The quest to lower greenhouse gas (GHG) emissions has spurred the progress and viability of many RE technologies. A reduction in the cost of renewable technologies driven by technological improvements, economies of scale, and an increasingly competitive supply chain all made renewable power generation technologies a more cost-competitive option for new power generation capacities in many countries globally (IRENA, 2020). The availability of RE resources varies based on geographical location, while some locations might have more solar resources; others may be better suited for wind or geothermal technologies. Therefore, identifying suitable locations for RE installation is important in maximizing outputs from these technologies. To do this, various data related to the location, weather, topology, framework of existing infrastructure, demand, etc., are all needed in making this decision (Suprova et al., 2021). Several researchers have employed the use of various Multi-Criteria Decision-Making (MCDM) methods in identifying the most suitable sites for RE plant installations based on selected criteria (Yunna and Geng, 2014; Fetanat and Khorasaninejad, 2015; Ao Xuan et al., 2022).

MCDM methods are used by decision-makers to pick the best option when faced with various alternatives and several criteria (Al Garni and Awasthi, 2017). This technique has been used severally in planning renewable energy systems (RES) for their technical, environmental, and economic factors. Fetanat and Khorasaninejad (Fetanat and Khorasaninejad, 2015) used MCDM along with integrated energy planning and coastal management to ascertain the best sites for offshore wind farms in Iran. Xuan et al. (Ao Xuan et al., 2022) using a combination of MCDM methods for assigning weights to criteria used the method for the location selection of a solar-powered hydrogen plant in Uzbekistan. Wu and Geng (Yunna and Geng, 2014) used the Analytic Hierarchy Process (AHP) to establish a decision framework for the site selection of a hybrid solar wind power plant in China. Furthermore, MCDM helps integrate the opinions of multiple decision-makers who are involved in the decision framework but have varying opinions regarding specific criteria or alternatives. This is because it would be inadequate to base the assortment of sites for RE on one criterion. According to Huang et al. (Huang et al., 1995) and Loken (Løken, 2007) MCDM could suitably handle site selection for energy planning problems.

MCDM methods have been extensively utilized in conjunction with Geographic Information Systems (GIS) to estimate both qualitative and quantitative spatial criteria. GIS has the capability of determining the spatial and temporal patterns or the characteristic attributes of events. The GIS is a cost-effective means used to capture, store, evaluate, model, and present data that is spatially referenced to help solve complex issues in management and planning (Suprova et al., 2021). GIS has been successfully used in mapping RE potentials (Ramachandra and Shruthi, 2007; Wang et al., 2016; Lovrak et al., 2020). By combining MCDM with GIS, the analytical strengths of decision-makers are improved (Messaoudi et al., 2019). Several studies have been carried out on this topic and have been used to identify suitable sites for wind (Sánchez-Lozano et al., 2014; Atici et al., 2015), a hybrid of solar and wind (Jahangiri et al., 2016), solar (Merrouni et al., 2016; Palmer et al., 2019; Okonkwo et al., 2020; Elboshy et al., 2022), and developmental potentials for mining, agriculture, fossil fuels, and RE (Oakleaf et al., 2019). Although the studies reviewed varied in their specific criteria for decision-making, they all shared a common consensus on the effectiveness of integrating GIS with MCDM for identifying appropriate locations for renewable energy (RE) plants. This research study specifically concentrates on the application of MCDM and GIS in the site selection process for utility-scale solar and wind technologies. Table 1 presents a summary of recent studies that have utilized different MCDM techniques combined with GIS to evaluate potential sites for solar and wind power plants.

