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A comprehensive assessment of the spatial and temporal patterns of the most common indicators of climate change and variability in the Arab world in the past four decades was carried out. Monthly maximum and minimum air temperature and precipitation amount data for the period 1980–2018 were obtained from the CHELSA project with a resolution of 1 km 2 , which is suitable for detecting local geographic variations in climatic patterns. This data was analyzed using a seasonal-Kendall metric, followed by Sen’s slope analysis. The findings indicate that almost all areas of the Arab world are getting hotter. Maximum air temperatures increased by magnitudes varying from 0.027 to 0.714 °C/decade with a mean of 0.318 °C/decade while minimum air temperatures increased by magnitudes varying from 0.030 to 0.800 °C/decade with a mean of 0.356 °C/decade. Most of the Arab world did not exhibit clear increasing or decreasing precipitation trends. The remaining areas showed either decreasing or increasing precipitation trends. Decreasing trends varied from −0.001 to −1.825 kg m −2 /decade with a mean of −0.163 kg m −2 /decade, while increasing trends varied from 0.001 to 4.286 kg m −2 /decade with a mean of 0.366 kg m −2 /decade. We also analyzed country-wise data and identified areas of most vulnerability in the Arab world.

The significance of land surface temperature (LST) and near-surface air temperature (T AIR ) extends to various applications, including the exploration of urban heat islands. Understanding urban heat islands is crucial for comprehending the intricate interactions among urbanization, climate dynamics, and human well-being. However, many aspects of these topics remain understudied. In this study, we conducted a comprehensive analysis of LST and T AIR , covering day and night and spanning all four seasons of a full year. We used global datasets and applied non-spatial and spatial analysis techniques in the Amman-Zarqa urban region, a typical arid to semiarid environment. The study had three primary objectives: (1) Assess how different human settlement types influence the variations in LST and T AIR across space and time. (2) Examine the spatial and temporal attributes of the relationships between T AIR and LST. (3) Synthesize insights regarding the spatial and temporal characteristics of urban heat islands in arid to semiarid environments. The findings unveiled that urban centers consistently exhibit the lowest daytime LST and maximum and minimum T AIR , across all seasons when compared to other human settlement types. Nighttime LST displayed more variable patterns. Urban centers act as surface urban cool islands during the day and canopy layer urban cool islands both day and night throughout the seasons. The presence of surface urban heat or cool islands at night is barely noticeable. Daytime and nighttime LST play a significant role in explaining the variability in maximum and minimum T AIR across all seasons, with the relationships exhibiting variations ranging from positive to non-significant to negative, influenced by location and seasonal changes. During the daytime, LST consistently exceeds T AIR across all seasons, whereas this relationship displays greater variability at night. The findings of this study hold significant implications for sustainable urban planning and efforts to combat the effects of urban heat islands.

There is limited understanding of how human development influences non–greenhouse gas (non-GHG) air pollutant emissions, particularly within the Arab world—a region of significant geopolitical importance. Addressing this gap is crucial to determining who pollutes more, a key issue in distributing environmental harm and responsibility, and central to environmental sustainability and justice. This study contributes to filling that gap by analyzing data on five non-GHG air pollutants—carbon monoxide (CO), nitrogen oxides (NO x ), non-methane volatile organic compounds (NMVOCs), ammonia (NH 3 ), and sulfur dioxide (SO 2 )—together with four human development indicators: the Human Development Index (HDI), a composite measure of overall development; the Gross National Income Index (GNII), reflecting economic progress; the Education Index (EI), representing educational attainment; and the Life Expectancy Index (LEI), measuring health outcomes. Using panel data from 16 Arab countries spanning 1990 to 2022, the study applies compound annual growth rate analysis and fixed effects econometric modeling. The main objectives are twofold: (1) to examine the temporal evolution of total emissions per capita alongside human development indicators, and (2) to assess the influence of human development indicators on total emissions per capita. The results show wide disparities in total emissions per capita and human development indicators across Arab countries, with fixed effects models explaining part of the variation but also highlighting the complex, multidimensional nature of the emissions–development relationship. Higher overall human development is generally associated with lower emissions; however, its components exert distinct effects. Economic growth tends to increase emissions, whereas improvements in education and health contribute to reducing them. Countries experiencing strong economic growth but weaker social development emit more, while those with balanced progress across income, education, and health emit less. These findings highlight the importance of integrated and equitable development strategies to advance environmental sustainability and justice in the Arab region.

