Dynamics of energy sector and GHG emissions in Saudi Arabia     

A. N. Khondaker  Karim Malik  Nahid Hossain  Shaikh Abdur Razzak  Rouf Ahmad Khan 《Climate Policy》2013,13(4):517-541

The energy sector is the main contributor to GHG emissions in Saudi Arabia. The tremendous growth of GHG emissions poses serious challenges for the Kingdom in terms of their reduction targets, and also the mitigation of the associated climate changes. The rising trend of population and urbanization affects the energy demand, which results in a faster rate of increase in GHG emissions. The major energy sector sources that contribute to GHG emissions include the electricity generation, road transport, desalination plants, petroleum refining, petrochemical, cement, iron and steel, and fertilizer industries. In recent years, the energy sector has become the major source, accounting for more than 90% of national CO₂ emissions. Although a substantial amount of research has been conducted on renewable energy resources, a sustainable shift from petroleum resources is yet to be achieved. Public awareness, access to energy-efficient technology, and the development and implementation of a legislative framework, energy pricing policies, and renewable and alternative energy policies are not mature enough to ensure a significant reduction in GHG emissions from the energy sector. An innovative and integrated solution that best serves the Kingdom's long-term needs and exploits potential indigenous, renewable, and alternative energy resources while maintaining its sustainable development stride is essential.

Policy relevance

The main contributor to GHG emissions in Saudi Arabia is the energy sector that accounts for more than 90% of the national CO₂ emissions. Tremendous growth of GHG emissions poses serious challenges for the Kingdom in their reduction and mitigating the associated climate changes. This study examines the changing patterns of different activities associated with energy sector, the pertinent challenges, and the opportunities that promise reduction of GHG emissions while providing national energy and economic security. The importance of achieving timely, sustained, and increasing reductions in GHG emissions means that a combination of policies may be needed. This study points to the long-term importance of making near- and medium-term policy choices on a well-informed, strategic basis. This analytical paper is expected to provide useful information to the national policy makers and other decision makers. It may also contribute to the GHG emission inventories and the climate change negotiations.  相似文献   

Deforestation effects on soil properties,runoff and erosion in northern Iran   总被引：2，自引：0，他引：2  

Ataollah Kavian  Ali Azmoodeh  Karim Solaimani 《Arabian Journal of Geosciences》2014,7(5):1941-1950

Improper cultivation practices are seriously degrading native forest ecosystems in northern Iran. Hence, the objectives of this study are to compare selected soil properties, runoff amount, erosion and also introducing equations to predict the runoff and soil erosion in three types of land use (forest, garden and cultivated). A simple portable rainfall simulator has been set in 90 random points to create experimental rainfall. Result showed that changes in natural forest led to a significant clay, organic carbon of soil, total N and antecedent soil moisture decrease and sand, pH and bulk density increasing. The rainfall runoff experiments indicate that runoff content of the natural forest soils was 35 % and respectively 38.45 % higher than the garden and cultivated land soils .This result could be related to the higher antecedent soil moisture in natural forest compared with the other land uses. According to the obtained results, garden soil erosion and cultivated land was 1.351 and respectively 1.587 times higher than the forest. The correlation matrix revealed that runoff content was positively correlated with antecedent soil moisture, bulk density and silt, and negatively with soil organic carbon, total N and sand. Also, soil organic carbon, total N, clay and sand showed negative correlation with soil erosion, while there is a positive correlation between erosion and silt, bulk density, pH and antecedent soil moisture. The results of multiple linear regression showed that runoff in forest, garden and cultivated land can be predicted with correlation coefficient of 0.637, 0.547 and 0.624, respectively. The correlation coefficients of 0.798, 0.628 and 0.560 in equations indicate their moderate potential in simulating soil erosion.  相似文献   

Fast direct sampling for multiple-point stochastic simulation   总被引：1，自引：0，他引：1  

Mohammad J. Abdollahifard  Karim Faez 《Arabian Journal of Geosciences》2014,7(5):1927-1939

