Search results

Results have been presented of investigations on the effect of the temperature change rate on the critical temperature of pitting corrosion. Investigations of 316L stainless steel have been conducted by cyclic thermometry. An increase has been stated of the critical pitting temperature with increase of the temperature change rate. The dependence of the pitting critical temperature is linear in character for all investigated temperature change rates. Values of the critical temperature of pitting corrosion for stationary conditions (E−E_S=0) were obtained by using the extrapolation procedure. The critical pitting temperature obtained by extrapolation practically does not depend on the temperature change rate in the investigated range and is equal to 336.9 K (63.9°C).

The effect of humidity, temperature and temperature ramping rate on the dimensional changes of the photo‐cured stereolithography (SL) resin SL5195 was investigated. It was found that moisture absorption by the SL resin is a very slow process at ambient temperatures. Varying relative humidity (RH) between 20 and 90 per cent in the environment only produced slight changes in the sample dimensions during the time period investigated. Increasing the environment temperature caused a significant increase in the sample dimensions through thermal expansion along with accelerated moisture absorption at 50 per cent or higher RH. Increasing the temperature ramping rate reduces the moisture absorption during the thermal cycles.

This study aims to explore the link between mortality and climate change. The focus is in particular on individuals’ adaptation to temperature changes. The authors analyze the relationship between climatic change (measured by temperature rate) and mortality in 23 Organisation for Economic Co-operation and Development countries during 1970-2010.

This study performs the adaptation regression model in the level form as a dynamic panel fixed effects model. The authors use a non-linear threshold estimation approach to examine the extreme temperature changes effect on the temperature–mortality relation. More specifically, the study explores whether the large increases/decreases in temperature rates affect mortality rates more than the modest changes.

This study indicates that the temperature–mortality relation is significant in early part of the sample period (before 1990) but insignificant during the second part (after 1990). After including controlling factors, as well as nation and year fixed effects, the authors provide evidence that people do adapt to the most of the temperature-related mortalities. Also, this study provides evidence of the non-linear relationship between national temperatures and mortality rates. It is observed that only after 5 per cent increase in the annual temperature, the relation between temperature and overall mortality is significant.

Most studies cover only one specific country, hence making it difficult to generalize across countries. Therefore, the authors argue that the best estimation of the health effects of temperature change can be found by modeling the past relationships between temperature and mortality across countries for a relatively long period. To the authors’ knowledge, previous studies have not systemically tested the adaptation effect across countries.

The purpose of this paper is to investigate thermoregulation properties of different composite phase change materials (PCMs), which could be used in the high temperature environmental conditions to protect human body against the extra heat flow.

Three kinds of composite PCM samples were prepared using the selected pure PCMs, including n-hexadecane, n-octadecane and n-eicosane. The DSC experiment was performed to get the samples’ phase change temperature range and enthalpy. The simulated high temperature experiments were performed using human arms in three different high temperature conditions (40°C, 45°C, 50°C), and the skin temperature variation curves varying with time were obtained. Then a comprehensive index TGP was introduced from the curves and calculated to evaluate the thermoregulation properties of different composite PCM samples comprehensively.

Results show that the composite PCM samples could provide much help to the high temperature human body. It could decrease the skin temperature quickly in a short time and it will not cause the over-cooling phenomenon. Comparing with other two composite PCM samples, the thermoregulation properties of the n-hexadecane and n-eicosane composite PCM is the best.

Using the n-hexadecane and n-eicosane composite PCM may provide people with better protection against the high temperature conditions, which is significative for the manufacture of functional thermoregulating textiles, garments or equipments.

The purpose of this paper is to investigate the impact of temperature on residential electricity demand in the city of Greater Accra, Ghana. It is believed that the increasing trend of temperatures may significantly affect people’s lives and demand for electricity from the national grid. Given the recurrent electricity crisis in Ghana, this study will investigate both the current and future residential energy demands in the light of temperature fluctuations. This will inform future power generation using renewable energy resources mix to find a sustainable solution to the recurrent energy demand challenges in Ghana. This study will help the Government of Ghana to better understand the temperature dependence of residential energy demand, which in turn will help in developing behavioral modification programs aimed at reducing energy consumption. Monthly data for the temperature and residential electricity consumption for Greater Accra Region from January 2007 to December 2018 obtained from the Ghana Meteorological Service (GMS) and Ghana Grid Company (Gridco), respectively, are used for the analysis.

This study used monthly time series data from 2007 to 2018. Data on monthly electricity demand and temperature are obtained from the Ghana Grid Company and GMS. The theoretical framework for residential electricity consumption, the log-linear demand equation and time series regression approaches was used for this study. To demonstrate certain desirable properties and to produce good estimators in this study, an analysis technique of ordinary least squares measurement was also applied.