This study aims to (1) determine the seasonalities and spatial and temporal rates of change of MODIS-based daytime and nighttime land surface temperature (LST) for the last 19 years from 2000 to 2018 and (2) investigate whether these rates are induced by natural (represented by elevation) or anthropogenic (represented by population counts) forcing. The study area is Jordan - a typical Middle Eastern semi-arid to arid country. Time-series additive seasonal decomposition and simple linear regression produced the following results. (1) For both daytime and nighttime the highest LST values were observed in June while the lowest LST values were observed in December. (2) No significant linear rates of change of LST were noticed in daytime, while significant linear rates of increase of LST, which varied from 0.041°C/year to 0.119°C/year, were observed in nighttime in about one-third of the area of the country mainly in the western parts. (3) The significant linear rates of increase of nighttime LST increased significantly by 0.005°C/year for every 1,000 m increase in elevation and by 0.003°C/year for every 1,000 people increase in population counts. (4) Both natural and anthropogenic factors affected LST in nighttime; however, anthropogenic factors seemed to be more important than natural factors.

Due to its importance, the field of urban heat islands (UHIs) has witnessed an increasing trend of interest over time to many scientists on the international level. Consequently, large number of papers has been published aiming at reviewing the literature about UHIs internationally. However, this topic started to attract attention of researchers in the Arab world only relatively recently. Hence, the major goal of the present endeavor is to narratively review the literature about UHIs in the Arab world. The focus is on two significant aspects of UHIs: (1) determination of UHIs and (2) assessment of the impacts of UHIs. The results of this review exposed to the surface the historical development, current status, and future prospects of literature about determination and assessment of the impacts of UHIs in the Arab world. The research about this specific topic in the Arab world can be described as still in its infancy stage with huge gaps still exist and more further studies are needed.

This study quantified the effect of imploding old concrete grain silos in Aqaba, Jordan, on the eastern side of the Gulf of Aqaba, an arid region, on air quality by measuring the PM 10 concentrations before and after the implosion at four monitoring locations. The implosion of the silos forms part of a comprehensive plan to relocate and upgrade the Port of Aqaba, which is situated on the coast of the Red Sea, with the goal of freeing space for development and improving the infrastructure in the heart of the city. The demolition, which occurred at 11:00 a.m. (local time) on 13 January 2019, generated a massive cloud of dust that was transported to nearby areas. To characterize these emissions, descriptive statistics, graphical methods, inverse distance weighting interpolation, decision trees constructed with recursive partitioning, the Gaussian dispersion model, the modified box model, and regression analysis were applied. The PM 10 concentrations were in compliance with the Jordanian 24-h standard of 120 µg m −3 prior to the implosion but substantially increased (although still varied by distance from the demolition site) at all four stations afterward, with the maximum values (259−587 µg m −3 ) exceeding the pre-implosion ones by as much as 26 times. However, these high concentrations were short-lived, and the majority of the stations returned to background levels within 30−33 hours. According to our calculations on the implosion, the PM 10 emission rate was 17 ± 2 mg m −2 s −1 , which is equivalent to 215 ± 22 kg silo −1 , and the air mixing height was 613 ± 72 m, or approximately eight times the height of the silos.

This study harnessed some of the many opportunities provided by the TRMM 3B43 data in order to generate maps illustrating the spatial and temporal distribution of significant linear rates of change of annual total precipitation for the surface of earth bounded by latitudes 50° S and 50° N for the years 1998–2018 by applying pixel-based simple linear regression. These maps are valuable for many applications and should enhance our understanding of the global precipitation patterns and trigger more research in order to explain what has not been explained. It has been found that the whole study area had a mean significant linear rate of change of − 0.4 mm/year. Nearly half of its area had significant linear rates of increase with a mean of 8.5 mm/year while the other half had significant linear rates of decrease with mean of − 7.6 mm/year. Landmass alone can be divided into nearly two halves; the first had significant linear rates of increase with a mean of 5.2 mm/year while the second had significant linear rates of decrease with mean of − 7.0 mm/year. Water areas alone also can nearly be divided into two halves; the first showed significant linear rates of increase with a mean of 9.6 mm/year while the second showed significant linear rates of decrease with mean of − 7.8 mm/year. Grouping the whole study area into six climatic zones and 21 administrative land and water regions and applying pixel-based Tukey test showed that the obtained significant linear rates of change varied significantly among these climatic and administrative regions.

