Climatic Areas Research Articles

Performance enhancement of air conditioner in hot climate by condenser cooling with cool air generated by direct evaporative cooling

This research studied the direct evaporative cooling technique for generating cool air in hot–dry and hot–humid climates. For direct evaporative cooling, three parameters affected the air temperature: feedwater temperature, wet-bulb temperature, and mass ratio of feedwater to circulating air were investigated. When the feedwater temperature was lower than the wet-bulb temperature, in a hot-humid climate, an increase in the mass ratio of feedwater to the circulating air decreased the outlet air temperature. Conversely, if the feedwater temperature was higher than the wet-bulb temperature, in a hot-dry climate, a decrease in the mass ratio was needed to reduce the air temperature. The cooled air obtained could be used for condenser cooling of air-conditioner for performance enhancement. According to a 1 TR air conditioner simulation, lower feedwater temperature resulted in higher energy efficiency ratio. High mass ratio, thus, was recommended in the hot-humid climate area whereas less mass ratio was preferable for the hot-dry climate area. The energy efficiency ratios of the unit with direct evaporative cooling for hot–dry and hot–humid climates ranged from 3.40 to 4.22 and 3.30 to 3.94, respectively, compared to 3.01 for the normal unit. The payback period for the unit with direct evaporative cooling in case of Chiang Mai (hot-humid climate) was around 2.87 year.

Water footprints of irrigated crop production and meteorological driving factors at multiple temporal scales

The water footprint (WF) of crop production indicates the water consumption for crop growth in a specific area over a certain time, enabling comprehensive water use efficiency assessments to be achieved for different types of water in an irrigation district. Daily and monthly blue (irrigation water) and green (rainfall) water resources are unevenly distributed in monsoon climate areas. However, the intra-annual evolution of the WF of crop production for a monsoon irrigation district is lacking. In the current study, maize and wheat production in the Baojixia Irrigation District (BID) of Shaanxi in China selected as the case study for the period 2008–2017, where the WF of crop production was analyzed based on a regional distributed hydrological model and the associated meteorological driving factors on daily, monthly, and yearly scales were identified. Results reveal that the method of WF of crop production established in the study can be applied to hydrological simulation of irrigated areas without drainage system. The blue WFs of maize and wheat production accounted for 34% and 36% of the irrigation water supplies, respectively. On a yearly scale, precipitation had the greatest impact on the green and blue WFs of maize, while sunshine hours and temperature had the greatest impact on those of wheat, respectively. On daily and monthly scales, different meteorological factors played key roles in the WF of crop production in different typical years. The time scale effect existed in the impact of meteorological driving factors on the WF of crop production, reaching its maximum on a monthly scale. Both water shortages and water waste coexist in BID. The irrigated area should rationally allocate blue water and effectively utilize green water resource to improve crop yield. Meanwhile, the time scale effect in the WF assessment of crop production and driving factors cannot be neglected. The irrigation strategy should be adjusted to cope with the impact of meteorological conditions according to the results and actual situation.

Regulation mechanism of biotic and abiotic factors on the nitrogen mineralization of forest soil

Global warming, a global ecological and environmental problem, attributes to the rapidly increased emission of greenhouse gases of which N2O ranks the third in the atmosphere after CO2 and CH4. On the one hand, nitrification and denitrification often take place in the process of forest soil nitrogen mineralization where N2O is produced from soils, thus, increasing the atmospheric N2O concentration. On the other hand, forest soil nitrogen mineralization, as a complex ecological process, is regulated by the interactions of biotic and abiotic environmental factors. Therefore, the investigation of the influencing factors and the regulatory mechanism of forest soil nitrogen mineralization, is conducive to the promotion of people’s understanding of the nitrogen cycling process of forest soils, thus playing an important role in the study of global change. However, previous studies on the nitrogen mineralization of forest soils were mainly limited to the effect of single factors with the lack of comparable research results, the cooperative regulation research on multiple factors (e.g., microbial-animal interaction), the study of forest soil nitrogen mineralization characteristics and impact mechanism under different circumstances of climate and land-use, and the research on the response of nitrogen mineralization to global climate change. Aimed to provide theoretical support for better understanding the spatiotemporal patterns of forest soil nitrogen mineralization in different climatic areas and their effects on global climate change, this study has conducted an examination of the spatiotemporal variations and the influencing factors of forest soil nitrogen mineralization, and provided an explanation of the characteristics and mechanism of the effect of abiotic (e.g., soil physicochemical environments) and biotic factors (e.g., forest vegetation cover, forest litter, and soil microorganisms and fauna) on forest soil nitrogen mineralization. It is advised that researches on soil nitrogen mineralization should, with unified and efficient methods, be focused on the influencing mechanism of the multi-factor coupling of soil microorganisms-fauna-environmental factors on forest soil nitrogen mineralization, the regulation mechanism of soil nitrogen mineralization under different climate and land-use circumstances, as well as the processes and mechanisms of forest soil nitrogen mineralization under the background of global change. [Ch, 69 ref.]

