Annual CO2 Emissions Research Articles

Near-Term Suitability Assessment of Deploying DAC System at Airport: A Case Study of 52 Large Airports in China

This study is the first to propose the deployment of direct air capture (DAC) systems at large airports to provide solutions for achieving carbon neutrality in aviation transportation. Here, an estimating model for carbon dioxide (CO2) emissions in the landing and take-off (LTO) phase of large airports was developed, and the suitability of deploying DAC systems at airports was evaluated by the analytic hierarchy process (AHP). This study found that the annual CO2 emissions of 52 large airports in the LTO phase are about 23 Mt, accounting for about 23% of the total CO2 emissions of civil aviation in China. The four dimensions of airport transportation conditions, meteorological conditions, space resources, and security levels had a decreasing impact on the deployment of DAC systems in that order. The airports with suitable DAC systems are mainly located in the Yangtze River Delta, the Pearl River Delta, and the Chengdu-Chongqing Airport Cluster. This study provides a theoretical basis for the deployment of DAC systems at airports, which provides new CO2 emission reduction solutions for the aviation transportation industry.

The environmental impact of keeping a tropical aquarium in Northern Europe.

Tropical fishkeeping is a popular practice in societies across the globe and involves recreating and sustaining an entire ecosystem in an aquarium within a domestic setting. The process invariably has an environmental impact, yet an assessment of this impact has previously been limited to the ecological consequences of harvesting fish from the wild or the release of non-native fish species. Provided here are the first estimates of carbon dioxide equivalent (CO2 eq) emissions produced from running a tropical aquarium across multiple countries in Northern Europe (France, Poland and the UK), along with water consumption. Estimates were produced in silico and are discussed in the context of freshwater and marine aquariums, calculated using example aquarium sizes of 50, 200 and 400 l. Using estimates from the UK, depending on size and running conditions, a tropical aquarium produces an estimated 85.3-635.2 kg of CO2 eq per year, equating to 1.6%-12.4% of the UK annual average household CO2 emissions, and uses 156-31,200 l of water per year, equating to 0.2%-30.1% of the UK annual average household water usage. Despite this, comparison with the CO2 eq of an average-size dog (127-1592 kg of CO2 eq per year) or cat (121-251 kg of CO2 eq per year), estimated from meat consumption alone, demonstrates that ornamental fishkeeping can be a more environmentally conscious pet choice. In addition, the majority of CO2 eq produced from tropical fishkeeping is generated from the energy consumption of aquarium equipment and as more national electricity grids begin to decarbonize, this estimate should decrease.

Carbon offset potential of biochar based straw management under rice- wheat system along Indo-Gangetic Plains of India

The Paris Agreement goal of a net-zero equation will require decarbonization technologies in agriculture. Agri-waste biochar offers huge potential for carbon abatement in agricultural soils. The present experiment was carried out to compare the effects of residue management, viz., no residue (NR), residue incorporation (RI), and biochar (BC), as well as nitrogen options for emission reduction and carbon capture under the rice-wheat cropping sequence (RWCS) of the Indo-Gangetic Plains (IGP), India. After two cycles of cropping pattern, the analysis revealed that the biochar application (BC) reduces the RWCS's annual CO2 emissions by 18.1 % over residue incorporation (RI), while CH4 and N2O emissions were reduced by 23 % and 20.6 % over RI and 11 % and 29.3 % over no residue (NR), respectively. The application of biochar-based nutrient composites with rice straw biourea (RSBU) at 100 % and 75 % significantly reduced greenhouse gases (CH4 and N2O) compared to commercial urea at 100 %. The global warming potential of cropping systems recorded with BC was 7 % and 19.3 % lower than NR and RI, respectively, while 6–15 % under RSBU over urea 100 %. The annual carbon footprint (CF) under BC and NR decreased by 37.2 % and 30.8 % over RI, respectively. The net CF under residue burning was estimated to be the highest (132.5 Tg CO2-Ce), followed by RI (55.3 Tg CO2-Ce), showing net positive emissions; however, net negative emissions were found under a biochar-based system. The estimated annual carbon offset potential of a complete biochar system over residue burning, incorporation, and partial biochar as calculated was 189, 112, and 92 Tg CO2-Ce yr−1, respectively. A biochar-based approach to managing rice straw had great carbon offset potential through a large drop in greenhouse gas emissions and an improved soil carbon pool under the rice wheat system along the IGP, India.

