Arid Climate Zones Research Articles

Mortality burden and economic loss attributable to cold and heat in Central and South America.

We quantify the mortality burden and economic loss attributable to nonoptimal temperatures for cold and heat in the Central and South American countries in the Multi-City Multi-Country (MCC) Collaborative Research Network. We collected data for 66 locations from 13 countries in Central and South America to estimate location-specific temperature-mortality associations using time-series regression with distributed lag nonlinear models. We calculated the attributable deaths for cold and heat as the 2.5th and 97.5th temperature percentiles, above and below the minimum mortality temperature, and used the value of a life year to estimate the economic loss of delayed deaths. The mortality impact of cold varied widely by country, from 9.64% in Uruguay to 0.22% in Costa Rica. The heat-attributable fraction for mortality ranged from 1.41% in Paraguay to 0.01% in Ecuador. Locations in arid and temperate climatic zones showed higher cold-related mortality (5.10% and 5.29%, respectively) than those in tropical climates (1.71%). Arid and temperate climatic zones saw lower heat-attributable fractions (0.69% and 0.58%) than arid climatic zones (0.92%). Exposure to cold led to an annual economic loss of $0.6 million in Costa Rica to $472.2 million in Argentina. In comparison, heat resulted in economic losses of $0.05 million in Ecuador to $90.6 million in Brazil. Most of the mortality burden for Central and South American countries is caused by cold compared to heat, generating annual economic losses of $2.1 billion and $290.7 million, respectively. Public health policies and adaptation measures in the region should account for the health effects associated with nonoptimal temperatures.

A Global Analysis of Historical and Future Changes in Mediterranean Climate‐Type Regions

ABSTRACTMediterranean climate‐type regions (MCRs) are characterised by warm‐to‐hot dry summers and mild‐wet winters. These regions are typically found on the western or southern edges of continents, for example, in the Mediterranean Basin, the west coast of North and South America, southern Africa and southwest Australia. The MCRs are vulnerable to climate variability and change related to their unique characteristics, such as pronounced rainfall seasonality and prolonged hot and dry summers. Based on historical observations and CMIP6 climate projections, we apply an empirical bio‐climatic assessment of how the geographic distribution of MCRs has changed during the last century and how these zones will be further impacted under continued warming. Results indicate a poleward and eastward expansion of MCRs in the Mediterranean Basin, North America‐California and South America‐Central Chile regions. For parts of Southern Africa and Southern Australia, a retreat of the MCR margins and an expansion of more arid climate zones are projected. These shifts are particularly profound according to high emission and radiative forcing pathways and future scenarios. The warming in MCRs is projected to accelerate (e.g., mean regional warming of up to 5.5°C under a 4°C global warming scenario), and precipitation will decrease by about 5%–10% for every additional degree of global warming. One exception is the California MCR, where rainfall will likely increase. Such changes can challenge water resources, food security and other aspects of human livelihood and ecosystems in these unique geographical zones.

Assessing the impact of urban parks across Köppen climatic zones: a systematic review

This review article addresses the gap in the literature concerning the role of urban parks in providing cooling effects in hot and arid climatic zones. Using systematic review and content analysis of manuscripts from 1999 to 2023 in Scopus and Web of Science databases, elements and indicators of landscape architecture and their impacts on mitigating urban heat islands (UHI) have been explored. Our data mining revealed 190 manuscripts categorized into four Köppen climatic zones: tropical/mega thermal, arid, temperate/mesothermal, and continental/microthermal. Results indicate a scarcity of studies on hardscape elements’ impact, particularly in desert and semi-arid zones, and limited recognition of landscape architecture’s role in urban park cooling, especially in hot desert climates. Green areas emerged as the most cost-effective cooling strategy, with grass planted to minimize water elements and enhance tree cooling effects. However, the lack of softscape in hot, arid zones poses a significant challenge in mitigating UHI. These findings bridge the literature gap and suggest avenues for future research, including investigating native urban tree species and optimizing park area, shape, and orientation.