Upon examining the studies listed in Table 1, it becomes evident that the authors considered various constraints that could limit the feasibility of solar or wind energy deployment in specific areas. These constraints included reserved areas, built-up areas, roads, and land use, amongst other factors. To account for these constraints, the authors employed a buffer zone approach, which involved creating a buffer around these restricted zones to identify suitable sites for solar and wind energy installations. They also assigned weights using MCDM based on the opinions of decision-makers and the objective to be reached. The articles reviewed highlighted that site selection for renewable energy plants is influenced by several key criteria. These criteria include economy, environment, risks, geography, ecology, climate, and society, each of which encompasses various sub-criteria (Ghasempour et al., 2019; Suprova et al., 2021). The economic aspect involves considerations such as cost-effectiveness and financial viability. The environmental criteria encompass factors like impact on ecosystems, biodiversity, and natural resources. Risk-related criteria may include hazards, safety concerns, and vulnerability to natural disasters. Geographic considerations involve aspects such as terrain, topography, and land availability. Ecological criteria encompass the preservation of sensitive habitats and species. Climate factors include solar irradiance, wind speed, and other climate patterns. Finally, societal criteria encompass aspects like public acceptance and community engagement.

The installation of RE systems is a way to decrease carbon emissions, however, when we decoupled the energy sector into final energy use, only 17% of total energy consumption is used in power generation, and another 51% was used in heating and cooling, while 32% is used in the transportation sector (British Petroleum, 2021). Despite this, RE use in transportation only accounts for 3.4% of total energy use as compared to 27.1% in the power sector (Antoine Ibrahim et al., 2021). This is because aviation, maritime, and long-haul road transportation are sectors that still require viable decarbonization solutions. Along with other sectors like the steel and petrochemical industries, individuals, businesses, organizations, and nations can also find other means to decrease their GHG emissions. One such way is through carbon offset. This is a way of reaching carbon neutrality by ensuring a balance between the amount of greenhouse gas emitted and the amount removed from the atmosphere. Carbon offsets provide a mechanism to compensate for carbon dioxide (CO₂) and other greenhouse gas (GHG) emissions by supporting projects that result in the reduction or removal of emissions elsewhere (Heintzman, 2021). Carbon offset schemes are in line with the Clean Development Mechanism (CDM) under Article 12 of the Kyoto Protocol aimed at helping developing countries to reduce their carbon footprints and ensuring industrialized nations comply with their emissions reduction commitments (United Nations, 1998). This is achieved through any project that reduces, avoids, or removes GHG emissions–these include land restoration, reforestation, afforestation, forest conservation, green building, or RE generation (Broekhoff et al., 2019). Both the 2005 Kyoto Protocol of the United Nations Framework Convention on Climate Change (UNFCCC) and the 2006 Intergovernmental Panel on Climate Change (IPCC) identify revegetation of areas above 500 m² as an activity that improves the uptake of carbon (Intergovernmental Panel on Climate Change IPCC, 2006; UNFCCC, 2006). Carbon offset programs also yield other social and environmental benefits beyond just GHG reduction, some of which include improvement in air and water quality, enhancing biodiversity, and habitat conservation. To ensure the viability of a carbon offset project, the offset projects must meet specific criteria. These include demonstrating additionality, meaning they exist solely to fulfill the offset requirement; delivering measurable emissions reductions; ensuring the reductions are permanent; and undergoing verification by an independent third party (Schmidt, 2009). Carbon dioxide sequestration occurs naturally through plants, and forests act as large lungs by which carbon dioxide is taken from the air and converted into biomass in the presence of sunlight through a process called photosynthesis (Issa et al., 2019). This shows that forests provide a mitigation route to stabilize GHG concentrations in the atmosphere as an estimated 2–4 G tons of carbon is sequestered annually by the global forests (Qureshi et al., 2012). Domke et al. (Domke et al., 2020) highlighted the importance of forestland as a source of carbon capture in the US and estimated that 1.2 billion planted trees could sequester between 16–28 MMT CO₂ annually. The total carbon stock sequestered by a tree species comprises the carbon in the biomass, soil organic carbon, and carbon litter which refers to the slow decomposition of dead organic debris and dead plants (Qureshi et al., 2012; Rytter and Rytter, 2020). Sharma et al. (Sharma et al., 2021) assessed the carbon sequestration potential of various tree groups. Their findings show that 139.86 tons of CO₂ are sequestered annually from 1997 trees on the campus. Highlighting the significance of trees in storing and sequestering carbon (Coracero and Malabrigo, 2020), assessed the carbon stock of certain tree species in the Philippines. A total of 139 species consisting of 2,239 individuals were identified, the aboveground and belowground biomass of the live trees amounted to 306.48 t/ha. Wotherspoon et al. (Wotherspoon et al., 2014) concluded that the total carbon pools for white cedar, hybrid poplar, red oak, Norway spruce, black walnut, and soybean were 99.4, 113.4, 99.2, 91.3, 91.5, and 71.1 t C/ha. Their result suggests greater atmospheric CO₂ sequestration as compared to conventional farming. Rytter and Rytter (Rytter and Rytter, 2020) in their study comparing the total carbon stock of six species of trees grown in former agricultural land concluded that though the total carbon sequestration rate may vary for different sites, the production of the trees has a quick and positive outcome on its total carbon sequestration. Thomas et al. (Thomas et al., 2007) further highlighted that species choice was the single most important factor for carbon sequestration forestry.

