The status of forest carbon markets in Latin America.

Tropical rainforests of Latin America (LATAM) are one of the world's largest carbon sinks, with substantial future carbon sequestration potential and contributing a major proportion of the global supply of forest carbon credits. LATAM is poised to contribute predominantly towards high-quality forest carbon offset projects designed to reduce emissions from deforestation and forest degradation, halt biodiversity loss, and provide equitable conservation benefits to people. Thus, carbon markets, including compliance carbon markets and voluntary carbon markets continue to expand in LATAM. However, the extent of the growth and status of forest carbon markets, pricing initiatives, stakeholders, amongst others, are yet to be explored and extensively reviewed for the entire LATAM region. Against this backdrop, we reviewed a total of 299 articles, including peer-reviewed and non-scientific gray literature sources, from January 2010 to March 2023. Herein, based on the extensive literature review, we present the results and provide perspectives classified into five categories: (i) the status and recent trends of forest carbon markets (ii) the interested parties and their role in the forest carbon markets, (iii) the measurement, reporting and verification (MRV) approaches and role of remote sensing, (iv) the challenges, and (v) the benefits, opportunities, future directions and recommendations to enhance forest carbon markets in LATAM. Despite the substantial challenges, better governance structures for forest carbon markets can increase the number, quality and integrity of projects and support the carbon sequestration capacity of the rainforests of LATAM. Due to the complex and extensive nature of forest carbon projects in LATAM, emerging technologies like remote sensing can enable scale and reduce technical barriers to MRV, if properly benchmarked. The future directions and recommendations provided are intended to improve upon the existing infrastructure and governance mechanisms, and encourage further participation from the public and private sectors in forest carbon markets in LATAM.

Ecotourism and mangrove conservation in Southeast Asia: Current trends and perspectives.

Mangroves in Southeast Asia provide numerous supporting, provisioning, regulating, and cultural services that are crucial to the environment and local livelihoods since they support biodiversity conservation and climate change resilience. However, Southeast Asia mangroves face deforestation threats from the expansion of commercial aquaculture, agriculture, and urban development, along with climate change-related natural processes. Ecotourism has gained prominence as a financial incentive tool to support mangrove conservation and restoration. Through a systematic literature review approach, we examined the relationships between ecotourism and mangrove conservation in Southeast Asia based on scientific papers published from 2010 to 2022. Most of the studies were reported in Indonesia, Malaysia, Philippines, Thailand, and Vietnam, respectively, which were associated with the highest number of vibrant mangrove ecotourism sites and largest mangrove areas compared to the other countries of Southeast Asia. Mangrove-related ecotourism activities in the above countries mainly include boat tours, bird and wildlife watching, mangrove planting, kayaking, eating seafood, and snorkeling. The economic benefits, such as an increase in income associated with mangrove ecotourism, have stimulated infrastructural development in ecotourism destinations. Local communities benefited from increased access to social amenities such as clean water, electricity, transportation networks, schools, and health services that are intended to make destinations more attractive to tourists. Economic benefits from mangrove ecotourism motivated the implementation of several community-based mangrove conservation and restoration initiatives, which attracted international financial incentives and public-private partnerships. Since mangroves are mostly located on the land occupied by indigenous people and local communities, ensuring respect for their land rights and equity in economic benefit sharing may increase their intrinsic motivation and participation in mangrove restoration and conservation initiatives. Remote sensing tools for mangrove monitoring, evaluation, and reporting, and integrated education and awareness campaigns can ensure the long-term conservation of mangroves while sustaining ecotourism's economic infrastructure and social amenities benefits.

Investigating the succession process of native desert plants over hydrocarbon-contaminated soils using remote sensing techniques.