Effects of environmental changes on soil respiration in arid, cold, temperate, and tropical zones

Soil respiration (Rs) is projected to be substantially affected by climate change, impacting the storage, equilibrium, and movement of terrestrial carbon (C). However, uncertainties surrounding the responses of Rs to climate change and soil nitrogen (N) enrichment are linked to mechanisms specific to diverse climate zones. A comprehensive meta-analysis was conducted to address this, evaluating the global effects of warming, increased precipitation, and N enrichment on Rs across various climate zones and ecosystems. Data from 123 studies, encompassing a total of 10,377 worldwide observations, were synthesized for this purpose. Annual Rs were modeled and their uncertainties were associated with a 1-km2 resolution global Rs database spanning from 1961 to 2022. Calibrating Rs using ensemble machine learning (EML) and employing 10-fold cross-validation, 13 environmental covariates were utilized. The meta-analysis findings revealed an upsurge in Rs rates in response to warming, with tropical, arid, and temperate climate zones exhibiting increases of 12 %, 13 %, and 16 %, respectively. Furthermore, increased precipitation led to stimulated Rs rates of 11 % and 9 % in tropical and temperate zones, respectively, while N deposition affected Rs in cold (+6 %) and tropical (+5 %) climate zones. The machine learning technique estimated the global soil respiration to range from 91 to 171 Pg C yr−1, with an average Rs of 700 ± 300 g C m−2 yr−1. The values ranged between 314 and 2500 g C m−2 yr−1, with the lowest and highest values observed in cold and tropical zones, respectively. Spatial variation in Rs was most pronounced in low-latitude areas, particularly in tropical rainforests and monsoon zones. Temperature, precipitation, and N deposition were identified as crucial environmental factors exerting significant influences on Rs rates worldwide. These factors underscore the interconnectedness between climate and ecosystem processes, therefore requiring explicit considerations of different climate zones when assessing responses of Rs to global change.

Identifying the barriers to green infrastructure implementation in semi-arid urban areas using the DPSIR framework: A case study of Amman, Jordan

Research has highlighted the role of green infrastructure (GI) in addressing climate change impacts and other societal and environmental challenges in semi-arid urban areas. Regardless of this potential, GI implementation and research in arid climate zones is limited. Accordingly, using Amman, Jordan as a case study, this research aims to investigate the barriers that impede and prevent GI implementation in semi-arid urban areas. The GI barriers are conceptualized using the Driving–Pressure–State–Impact–Response (DPSIR) framework which was applied on data collected from semi-structured interviews with GI stakeholders in the city. The findings highlighted 17 general implementation barriers grouped into 6 categories. The DPSIR framework specifically highlighted the role of natural and human drivers (e.g. rapid urbanization, institutional capacities, and lacking financial resources) in creating significant barriers to GI implementation. It also illustrated the focus on open spaces and green cover in GI planning in Amman, lacking performance data on GI best practices in semi-arid contexts, and the need of integrated pathways to overcome the identified barriers. The DPSIR framework presents an easy-to-communicate picture of the state of GI implementation in the city that can be utilized by decision-makers, particularly those lacking access to diverse resources. The outcomes of this study enhances our understanding of GI planning in semi-arid urban areas and are beneficial for policymakers and practitioners looking for pathways to promote resilient urban development strategies. Overall, the study calls for further GI research on semi-arid developing contexts.

Year-round performance evaluation of photovoltaic-thermal collector with nano-modified phase-change material for building application in an arid desert climate zone

This study provides a comprehensive analysis of the energetic and thermoelectric characteristics of a solar photovoltaic-thermal (PVT) collector equipped with a nano-modified phase-changing material (NPCM) for PV cooling. The operational effectiveness of the collector is evaluated using various parameters such as PV temperature, electrical and thermal powers, melting time, PCM liquid fraction, and PV cooling duration. These factors are meticulously examined under different operating conditions of solar irradiance, ambient air temperature, and the thickness of the NPCM layer. Hail, Saudi Arabia, a city known for its arid desert climate, is chosen as the geographic setting for the study. A numerical methodology based on finite volume discretization is used to solve the governing mathematical models. The year-round performance of the combined PVT and NPCM unit is systematically assessed in terms of monthly averages across the four seasons, considering varying NPCM layer thickness over different time frames. The results indicate that an NPCM with a nanoparticle volumetric concentration of 5% and an appropriately chosen NPCM layer thickness provides effective PV cooling, with cooling durations ranging from 54 to 305 min throughout the year. In terms of electrical performance, months with high solar irradiance yielded a greater power output, peaking at approximately 52.5 Watts, while the winter months exhibited the lowest output. The thermal performance followed a similar pattern, demonstrating the significant influence of solar irradiance on thermal efficiency, with peak outputs reaching up to 225 Watts during high solar intensity months.

