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.

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.

The impact of COVID-19 lockdowns on surface urban heat island changes and air-quality improvements across 21 major cities in the Middle East.

This study investigates changes in air quality conditions during the restricted COVID-19 lockdown period in 2020 across 21 metropolitan areas in the Middle East and how these relate to surface urban heat island (SUHI) characteristics. Based on satellite observations of atmospheric gases from Sentinel-5, results indicate significant reductions in the levels of atmospheric pollutants, particularly nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO). Air quality improved significantly during the middle phases of the lockdown (April and May), especially in small metropolitan cities like Amman, Beirut, and Jeddah, while it was less significant in "mega" cities like Cairo, Tehran, and Istanbul. For example, the concentrations of NO2 in Amman, Beirut, and Jeddah decreased by -56.6%, -43.4%, and -32.3%, respectively, during April 2020, compared to April 2019. Rather, there was a small decrease in NO2 levels in megacities like Tehran (-0.9%) and Cairo (-3.1%). Notably, during the lockdown period, there was a decrease in the mean intensity of nighttime SUHI, while the mean intensity of daytime SUHI experienced either an increase or a slight decrease across these locations. Together with the Gulf metropolitans (e.g. Kuwait, Dubai, and Muscat), the megacities (e.g. Tehran, Ankara, and Istanbul) exhibited anomalous increases in the intensity of daytime SUHI, which may exceed 2 °C. Statistical relationships were established to explore the association between changes in the mean intensity and the hotspot area in each metropolitan location during the lockdown. The findings indicate that the mean intensity of SUHI and the spatial extension of hotspot areas within each metropolitan had a statistically significant negative relationship, with Pearson's r values generally exceeding - 0.55, especially for daytime SUHI. This negative dependency was evident for both daytime and nighttime SUHI during all months of the lockdown. Our findings demonstrate that the decrease in primary pollutant levels during the lockdown contributed to the decrease in the intensity of nighttime SUHIs in the Middle East, especially in April and May. Changes in the characteristics of SUHIs during the lockdown period should be interpreted in the context of long-term climate change, rather than just the consequence of restrictive measures. This is simply because short-term air quality improvements were insufficient to generate meaningful changes in the region's urban climate.

Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach.

Local, bivariate relationships between coronavirus 2019 (COVID-19) infection rates and a set of demographic and socioeconomic variables were explored at the district level in Oman. To limit multicollinearity a principal component analysis was conducted, the results of which showed that three components together could explain 65% of the total variance that were therefore subjected to further study. Comparison of a generalized linear model (GLM) and geographically weighted regression (GWR) indicated an improvement in model performance using GWR (goodness of fit=93%) compared to GLM (goodness of fit=86%). The local coefficient of determination (R2) showed a significant influence of specific demographic and socioeconomic factors on COVID-19, including percentages of Omani and non-Omani population at various age levels; spatial interaction; population density; number of hospital beds; total number of households; purchasing power; and purchasing power per km2. No direct correlation between COVID- 19 rates and health facilities distribution or tobacco usage. This study suggests that Poisson regression using GWR and GLM can address unobserved spatial non-stationary relationships. Findings of this study can promote current understanding of the demographic and socioeconomic variables impacting the spatial patterns of COVID-19 in Oman, allowing local and national authorities to adopt more appropriate strategies to cope with this pandemic in the future and also to allocate more effective prevention resources.

Wastewater treatment, reuse, and disposal-associated effects on environment and health.

This paper presents the review of the literature published in the year 2019 related to treatment and reuse of wastewater and effects on the environment and human health. The scientific review on the treatment and reuse of wastewaters is divided into various sections in the paper. The review sections cover wastewater management, reuse, removal of microorganisms, and chemical constituents. Besides, the review also covers research focused on wastewater treatment plants, disposal, and the management of wastewater sludge as well as biosolids in the environment. PRACTITIONER POINTS: This paper highlights the review of scientific literature published in the year 2019.Review provide issues related to health risks associated with human and the general environment on the reuse of wastewater, treatment as well as disposal.The literature review covers selected papers relevant to the topic.

Ecological and human health risk assessment.

The literature review presented in this paper includes the ecological and human health risk assessment in the form of receptors in the environment. The main objective of this review to highlight a summary of the many studies undertaken in the year 2019. The first part of the review covers the papers published on the health risk assessment related to human and ecological health. This article focuses on methods and tools utilized for the analysis of scientific studies and the data. The review provides main issues such as interpretation of data, uncertainty, and policies related to the management of risks. The ecological and human health risk assessment is divided into two main sections. Each of these sections presents in broad the risk assessment process namely pollution studies, remediation, and tools required for the management of natural resources and the environment.

Pesticides and herbicides.

This paper highlights a review of scientific papers published in the year 2019 regarding pesticides and herbicides. The scientific review presented in this paper includes the presence and occurrence of pesticides and herbicides in the environment. The entire review divided into different sections, which are grouped into four main sections. Each of these sections provides studies conducted on toxicology, ecological risk assessment, strategies of treatment, policies, modeling, and guidelines regarding pesticides and herbicides management. PRACTITIONERS POINTS: This paper highlights the review of scientific literature published in the year 2019. The review includes the presence and occurrence of pesticides and herbicides in the environment. The review focuses on toxicology, ecological risk assessment, strategies of treatment, policies, modelling and guidelines regarding pesticides and herbicides management. The literature review covers selected papers relevant to the topic.

Spatiotemporal Assessment of COVID-19 Spread over Oman Using GIS Techniques.

Coronavirus disease (COVID-19), caused by acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a worldwide challenge effecting millions of people in more than 210 countries, including the Sultanate of Oman (Oman). Spatiotemporal analysis was adopted to explore the spatial patterns of the spread of COVID-19 during the period from 29th April to 30th June 2020. Our assessment was made using five geospatial techniques within a Geographical Information System (GIS) context, including a weighted mean centre (WMC), standard deviational ellipses, Moran's I autocorrelation coefficient, Getis-Ord General-G high/low clustering, and Getis-Ord G i ∗ statistic. The Moran's I-/G- statistics proved that COVID-19 cases in datasets (numbers of cases) were clustered throughout the study period. The Moran's I and Z scores were above the 2.25 threshold (a confidence level above 95%), ranging from 2274 cases on 29th April to 40,070 cases on 30th June 2020. The results of G i ∗ showed varying rates of infections, with a large spatial variability between the different wilayats (district). The epidemic situation in some wilayats, such as Mutrah, As-Seeb, and Bowsher in the Muscat Governorate, was more severe, with Z score higher than 5, and the current transmission still presents an increasing trend. This study indicated that the directional pattern of COVID-19 cases has moved from northeast to northwest and southwest, with the total impacted region increasing over time. Also, the results indicate that the rate of COVID-19 infections is higher in the most populated areas. The findings of this paper provide a solid basis for future study by investigating the most resolute hotspots in more detail and may help decision-makers identify targeted zones for alleviation plans. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41748-020-00194-2.