Spatiotemporal Analysis of the Impacts of Climate Change on UAE Mangroves

Mangroves are imperative to coastal systems, providing security against extreme weather events by acting as natural barriers. These halophytic plants play a crucial role in mitigating global warming and act as an invaluable resource for consumption. Despite proving to be resilient, mangroves exhibit sensitivity to climatic (e.g., Land Surface Temperature, Salinity, etc.) and man-made factors (e.g., Land Use/Land Cover Changes). Numerous past studies recording the relationship between mangrove growth & development with the aforesaid constituents, but those were mostly restricted to visual observation/pattern recognition and single type of regression analysis. Also, the evaluation of simultaneous exploration of multiple aspects influencing mangrove evolution was not prominent. Therefore, the main objective of this study was to focus on the impact of both salinity and land surface temperature on mangrove biomass by the joint-venture of remote sensing, geographic information system and several machine learning algorithms. The study considered appropriate mangrove site selections with pre-processing of the acquired satellite images. Also, mathematical computations were performed on the raster layers to determine the previously mentioned natural aspects. Finally, several types of regression analysis were conducted to delineate potential patterns, governing mangrove vegetation health by virtue of temperature and salinity. Mangroves’ relationship with temperature and salinity showed insignificant coefficient of determination. However, the generated response curves postulated that high mangrove biomass could be achieved for a specific temperature window (30-33◦C) and vegetation health could deteriorate at increasing salinity. Overall, combined effects of surface temperature and salinity on mangrove vegetation were significantly more (i.e., Maximum coefficient of determination of 0.31) than individual component alone

Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tree Models

© Copyright © 2020 Elmahdy, Ali, Mohamed, Howari, Abouleish and Simonet. Mangrove forests are acting as a green lung for the coastal cities of the United Arab Emirates, providing a habitat for wildlife, storing blue carbon in sediment and protecting shoreline. Thus, the first step toward conservation and a better understanding of the ecological setting of mangroves is mapping and monitoring mangrove extent over multiple spatial scales. This study aims to develop a novel low-cost remote sensing approach for spatiotemporal mapping and monitoring mangrove forest extent in the northern part of the United Arab Emirates. The approach was developed based on random forest (RF), Kernel logistic regression (KLR), and Naive Bayes Tree machine learning algorithms which use multitemporal Landsat images. Our results of accuracy metrics include accuracy, precision, and recall, F1 score revealed that RF outperformed the KLR and NB with an F1 score of more than 0.90. Each pair of produced mangrove maps (1990–2000, 2000–2010, 2010–2019, and 1990–2019) was used to image difference algorithm to monitor mangrove extent by applying a threshold ranges from +1 to −1. Our results are of great importance to the ecological and research community. The new maps presented in this study will be a good reference and a useful source for the coastal management organization

The Emirates at 2050: Balancing Development and Environmental Stewardship

The United Arab Emirates (UAE) faces the challenge of balancing rapid economic development with environmental preservation and conservation in the Anthropocene era. The nation’s unique ecosystems, characterized by arid desert, rugged mountains, and diverse marine habitats, are vulnerable to disturbances such as urbanization, habitat degradation, groundwater extraction and climate change. To chart a more sustainable course for the Emirates by 2050, the paper proposes policy recommendations such as adopting a national strategy for sustainable development, strengthening environmental policies, investing in urban planning and design, promoting sustainable water management, encouraging use of nature-based solutions, addressing climate change, fostering environmental education, supporting research in environmental sciences, encouraging national and regional cooperation, promoting sustainable business practices in the private sector, and monitoring the progress of environmental policies. By embracing a vision of development that respects the natural environment and safeguards its plant and animal life, the UAE can demonstrate its commitment and serve as a model for other nations to follow, becoming a shining example of responsible development by 2050

Seasonal impact to air qualities in industrial areas of the arabian gulf region

© 2018 Korean Society of Environmental Engineers. Air quality conditions and pollution status have been evaluated in the industrial area between Sharjah and Ajman border in UAE. Daily concentrations of O3, CO, NO2, SO2, PM2.5, PM10, Total Volatile Organic Compounds (TVOC) and Total Suspended Particulate (TSP) have been monitored from Sept. 2015 to April 2016. The monthly average concentrations of O3, CO, NO2, SO2, TVOC were within the UAE ambient air quality standards during the survey period. However, PM10 and TSP levels exceeded the recommended limits in Sept. 2015, Oct. 2015 and March 2016. Temporal variations in air quality parameters showed highest levels in March 2016 for PM2.5, PM10, NO2, TVOC and TSP, whereas O3, SO2 and CO showed relatively low values in this month. PM2.5 levels in ambient air were above the EPA guideline of 35 μg/m³ in all months. PM2.5 was the critical ambient air pollutant with Index for Pollutant (Ip) values varying from 103-209, indicating Air Quality Index categories of unhealthy for sensitive groups (62.5%) to unhealthy (25%) to very unhealthy (12.5%). The Ip average values of PM2.5 decreased from Sept. 2015 to reach lowest value in Dec. 2015 before increasing gradually, peaking in March 2016. These results suggest the potential health risks associated with PM2.5 is low in winter, where the prevailing meteorological conditions of lower temperatures, higher humidity, higher wind speed reduced particulate matter. The results revealed the industrial area is impacted by anthropogenic and natural sources of particulate matter