Assessment of long-term multisource surface and subsurface soil moisture products and estimate methods on the Tibetan Plateau

This research is the first attempt to extensively assess the accuracy of commonly used surface and subsurface soil moisture (SM) datasets in reproducing temporal dynamics and trend changes SM observations for a long period on the Tibetan Plateau (TP). To this end, 12 satellite-based and 10 model-based SM products are evaluated using a 10-year upscaled SM dataset obtained from two in situ monitoring networks situated respectively in humid and arid climate zones over the TP. Moreover, the ability of using the outperforming satellite-based surface SM data in combination with cumulative distribution function (CDF) matching and exponential filter (ExpF) methods to improve model-based SM profile estimations is investigated for the first time. Among the 12 satellite-based products, SMAP_L3 provides the best surface SM retrievals, with the DCA and SCA-V products showing superior performance in the humid and arid areas, respectively. Consequently, the harmonized products produced based on the SMAP data (i.e., SMOSMAP and NNsm) also give relatively higher accuracy. It is surprised to find that the latest version of both CCI passive and active products presents degraded performance compared to its predecessor (i.e. v5.3). Among the 10 model-based products, SMAP_L4 with assimilation of L-band brightness temperature (TB) measurements provides relatively better estimations of surface and subsurface SM on the TP. Above findings highlight the superiority of utilizing the L-band TB measurements especially from the SMAP satellite to generate surface SM and improve the model-based SM estimations via data assimilation. Alternatively, it is further demonstrated that incorporating surface SM data from SMAP_L3, in conjunction with both CDF matching and ExpF methods, significantly enhances the precision of model-based SM estimations. This may open up a new possibility for improving the model-based SM profile data across the TP.

A dataset of annual TCI, VCI, VHI and TVDI with the resolution of 1 km in the Yellow River Basin (2003–2022)

Primarily situated in arid and semi-arid climatic zones, characterized by naturally limited water resources, the Yellow River Basin is the most drought-affected among China's major basins. As global environmental and climate change continue to evolve, droughts in the Yellow River Basin have become increasingly frequent, making drought monitoring research a current focal point. Based on MODIS vegetation data and surface temperature products, this dataset undergoes quality control procedures such as cloud removal and data reconstruction to collect the data of annual Temperature Condition Index (TCI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI) and Temperature Vegetation Dryness Index (TVDI) in the Yellow River Basin from 2003 to 2022. The spatial scope of this dataset ranges from 32°10′N–41°50′N，95°53′E–119°05′E. The dataset is in GeoTiff format with a spatial resolution of 1km. It can provide foundational data and scientific support for drought disaster monitoring in the Yellow River Basin.

Gender, climate and landowning: Sources of variability in the weather pattern change and ideal fertility relationship in Sahelian West Africa

This paper advances our understanding of the relationship between climate change and ideal fertility in Sahelian West Africa by exploring sources of variation in that relationship. Using an integrated dataset of Demographic and Health Surveys with monthly rainfall and temperature data, the analyses model dimensions of prospective ideal fertility for young, childless men and women in Senegal, Mali, Burkina Faso and Nigeria. Temperature, particularly in the arid climate zone, is shown to have a positive effect on ideal fertility. Landowning insulates individuals from adjusting their fertility ideals in response to change. Gender-stratified models reveal that under hotter conditions, women have a higher ideal number of children but their ideal gender composition remains relatively balanced, while men do not change their ideal number of children but show a preference for more sons. The increase in ideal fertility in response to weather change may be understood as an increasing need to generate human capital to meet the increased labour demands that climate change brings over both the short and the long term.