Date Palm Trees (Phoenix dactylifera): Qatar is located in the arid plains of the Arabian Peninsula, it is characterized by extreme heat and water stress leading to large portions of non-arable land (Okonkwo et al., 2021a). Qatar’s northern part is the most suitable for agriculture and this covers 19% of its landmass with a salinity level of 500–3,000 ppm (Darwish and Mohtar, 2013). Currently, agricultural practices for crop and vegetable farming are carried out using high-tech greenhouses. Water used in agriculture is obtained from groundwater abstraction (92%) and the rest of the water is obtained from treated wastewater (66.29 million m³). These conditions limit the species of trees that can be planted to aid atmospheric CO₂ sequestration in Qatar. Under such conditions, a tree that can withstand high temperatures, droughts, and high soil salinity is required. The date palm (Phoenix dactylifera) is a plant species that has existed for thousands of years and is particularly concentrated in the MENA region (Middle East North Africa). Date palms have traditional, religious, and nutritional significance in the region and have been an important part of the farming systems in arid regions (Issa et al., 2019). The date palm tree can thrive in several geographical and climatic conditions and can tolerate high temperatures, droughts, and saline sand (500–2000 ppm) better than any other fruit crop species (Betemariyam and Kefalew, 2022). The date palm (DP) has a lifespan of over 200 years and can grow in high altitudes of 392 m–1,500 m above sea level with an average tree height of 24–30 m. The leaves of the tree are dense (four to five m), with each leaf having approximately 150 leaflets (each leaflet is around 30 cm in length and 2 cm in width) (Al-khayri et al., 2015). The amount of CO₂ and carbon stocks absorbed in the trunk and roots of the tree is dependent on the size of the plant’s green parts, and when compared to other species of the same size, the date palm can absorb significantly greater CO₂ (Sharif et al., 2010).

Water constitutes 25% of the whole tree, while carbon makes up 50% of the dry wood. Sharif et al. (Sharif et al., 2010), estimate that the date palm converts a large amount of CO₂ equivalent to about 200 kg annually as well as produces food. They further estimated that a tree 15 m in height with a diameter of 0.5 m, and a trunk mass of approximately 1,472 kg would have a lifetime amount of 2020.3 kg of CO₂ sequestered as carbon stored in its trunk and roots. Another study estimated the carbon stock of date palm farms in Ethiopia (Betemariyam and Kefalew, 2022) and found the total carbon stock of date palm farms to be 82.3 tonnes of carbon per hectare and calculated the mean biomass carbon stocks of date palm trees older than 20 years to be 238.61 kg/plant. In comparison, this value was found to be 225.58 kg/plant in Abu Dhabi (Issa et al., 2019). Based on a review of the available literature, it is estimated that a single date palm tree can potentially reduce CO₂ emissions by approximately 70–200 kg annually. Moreover, growing date palms on a large scale not only contributes to CO₂ reduction but also has the potential to generate substantial revenue and employment opportunities. With the annual crop yield of dates from a single date palm exceeding 100 kg, the cultivation of date palms can provide economic benefits and job prospects.