Hydrocarbon-contaminated soils are considered as one of the major environmental issues that harm human well-being, particularly in arid regions of the world. Phytoremediation is a possible mitigation measure for this issue and has been suggested as it is cost-effective compared with other remediation technologies for soil clean-up, such as soil thermal treatment and soil washing. However, there are still gaps in the literature regarding the behavior of annual and perennial desert plants and their ability to survive in hydrocarbon-contaminated soils in arid ecosystems. Therefore, this study aims to develop an integrated approach using remote sensing techniques to understand the behavior of annual and perennial desert plants over different types of oil-contaminated soils (oil tarcrete, wet-oil lake, bare soil, and vegetation cover) in the Kuwait Desert and to explore the impact of climate and physical soil properties on the regrowth of native desert plants. The Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and ferrous iron (Fe2+) index (FI) were used to determine the changes in oil contamination and vegetation cover from 1992 to 2002, and 2013-2020. Subsequently, statistical tests were performed to determine the influence of climatic and soil physical characteristics on changes in hydrocarbon contamination and desert plant behavior. The results showed that hydrocarbon contamination was high at the study sites in the first six years (1992-1997) after contamination, and then decreased in the following years. However, vegetation cover was low in the first six years but significantly increased after 1998, reaching >65%. It was also found that annual plants had the highest distribution rate compared to perennial plants, which mainly depended on the soil type. We concluded that certain annual and perennial plants could successfully grow over tarcrete-contaminated sites, making these sites more suitable for the restoration of native desert plants than hydrocarbon-contaminated sites. We also observed that the succession process of vegetation growth over hydrocarbon-contaminated soils could be associated with vegetation growth on a clean sediment layer covering the oil layer. Additionally, we observed that the remobilization of aeolian sediment over many contaminated sites in Kuwait resulted in the accumulation of organic matter, plant seeds, and dust particles that create layers of nutrient-rich soil for the initial growth of plants.

Investigating the applicability of UAVs in characterizing desert shrub biomass and developing biological indicators for the selection of suitable revegetation sites.

This study focused on evaluating factors influencing the growth of perennial shrubs by integrating field-based experiments and spatial analysis using unmanned aerial vehicles (UAVs) to identify ecological indicators that can help detect potential locations for restoration and revegetation of native plants. The experiment was implemented in the Al-Abduli protected area in Kuwait, which is mainly dominated by a Rhanterium epapposum community (desert shrub). Aerial imagery of the study site was acquired using UAVs during the growing season to estimate the desert shrub biomass and carbon stock. Then, soil samples were collected based on vegetation density to determine the impact of the soil's physical and chemical properties on vegetation biomass, growth, and distribution. It was found that shrub biomass was significantly correlated with crown area and shrub volume. We also observed that annual plants support the growth of perennial shrubs, as the mean shrub height and crown area (CA) are significantly higher, with averages of 0.7 m and 3 cm, respectively, in the presence of high annual plant density. However, shrubs in plots with low annual density had an average shrub height of 0.5 m and CA of 1.4 cm. Annual plants also enhance the soil by providing approximately 50% higher soil moisture, phosphorous (P), organic matter (OM), and carbon dioxide (CO2) sequestration. In addition, annual plants are mainly supported by loamy soils in the deeper soil layers. We concluded that locations covered with annual plants represent suitable soils and that this can be considered a biological indicator for convenient locations for restoration and revegetation of native perennial shrubs. Remote sensing technologies could be utilized for initial assessments to detect sites that may support annual plant growth over a large scale for classification as potential restoration and revegetation areas.

The use of spatial empirical models to estimate soil erosion in arid ecosystems.

The central objective of this project was to utilize geographical information systems and remote sensing to compare soil erosion models, including Modified Pacific South-west Inter Agency Committee (MPSIAC), Erosion Potential Method (EPM), and Revised Universal Soil Loss Equation (RUSLE), and to determine their applicability for arid regions such as Kuwait. The northern portion of Umm Nigga, containing both coastal and desert ecosystems, falls within the boundaries of the de-militarized zone (DMZ) adjacent to Iraq and has been fenced off to restrict public access since 1994. Results showed that the MPSIAC and EPM models were similar in spatial distribution of erosion, though the MPSIAC had a more realistic spatial distribution of erosion and presented finer level details. The RUSLE presented unrealistic results. We then predicted the amount of soil loss between coastal and desert areas and fenced and unfenced sites for each model. In the MPSIAC and EPM models, soil loss was different between fenced and unfenced sites at the desert areas, which was higher at the unfenced due to the low vegetation cover. The overall results implied that vegetation cover played an important role in reducing soil erosion and that fencing is much more important in the desert ecosystems to protect against human activities such as overgrazing. We conclude that the MPSIAC model is best for predicting soil erosion for arid regions such as Kuwait. We also recommend the integration of field-based experiments with lab-based spatial analysis and modeling in future research.

AI-assisted systematic review on remediation of contaminated soils with PAHs and heavy metals.