Multi-performance collaborative optimization of existing residential building retrofitting in extremely arid and hot climate zone: A case study in Turpan, China

Multi-dimensional performance optimization of buildings is crucial to achieving comfort and realizing green and sustainable development. This study developed a multi-performance collaborative optimization framework (MPC_BPO) to analyze modern residential retrofitting in extremely arid and hot climate zone. The parametric environmental simulation (PES) demonstrated high consistency with actual operating results (R2 > 0.92), and the multi-objective optimized artificial neural network (OPT-ANN) effectively established a high precision multi-performance prediction model (R2 > 0.96). Various multi-objective algorithms exhibited a high convergence level in the high-dimensional complex optimization process. The entropy weight and subjective weight methods ranked the Pareto frontier solution set, where the optimization scheme dominated by energy use intensity (EUI) increased daylighting index (DLI) and thermal comfort hours (TCH) by 12.32 % and 6.67 %, respectively, while reducing EUI by over 8.47 %. Applying different scenarios to other household buildings verified the generalization characteristics, showing overall high consistency despite variations in performance indicators. This research provides a scientific basis for improving residential performance in special climate zones through an appropriate framework. Using scientific methods, it analyzes the intrinsic logic between high-dimensional parameters and multiple building performances.

The power of attention: Government climate-risk attention and agricultural-land carbon emissions

Climate change is a common challenge faced by all humanity. Promoting emission and carbon reduction in agricultural land is the most important priority for addressing climate change and realizing sustainable development. Based on data from 296 prefecture-level cities in China from 2011 to 2021, this study utilizes machine-learning and text-analysis methods to construct an indicator of government climate-risk attention (GCRA). It combines a two-way fixed-effects model to investigate how GCRA affects agricultural-land carbon emissions (ALCE) and carbon intensity (ALCI) and the mechanism of the impact. The results indicate that (1) GCRA substantially reduces ALCE and ALCI, and the conclusions are robust to a battery of tests. Furthermore, (2) mechanism analysis reveals that GCRA primarily uses three mechanisms—strengthening environmental regulation, promoting agricultural green-technology innovation, and upgrading agricultural-land mechanization—to reduce ALCE and lower ALCI. Additionally, (3) heterogeneity analysis suggests that the carbon-emission reduction effect of GCRA is more significant in the east, in arid and humid climate zones, and in non-grain-producing regions. Finally, (4) spatial-spillover effect analysis and quantile regression results demonstrate that GCRA also significantly inhibits carbon emissions and the carbon intensity of nearby agricultural land, with the inhibition effect becoming more pronounced at higher levels of government attention. This study's discoveries are helpful in promoting the emission reduction and carbon sequestration of agricultural land and provide references for developing countries to cope with climate change.

Observed Changes of Köppen Climate Zones in Spain since 1951

Despite of having been originally formulated more than one hundred years ago, the Köppen classification is still nowadays the climate classification most widely used in climatological studies. Based on the empirical relationship between climate and vegetation, this climate classification provides an efficient and easy way to describe climate conditions and their seasonality by using a simple but ecologically meaningful classification scheme. This study examines the temporal evolution of the Köppen climate classification in Spain for the period 1951-2020, using high-resolution gridded datasets of monthly mean temperature and precipitation with 1 x 1 km spatial resolution. Climate classification maps for consecutive 30-year reference periods are compared, and the temporal evolution of each climate type in Spain is analysed, showing a progressive expansion of the arid climate zones and a contraction of the cold climate zones along the study period.

Controls on timescales of soil organic carbon persistence across sub-Saharan Africa.

Given the importance of soil for the global carbon cycle, it is essential to understand not only how much carbon soil stores but also how long this carbon persists. Previous studies have shown that the amount and age of soil carbon are strongly affected by the interaction of climate, vegetation, and mineralogy. However, these findings are primarily based on studies from temperate regions and from fine-scale studies, leaving large knowledge gaps for soils from understudied regions such as sub-Saharan Africa. In addition, there is a lack of data to validate modeled soil C dynamics at broad scales. Here, we present insights into organic carbon cycling, based on a new broad-scale radiocarbon and mineral dataset for sub-Saharan Africa. We found that in moderately weathered soils in seasonal climate zones with poorly crystalline and reactive clay minerals, organic carbon persists longer on average (topsoil: 201 ± 130 years; subsoil: 645 ± 385 years) than in highly weathered soils in humid regions (topsoil: 140 ± 46 years; subsoil: 454 ± 247 years) with less reactive minerals. Soils in arid climate zones (topsoil: 396 ± 339 years; subsoil: 963 ± 669 years) store organic carbon for periods more similar to those in seasonal climate zones, likely reflecting climatic constraints on weathering, carbon inputs and microbial decomposition. These insights into the timescales of organic carbon persistence in soils of sub-Saharan Africa suggest that a process-oriented grouping of soils based on pedo-climatic conditions may be useful to improve predictions of soil responses to climate change at broader scales.