The State of Qatar, situated on the northeastern coast of the Arabian Peninsula, covers an area of 11,400 km². It is renowned for its energy security, primarily attributed to the abundant reserves of fossil fuel (Okonkwo et al., 2021b). Qatar is also geographically rich in abundant solar radiation and wind resources making it possible to integrate both solar and wind energy systems into the grid (Okonkwo et al., 2021c). Currently, fossil fuels mainly from the use of gas supply over 99% of the nation’s energy needs (Okonkwo et al., 2021a). Based on the British Petroleum statistical review of world energy, the total carbon emissions from Qatar in the year 2020 amounted to approximately 87 million metric tons (Mt). Out of this total, around 26.2% of the emissions were attributed to activities associated with power generation (British Petroleum, 2021). Indeed, harnessing Qatar’s abundant fossil fuel resources to introduce new renewable generation capacity into the grid would play an important role in reducing the country’s carbon footprint. By expanding the contribution of renewable energy (RE) to the nation’s energy mix, Qatar can lower its emissions and contribute to international efforts in combating climate change (Bohra and Shah, 2020). In this regard, Qatar has an average daily sun hour of 9.5 h with a global horizon irradiance (GHI) of 2,140 kWh/m²/year which makes it a promising location for solar PV systems (Govinda Rao and Al-Kuwari, 2013). Furthermore, Qatar exhibits promising potential for CSP due to its annual direct normal irradiance (DNI) surpassing the required installation threshold. With an annual DNI of over 2008 kWh/m²/year, it exceeds the necessary threshold of 1800 kWh/m²/year, making it conducive for the implementation of CSP projects. Moreover, Qatar’s average wind speed of approximately 4.4 m/s indicates suitability for the installation of small and medium-scale wind turbines. This wind speed range provides favorable conditions for generating wind energy, thereby offering opportunities for wind power projects in the country (Marafia and Ashour, 2002; Govinda Rao and Al-Kuwari, 2013).

Under the Environmental Development Pillar of the Qatar National Vision 2030, the State of Qatar aims to decrease pollution and environmental degradation. In a bid to support this pillar, Qatar’s water and electricity provider, KAHRAMAA has set a goal to meet 20% of its energy demand from RE by 2030. The annual electricity and water consumption for the year 2020 in Qatar were 49 TWh and 691 M m³, respectively, with an estimated 24 Mt of CO₂ emitted from electricity generation activities (KAHRAMAA, 2020). Qatar’s installed electricity generation capacity is 10,579 MW where the maximum and minimum system load is 8600 MW and 2910 MW, respectively (KAHRAMAA, 2020). The initial goal was to reach 1800 MW of solar capacity by 2020 but that has been revised to 2030, however, an 800 MW grid-connected solar plant in Al-Kharsaah is under construction and is scheduled to be commissioned in the second half of 2022 (Gulf Times, 2020). In August of 2021, following the provisions and principles outlined in the United Nations Framework Convention on Climate Change (UNFCCC), the Ministry of Municipality and Environment in Qatar unveiled its Nationally Determined Contribution (NDC). The NDC outlines Qatar’s commitment to reducing its overall greenhouse gas (GHG) emissions as a response to the guidance provided in Article 4.4 of the Paris Agreement. Qatar has pledged to achieve a 25% reduction in its GHG emissions by the year 2030, relative to a baseline scenario. This commitment reflects Qatar’s dedication to actively contribute to global efforts in mitigating climate change and aligning with the goals outlined in the Paris Agreement. (Ministry of Municipality and Environment, 2021).

This study outlines several pathways, which Qatar can explore to achieve its national set goals of reducing GHG emissions by 25% and generating at least 20% of electricity from renewable resources by the year 2030. The RE generation capacity presented in this study is based on weather data from seven weather stations across Qatar. These weather stations take measurements of the wind and solar energy potential in Qatar. This is pioneer research as no literature is available on wind and solar energy generation potential that takes into consideration legal and physical limitations. For instance, a large portion of land is designated as natural reserves to protect wildlife, particularly Arabian Oryx. Similarly, the west coastline is highly populated with important life-supporting infrastructures, these areas occupy a significant portion of land that cannot be utilized for solar or wind energy generation. These legal and physical constraints were not accounted for in previous studies leading to significant uncertainty in national RE potential estimation. Furthermore, previous research has estimated wind power generation from a single location in the northern part mainly due to the data constraints (Marafia and Ashour, 2002; Alnaser and Almohanadi, 1990). This study in considering data from seven weather stations across the country can generate a more representative RE map for solar and wind energy generation and quantify the expected annual electricity generation from these plants. The study also explores Qatar’s potential for carbon offset through planting trees by identifying the date palm (Phoenix dactylifera) as a suitable tree species that would promote atmospheric CO₂ sequestration in the country. Finally, the cost implication of offsetting emissions using verified carbon credits is considered and compared with the option of RE installation. Policy recommendations for emission reduction in other key sectors of the Qatar economy such as the energy industry, other petrochemical industries, and transportation are also made.