Lateral Constrained Inversion of DC-Resistivity Data Observed at the Area North of Tenth of Ramadan City, Egypt for Groundwater Exploration

In the arid climate area north of Tenth of Ramadan City, southeast of the Nile Delta, Egypt, it is necessary to search for additional water resources for sustainable developments such as agricultural and industrial activities. Thirty two vertical electrical soundings (VES) of a electrical resistivity (DC) survey were carried out along four main profiles by using the Schlumberger array with electrode distances (AB/2) up to 500 m, to explore the shallow Pleistocene groundwater aquifer. The collected data was interpreted by a one-dimensional laterally constrained inversion (1D-LCI) and two-dimensional inversion algorithms to derive a best fit layered-earth resistivity model. The derived resistivity sections are geologically well interpreted based on information taken from the available water boreholes (P2-Well and P3-Well). The lateral constraints are part of the inversion where all data sets are inverted simultaneously, and consequently the output models are balanced between the constraints and the data-model fit. The 1D-LCI offers good analysis of the model parameters, which was successfully used to characterize a zone of groundwater aquifer, as it produces a laterally smooth model with sharp layer boundaries. The 1D-LCI inversion results show that the study area is subdivided into five geo-electrical layers of varied resistivity and thickness. In particular, the resistivity values of the last layer range between 9.3 and 110 Ωm representing the existing shallow Pleistocene aquifer located at depths between 134.5 and 118.4 m. Such results are tied and confirmed well with the results of the 2D inversion of the DC data. It reveals three interpreted geo-electric layers along the four profiles and shows that the area is affected by some normal faults striking nearly in the E–W direction. The very low resistivities of the groundwater aquifer beneath the agricultural part of the survey area probably indicates contamination due to the possible effect of irrigation operated in the cultivated lowlands. The results obtained could help the stakeholder to find additional information about the ground water aquifers in the newly reclaimed arid area and possible locations of new sites for drilling new water wells as additional water resources.

A case in subtropical climate city: Assessing the bioretention hydraulic performance on storm in response to poor permeability soil

Bioretention has been widely used in China for the purpose of sponge city construction. In subtropical climate areas, the performance of bioretention cell under condition of low infiltration underlying soil and heavy storms is still poorly understood. This study aimed to assess the effects of low infiltration underlying soil and precipitation characteristics on the hydraulic performance of a bioretention cell using the Storm Water Management Model (SWMM). The hydraulic performance of a bioretention cell were investigated under a Typical year rainfall event (P(total) (total precipitation) = 1299.2 mm) and seven heavy storms (i.e., Ptotal range from 53.1 mm to 287.3 mm), at different SF(i) (seepage rates of the underlying soil) (i.e., range from 2.5 mm/h to 15 mm/h). Then, sensitivity of the optimal design to the different design parameters, including the hydraulic conductivity of soil medium layer and the berm height of surface layer, was examined. The results show that the increase in SF(i) was effective in increasing the ARVR(i) (annual runoff volume reduction) and RVR(i) (runoff volume reduction), while little effective in increasing PFR(i) (peak flow reduction). Moreover, the ARVR(i) could meet the designed goal of 70% when the SF(i) was more than 7.5 mm/h. For RVR(i), the key variable of precipitation characteristic changes from Ptotal to P4h(max) (maximum precipitation in 4 h) as SF(i) increases, while P4h(max) remains as the key variable for PFR(i) all the time. The sensitivity studies demonstrate that the hydraulic conductivity is more effective in increasing PFR(i) than the berm height. For the bioretention cell under condition of low infiltration underlying soil and heavy storms, in order to simultaneously achieve expected reduction goal of both peak flow and runoff volume, and make the best comprehensive performance of bioretention cell, it requires not only a maintenance action to increase the hydraulic conductivity of soil medium layer, but also a drain pipe to be added in the storage layer, and meanwhile other LID practices should be combined.