This systematic review addresses soil contamination by crude oil, a pressing global environmental issue, by exploring effective treatment strategies for sites co-contaminated with heavy metals and polycyclic aromatic hydrocarbons (PAHs). Our study aims to answer pivotal research questions: (1) What are the interaction mechanisms between heavy metals and PAHs in contaminated soils, and how do these affect the efficacy of different remediation methods? (2) What are the challenges and limitations of combined remediation techniques for co-contaminated soils compared to single-treatment methods in terms of efficiency, stability, and specificity? (3) How do various factors influence the effectiveness of biological, chemical, and physical remediation methods, both individually and combined, in co-contaminated soils, and what role do specific agents play in the degradation, immobilization, or removal of heavy metals and PAHs under diverse environmental conditions? (4) Do AI-powered search tools offer a superior alternative to conventional search methodologies for executing an exhaustive systematic review? Utilizing big-data analytics and AI tools such as Litmaps.co, ResearchRabbit, and MAXQDA, this study conducts a thorough analysis of remediation techniques for soils co-contaminated with heavy metals and PAHs. It emphasizes the significance of cation-π interactions and soil composition in dictating the solubility and behavior of these pollutants. The study pays particular attention to the interplay between heavy metals and PAH solubility, as well as the impact of soil properties like clay type and organic matter on heavy metal adsorption, which results in nonlinear sorption patterns. The research identifies a growing trend towards employing combined remediation techniques, especially biological strategies like biostimulation-bioaugmentation, noting their effectiveness in laboratory settings, albeit with potentially higher costs in field applications. Plants such as Medicago sativa L. and Solanum nigrum L. are highlighted for their effectiveness in phytoremediation, working synergistically with beneficial microbes to decompose contaminants. Furthermore, the study illustrates that the incorporation of biochar and surfactants, along with chelating agents like EDTA, can significantly enhance treatment efficiency. However, the research acknowledges that varying environmental conditions necessitate site-specific adaptations in remediation strategies. Life Cycle Assessment (LCA) findings indicate that while high-energy methods like Steam Enhanced Extraction and Thermal Resistivity - ERH are effective, they also entail substantial environmental and financial costs. Conversely, Natural Attenuation, despite being a low-impact and cost-effective option, may require prolonged monitoring. The study advocates for an integrative approach to soil remediation, one that harmoniously balances environmental sustainability, cost-effectiveness, and the specific requirements of contaminated sites. It underscores the necessity of a holistic strategy that combines various remediation methods, tailored to meet both regulatory compliance and the long-term sustainability of decontamination efforts.

Remote sensing-based mangrove blue carbon assessment in the Asia-Pacific: A systematic review.

Accurate measuring, mapping, and monitoring of mangrove forests support the sustainable management of mangrove blue carbon in the Asia-Pacific. Remote sensing coupled with modeling can efficiently and accurately estimate mangrove blue carbon stocks at larger spatiotemporal extents. This study aimed to identify trends in remote sensing/modeling employed in estimating mangrove blue carbon, attributes/variations in mangrove carbon sequestration estimated using remote sensing, and to compile research gaps and opportunities, followed by providing recommendations for future research. Using a systematic literature review approach, we reviewed 105 remote sensing-based peer-reviewed articles (1990 - June 2023). Despite their high mangrove extent, there was a paucity of studies from Myanmar, Bangladesh, and Papua New Guinea. The most frequently used sensor was Sentinel-2 MSI, accounting for 14.5 % of overall usage, followed by Landsat 8 OLI (11.5 %), ALOS-2 PALSAR-2 (7.3 %), ALOS PALSAR (7.2 %), Landsat 7 ETM+ (6.1 %), Sentinel-1 (6.7 %), Landsat 5 TM (5.5 %), SRTM DEM (5.5 %), and UAV-LiDAR (4.8 %). Although parametric methods like linear regression remain the most widely used, machine learning regression models such as Random Forest (RF) and eXtreme Gradient Boost (XGB) have become popular in recent years and have shown good accuracy. Among a variety of attributes estimated, below-ground mangrove blue carbon and the valuation of carbon stock were less studied. The variation in carbon sequestration potential as a result of location, species, and forest type was widely studied. To improve the accuracy of blue carbon measurements, standardized/coordinated and innovative methodologies accompanied by credible information and actionable data should be carried out. Technical monitoring (every 2-5 years) enhanced by remote sensing can provide accurate and precise data for sustainable mangrove management while opening ventures for voluntary carbon markets to benefit the environment and local livelihood in developing countries in the Asia-Pacific region.