ASSESSING THE IMPACTS OF SEA LEVEL RISE ON LAND-USE ACROSS THE NORTH-EASTERN PARTS OF THE UAE COASTAL AREAS USING REMOTE SENSING TECHNOLOGY

The consequences of global warming and climate change would result in a considerable rise in sea level. Other larger consequences on coastal lands, agriculture, buildings, and facilities are expected. The goal of this study is to assess the effects of Sea-Level Rise (SLR) on various land uses in the UAE\u27s North-Eastern coastal districts (Fujairah and Kalba cities). Four SLR scenarios will be developed through the QGIS platform and the Landsat images that have been acquired from the USGS Earth Explorer. The area will be observed over 20 years (2000 – 2020). The second goal of this study is to develop a coastal vulnerability index that can support policy-makers and stakeholders in developing strategic plans in order to be prepared for the effects of this phenomenon in the most vulnerable areas. A confusion matrix was conducted to assess the accuracy of the land classifications in the study resulting in an 80% classification accuracy. The level of damages due to SLR in the year 2000 will rise to 21%, 27%, and 7% of the agricultural, built up, and open areas respectively. However, it will reach 29%, 28%, and 8% for the same areas in the year 2020. Around 15% of the study area in the year 2000 is considered to have high vulnerability to SLR where about 29% of the study area in the year 2020 is considered to have high vulnerability to SLR. The development projects in the study area have increased throughout 20 years and it is the most affected by SLR. It is widely assumed that any future actions and preparations to mitigate the impact of SLR should focus on the vulnerable areas mentioned above. Proper early planning for long-term consequences will definitely save time, resources, and effort

ASSESSMENT OF THE IMPACT OF CLIMATE CHANGE ON LAND USE IN THE EMIRATE OF ABU DHABI - AN ENVIRONMENTAL AND SOCIO-ECONOMIC PERSPECTIVE

This dissertation focuses on the impact of climate change on land use in the Emirate of Abu Dhabi – UAE. Climate change is a significant challenge resulting from natural and anthropogenic causes. Land use can stimulate changes in communities under climate change. The main objective of this dissertation is to assess the impact of climate change from an environmental and socio-economic perspective. In 2001, coastal sabkhas, mixed class and urbanized areas experienced an increase in temperature by (0.67, 1.14 and 1.16°C) respectively. In cities, urban areas are warmer than neighbouring rural areas. Unexpectedly, urbanization in desert areas in UAE led to a decrease of 3–5°C in the overall LST. The maximum air temperatures are going to increase in the coming years based on the predictions according to the different scenarios in 2095 using MarksimGCM by more than 4°C in UAE. Urban expansion and changing lifestyles have led to an increase in energy consumption. Data was gathered from (321) residents in Abu Dhabi Emirate. More than 50% of the participants agreed that climate change is controlling their energy and water consumption. About 94% of participants believe that their energy consumption is increasing. About 50% of participants consider moving to another city if energy prices increased due to energy consumption and the effects of climate change. Changes in the global environmental conditions affect agricultural activities. Three hundred and one surveys were collected throughout Abu Dhabi Emirate. Approximately 68% of the respondents in Al-Ain agreed that it is currently much easier and more profitable to manage a farm than it was 20 years ago. Thirty-nine per cent of the farmers agreed that both product quality and quantity have improved over the past 20 years. Farmers aged between 51-60 years agreed more that the groundwater levels and quality had changed over the past 20 years. The research covered a past, present and future periods of time that represented a firm timeline of the study. The study reflects the importance of awareness among people to overcome and cope with the effects of climate change

Assessing Atmospheric Pollution and Its Impacts on the Human Health

This reprint contains articles published in the Special Issue entitled "Assessing Atmospheric Pollution and Its Impacts on the Human Health" in the journal Atmosphere. The research focuses on the evaluation of atmospheric pollution by statistical methods on the one hand, and on the other hand, on the evaluation of the relationship between the level of pollution and the extent of its effect on the population's health, especially on pulmonary diseases

Monitoring Changes and Soil Characterization in Mangrove Forests of the United Arab Emirates Using the Canonical Correlation Forest Model by Multitemporal of Landsat Data