On the optimization of building energy, material, and economic management using soft computing

This paper provides energy and economic analysis relevant to the cooling season in building enclosures. For a whole year, an Energy Plus thermal transfer model has been created and simulated. Simulations were made from the cities in five different areas of climate in China using weather data files. Energy savings were done from natural cold (e.g., outdoor air), and electricity reductions were performed from air-conditioning electricity devices. This research has investigated the relationship between the cost and building energy while finding a strong and positive correlation. This study has used the Artificial Intelligence (AI) model as Extreme Learning Machine (ELM) and Teaching Learning Based Optimization (TLBO) to calculate the accurate measurement. Three regression models as Pearson correlation coefficient (r), root mean square (RMSE), and coefficient of determination (R2) was used to calculate the results. Following the results of (R2) and RMSE, ELM has shown its higher performance in predicting the strength, energy, and cost of building materials. Based on the simulation results, for office buildings situated in cold areas, the energy savings resulting from phase change materials (PCM) are more prevalent. The test findings demonstrate that the energy savings from PCM applications for the cool area and hot summers and cold winter office buildings were increased. Simple payback time indicated that PCMBs in inhabited buildings could be used costeffectively in a mild temperature environment.

Environmental isotope concepts of precipitation and surface water and groundwater in the Central Andes: A review

A preliminary review of existing information on the isotopic composition of oxygen (δ18O) and hydrogen (δ2H) of the water molecule in the northern sector of the Chilean Andes, between 17°30´ S and 25°30´ S, is presented. During the austral summer, the winds from the east favour the arrival of Atlantic humidity, dominantly through the Amazonas Basin, which produces more than the 80% of the annual precipitation. The Central Andes cordillera acts as a barrier to the wet air from the south-eastern Atlantic and in the Chilean northern coast produces the driest climatic area of the Earth. What is known about isotopic hydrology is briefly reviewed. This knowledge has allowed answers to questions such as the origin of precipitation, the possible links between basins, and the detection of processes that modify water isotopy, such as evaporation and geothermal effects. It has been observed in the surface water, groundwater and rainfall of northern Chile, that there is an enrichment in heavy isotopes in the north-south direction, from the region of Arica and Parinacota to the Antofagasta region. Continuing the research on precipitation and surface and groundwater isotopy is essential to achieve sustainable management of water resources and to understand current climate conditions and the past and future variations.

The effect of ambient temperature on blood pressure of patients undergoing hemodialysis in the Pantanal-Brazil

The objective was to analyze the association of changes in pre-dialysis systolic and diastolic blood pressure with air temperature in a municipality in the Brazilian Pantanal, a tropical climate area. Longitudinal panel study, with analysis of mixed effects models of 133 hemodialysis patients in the city of Cáceres-Mato Grosso in 2014. Air temperature showed an inverse association with pre-dialysis systolic and diastolic blood pressure. With each increase of 1 °C in the mean air temperature, the pre-dialysis systolic blood pressure decreases -0.730mmHg (p ≤ 0.000) and the pre-dialysis diastolic blood pressure decreases -0.280mmHg (p ≤ 0.000). The estimated effect was greater for systolic blood pressure, but both pre-dialysis blood pressure measures are reduced with an increase in lag (up to two days), even when adjusted for relative air humidity. Air temperature is determinant for changes in pre-dialysis systolic and diastolic blood pressure in hemodialysis patients. The temperature effect was greater for systolic blood pressure than for diastolic blood pressure.