Greening of China and possible vegetation effects on soil moisture

Wetting and drying climate sequences and anthropogenic vegetation changes can have profound effects on the hydrological cycle and sustainability of terrestrial ecosystems. China contains many different climates, from humid to extremely arid and it contributes to the global mitigation strategies of climate change. China is also an important contributor to global greening and carbon sequestration. In view of this, we estimated the spatial and temporal variation of leaf area index (LAI), dryness/wetness index (DWI), and soil moisture (SM) in arid (A), semi-arid (SA), semi-humid (SH), and humid (H) climate zones during 1981–2018 in China and analyzed the patterns of DWI and LAI effects on SM under different vegetation greenness. The results showed a significantly increasing trend of LAI in all climatic zones, and the contribution was from highest to lowest: SH (8.17 × 10-3 m2 m−2 year−1), SA (7 × 10-3 m2 m−2 year−1), H (4.71 × 10-3 m2 m−2 year−1), and A (3.98 × 10-3 m2 m−2 year−1). The SA and A zones are becoming wetter, while the soil of SH and H zones are drying. The dry/wet climate variation plays a decisive role in soil moisture, while the role of vegetation is limited. Additionally, the LAI3 (mean LAI from 2016 to 2018) thresholds were 0.25–0.41 and 0.84–0.86 for A and SA as a whole, respectively, as well as 0.47–0.54 and 0.93–1.18 for grassland, respectively. When vegetation exceeded this threshold, the effect of vegetation on soil moisture showed a shift from increasing to decreasing change. Overall, the results of the study provide improved understanding of the atmosphere-soil-vegetation interactions under climate change, as well as effects of vegetation restoration and water conservation efforts.

Audio‐Magnetotelluric Survey for Groundwater Investigation in the Al‐Jaww Plain in Eastern Abu Dhabi, Al‐Ain, United Arab Emirates

AbstractThe United Arab Emirates (UAE), located in an arid climate zone with low rainfall, relies on shallow aquifers for freshwater. Understanding the depth and extent of such aquifers is crucial for meeting water supply needs. The UAE's hydrogeology is influenced by neighboring mountains in Oman. The Al‐Jaww Plain in southeast of Al‐Ain city is an essential groundwater source, characterized by a large, flat area of gravel and sand deposits from the Oman Mountains. This study aims to map groundwater aquifers in the Al‐Jaww Plain by integrating the audio‐magnetotelluric (AMT) method, seismic reflection profiling, and borehole data. AMT data were collected along an 11‐km ENE–WSW profile and a 2D resistivity model was generated. The resulting model delineates three distinct geo‐electrical zones from the surface to a depth of 5 km. First, a shallow layer with low resistivity (0–15 Ωm) represents the Quaternary and Pliocene aquifers, in addition to the Upper Cretaceous Simsima and Tertiary groundwater aquifer zone, extending to a depth of 1.5 km. Second, a moderately resistive layer (15–250 Ωm) is recorded beneath the first layer, corresponding to the Upper Cretaceous Aruma foreland basin sequence. Finally, a high‐resistivity region (>250 Ωm) at depths exceeding 3 km is attributed to the allochthonous Hawasina thrust sheet, which is associated with Late Cretaceous obduction of the Semail ophiolite. These findings have practical implications for managing groundwater resources in Al‐Ain.