Countries' vulnerability to food supply disruptions caused by the Russia-Ukraine war from a trade dependency perspective.

Disruptions of key food and fertilizer exports from Russia and Ukraine have exposed many countries to challenges accessing some commodities since these countries' war began. We evaluated the short-term, external, and direct impacts of disruptions of six food commodities and three types of fertilizer supplies from Russia and Ukraine on food access for all trading partners of the two countries by applying a set of trade and socioeconomic indicators. We found that the external food supplies of 279 countries and territories were affected to varying degrees; 24 countries-especially Georgia, Armenia, Kazakhstan, Azerbaijan, and Mongolia-are extremely vulnerable because they depend almost entirely on a variety of food imports from Russia and Ukraine. Access to fertilizers was affected in 136 countries and territories, particularly Estonia (potassic fertilizer), Mongolia (nitrogenous fertilizers), Kazakhstan (mixed fertilizers), and Brazil, the United States, China, and India (all types of fertilizers). An integrated assessment of countries' import types, purchasing power parity per capita, and populations indicated that the Democratic Republic of the Congo, Ethiopia, Egypt, and Pakistan are most vulnerable to such supply disruptions. Development of research into diversification and decentralization strategies for food access is needed to guide stable food supply policies.

A Preliminary Assessment of Global CO2: Spatial Patterns, Temporal Trends, and Policy Implications.

This study offers a comprehensive analysis of the distribution, evolution, and driving factors of CO2 emissions from 1990 to 2016 at multiple spatial scales. Utilizing 26 indicators encompassing various facets of CO2 emissions, it is employed principal component analysis (PCA) and empirical orthogonal functions (EOFs) to identify the dominant characteristics of global CO2 emissions. This model retained three core components, accounting for 93% of the global CO2 variation, reflecting emission trajectories and associated economic metrics, such as Gross domestic product (GDP). The analysis differentiated the effects of these components based on countries' economic standings. Using a novel aggregated index, significant national contributors to global CO2 emissions are pinpointed. Notably, the leading contributors are found among developed nations (e.g., the United States, Canada, Japan), Gulf states (e.g., Saudi Arabia, Qatar), and emerging economies (e.g., China, Brazil, Mexico). Furthermore, these results highlight that shifts in global CO2 emissions over the past 30 years are predominantly influenced by factors like industrial emissions and GDP. Results also demonstrate a distinct relationship between a country's CO2 emissions and its physical and socioeconomic factors. Specifically, the nation's coastline length, population density in coastal regions, and the diversity of its climatic conditions significantly influence its carbon footprint.

Influence of urban forests on residential property values: A systematic review of remote sensing-based studies.

Urban forests provide direct and indirect benefits to human well-being that are increasingly captured in residential property values. Remote Sensing (RS) can be used to measure a wide range of forest and vegetation parameters that allows for a more detailed and better understanding of their specific influences on housing prices. Herein, through a systematic literature review approach, we reviewed 89 papers (from 2010 to 2022) from 21 different countries that used RS data to quantify vegetation indices, forest and tree parameters of urban forests and estimated their influence on residential property values. The main aim of this study was to understand and provide insights into how urban forests influence residential property values based on RS studies. Although more studies were conducted in developed (n = 55, 61.7%) than developing countries (n = 34, 38.3%), the results indicated for the most part that increasing tree canopy cover on property and neighborhood level, forest size, type, greenness, and proximity to urban forests increased housing prices. RS studies benefited from spatially explicit repetitive data that offer superior efficiency to quantify vegetation, forest, and tree parameters of urban forests over large areas and longer periods compared to studies that used field inventory data. Through this work, we identify and underscore that urban forest benefits outweigh management costs and have a mostly positive influence on housing prices. Thus, we encourage further discussions about prioritizing reforestation and conservation of urban forests during the urban planning of cities and suburbs, which could support UN Sustainable Development Goals (SDGs) and urban policy reforms.

Revegetation of native desert plants enhances food security and water sustainability in arid regions: Integrated modeling assessment.