Effect of O2 transport membrane and CO2 capture membranes on the performance of the biomass-based power generation: An artificial intelligence based multi-objective optimization and techno-economic and environmental evaluation

One of the most important causes of global warming is the release of carbon dioxide (CO2) gas into the atmosphere due to the production of electricity to meet the global community's need for energy. The main goal of this research is to present a power generation system based on biomass gasification equipped with a membrane-based carbon capture system. In this system, a gasifier and an oxygen transport membrane (OTM) were coupled with each other to produce pure O2 as a gasification agent. Moreover, a three-membrane system is considered to separate CO2 from combustion gases coming out of the combined Brayton-Rankin cycle. The desired system has been carefully examined from a thermodynamic outlook. In the next step, the cost of electricity has been obtained by using a detailed economic study, taking into account the life of the employed membranes. Finally, by using artificial intelligence (AI)-based multi-objective optimization, the presented system has been optimized from the economic point of view and thermodynamic performance. The results of this research show that the use of OTM to produce pure oxygen as a gasification agent leads to a 53% improvement in the heating value of the produced fuel compared to the use of air (without OTM). Furthermore, the use of CO2 capture membranes (CCM) led to the reduction of annual CO2 emissions from 50.41 Mkg to 9.9 Mkg. According to the Pareto front, the results obtained from the minimization of the electricity cost and the maximization of the net power production showed that the minimum electricity cost and the maximum produced power were 0.4275 $/kWh and 7039 kW, respectively. It can be acknowledged that the optimization and the addition of the carbon capture system in the carbon tax of 303$/Tonne-CO2 (and more than that) not only can produce electricity at a lower cost, but also reduce the amount of CO2 emission from 50.43 million kilograms per year to of 6.9 million kilograms per year.

Role of inter-annual variability in the magnitude of river discharge on CO2 fluxes in the Godavari tidal river zone, India

Variations in the magnitude of river discharge may alter pH, pCO2 of surface water, and flux of CO2 to the atmosphere in the Tidal River Zone (TRZ). To test this hypothesis, a nearly decade-long time-series data of salinity, pH, and pCO2 data were collected and analyzed in the TRZ of Godavari River. The higher freshwater discharge occurred in the TRZ during the wet period (June to December) compared to the dry period (January to May). An increase in annual mean discharge was noticed between 2008 and 2019 due to surplus rainfall and the expansion of the hydropower plant. The surface water pH and pCO2 in the TRZ were controlled by the river discharge as evidenced by the linear positive and negative relationships with the rate of river discharge respectively. A strong relationship was observed between apparent oxygen utilization (AOU) and excess CO2 indicating a strong influence of heterotrophic activity on pCO2 levels in the TRZ. The respiration quotient (RQ) was above the aerobic respiration value of 1.35 indicating that terrestrial sources, such as sewage, and groundwater discharge, may have contributed to pH and pCO2 levels in the TRZ. The CO2 fluxes during the peak discharge period contribute to 48–88% of annual mean fluxes followed by moderate (12–52%) and dry periods (<4%). The annual mean CO2 emission amounted to 0.04 ± 0.05 TgC for the area of 36.9 × 106 m2 and increased at the rate of 0.005 TgC y−1 between 2008 and 2019 due to an increase in river discharge. The CO2 flux from the Godavari TRZ (0.04 TgC y−1) contributes to ∼0.2% of global tropical estuaries (18 TgC y−1). The CO2 flux contributed to ∼1.5% of the total carbon (both particulate and dissolved) exported from the Godavari TRZ to the Bay of Bengal and it is lower than the global mean contribution of 16%.