A robust integrated Bayesian multi-model uncertainty estimation framework (IBMUEF) for quantifying the uncertainty of hybrid meta-heuristic in global horizontal irradiation predictions

Accurate and stable prediction of global horizontal irradiation (GHI) is vital for managing energy systems, irrigation planning, and also decision making for future investment. Existing artificial intelligence (AI) models for prediction GHI generally have high performance, but suffer from instability and uncertainty, especially in different climate areas. Therefore, the aim of this study is to implement an ensemble strategy based on the Integrated Bayesian Multi-model Uncertainty Estimation Framework (IBMUEF) for simultaneous input parameters and model structure uncertainty quantification in AIs. In this study, robust prediction techniques of meta-heuristic optimization algorithms (Multiverse optimization (MVO), Sine-cosine algorithm (SCA), Salp swarm algorithm (SSA)) are hybridized with machine learning models of Adaptive Neuro Fuzzy Inference System (ANFIS) and Extreme Learning Machine (ELM) for GHI predictions. The ensemble IBMUEF combines the advantages of developed models to improve the predicting performance. Comparing results of IBMUEF against the developed individual models show the predictive skill and strength of IBMUEF for four meteorological stations in two climate areas (arid and semi-arid) located in Iran. The results of developed individual models showed that all six hybrid models (ANFIS-MVO, ANFIS-SCA, ANFIS-SSA, ELM-MVO, ELM-SCA, ELM-SSA) performed well in four stations. The ranking of models carried out by Multi-Criteria Decision-Making (MCDM) method of Weighted Aggregated Sum Product Assessment (WASPAS). The ANFIS-MVO model with the highest rank was selected as the best model that R2, RMSE, MAE, and NSE values were ranged from 0.9929 to 0.9989, from 16.23 to 54.78 Wh/m2/day, from 4.21 to 10.39 Wh/m2/day, and from 0.993 to 0.999, respectively. The accuracy of ensemble IBMUEF based on the average RMSE was 23.7% and 32.2% better than the ANFIS-MVO model in arid and semi-arid climates, respectively. Evaluation results related to input parameters and model structure uncertainties proved the superiority of ensemble IBMUEF over the individual models, while 95% confidence interval covered almost 96% of observation data. The results highlighted the significance of combining individual models in IBMUEF for more accurate prediction of GHI with a suitable level of uncertainty. In conclusion, simultaneous considering of model input uncertainty and model parameter uncertainty is crucial for obtaining realistic and certain GHI predictions and correct quantification of the uncertainty bounds.

Free and Conjugated Phenolic Profiles and Antioxidant Activity in Quinoa Seeds and Their Relationship with Genotype and Environment.

The nutraceutical interest in quinoa (Chenopodium quinoa Willd.) seeds is associated with the presence of macronutrients, micronutrients, minerals, vitamins, and polyphenols. In particular, polyphenols contribute to the health-promoting effects of this food crop, and their levels are influenced by environmental conditions. Production of quinoa is recently being explored in temperate climate areas, including Italy. The aim of this research was to assess the profile of bioactive compounds in seeds of two quinoa varieties, Regalona-Baer and Titicaca, grown in northern Italy, compared to that of seeds of those varieties grown in Chile and Denmark, respectively. High-performance liquid chromatography-diode array detector (HPLC-DAD) analysis of phenolic acid and flavonoid profiles, both in their free and soluble conjugated forms, showed that the main differences between Regalona grown in Chile and Italy were for the free vanillic acid and daidzein contents, while the two Titicaca samples mainly differed in quercetin derivative levels. The total phenolic index was comparable in Titicaca and Regalona, and only a slight decrease in this parameter was found in seeds of the two varieties grown in Italy. The in vitro antioxidant activity of seed extracts, evaluated by means of three different assays, indicated that it correlated with flavonol (quercetin derivative) levels. In conclusion, the results indicate that, although environmental conditions alter the polyphenolic profile and biological activities, it is possible to grow good-quality quinoa in northern Italy.