Food security and water sustainability in arid and semiarid regions are threatened by rapid population growth, declining natural resources, and global climate change. Countries in the arid regions compensate meat import by raising domestic livestock with cultivated green fodder, which diminishes lands for other crops and depletes precious water resources. This study presents for the first time an in-depth integrated food water ecosystem (FWEco) nexus modeling on the feasibility of restoring 10% of Kuwait's desert as grazing rangeland to alleviate water consumption from fodder production. Our results showed that revegetating 10% of the country's land with native species could support up to 23% of domestic livestock through natural grazing at optimal coverage (70%) and high productivity, and decrease water consumption by up to 90%. However, depending solely on natural rainfall is unlikely to achieve the optimal coverage. Strategic supplemental irrigation in the fall season (e.g., October and November) is required to maximize vegetation coverage and enhance food security and water sustainability. Significantly, strategic irrigation results in much lower net water consumption because irrigating native species requires much less water than green fodder cultivation. Therefore, revegetating desert lands with native species to restore their natural grazing service can be a sustainable approach to simultaneously improve food security and water sustainability in arid landscapes.

The Impact of Different Types of Hydrocarbon Disturbance on the Resiliency of Native Desert Vegetation in a War-Affected Area: A Case Study from the State of Kuwait.

This study assesses the impact of total petroleum hydrocarbon (TPH) concentration and soil parameters (heavy metals, chemical properties, and water-soluble boron) on the succession process of vegetation survival in the Al-Burgan oil field in Kuwait. A total of 145 soil samples were randomly collected from the three main types of hydrocarbon contamination, including dry oil lake (DOL), wet oil lake (WOL), and tarcrete. Sampling was also extended to noncontaminated bare soils that were considered reference sites. Remote-sensing data from Sentinel-2 were also processed to assess the level of contamination in relation to soil surface cover. The results showed that TPH concentration was significantly higher in WOL and DOL (87,961.4 and 35,740.6 mg/kg, respectively) compared with that in tarcrete (24,063.3 mg/kg), leading to a significant increase in soil minerals and heavy metals, greater than 50 mg/kg for Ba, and 10 mg/kg for V, Zn, Ni, and Cr. Such high concentrations of heavy metals massively affected the native vegetation's resiliency at these sites (<5% vegetation cover). However, vegetation cover was significantly higher (60%) at tarcrete-contaminated sites, as TPH concentration was lower, almost similar to that in uncontaminated areas, especially at subsurface soil layers. The presence of vegetation at tarcrete locations was also associated with the lower concentration of Ba, V, Zn, Ni, and Cr. The growth of native vegetation was more likely related to the low concentration of TPH contamination at the subsurface layer of the soils in tarcrete sites, making them more suitable sites for restoration and revegetation planning. We concluded that further investigations are required to provide greater insight into the native plants' phytoextraction potential and phytoremediation.

The use of UAV-based remote sensing to estimate biomass and carbon stock for native desert shrubs.

Unmanned Aerial Vehicles (UAVs) have started to receive more attention in the ecological field in the past 15 years, as they provide very high-resolution imagery that ranges from meters to millimeters. Very high-resolution multispectral imagery obtained from UAVs can help in assessing and monitoring native desert vegetation. Thus, this study use UAVs to develop a method to estimate the biomass and carbon stock of native desert shrubs. The method integrates different techniques and software to monitor native plants' coverage, biomass, and carbon stock. The techniques used in this work are also applicable for other native desert shrubs in the region and could support ecosystem managers in assessing and monitoring arid ecosystems and restoration and revegetation programs. A three-stage image and data management are discussed, including: (1) fieldwork and image acquisition using UAVs, (2) image pre-processing, and (3) image processing using different techniques and software.•Determining shrub biomass is not restricted to multispectral data only but could be applicable for RGB data since it mainly depends on the DSM and DTM.•Allometric parameters could help in estimating desert shrub biomass which could be measured easily and rapidly using UAV imagery.•SVM Supervised classification could help in distinguishing between native shrubs and grasses.

The Use of Very-High-Resolution Aerial Imagery to Estimate the Structure and Distribution of the Rhanterium epapposum Community for Long-Term Monitoring in Desert Ecosystems.