Multiple-point statistics simulation has recently attracted significant attention for the simulation of complex geological structures. In this paper, a fast direct sampling (FDS) algorithm is presented based on a fast gradient descent pattern matching strategy. The match is directly extracted from the training image (TI) and so the method does not require intensive preprocessing and database storage. The initial node of the search path is selected randomly but the following nodes are selected in a principled manner so that the path is conducted to the right match. Each node is selected based on the matching accuracy and the behavior of the TI in the previous node. A simple initialization strategy is presented in this paper which significantly accelerates the matching process at the expense of a very naïve preprocessing stage. The proposed simulation algorithm has several outstanding advantages: it needs no (or very limited) preprocessing, does not need any database storage, searches for the match directly in the TI, is not limited to fixed size patterns (the pattern size can be easily changed during simulation), is capable of handling both continuous and categorical data, is capable of handling multivariate data, and finally and more importantly, is a fast method while maintaining high standards for the matching quality. Experiments on different TIs reveal that the simulation results of FDS and DS are comparable in terms of pattern reproduction and connectivity while FDS is far faster than DS.  相似文献   

Hierarchical approach to hydrological model calibration     

Ayfer Ozdemir  Ugur Murat Leloglu  Karim C. Abbaspour 《Environmental Earth Sciences》2017,76(8):318

Hydrological models have been widely used for water resources management. Successful application of hydrological models depends on careful calibration and uncertainty analysis. Spatial unit of water balance calculations may differ widely in different models from grids to hydrological response units (HRU). The Soil and Water Assessment Tool (SWAT) software uses HRU as the spatial unit. SWAT simulates hydrological processes at sub-basin level by deriving HRUs by thresholding areas of soil type, land use, and slope combinations. This may ignore some important areas, which may have great impact on hydrological processes in the watershed. In this study, a hierarchical HRU approach was developed in order to increase model performance and reduce computational complexity simultaneously. For hierarchical optimization, HRUs are first divided into two-HRU types and are optimized with respect to some relevant influence parameters. Then, each HRU is further divided into two. Each child HRU inherits the optimum parameter values of the parent HRU as its initial value. This approach decreases the total calibration time while obtaining a better result. The performance of the hierarchical methodology is demonstrated on two basins, namely Sarisu-Eylikler and Namazgah Dam Lake Basins in Turkey. In Sarisu-Eylikler, we obtained good results by a combination of curve number (CN2), soil hydraulic conductivity, and slope for generating HRUs, while in Namazgah use of only CN2 gave better results.  相似文献   

Hyperspectral image betweenness centrality clustering based adaptive spatial and spectral neighborhood approach for anomaly detection     

Karim Saheb Ettabaa  Manel Ben Salem  Med Salim Bouhlel 《Arabian Journal of Geosciences》2017,10(18):412

Segmentation-based anomaly detectors proceeds to the clustering of the hyperspectral image as a first step. However, most of the well-known clustering methods cluster anomalous pixels as a part of the background. This paper presents a new hyperspectral image clustering approach based on the betweenness centrality measure. The proposed approach starts by the construction of an adaptive spatial and spectral neighborhood for each pixel. This neighborhood is based on the selection of the nearest spectral and spatial neighbors in multiple windows around each pixel to allow well-suited representation of the image features. In the next step, this neighborhood is clustered based on the edge betweenness measure algorithm that splits the image into regions sharing similar features. This approach (1) allows the reduction of intercluster relationship, (2) favors intracluster relations, and (3) preserves small clusters that can hold anomalous pixels. Experimental results show that the proposed approach is efficient for clustering and overcomes the state of the art approaches.  相似文献   

Finite strain analysis for deformed Neoproterozoic rock associations of the Al Amar fault zone,Eastern Arabian Shield,Saudi Arabia     

Mohammed  Lami Abdel Karim Nouaman  Kassem  Osama Mohamed Kaoud  Al Bassam  Abdel Aziz Mohamed 《Arabian Journal of Geosciences》2020,13(6):1-6

Arabian Journal of Geosciences - In this work, quantitative analysis of coastal zone landform morphology is carried out through the integration of landscape index, remote sensing (RS) and...  相似文献