Geomorphological Changes by the Action of Coastal Processes and Anthropogenic Activties along the Coastal Zone between Ras Al-Jalaiah And Ras Az-Zour, Southern Kuwait

The coastline is one of the most important linear features on the earth s surface which displays a dynamic nature The natural processes that interact with the coastal environment of Kuwait are tides currents and waves The main shoreline of the coast of Kuwait is about 325 km long In the north the coast is characterized by wide intertidal mudflats bounded by a large-scale coastal sabkha partly covered with sand drifts The southern shore is characterized by relatively steep sand beaches with narrow to moderately wide rocky intertidal platforms which are partly covered by sand and algal mats The area of interest is the coastal area between Ras al-Julaiha and Ras Az-Zour in the southern area of Kuwait Sandy berm and wave-cut cliff bound this southern intertidal environment The study area is a superficial open vulnerable bay of a maximum depth of 28 m extending along the southern shore of Kuwait Ras Al-Jalaiah promontory bounds the area northwards and Ras Az-Zour promontory bounds it southward with a distance measured vertically of 18 085 k

Influence of ambient air pollution on rheumatoid arthritis disease activity score Index

Rheumatoid arthritis (RA) is a chronic autoimmune of an unknown etiology. Air pollution has been proposed as one of the possible risk factors associated with disease activity, although has not been extensively studied. In this study, we measured the relationship between exposure to air pollutants and RA activity. Data on RA patients were extracted from the Kuwait Registry for Rheumatic Diseases (KRRD). Disease activity was measured using disease activity score with 28 examined joints (DAS-28) and the Clinical Disease Activity Index (CDAI) during their hospital visits from 2013 to 2017. Air pollution was assessed using air pollution components (PM 10, NO 2, SO 2, O 3, and CO). Air pollution data were obtained from Kuwait Environmental Public Authority (K-EPA) from six different air quality-monitoring stations during the same period. Multiple imputations by the chained equations (MICE) algorithm were applied to estimate missing air pollution data. Patients data were linked with air pollution data according to date and patient governorate address. Descriptive statistics, correlation analysis, and linear regression techniques were employed using STATA software. In total, 1651 RA patients with 9875 follow-up visits were studied. We detected an increased risk of RA using DAS-28 in participants exposed to SO 2 and NO 2 with β = 0.003 (95% CI: 0.0004–0.005, p < 0.01) and β = 0.003 (95% CI: 0.002–0.005, p < 0.01), respectively, but not to PM 10, O 3, and CO concentrations. Conclusively, we observed a strong association between air pollution with RA disease activity. This study suggests air pollution as a risk factor for RA and recommends further measures to be taken by the authorities to control this health problem

Air quality assessment in the State of Kuwait during 2012 to 2017

This study aimed to examine the trend of ambient air pollution (i.e., ozone (O3), nitrogen monoxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulfur dioxide (SO2), carbon monoxide (CO), benzene (C6H6) and particulate matter with an aerodynamic diameter smaller than 10 microns (PM10), and non-methane hydrocarbons (NMHCs) at 10 monitoring stations located in the main residential and industrial areas in the State of Kuwait over 6 years (2012–2017). We found that the SO2 level in industrial areas (0.065 ppm) exceeded the allowable range of SO2 in residential areas (0.030 ppm). Air pollution variables were defined by the Environmental Public Authority of Kuwait (K-EPA). In this study, integrated statistical analysis was performed to compare an established air pollution database to Kuwait Ambient Air Quality Guidelines and to determine the association between pollutants and meteorological factors. All pollutants were positively correlated, with the exception of most pollutants and PM10 and O3. Meteorological factors, i.e., the ambient temperature, wind speed and humidity, were also significantly associated with the above pollutants. Spatial distribution mapping indicated that the PM10 level remained high during the southwest monsoon (the hot and dry season), while the CO level was high during the northeast monsoon (the wet season). The NO2 and O3 levels were high during the first intermonsoon season

Spatio-temporal Evolution of Coastal Sabkhas in Arid Rapid Urban Development Area of Kuwait

Sabkha is the Arabic term meaning "salt flat". It is usually used to describe coastal flat areas extending above the high tide level and which are evaporate-rich clastic sediments. In Kuwait, sabkhas exist along the southern and northern coastal areas. Previous studies did not discuss the chronological changes of the coastal sabkhas in Kuwait, especially the northern sabkhas, where the Government of the State of Kuwait plans urban expansion to the North to achieve Kuwait Vision 2035. This current study aims to detect the geomorphological, spatial, and temporal evolution of coastal sabkhas in Kuwait using remote sensing data and Geographic Information System (GIS) methods. Landsat satellite images were used to study the distribution and evolution of the sabkhas across Kuwait's coasts. The selected images from Landsat MSS 1985 (before the gulf war), Landsat ETM+ 2002 (after the war), and Landsat OLI 2022 (current form) have been classified using the IsoData unsupervised classification method that takes into account near and short infrared radiation. The classification accuracy was validated for 2022 images using the Kappa coefficient, where the value was 0.81. The results showed that sabkhas in Kuwait have changed geomorphologically; anthropogenic activities and urban expansion have certainly influenced this change to cope with socioeconomic demands.The area of the sabkhas shrank from 1,267 to 1,019 km2 (-17%). The results also showed that the southern sabkhas of Kuwait are declining significantly, from 207km2 in 1985 to 52km2 in 2022. The current study presents a methodology to study the spatio-temporal evolution of sabkhas in dry areas around the world, using spatial analysis and in the context of the rapid urban development that the world is witnessing.

Geo-Historical and Geomorphological Evolution of the Sabkhas and Ridges at the Al-Khiran Area, State of Kuwait

International audienc

Handling complex missing data using random forest approach for an air quality monitoring dataset : a case study of Kuwait environmental data (2012 to 2018)

In environmental research, missing data are often a challenge for statistical modeling. This paper addressed some advanced techniques to deal with missing values in a data set measuring air quality using a multiple imputation (MI) approach. MCAR, MAR, and NMAR missing data techniques are applied to the data set. Five missing data levels are considered: 5%, 10%, 20%, 30%, and 40%. The imputation method used in this paper is an iterative imputation method, missForest, which is related to the random forest approach. Air quality data sets were gathered from five monitoring stations in Kuwait, aggregated to a daily basis. Logarithm transformation was carried out for all pollutant data, in order to normalize their distributions and to minimize skewness. We found high levels of missing values for NO2 (18.4%), CO (18.5%), PM10 (57.4%), SO2 (19.0%), and O3 (18.2%) data. Climatological data (i.e., air temperature, relative humidity, wind direction, and wind speed) were used as control variables for better estimation. The results show that the MAR technique had the lowest RMSE and MAE. We conclude that MI using the missForest approach has a high level of accuracy in estimating missing values. MissForest had the lowest imputation error (RMSE and MAE) among the other imputation methods and, thus, can be considered to be appropriate for analyzing air quality data