Ensemble framework for daily carbon dioxide emissions forecasting based on the signal decomposition–reconstruction model

The accurate prediction of daily carbon dioxide (CO2) emissions is crucial for grasping the real-time dynamics of CO2 emissions and formulating emission reduction policies. The use of the artificial intelligence model in CO2 emissions prediction has frequently been reported; however, research on the signal decomposition–reconstruction prediction model has rarely been conducted. Daily CO2 emissions are heavily influenced by human activities and show strong non-stationarity, potentially preventing a single artificial intelligence model from yielding satisfactory prediction results. To improve the accuracy of daily CO2 emissions prediction, we propose an ensemble framework based on signal decomposition–reconstruction model for predicting daily CO2 emissions. Our proposed ensemble frameworkis tested on real-world data from 14 regions. The research results show that in predicting daily industrial CO2 emissions, the coefficient of determination (R2) of our proposed model exceeds 0.96, the mean absolute percentage error (MAPE) and root mean square error (RMSE) values are better than those of other models. MAPE is generally within 20% for different forecast lead times. For another kind of CO2 emissions data, our proposed ensemble framework has also demonstrated robust prediction performance for daily ground transport CO2 emissions data, with an R2 exceeding 0.9 in most cases, and a MAPE within 17% for different forecast lead times. This study highlights the efficiency of the proposed model in addressing the issue of daily CO2 emissions prediction. It also provides a method for predicting hourly and annual CO2 emissions.

Planting hedgerows: Biomass carbon sequestration and contribution towards net-zero targets

Agroforestry practices, such as hedgerow planting, are widely encouraged for climate change mitigation and there is an urgent need to assess their contribution to national ‘net-zero’ targets. This study examined the impact that planting hedgerows at different rates could make to UK net-zero goals over the next 40 years, with a focus on 2050. We analysed the carbon (C) content of native hedgerow species and determined hedge aboveground biomass (AGB) C stock via destructive sampling of hedges of known ages. AGB C stocks ranged from 8.34 Mg C ha−1 in the youngest hedges, to 40.42 Mg C ha−1 in old ones. Knowing the age of the hedgerows, we calculated their annual average AGB C sequestration rate, which was highest in young hedges (2.09 Mg C ha−1 yr−1), and lowest in 39 year old mature, regularly trimmed hedgerows (0.86 Mg C ha−1 yr−1). We present a time series of the annual AGB C sequestration rate change between hedge age categories, which increases from 2.09 Mg C ha−1 yr−1 in the first 6 years after planting, to 2.26 Mg C ha−1 yr−1 in the next 6 years, and then decreases to 0.43 Mg C ha−1 yr−1 between years 13 and 40. Our results indicate that, if encouraged widely, hedgerow planting can be a valuable tool for atmospheric CO2 capture and storage, contributing towards net-zero targets. However, current planting rates (1778.8 km yr−1) are too low to reach the net-zero goal set by the UK Climate Change Committee of increasing hedgerow length by 40 % by 2050. An increased planting rate of 7148.1 km yr−1 will achieve this goal by 2050, and, over 40 years, store 3.41 Tg CO2 in hedge AGB, or 10.13 Tg CO2 in hedge total biomass and in the soil, annually offsetting 1.5 %–4.5 % of UK annual agricultural CO2 emissions.

Copper-Based Electrocatalysts for Nitrate Reduction to Ammonia.

Ammonia (NH3) is a highly important industrial chemical used as fuel and fertilizer. The industrial synthesis of NH3 relies heavily on the Haber-Bosch route, which accounts for roughly 1.2% of global annual CO2 emissions. As an alternative route, the electrosynthesis of NH3 from nitrate anion (NO3-) reduction (NO3-RR) has drawn increasing attention, since NO3-RR from wastewater to produce NH3 can not only recycle waste into treasure but also alleviate the adverse effects of excessive NO3- contamination in the environment. This review presents contemporary views on the state of the art in electrocatalytic NO3- reduction over Cu-based nanostructured materials, discusses the merits of electrocatalytic performance, and summarizes current advances in the exploration of this technology using different strategies for nanostructured-material modification. The electrocatalytic mechanism of nitrate reduction is also reviewed here, especially with regard to copper-based catalysts.