Cancer in Jordan is a major public health problem and the second leading cause of death after heart disease. This study aimed at studying the spatial and temporal characteristics of cancer in Jordan and its 12 governorates for the period 2004-2013 to establish a baseline for future research and identification of cancer risk factors paving the way for developing a cancer control plan in the country. Numerical and graphical summaries, time-series additive seasonal decomposition, the method of least squares, and spacetime scan statistics were applied in a geographic information systems environment. Although the results indicate that the cancer incidence in Jordan is comparatively low, it is increasing over time. In the 10-year study period, a total of 44,741 cases was reported with a mean annual crude incidence rate of 68.4 cases/100,000, mean annual age-adjusted incidence rate of 111.9 cases/100,000, and a monthly rate increase of 1.2 (cases/100,000)/month. This study also revealed that the spatial and temporal characteristics of cancer vary among the governorates. Amman, which includes the capital city and hosts more than one-third of the population of the country, reported 61.0% of the total number of cases. Amman also reported the highest annual crude incidence rate (105.3 cases/100,000), the highest annual age-adjusted incidence rate (160.6 cases/100,000), and the highest rate of increase (0.7 (cases/100,000)/month) forming a high-rate cluster. Excluding the three governorates Amman, Balqa, and Ma’daba, low-rate clusters were found with regard to the remaining governorates. All governorates, except Irbid and Mafraq, showed significant rates of increase of cancer incidence. However, no clear seasonality pattern with respect to cancer incidence was discerned.

This study explores the spatial trends of cutaneous leishmaniasis (CL) and characterises the relationships between the observed spatial patterns and climate in Jordan, Syria, Iraq and Saudi Arabia in 2009. Areal interpolation revealed the presence of four major hotspots of relatively high incidence rates covering most parts of Syria, central parts of Iraq, and north-western, central, south-eastern and south-western parts of Saudi Arabia. The severity of these hotspots was seen to decrease from high to low latitudes. The spatial patterns could be partly linked to precipitation (the higher the precipitation, the higher the incidence rates) and to a lesser degree to temperature (the lower the temperature, the higher the incidence rates). No significant relationship was deduced between the observed spatial patterns of incidence rates and humidity. However, these three climatic factors could be used jointly as explanatory variables (ceteris paribus) to explain part of the spatial variations of the CL incidence rates in the study area by applying geographically weighted regression.

Soil organic carbon (SOC) sequestration is a component of larger strategies to control the accumulation of greenhouse gases that may be causing global warming. To implement this approach, it is necessary to improve the methods of measuring SOC content. Among these methods are indirect remote sensing and geographic information systems (GIS) techniques that are required to provide non-intrusive, low cost, and spatially continuous information that cover large areas on a repetitive basis. The main goal of this study is to evaluate the effects of using Hyperion hyperspectral data on improving the existing remote sensing and GIS-based methodologies for rapidly, efficiently, and accurately measuring SOC content on farmland. The study area is Big Creek Watershed (BCW) in Southern Illinois. The methodology consists of compiling a GIS database (consisting of remote sensing and soil variables) for 303 composite soil samples collected from representative pixels along the Hyperion coverage area of the watershed. Stepwise procedures were used to calibrate and validate linear multiple regression models where SOC was regarded as the response and the other remote sensing and soil variables as the predictors. Two models were selected. The first was the best all variables model and the second was the best only raster variables model. Map algebra was implemented to extrapolate the best only raster variables model and produce a SOC map for the BGW. This study concluded that Hyperion data marginally improved the predictability of the existing SOC statistical models based on multispectral satellite remote sensing sensors with correlation coefficient of 0.37 and root mean square error of 3.19 metric tons/hectare to a 15-cm depth. The total SOC pool of the study area is about 225,232 metric tons to 15-cm depth. The nonforested wetlands contained the highest SOC density (34.3 metric tons/hectare/15cm) with total SOC content of about 2,003.5 metric tons to 15-cm depth, where croplands had the lowest SOC density (21.6 metric tons/hectare/15cm) with total SOC content of about 44,571.2 metric tons to 15-cm depth.