This section discusses the various criteria considered in selecting the appropriate site for solar and wind energy installations in Qatar.

The proposed renewable energy technologies (solar PV and wind) are accessed based on the proposed site suitability for each technology and the available renewable resources within the country. Using the maximum possible installed capacity of each technology based on the recommended suitable area, an assessment of renewable share, market economic results, and CO₂ emissions are quantified using the EnergyPLAN tool.

Date palm absorbs CO₂ into organic compounds like sugar (glucose), oxygen, and water using sunlight just like other plants. To calculate the quantity of CO₂ sequestered, the carbon stock of the tree is multiplied by a factor of 3.67, this factor represents the ratio of carbon dioxide to carbon in trees (Pascua et al., 2021).

In this subsection, the study compares various ways of reaching the emissions target of a 25% reduction of GHG by 2030. The study compares the optimum RE installation in the country with the option of tree planting and buying verifiable carbon offset credits from the international market. The various scenarios are investigated under the following rule.

• The installed capacity of RE generation (solar PV and wind) is limited to the most suitable available area.

Areas that are deemed unsuitable for wind energy development due to physical limitations and regulatory constraints are excluded from the estimation of wind and solar energy potential. Figure 3 illustrates the exclusion areas based on factors that strongly influence land exclusion.

After removing these restricted areas, approximately 37% of the total area remains available for wind energy development, equivalent to 4,153 km² out of the research site’s total size of 11,182 km². When considering the size of the non-excluded zones, the municipalities of Shahanaya, Ar Rayyan, and Al Wakrah exhibit the greatest potential for wind energy development. Concerning the overall size of the municipal area, Ash Shamal also has a higher potential. However, the quality of wind in this area is low when compared to Al Khor, Dukhan, and Salwa. In comparison, a larger portion of land is available for solar energy generation 53% (5,899 km²) as compared to the area that is available for wind energy. The main reason for this land increment is the consideration of a larger buffer zone for wind energy generation to protect built and protected areas from the noise pollution created by the wind blades.

Concerning the type of excluded land, the majority of the land is excluded due to legal regulations concerning urban areas, farms, natural protected areas, coastal areas, and the distance buffer around them. The State of Qatar has twelve national reserves designated as protected areas, which consist of Al Reem Reserve, and Khor Al Adaid Reserve followed by smaller size reserves like Al Thakira, Al Eraiq, and Al Rafa Reserves. In addition to the buffer zone of 500 m, those areas close to the national protected areas are given low scores in the AHP. Wildlife including the Arabian Oryx and other reptiles are important natural assets to Qatar. To further enhance their protection, especially from wind turbine noise, surrounding areas are given lower scores while areas further away areas are given higher scores. Similarly, areas surrounding urbanized and farming areas are scored lower to protect residents from noise pollution.

As shown in Figure 4, wind speed varies greatly over the State of Qatar. The northeastern coastal areas, particularly Al Khor and the eastern border areas with Saudi Arabia have greater wind energy potential. In addition, the coastal areas of Dukhan also exhibit positive wind energy potential. However, the majority of the available area in Al Shahaniya and Ar Rayyan municipality is of low wind speed meaning lower wind energy potential. Based on the average wind speed from 7 weather stations, the average wind speed is 5.5 m/s with over 6 m/s in some areas of Al Khor and Salwa. In contrast, solar energy is evenly distributed with small variation in coastal areas as water absorbs more incoming solar radiation as compared to sand because of differences in albedo thus affecting Global Horizontal Irradiance GHI. In addition, the soil texture also influences the GHI as shown in Figure 4. The northern areas have less GHI as compared to the Southern area mainly due to the different soil texture and presence of vegetation.