Evaluation of Empirical Equations and Machine Learning Models for Daily Reference Evapotranspiration Prediction Using Public Weather Forecasts

Although the studies on model prediction of daily ETo based on public weather forecasts have been widely used, these studies lack the comparative evaluation of different types of models and do not evaluate the seasonal variation in model prediction of daily ETo performance; this may result in the selected model not being the best model. In this study, to select the best daily ETo forecast model for the irrigation season at three stations (Yinchuan, Tongxin, and Guyuan) in different climatic regions in Ningxia, China, the daily ETos of the three sites calculated using FAO Penman–Monteith equations were used as the reference values. Three empirical equations (temperature Penman–Monteith (PMT) equation, Penman–Monteith forecast (PMF) equation, and Hargreaves–Samani (HS) equation) were calibrated and validated, and four machine learning models (multilayer perceptron (MLP), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and gradient boosting with categorical features support (CatBoost)) were trained and validated against daily observed meteorological data (1995–2015 and 2016–2019). Based on public weather forecasts and daily observed meteorological data (2020–2021), the three empirical equations (PMT, PMF, and HS) and four machine learning models (MLP, XGBoost, LightGBM, and CatBoost) were compared in terms of their daily ETo prediction performance. The results showed that the daily ETo performance of the seven models in the irrigation season with a lead time of 1–7 days predicted by the three research sites decreased in the order of spring, autumn, and summer. PMT was the best model for the irrigation seasons (spring, summer, and autumn) at station YC; PMT and CatBoost with C3 (Tmax, Tmin, and Wspd) as the inputs were the best models for the spring, autumn irrigation seasons, and summer irrigation seasons at station TX, respectively. PMF, CatBoost with C4 (Tmax, Tmin) as input, and PMT are the best models for the spring irrigation season, summer irrigation season, and autumn irrigation season at the GY station, respectively. In addition, wind speed (converted from the wind level of the public weather forecast) and sunshine hours (converted from the weather type of the public weather forecast) from the public weather forecast were the main sources of error in predicting the daily ETo by the models at stations YC and TX(GY), respectively. Empirical equations and machine learning models were used for the prediction of daily ETo in different climatic zones and evaluated according to the irrigation season to obtain the best ETo prediction model for the irrigation season at the study stations. This provides a new idea and theoretical basis for realizing water-saving irrigation during crop fertility in other arid and water-scarce climatic zones in China.

Enhancement of Condenser Performance in Vapor Absorption Refrigeration Systems Operating in Arid Climatic Zones—Selection of Best Option

Generators and condensers are the two vital equipment items that determine the output of vapor absorption refrigeration systems. Arid weather conditions produce a significant reduction in the performance of the vapor absorption refrigeration cycle due to low condenser heat dissipation despite high generator temperatures. Although numerous studies on condenser cooling methods in vapor compression systems have been reported in the literature, solar-operated vapor absorption systems have not been studied. Limitations in generator temperatures of solar-operated vapor absorption systems necessitate a focused study in this area. This study makes the selection of the best choice for condenser cooling from among four different condenser cooling methods which have an impact on the performance of the vapor absorption refrigeration system for effective cooling using solar energy. A solar vapor absorption refrigeration system working with low-grade heat using a compound parabolic collector is considered in this study. Analysis of a vapor absorption refrigeration system for cooling in arid weather conditions is carried out using different condenser cooling methods with Engineering Equation Solver. Initially, the model used in the study is compared with a similar study reported in the literature. Techniques considered are air, water, evaporative, and hybrid cooling techniques. The performance of the vapor absorption cooling system was analyzed using experimental values of a solar compound parabolic collector obtained from real-time measurements for simulating the model. Results show that water cooling can provide suitable condenser cooling and improve the coefficient of performance of the solar vapor absorption refrigeration system using the solar collector. The water-cooled condenser has 1.9%, 3.3%, and 2.1% higher COP when compared to air-cooled condensers for spring, summer, and autumn seasons respectively, whereas the water-cooled condenser cooling recorded 6%, 14%, and 8% higher COP relative to the evaporative cooling method. Cost comparison showed maximum cost for water-cooled condensers and minimum cost for hybrid-cooled condensers. The effect of each cooling method on the environment is discussed.