Ground penetrating radar for soil-water measurement in a semi-arid climate in the Orkhon River basin, central Mongolia

In this paper, we present a velocity analysis technique using ground-penetrating radar (GPR) data to estimate near-surface soil-water content affected by topography and solar radiation on a mountain peak, mountain mid-slope, and alluvial plain sites in a semi-arid climate area in central Asia. By making precise measurements of reflected EM wave velocity, the water content in the near-surface soil was determined. The GPR experiments at several frequencies were carried out in two sequential phases (comprising common-offset and multi-offset methods) to obtain the soil-water content and illustrate the subsurface structure. We then tried to determine the relationship between near-surface moisture content and permafrost thawing. Therefore, we used several different methods including time-domain reflectometry and a resistivity survey. We also confirmed via the GPR data that vegetation cover indicates soil-water content in the near-surface soil. The results evaluated in this study provide meaningful information about soil water as well as subsurface structures. The GPR data acquired at the survey sites indicated a large range of near-surface water content due to the topography of the survey lines.

Assessing the Impacts of Climate Variations on the Potato Production in Bangladesh: A Supply and Demand Model Approach

From the perspective of nutritional security, we investigated the influence of climate change on potato production in Bangladesh using a supply and demand model by considering the potato as an important non-cereal food crop. To provide an outlook on the variation in potato supplies and market prices under changing climatic factors (temperature, rainfall, and solar-radiation), the yield, area, import, and demand functions were assessed using district-level time-series data of Bangladesh (1988–2013), disaggregated into seven climatic zones. Results suggest that temperatures above or below the optimal range (18–22 °C) lowered yields. Little rainfall and low solar radiation hinder potato cultivation areas during the potato maturity stage. During the simulated period, the annual production was projected to rise from 88 to 111 million metric tons (MT), with an equilibrium farm price of 155 to 215 US dollars MT−1. Between 2014 and 2030, the nation’s per-capita potato intake is expected to increase from 49 to 55 kg year−1 because of changing dietary patterns. According to the estimated equilibrator, scenario simulations that incorporated various dimensions of Intergovernmental Panel on Climate Change (IPCC) scenarios indicate that potato production and consumption can increase in the future.

Relative influence of stand and site factors on aboveground live-tree carbon sequestration and mortality in managed and unmanaged forests

We compiled data from several independent, long-term silvicultural studies on USDA Forest Service experimental forests across a latitudinal gradient in the northeastern and north-central U.S.A. to evaluate factors influencing aboveground live-tree carbon sequestration and mortality. Data represent five sites with more than 70,000 repeated tree records spanning eight decades, five ecoregions, and a range of stand conditions. We used these data to test the relative influence of factors such as climate, treatment history (uneven-aged or no management), species composition, and stand structural conditions on aboveground live-tree carbon sequestration and mortality in repeatedly measured trees. Relative to no management, we found that uneven-aged management tended to have a positive effect on carbon sequestration at low stocking levels and in areas of favorable climate (expressed as a combination of growing season precipitation and annual growing degree days > 5 °C). In addition, losses of carbon from the aboveground live-tree pool due to tree mortality were lower in managed than unmanaged stands. These findings suggest that there may be conditions at which rate of sequestration in living trees is higher in stands managed with uneven-aged silviculture than in unmanaged stands, and that this benefit is greatest where climate is favorable.

Sub-Cloud Secondary Evaporation in Precipitation Stable Isotopes Based on the Stewart Model in Yangtze River Basin

The stable isotopes (2H, 18O) of precipitation change due to the sub-cloud secondary evaporation during raindrop fall. The study of the temporal and spatial variation of sub-cloud secondary evaporation and its causes by using hydrogen and oxygen stable isotopes is of great significance to the study of the regional water cycle process. Based on the hourly meteorological data of 648 meteorological stations in 17 provinces (cities) of the Yangtze River Basin from March 2018 to February 2019, we analyzed the temporal and spatial characteristics of precipitation excess deuterium variation (Δd) in the region, based on the improved Stewart model. We discuss the various influence factors under different magnitude Δd value change and the impact factor of each partition sub-cloud secondary evaporation influence of the difference. The results show the following: (1) In terms of hourly variation, the sub-cloud secondary evaporation in the daytime is stronger than that at night. In terms of monthly variation, different regions of the study area have different characteristics; that is, the effect of sub-cloud secondary evaporation is more significant in summer and autumn in the northern subtropics and south temperate zones, and in spring and summer in the mid-subtropics and plateau climate zones. (2) There were significant spatial differences in the study area in different seasons, and the effect of sub-cloud secondary evaporation was the most significant in the plateau climate area throughout the year. (3) When the rainfall is 0–5 mm, the temperature is >30 °C, the vapor pressure is <3 hPa, the relative humidity is 50–60%, and the raindrop diameter is 0.5–1 mm; the sub-cloud secondary evaporation effect is the most obvious.