Based on the modeling, a land suitability map is generated for the potential wind energy generation locations. One of the most important criteria in wind suitability assessment was the wind speed, wind speed exceeds 6 m/s in the northeastern coastal areas in Al Khor and the south-western border area with Saudi Arabia in Abu Samra (Figure 5). From Figure 5, the areas with the darker shades of brown were identified as the most suitable areas for both wind and solar respectively, as compared to the areas within bright yellow colour. The most suitable area for wind is 26 km² which is equal to 1% of the total available land for wind energy generation. The second most suitable area is 663 km² abundantly available in the southwestern coastal areas in Abu Samra and Dukhan and the northeastern areas in Al Khor. The average wind speed in this area is 5.8 m/s which is considered preferred for wind energy generation. The remaining area is moderately and equally suitable for wind energy generation and this area is mostly available in the western coastal areas as most of the eastern coastal areas are urbanized and excluded from the modelling. The indices used in Figure 5 can be better understood using Table 4.

In comparison to wind energy, a larger area is available for solar energy generation. Since the solar irradiance is almost uniform in the State of Qatar with some minute variation in the coastal areas and northern areas the resultant solar suitability map is uniform in terms of suitable land types. A total of 7,889 km² (53%) area is available for solar energy generation. This area is further assessed for solar energy generation suitability based on the high medium and low criteria. A highly suitable area for solar installation is located in the north-eastern coastal area of Al Khor which is about 21 km². The second most suitable area is situated near the urban settlement on the east coast while a large portion of this land is also identified on the west coast. The size of this area is 1,523 km² almost 37% of the total available land. Interestingly, the Al Kharsaah solar power plant (800 MWp) which was expected to be completed by 2022 also comes under the second most suitable land type area (Figure 5). These two land types are located close to urban and protected areas this is because wastewater treatment plants are installed in the urban areas. Wastewater is used for the cleaning of solar panels as dust is one of the most important limiting factors for the solar industry in the State of Qatar. In addition, the use of seawater is not considered in the AHP process as saline water has negative impacts on the efficiency and lifespan of solar panels. The remaining identified suitable area is scattered in the western coastal areas and northern areas. A summary of the land suitability for wind and solar is presented in Table 4.

The section presents the results of the gross electricity production from RES installed based on the highly suitable areas presented in Table 4. For wind energy, the installed capacity is limited to the 663.42 km² (15.93%) suitability presented in Table 4. While for solar PV, installed capacity is initially limited to a 2,000 MW plant representing the 1% most suitable area. According to the National Renewable Energy Laboratory, the capacity-weighted average land use for solar PV is 8.3 acres (0.033 km²)/MW (Ong et al., 2013), and the capacity density of 3.0 ± 1.7 23 MW/km² for wind energy (Paul et al., 2009).

Table 5 shows the result from the EnergyPLAN simulation. In Table 5, the natural gas column represents the base case where all the electricity needs of 49 TWh/year are met by natural gas power plants alone. The subsequent column shows the effect of adding the RES to the energy mix and their subsequent effect on the total cost of the Qatar energy system, CO₂ emissions, and percentage emission reduction witnessed. Adding wind energy to the current system is seen to reduce emissions by 11% as compared to 7.3% from the 2,000 MW solar PV plant. The cost parameter shows that installing renewables would be cheaper over the lifetime of the project due to the recurring cost of natural gas used to run the power plant.

Figure 6 shows the renewable share of electricity produced for a 2,000 MW solar PV plant (blue), a 1921 MW wind plant (orange), and a hybrid (grey) of both systems connected to the existing electricity grid. RES share of electricity produced is seen to peak in May-June for the hybrid system with about 27% share due to the peak solar outputs within that period of the year. Figure 7 illustrates the effect of increasing the capacity of each RES technology on the emissions. It is observed that by adding a thousand MW of solar PV (3,000 MW) the emissions decreased by 0.9 Mt of CO₂ and by 1.44 Mt if 3,000 MW of wind energy could be installed. The results show that Qatar has the potential to meet 20% of energy demand by 2030 from renewable sources using solar PV or a hybrid of wind and solar. In addition, while land suitability might not favor greater than 2,000 MW installation for onshore wind energy, the country has the option of harnessing its huge coastline for offshore wind energy.