An overview of groundwater response to a changing climate in the Murray-Darling Basin, Australia: potential implications for the basin system and opportunities for management

The Murray-Darling Basin (MDB) is a highly allocated and regulated, mostly semiarid basin in south-eastern Australia, where groundwater is a significant water resource. Future climate predictions for the MDB include an expansion of arid and semiarid climate zones to replace temperate areas. The impacts of climate change are already evident in declining groundwater levels and changes in the connection status between rivers and groundwater, and modelling has predicted a further reduction in future groundwater recharge and ongoing declines in groundwater levels. This is predicted to further reduce river baseflow and negatively impact groundwater-dependent ecosystems (GDEs), and these system responses to a changing climate and extreme events are complex and not always well understood. This report provides an overview of the current state of knowledge of groundwater response to a changing climate for the MDB, and outlines challenges and opportunities for future groundwater research and management. Opportunities for the region include improving data systems and acquisition through automation and novel data sources, and growing capability in integrated, risk-based modelling. Quantification of the groundwater/surface-water connection response to declining groundwater levels, and assessing GDE water requirements and thresholds, would enable identification of vulnerable systems and inform the development of metrics for adaptive management, improving the ability to respond to climate extremes. There is potential to adapt policy to support active management of groundwater where required, including conjunctive use and water banking. Improving knowledge sharing and water literacy, including understanding community values of groundwater and GDEs, would support future decision-making.

Climate change as challenges and prospects for architecture development

While the causes of climate changes remain poorly understood, their nature is undeniable. The shift in climate zone boundaries is accompanied by a rapid increase in the number and scale of extreme weather events, temperature and humidity variations. For many regions of Eurasia, climatic changes are manifested in the onset of desert and semi-desert (arid) climate zones. Extreme weather phenomena have a particularly threatening impact on urban life. For a variety of reasons, the urban environment is less resilient to weather disasters. The ways of increasing the resilience of urban environment, which are offered by the architectural mainstream, look insufficiently effective. The article substantiates the concept of using traditional and vernacular architectural and construction technologies preserved in regions with arid climate (Middle East, North Africa). Examples of successful application of traditional methods of house-building in combination with elements of the latest technologies are given.

A novel method to evaluate phase change materials' impact on buildings' energy, economic, and environmental performance via controlled natural ventilation

The construction industry consumes a significant portion of global energy, with space conditioning in buildings accounting for a substantial 34% of energy usage. Notably, the energy consumption of a building is significantly influenced by its envelope. Researchers widely acknowledge that incorporating phase change materials (PCM) into the building envelope is a promising way to enhance energy efficiency and mitigate CO2 emissions in the building sector, owing to their high latent heat capacity. However, PCM must be completely charged after each cycle to exploit its full potential. Natural ventilation is a viable technique to facilitate the charging and discharging cycle of PCM within a 24-h period. To this end, the present study utilized EnergyPlus simulations to optimize the cooling energy savings of a residential building incorporating PCM into its envelope for PCM melting temperatures, considering various ventilation strategies across 45 cities in 15 climate zones worldwide. In order to evaluate the latent heat utilization of PCM and its improvement facilitated by natural ventilation, two novel indicators, namely HS and HR, were formulated to represent the heat stored and released by PCM during a 24-h cycle, respectively. In addition, following an economic analysis of PCM integration, a comprehensive environmental evaluation was carried out, which included the carbon intensities (CI) of all fuel sources contributing to power generation. The study's findings reveal substantial energy savings across all climate zones when controlled natural ventilation is coupled with PCM, and the newly proposed indicators precisely quantify the performance of PCM in all scenarios evaluated. In the arid climate zone (A), combining PCM and natural ventilation enhances energy savings, albeit to a similar extent as using ventilation alone. However, the integration of PCM with temperature-controlled ventilation yields striking energy reductions of up to 72.8%, 85.3%, and 61% in arid (B), warm temperate (C), and snow (D) climate zones, respectively. The cost-benefit analysis reveals a minimal return period of as short as five years in climate zone C. In the same climate zone C, the in-depth environmental analysis reveals a maximal reduction of 42,004 CO2-e kg/year in carbon emissions. In conclusion, this research study demonstrated that integrating PCM with controlled natural ventilation offers a practical, sustainable, and cost-effective solution with eco-friendly and energy-efficient outcomes.