences of weather fluctuations on the extent of pasture, cropland, and rainfed lands planted with rice and other crops, and on mother's age at first marriage. Our results underline that climate change has real consequences for the health of very young populations in vulnerable areas. • We study the impact of climate change over 50 years on the nutritional status of very young children. • We evaluate the consequences of temperature, relative humidity, and rainfall jointly. • Excess heat at birth has negative effects while humidity has positive effects on children's MUAC. • The impact of humidity persists when child, mother and household controls are included. • Mechanisms include changes in cropland, rainfed rice lands, and in mother's age at first marriage. [ABSTRACT FROM AUTHOR]

A Dehumidifier's performance mainly depends upon the climatic conditions of the area it is placed in. Also, the geographical location of the area influences its design. The current paper focuses on constructing a multistage dynamic dehumidifier where the packing has a reciprocating motion inside the duct. It is built for areas that has weather conditions similar to that of the United Arab Emirates. Packing is allowed to dip in the calcium chloride desiccant tank and the air interacts with soaked pads in the duct in the counter flow direction. Experiments and predictions are carried out by changing the climatic conditions and packing thickness. A mathematical model is constructed by adopting the heat and mass governing equations and validated by comparing with the experimental results. Performance parameters such as temperature changes, specific humidity changes, moisture effectiveness, moisture removal rate, and mass transfer coefficient are predicted. Results indicates that with an increase in the inlet dry bulb temperature and relative humidity, there is an increase in the dehumidification performance. Experimental and theoretical results agree with each other and are found to be within 9% deviation range. Performance parameters improved until the packing thickness was increased to 20 cm. However, with further increase in the pad thickness, the performance deteriorated. The system gave maximum moisture effectiveness, and the moisture removal rate is equal to 0.75 and 4.89 g/s. Experimental results revealed that climatic variations of change in relative humidity influences dehumidification performance more than the climatic changes involved with only temperature values. Air quality check revealed that air released to the working space is of high quality with zero carryover. • Design and fabrication of a novel reciprocating multistage dynamic dehumidification experimental test rig. • Construction of the theoretical model for varying climatic conditions. • Prediction of the system performance for varied operating and pad thicknesses. • Multistage packing system gave better results than a single stage. • A maximum deviation of 10% is observed between theoretical and experimental results. [ABSTRACT FROM AUTHOR]

Bioenergy is considered a promising alternative to achieve carbon neutrality and emission reduction. There is a debate over the role of bioenergy in climate change mitigation because of carbon emissions from the production and utilization of biofuels. Recently, studies on emissions of biogenic volatile organic compounds (BVOCs) have substantially increased as they have a significant impact on human health and climate change due to large emissions and high reactivity. A scientometric analysis of 2895 journal papers during 1991 and 2020 related to BVOC emissions from the Web of Science Core Collection was conducted by CiteSpace and Carrot2. Results showed that three main knowledge domains were BVOC emissions and drivers, BVOCs and their oxidation products in biosphere-atmosphere exchange, and soil BVOCs in plant-microbe interactions during the period under study. Generally, the relationships between plant BVOC emissions and environmental variables (e.g., temperature, drought, light solar radiation, humidity, availability of nutrients, carbon dioxide, ozone, etc.) can be investigated by measurement techniques (i.e., chamber) or models (i.e., Model of Emissions of Gases and Aerosols from Nature). Soils could work as both the sink and source of BVOCs through various processes that are affected by soil temperatures, pH, organic matter, and moisture. Anthropogenic activities might affect the emission of BVOCs and promote the formation of BVOC-derived pollutants (e.g., ozone, particles, etc.). Incorporating BVOC emissions and their relationships with pollutants, biomass, and energy into environmental management and decision-making is a promising direction. [Display omitted] • A scientometric analysis was conducted on the research evolution of BVOC emissions. • Ten clusters generated by CiteSpace were logically reclassified into three hotspots. • MEGAN is the most frequently empirical model for BVOC emission assessment. • BVOC-derived pollutants like SOA are likely affected by anthropogenic activities. • Soils in terrestrial ecosystems can act as both the source and sink of BVOCs. [ABSTRACT FROM AUTHOR]