An endeavor to develop date palm plantations in the country would benefit the nation significantly in the area of carbon sequestration, job creation, export earnings as well and enhancing biodiversity. Abu-Qaoud (Abu-Qaoud, 2015) estimates that the cost of establishing a date palm offshoot is US$ 100 for the first 3 years. After which production begins in the 4 years and the cost of a tree becomes positive (+US$ 50), with revenue coming from both fruit and offshoots (Daiq, 2007). It should be noted that there is no recent study on the cost of planting date palms in Qatar. Abu-Qaoud’s (Abu-Qaoud, 2015) study was conducted in Palestine during a period that is not recent. Palestine shares a similar climatic profile with Qatar although we envisage that there will exist possible variations in the cost of planting in Qatar due mainly to the higher water stress in Qatar. Based on photosynthesis calculation from Sharif et al. (Sharif et al., 2010), a matured date palm tree (>10 years) would lead to a reduction of about 200 kg (0.2 tonnes) of CO₂ annually. Hence, 10 million trees would absorb 2 Mt of CO₂ annually, and an estimated 36 km² would be sufficient to plant one million date palm trees if they are planted about 5.5 m apart. It should be noted that the carbon stock of date palm trees varies based on the location where they are planted and the ecosystem of the soil. Table 6 shows the projected revenue and cost expected from a date palm tree.

The optimum case presented in this study by adopting RE systems and planting trees could lead to a net annual 12.42 Mt reduction in carbon emissions from the electricity sector. This would represent a reduction of 50.7% in electricity and heating-related emissions but only 14.28% of overall emissions by the country. Table 7 shows the impact of our optimum installed capacity per thousand megawatts on the carbon emissions from this sector. The 14.28% reduction from using RE systems (Solar PV and Wind), and planting date palm trees are short of the 25% (21.75 Mt) national target set for 2030. To achieve the target an additional 7.42 Mt needs to be removed from the current emissions level of 87 Mt per annum.

The international carbon credit market offers another opportunity for corporate bodies to buy verifiable carbon credits to offset their unavoidable carbon emissions. While the cost of carbon credits varies based on project type, size, location, and other determining factors, the New York Mercantile Exchange, Global Emissions Offset CBL futures traded at US$ 7.53/ton in January 2022. This market could evolve to primarily help countries achieve their climate targets–a possibility outlined at COP-26 in Glasgow. Should this be the case, Bloomberg New Energy Finance estimates that the price for verified carbon offset credits could cost $11/ton by 2030, up from just $2.50 in 2020 (Bloomberg New Energy Finance, 2022). Figure 8 presents a cost comparison of various pathways to achieving a 25% (21.75 Mt) reduction in carbon emissions over 20 years. The options presented include:

• Using only verified carbon credit to offset 25% (21.75 Mt) of carbon emissions in Qatar.

Figure 8 is computed based on data from Tables 3 and 6, at an annual interest rate of 3%. The figure shows that while the first 3 years would not have a positive yield on any of the emission reduction options, considerable returns on investments are seen from 2030 for all options paired with the date palm tree due to the potential profits from harvesting their dates.

So far, this study has focused on emissions related to the electricity and heat sectors. The global share of renewable energy use is significantly improving in the electricity generation sector as compared to other sectors (REN 21, 2020). However, a collective effort to decarbonize all sectors is needed if the set goal of 25% by 2030 is to be attained. Figure 9 shows the carbon emissions by sector in Qatar since 1990. Emissions from Qatar’s energy industry accounted for 36% of total emissions in the country in 2019. This is due to the exploration and refining of crude oil and natural gas in the country. As this is a difficult-to-decarbonize sector and a major revenue earner for the country, certain measures can be taken to limit emissions from this sector.