This study showed an impact on residential electricity requirements in the selected regions of Greater Accra owing to temperature change. The analysis suggests a substantial positive response to an increase in temperature demand for residential electricity and thus indicates a growth of the region’s demand for electricity in the future because of temperature changes. As this analysis projects, the growth in the electricity demand seems too small for concern, perhaps because of the incoherence of the mechanisms used to regulate the temperature by the residents. However, two points should be considered when drawing any conclusions even in the case of Greater Accra alone. First, the growth in the demand for electricity shown in the present study is the growth of demand due only to increasing temperatures that do not consider changes in all the other factors driving the growth of demand. The electricity demand will in the future increase beyond what is induced by temperature, due to increasing demand, population and mechanization and other socioeconomic factors. Second, power consumption understated genuine electricity demand, owing to the massive shedding of loads (Dumsor) which occurred in Ghana from 2012 to 2015 in the analysis period that also applies in the Greater Accra region. Given both of these factors, the growth in demand for electricity is set to increase in response to climate change, which draws on the authorities to prepare more critically on capacity building which loads balancing. The results also revealed that monthly total residential electricity consumption, particularly the monthly peak electricity consumption in the city of Accra is highly sensitive to temperature. Therefore, the rise in temperature under different climate change scenarios would have a high impact on residential electricity consumption. This study reveals that the monthly total residential electricity demand in Greater Accra will increase by up to 3.1%.

The research data was largely restricted to only one region in Ghana because of the inconsistencies in the data from the other regions. The only climate variable use was temperature because it was proven in the literature that it was the most dominant variable that affects electricity demand, so it was not out of place to use only this variable. The research, however, can be extended to capture the entire regions of the country if sponsorship and accurate data can be obtained.

The government as the policy and law-making authority has to play the most influential role to ensure adaptation at all levels toward the impact of climate change for residential consumers. It is the main responsibility of the government to arrange enough supports to help residential consumers adapt to climate change and try to make consumers self-sufficient by modification of certain behaviors rather than supply dependent. Government bodies need to carefully define their climate adaptation supports and incentive programs to influence residential-level consumption practices and demand management. Here, energy policies and investments need to be more strategic. The most critical problem is to identify the appropriate adaptation policies that favor the most vulnerable sectors such as the residential sector.

To evaluate both mitigation and adaptation policies, it is important to estimate the effect of climate change on energy usage around the world. Existing empirical figures, however, are concentrated in Western nations, especially the USA. To predict how electricity usage will shift in the city of Greater Accra, Ghana, the authors used regular household electricity consumption data.

The motivation for this paper and in particular the empirical analysis for Ghana is originality for the literature. This paper demonstrates an adequate understanding of the relevant literature in modern times.

The purpose of this paper is to provide a detailed analysis of the trends in temperature and rainfall over the period 1967–2016 (50 years) for the Kingdom of Saudi Arabia and estimate the effect of these climatic changes on major crop production.

To set up an empirical association between crop yields and climatic variables, the study uses a fixed effect regression framework. This approach makes it possible to capture the effects of time-invariant indicators and farmers' independent adaptation strategies in reaction to year-to-year variations in precipitation and temperature.

The study observes a significant increase in average temperature by 1.9 degrees Celsius in the last 50 years and the greatest increase is noted in the summer. However, there is no significant change in rainfall. The results indicate that a one-degree Celsius increase in temperature reduces crop yields by 7–25%. The results also indicate that rainfall has a positive effect on all the crops. But, rainfall could not offset much of the adverse effects of temperature.

Future research can focus on the analysis of the climate change impact assessment for different regions in the Kingdom of Saudi Arabia and develop a place-based policy.

The recent initiative to phase out crop production makes the Kingdom of Saudi Arabia entirely rely on imports. This may have little or no impact presently. However, in the future, it is possible that any global shocks on agriculture due to climate change or geopolitical instability will make the situation worse off. It will threaten both food and nutrition security in the Kingdom of Saudi Arabia. Therefore, it is important to study these in the present context to prepare a road map for future food, water and nutrition security.

The purpose of this paper is to assess the extent of climate change likely to be manifested in the MENA region using statistical tools as well as outputs from physics‐based General Circulation Models (GCMs).

Atmospheric temperature and precipitation primarily capture climate change features and are considered the drivers of other manifestations of climate change such as rises in sea‐level, tropical cyclone intensities, severe floods, prolonged droughts, and retreating ice. Data on atmospheric temperature and precipitation have been statistically analysed for trend, distribution and variability in this study. Long‐range prediction is then made using time series analysis. Long‐range projections have also been made by many investigators using physics‐based GCMs and the Fourth Assessment Report of IPCC provides a summary. IPCC projections are not indisputable because of some inherent limitations of GCMs. A comparative study is made between statistical predictions and IPCC projections, as well as forecasts from some GCMs specifically applied to the region, to develop a more reliable forecast scenario. Water resources projects are quite vulnerable to changes in atmospheric temperature and precipitation amounts. The various aspects of planning, design and management of water resources projects which are likely to be influenced by climate change are discussed.