Mangrove forests are an important indicator of blue carbon storage and biodiversity and provide several benefits to the environment. This study showed the first attempt to apply the canonical correlation forest (CCF) model to classify mangroves and monitor changes in the mangrove forests of the entire region. The CCF model obtained a satisfactory accuracy with an F1 score of more than 0.90. Compared to Sentinel-2, Landsat 8 exhibited good temporal resolution with relatively little mangrove details. The resultant mangrove maps (1990–2020) were used to monitor changes in mangrove forests by applying a threshold value ranging from +1 to −1. The results showed a significant increase in the UAE mangroves over the period from 1990 to 2020. To characterize soil in mangrove forests, a set of interpolated maps for calcium carbonate, salinity concentration, nitrogen, and organic matter content was constructed. The results showed that there is a positive relationship between mangrove distribution and the calcium carbonate, nitrogen, salinity, and organic matter concentrations in the soil of the mangrove forests. Our results are of great importance to the ecological and research community. The new maps presented in this study will be a good reference and a useful source for the coastal management organization

Epidemiology of Taenia saginata taeniosis/cysticercosis: a systematic review of the distribution in the Middle East and North Africa

BackgroundThe zoonotic parasite Taenia saginata utilizes bovines as an intermediate host (causing cysticercosis) and humans as the definitive host (causing taeniosis). The public health burden of T. saginata is assumed to be low, but the economic burden is large, due to the resources utilized in the detection and condemnation of infected carcasses and carcass parts. As part of a collaborative effort to synthesize worldwide epidemiological data on this parasite, we present here the results of a systematic review on the distribution of T. saginata taeniosis and bovine cysticercosis in the Middle East and North Africa (MENA).MethodsInformation on the occurrence and prevalence of T. saginata taeniosis and cysticercosis in the MENA region was obtained through a systematic review of published and grey literature, including OIE reports, published between January 1st, 1990 and December 31st, 2017.ResultsA total of 63 publications were retrieved across the 21 MENA countries. Taenia saginata taeniosis was reported in 11 of these countries, whereas unspecified taeniosis was reported for a further seven. Microscopy-based prevalence values ranged between 0.02-8.6%. Bovine cysticercosis prevalence estimates based on meat inspection were only reported for Egypt and Israel, with prevalence data ranging between 0.2-20% and 0.1-9.1% for cattle and buffaloes, respectively. The presence of bovine cysticercosis could be confirmed for 10 additional countries through OIE reports.ConclusionsHuman taeniosis occurrence was confirmed for 86% (18/21) of the countries in the MENA region, although in several of these countries the species responsible was not specified. Religious prohibitions on the consumption of pork and the limited extent of pig farming across much of this region, however, suggest that many reported taeniosis cases are likely to be attributable to T. saginata rather than Taenia solium or Taenia asiatica. There was a paucity of data regarding both the prevalence and economic impact of bovine cysticercosis. More detailed epidemiological data on both T. saginata taeniosis and bovine cysticercosis could be obtained by adopting an integrated One Health approach, considering the characteristics (e.g. ecosystem related and sociopolitical aspects) of the MENA region. Compared with more conventional approaches, this could lead to an enhanced performance and cost-effectiveness of surveillance systems

ASSESSING THE IMPACT OF ALFALFA (MEDICAGO SATIVA) CROP ON GROUNDWATER RESOURCES IN THE EMIRATE of ABU DHABI USING GEOSPATIAL TECHNIQUES

Groundwater is a major source of fresh water in the world, especially in arid and semi-arid countries like the United Arab Emirates (UAE), where rainfall is not evenly distributed through the four seasons of the year. Therefore, it is necessary to pay serious attention to the importance of preserving groundwater resources. The agriculture sector poses a real threat to groundwater. Irrigated crop cultivation practices change groundwater levels as a result of cultivating crops or farming plants that consume large amounts of water. Alfalfa is an example of a high-water consuming crop, being a widely cultivated crop in the UAE. This research has been conducted with the objective of studying the impact of the alfalfa-cultivated areas on groundwater. It is based on calculating the groundwater level (GWL) in wells located near or inside a number of farms, with the end goal of generating a map that shows the areas planted with alfalfa in the same area for three different years using images provided by the Landsat satellite. The study assessed in a detailed manner, the expansion of alfalfa-cultivated areas in the Emirate of Abu Dhabi. A total of five vegetation indices (VIs) were calculated and stacked with visible and near infrared bands (VNIR), producing a composite image. The image was then classified applying unsupervised ISODATA algorithm. Furthermore, GWL was calculated using two parameters: the height above mean sea level and the depth of groundwater in the wells. The data were provided by the National Water and Energy Center (NWEC). The aim was to study the effect of the cultivation alfalfa crop on groundwater storage. As a result, we detected an ongoing increase in the area occupied by alfalfa in the last two decades, which increased from 102.32 km2 to 430.59 km2 between 2002 and 2020. The output was cross validated with field samples, and the overall accuracy of the method was around 81.7%. The well measurements, which were located near or inside the farms accessed and used in this study, showed that there was a significant decrease in the average groundwater amount in the Emirate of Abu Dhabi from 2005 to 2013 and that the mean groundwater level (MGWL) has decreased from 41.4 m to 5.11 m between the years 2005 and 2017, despite the fact that the amount of precipitation had not significantly changed during the mentioned period. In conclusion, the study indicates that the more the area is planted with Alfalfa, the lower the groundwater levels are