The rapid assessment and monitoring of native desert plants are essential in restoration and revegetation projects to track the changes in vegetation patterns in terms of vegetation coverage and structure. This work investigated advanced vegetation monitoring methods utilizing UAVs and remote sensing techniques at the Al Abdali protected site in Kuwait. The study examined the effectiveness of using UAV techniques to assess the structure of desert plants. We specifically examined the use of very-high-resolution aerial imagery to estimate the vegetation structure of Rhanterium epapposum (perennial desert shrub), assess the vegetation cover density changes in desert plants after rainfall events, and investigate the relationship between the distribution of perennial shrub structure and vegetation cover density of annual plants. The images were classified using supervised classification techniques (the SVM method) to assess the changes in desert plants after extreme rainfall events. A digital terrain model (DTM) and a digital surface model (DSM) were also generated to estimate the maximum shrub heights. The classified imagery results show that a significant increase in vegetation coverage occurred in the annual plants after rainfall events. The results also show a reasonable correlation between the shrub heights estimated using UAVs and the ground-truth measurements (R2 = 0.66, p < 0.01). The shrub heights were higher in the high-cover-density plots, with coverage >30% and an average height of 77 cm. However, in the medium-cover-density (MD) plots, the coverage was <30%, and the average height was 52 cm. Our study suggests that utilizing UAVs can provide several advantages to critically support future ecological studies and revegetation and restoration programs in desert ecosystems.

The immediate impact of the associated COVID-19's lockdown campaign on the native vegetation recovery of Wadi Al Batin Tri-state desert.

Law enforcement and massive media awareness, limiting the anthropogenic disturbance, is the way to go for implementing successful desert native vegetation recovery plans. A lesson learned on the resiliency of desert ecosystems throughout studying the native vegetation coverage in the Wadi Al-Batin desert ecosystem during the COVID-19 pandemic. Wadi Al-Batin tri-state desert (89,315 km2) covers the South-western part of Iraq, State of Kuwait, and the North-eastern part of Saudi Arabia. In this study, the spatiotemporal changes in vegetation coverage was detected, by using Sentinel-2A imageries, during the period from 2017 to 2020. For better understanding the impact of associated law enforcement and media practices during COVID-19 pandemic, native vegetation coverage of years with relevant rainfall records were compared. The results revealed that despite receiving the least amount of rain of the three years (≤93 mm), the COVID-19 year (2020) had the highest native vegetation coverage at 28.5% compared with 6% in 2017, and 2% in 2018. These results prove that the main drivers of desert vegetation deterioration are anthropogenic activities, such as quarrying, overgrazing, distractive camping, and off-road vehicle movements. Moreover, the estimated 63% vegetation coverage in Wadi Al-Batin desert in 2019 assures the significant role of precipitation in desert vegetation recovery. This bulk increase in vegetation coverage detected during COVID-19 pandemic shows that the desert vegetation adapts to harsh environments (low rainfall) and rapidly recovers once the source of the disturbance was removed by enforcing the environmental rules. Thus, the protection of natural resources and ecosystems can be achieved through the synergy between governments and civil communities, including intensive awareness of environmental impacts via media, enforcing environmental regulations, and promoting regional collaboration.

Use of online resources by undergraduate medical students at College of Medicine, Majmaah University, Kingdom of Saudi Arabia.

The current pandemic has revolutionized medical education with a rapid shift to online teaching and learning strategies. The students have coped by turning to the online resources to keep pace with the change. To determine the type and practice of online resources used by undergraduate medical students and compare the use of online resources with gender and GPA. This was a cross-sectional study in which an online self-administered questionnaire was used to evaluate the type and practices of the online resources used by the medical students during the Covid-19 pandemic. Complete enumeration sampling method was used to collect the data from 180 medical students studying at College of Medicine, Majmaah University, Saudi Arabia. One hundred and thirty students (72.2%) were unaware of the free online resources offered by the University. Most students (58.3%, n = 105) consulted peers for online references. Male students preferred PowerPoint presentations and consulting online resources for studying as compared to the females, whereas females preferred to study textbooks predominantly as compared to males (p = 0.005). Male students significantly shifted to the online resources during the COVID-19 pandemic as compared to females (p = 0.028). Students with the highest GPA scores shifted to online educational resources during pandemic. A significant proportion of the undergraduate medical students at College of Medicine, Majmaah University used online educational resources for learning. We recommend that the college administration for deliberation with the medical educationalists for necessary curricular amendments and taking necessary steps to make the college Academic supervision and mentorship program more proactive to meet the challenges of students' use of online educational resources.

Mapping air quality zones for coastal urban centers.

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land-sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year's worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates. IMPLICATIONS: A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land-sea breeze effects that can be used to manage local air quality in areas of similar microclimates.