Evaluation of the Olweus Bullying Prevention Program in US Urban Middle Schools Using a Multiple Baseline Experimental Design.

We evaluated the impact of the Olweus Bullying Prevention Program (OBPP) in an 8-year study in urban middle schools that served primarily African American students living in low-income areas. Participants included 2755 students and 242 teachers. We evaluated the OBPP with a multiple-baseline experimental design where the order and intervention start time was randomly assigned for each school. We assessed the frequency of bullying behaviors and experiences including physical, relational, and verbal aggression and victimization using teacher ratings of student behavior and student-reported data, as well as cyber aggression and victimization and school climate measures using student-reported data. For teacher ratings of student behavior, we found significant main effects across all subtypes of aggression and victimization, with some variability in the timing of effects. The pattern of findings showed delayed intervention effects for boys and a weaker impact of the OBPP on 6th graders. We found main effects for student-reported cyber aggression and victimization, relational aggression, and a composite of physical, verbal, and relational victimization. Decreases in victimization emerged in the 1st or 2nd year of intervention, and reductions in aggression emerged during the 3rd year. Across all findings, once intervention effects emerged, they remained significant in subsequent intervention years. The OBPP resulted in significant decreases in student- and teacher-reported aggression and victimization. However, this intervention had limited impact on general areas of school climate including teacher support, positive peer interactions, and school safety. Overall, the findings offer important prevention and research implications.

Assessment of potential risks induced by increasing extreme precipitation under climate change

A warmer climate has caused more extreme climate events like the heatwave or extreme precipitation, which has led to a large number of lives and economic losses. In this study, we adopt historical daily precipitation from rainfall estimates on a gridded network (REGEN) and future daily projections from 10 general circulation models (GCMs) to analyze the potential risks of extreme precipitation due to changes in the magnitude and frequency. We calculate the 10-year and 100-year return levels by fitting the partial duration series (PDS) data with the generalized Pareto (GP) distribution. The potential risks are quantified in two terms: by the ratio of the magnitude to the threshold and by the exceedance frequency comparing to the theoretical value. The results show that in the future, about 46% of the world may suffer from mid or high risk of change in extreme precipitation. Most regions show higher risk due to the increased frequency of extreme precipitation events under the RCP8.5 scenario. The high risk of humid regions mainly appears under the RCP8.5 scenario and is mainly driven by frequency change, while that of arid regions appears under both the scenarios and is driven by both the frequency and magnitude change. The tropical rainforest climate areas of South America (SA (N)), the tropical savanna or tropical wet monsoon and tropical dry areas of South Asia (SA), and the subarctic climate areas of Northern Asia (NOA) may suffer more risks from the view of both magnitude and frequency changes of extreme precipitation.

Social Dimensions of Projected Climate Change Impacts on Ecosystem Services in the Coastal-Rural Area of Nemunas River Reaches and Curonian Lagoon (Lithuania)

The capacity of ecosystems to provide ecosystem services (hereinafter referred to as ES) depends on the state of their structure, processes, and functions, which is determined by interactions with other systems. These interactions are complex and take place in different climatic areas, and have different impacts on ecosystems and the use of ES. As the most sensitive part of the Lithuanian shore zone to climate change is the seaside zone or the coastal zone, which includes the Curonian Lagoon and the sea coast, the said area was therefore chosen for research. The case study examined those ES that were specific to the study area, without attempting to account for absolutely all ES. With an emphasis on the representation of different perspectives (in the process of assessing and preserving the potential of ES), the empirical study involved representatives of different (public and private) sectors. The public sector was represented by elders and eldership employees, the private sector by farmers and businesspeople. Respondents were selected purposefully to reflect the entire existing totality of the existing area. The evaluation of the obtained theoretical and practical results of the research identified the potential of the existing area ecosystem services and perspectives for the implementation of services by assessing their use according to respondents’ opinions, regional climate change, and national scale in EU environmental policy.