There is considerable variability in atmospheric temperature and precipitation in recent observations but if the variability is filtered out and the underlying trend extrapolated it is found that there is in general an agreement between IPCC projections and statistical predictions. For rise in atmospheric temperature projections made from many GCMs applied to the region, as well as projections summarised in the Fourth Assessment Report of IPCC, appear to be good estimates to be included in design considerations. For precipitation, statistical predictions are perhaps a better choice because GCM projections are less reliable with precipitation since associated meteorological processes occur at a much smaller scale than the grid size of a GCM. For low‐lying coastal regions sea‐level rise and more frequent extreme climatic events such as tropical cyclones add to the dimensionality of design considerations especially for infrastructure design.

This paper presents a comparative study of possible climate change in the long‐term between physics‐based model projections and statistical predictions. This should provide greater insight into climate change that is expected in MENA and reduce uncertainty, thereby instilling greater confidence in water resources planners and practitioners to incorporate climate change aspects into decision making. This research is believed to be particularly helpful because of scant research work done on this part of the globe on climate change.

Climate change is a problem that concerns all of us. Despite the information produced by organizations such as the Expert Team on Climate Change Detection and Indices and the United Nations, only a few cities have been planned taking into account the climate changes indices. This paper aims to study climatic variations, how climate conditions might change in the future and how these changes will affect the activities and living conditions in cities, specifically focusing on Mexico city.

In this approach, two distinct machine learning regression models, k-Nearest Neighbors and Support Vector Regression, were used to predict variations in climate change indices within select urban areas of Mexico city. The calculated indices are based on maximum, minimum and average temperature data collected from the National Water Commission in Mexico and the Scientific Research Center of Ensenada. The methodology involves pre-processing temperature data to create a training data set for regression algorithms. It then computes predictions for each temperature parameter and ultimately assesses the performance of these algorithms based on precision metrics scores.

This paper combines a geospatial perspective with computational tools and machine learning algorithms. Among the two regression algorithms used, it was observed that k-Nearest Neighbors produced superior results, achieving an R² score of 0.99, in contrast to Support Vector Regression, which yielded an R² score of 0.74.

The full potential of machine learning algorithms has not been fully harnessed for predicting climate indices. This paper also identifies the strengths and weaknesses of each algorithm and how the generated estimations can then be considered in the decision-making process.

The purpose of this paper is to assess the inter-seasonal temperature and precipitation changes in Setif high plains region under future greenhouse gas emissions, by using four general circulation models (GCMs) output data between three time slices of twenty-first century. The objective is to show the vulnerability of the region and the strategy of adaptation to these changes.

This study investigates likely changes in seasonal temperature and precipitation over Setif high plains region (North East of Algeria) between three time slices: 2025, 2050 and 2075. The projections are based on the SRES A2 and B2 scenarios. MAGICC-SCENGEN 5.3v.2 was used as a tool for downscaling the four selected GCMs output data. The vulnerability of the region, coupled with the possible impacts climate change, stresses the need for adaptive strategies in key sectors in the region for the long term sustainable development.

The results for change in seasonal temperature indicate a general warming under the two scenarios till the year 2075.The results of GFDLCM21 and GFDLCM20 show a general reduction of spring and autumn precipitations and an increase in winter and summer. BCCRBCM2 predicts a decrease in winter, spring and summer precipitations and an increase in autumn. Climate change, as well as increases in climate variability, will alter precipitation, temperature and evaporation regimes, and will increase the vulnerability of Setif high plains to changes in hydrological cycles. Climate and weather forecasting coupled with biotechnological advances in improving crop yields and tolerances to aridity, is likely to bring significant payoffs for strategy of adaptation in the field of agricultural water management.

This work is one of the first to study inter-seasonal temperature and precipitation changes under global warming over the region, and suggest some adaptive strategies to limit the effect of these changes.

The purpose of this study was to investigate the psychological response to changes in temperature and humidity near the skin, and the psychological factors of thermal discomfort.

The experiments involved changing the temperature and humidity from a neutral to a hot-humid environment, and vice versa, every 30 min. The psychological response to temperature (which ranged from 24 to 40°C) and humidity (which ranged from 30 to 80% relative humidity) was investigated.

The sensory scores shifted according to the direction of the change in temperature and humidity. The environment seemed to be evaluated relatively, whereby the sensory perception was dependent on the prior thermal environment. The psychological response to changes in temperature and humidity near the skin tended to shift from simple situational perceptions, such as feeling hot, to stifling and uncomfortable perceptions, and finally to the perception of dullness. Examining the psychological components revealed that the uncomfortable feeling was affected by “stifling” and “sweaty” perceptions with increasing temperature, by “stifling”, “sweaty”, and “sticky” perceptions with decreasing temperature, by “stifling”, “dull”, “sticky”, and “hot” perceptions with increasing humidity, and by “sweaty”, “dull”, and “humid” perceptions with decreasing humidity.

This study identified the psychological response that accompanies changes in temperature and humidity near the skin, as well as the psychological components of discomfort associated with changes in temperature and humidity. These results provide insights into the microclimate and thermal comfort of clothing.