Experimental Investigations of a Solar Water Treatment System for Remote Desert Areas of Pakistan

Pakistan is among the countries that have already crossed the water scarcity line, and the situation is worsened due to the recent pandemic. This is because the major budget of the country is shifted to primary healthcare activities from other development projects that included water treatment and transportation infrastructure. Consequently, water-borne diseases have increased drastically in the past few months. Therefore, there is a dire need to address this issue on a priority basis to ameliorate the worsening situation. One possible solution is to shift the focus/load from mega-projects that require a plethora of resources, money, and time to small domestic-scale systems for water treatment. For this purpose, domestic-scale solar stills are designed, fabricated, and tested in one of the harshest climatic condition areas of Pakistan, Rahim Yar Khan. A comprehensive overview of the regional climatology, including wind speed, solar potential, and ambient temperature is presented for the whole year. The analysis shows that the proposed system can adequately resolve the drinking water problems of deprived areas of Pakistan. The average water productivity of 1.5 L/d/m2 is achieved with a total investment of PKR 3000 (<$20). This real site testing data will serve as a guideline for similar system design in other arid areas globally.

A new approach of deep neural computing for spatial prediction of wildfire danger at tropical climate areas

Wildfire is an environmental hazard that has both local and global effects, causing economic losses and various severe environmental problems. Due to the adverse effects of climate changes and anthropogenic activities, wildfire is anticipated more frequent and extreme; therefore, new and more efficient tools for forest fire prevention and control are essential. This study proposes a new deep neural computing approach for spatial prediction of wildfire in a tropical climate area. For this purpose, deep neural computing (Deep-NC) with a structure of 3 hidden layers was proposed. The Rectified Linear Unit (ReLU) activation function was adopted to infer wildfire dangers from the input factors. To search and optimize the weights of the model, Stochastic Gradient Descent (SGD), Root Mean Square Propagation (RMSProp), Adaptive Moment Estimation (Adam), and Adadelta optimizers were employed. Also, this study has established a Geographic Information System (GIS) database for Gia Lai province (Vietnam) to train and verify the newly developed deep computing approach. The twelve ignition factors, namely, slope, aspect, elevation, curvature, land use, NVDI, NDWI, NDMI, temperature, wind speed, relative humidity, and rainfall, have been used to characterize the study area with respect to forest fire susceptibility. According to experimental results, the Adam optimized Deep-NC model delivered the highest predictive accuracy (AUC = 0.894, Kappa = 0.63). Accordingly, this model has been employed to establish a forest fire susceptibility map for Gia Lai province. The proposed Deep-NC model and the newly constructed forest fire susceptibility map can help local authorities in land use planning and hazard mitigation/prevention.

Overheating assessment in flats with glazed balconies in warm-summer humid continental climate

Greenhouse systems in the form of glazed balconies may be accomplished both in the newly designed buildings and in the existing ones, raising their energy standard in a quick and inexpensive way. However, basic parameters influencing the efficiency of the systems are often chosen intuitively, not allowing to fully benefit from the sunspaces or causing overheating of the rooms and discomfort for the users. These issues are common drawbacks of passive systems and may become especially important in the aspect of anthropogenic climate changes, including temperature rise and summer heatwaves. The paper presents results of a long-term summer temperature monitoring in flats with glazed balconies of different construction. They were located in prefabricated multi-family buildings, in residential districts of Lublin and Zamość. The cities are situated in the south-eastern part of Poland, belonging to the warm-summer humid continental climate area. The monitoring enabled overheating assessment according to the concept of adaptive comfort and connecting it with the sunspace construction and the inhabitants’ behaviour. These issues are new aspects in the research area, and the work is a part of extensive studies including monitoring and dynamic simulations of dwellings with passive greenhouse systems in Poland. Practical application: Glazed balconies raise the energy standard of buildings in a quick and inexpensive way, but it is important to consider their function not only during the heating season but also in the summer. Recording of temperatures enabled the monitoring of thermal conditions in the flats and the overheating assessment. It is possible to keep the internal temperature in the rooms within the desired range thanks to the sunspace ventilation and occupants’ behaviour.