Investigation of hot spring gas components and soil gas fluxes in Arxan Holocene volcanic field, Inner Mongolia, NE China

The latest research results show that there is a unified magma system and heating channel beneath the Arxan volcanic field, indicating a potential risk of eruption. The Arxan volcanic field features multiple gas emission sites (e.g., Jinjianggou hot springs and Yinjianggou hot springs) and exhibits strong hydrothermal activity. In this study, measurements of the hot spring gas composition and soil CO2 flux in the Arxan Holocene volcanic field were conducted, and the results were combined with previous research results to analyze the degassing characteristics of this region. The results show that the volcanic gases in the Arxan volcanic field are composed of 0.07%–1.09% CO2, 0.33–12 ppm CH4, 1.57–53 ppm H2, 800–30,241 ppm He, and 1.14%–1.86% Ar. The He content in this area is notably higher than that in other dormant volcanoes in China. This difference is possibly caused by U–Th decay in the Mesozoic granodiorite and acidic volcanic rocks in the study area, which can produce substantial radiogenic He. The soil gas concentrations near the Jinjianggou and Yinjianggou hot springs are higher than those of two Holocene volcanoes. The peak CO2 concentration in the soil near the Jinjianggou hot spring can reach 35,161 ppm. The single-site soil microseepage CO2 flux in the Arxan volcanic field is 4.66–107.18 g m−2 d−1, and the estimated annual CO2 emission flux from the volcanic field to the atmosphere is 0.63 × 105 t, which also demonstrates that soil CO2 flux of Arxan volcano is comparable to the soil CO2 emission level of the Iwojima volcano.

Flux and stable isotope fractionation of CO2 in a mesic prairie headwater stream

Abstract The carbon dioxide (CO2) fluxes from headwater streams are not well quantified and could be a source of significant carbon, particularly in systems underlain by carbonate lithology. Also, the sensitivity of carbonate systems to changes in temperature will make these fluxes even more significant as climate changes. This study quantifies small-scale CO2 efflux and estimates annual CO2 emission from a headwater stream at the Konza Prairie Long-Term Ecological Research Site and Biological Station (Konza), in a complex terrain of horizontal, alternating limestones and shales with small-scale karst features. CO2 effluxes ranged from 2.2 to 214 g CO2 m−2 day−1 (mean: 20.9 CO2 m−2 day−1). Downstream of point groundwater discharge sources, CO2 efflux decreased, over 2 m, to 3–40% of the point-source flux, while δ13C-CO2 increased, ranging from −9.8 ‰ to −23.2 ‰ V-PDB. The δ13C-CO2 increase was not strictly proportional to the CO2 flux but related to the origin of vadose zone CO2. The high spatial and temporal variability of CO2 efflux from this headwater stream informs those doing similar measurements and those working on upscaling stream data, that local variability should be assessed to estimate the impact of headwater stream CO2 efflux on the global carbon cycle.

Effect of Changes in Throughfall on Soil Respiration in Global Forest Ecosystems: A Meta-Analysis

To date, there has been limited knowledge about how soil carbon dioxide (CO2) emissions from forest ecosystems at a global scale respond to the altered precipitation, and the key influencing mechanisms involved. Thirty-seven studies conducted under throughfall manipulation conditions in forest ecosystems around the globe were selected in this meta-analysis, with a total of 103 paired observations. Experimental categories such as climate types, forest types, soil texture, and the area size of changes in throughfall manipulation were included to qualify the responses of annual soil CO2 emissions to the altered throughfall. The responses of the annual soil CO2 emissions to the altered throughfall would be more sensitive in temperate forests than those in tropical and subtropical forests, probably due to the relatively long residence time of soil carbon (C) and the seasonal freeze–thaw events in temperate forests, as well as the relatively high concentration of non-structural carbohydrates in the belowground part of temperate terrestrial plants. A relatively large positive response of the soil CO2 emissions to the increased throughfall was observed in Mediterranean forests due to small precipitation during the growing season and mostly coarse-textured soils. Besides climate types, the sizes of the effect of the altered throughfall on the soil CO2 emissions (lnRCO2) varied with forest types and soil texture categories. Based on the regression analysis of the lnRCO2 values against the changes in throughfall, the annual soil CO2 emissions in forest ecosystems at a global scale would be increased by 6.9%, provided that the change in annual precipitation was increased by 10%. The results of structural equation modeling analysis indicate that fine root biomass and soil microbial biomass, along with the changes in annual precipitation, would substantially affect the altered throughfall-induced annual soil CO2 emissions in global forest ecosystems. The findings of this meta-analysis highlight that the measurement of soil respiration components, the priming effects of soil organic C decomposition, and C allocation between the aboveground and belowground parts of different tree species under the altered precipitation conditions, deserve more attention in the future.

Simulation and Multi-Objective Optimization of Three-Column Double-Effect Methanol Distillation by NSGA-III Algorithm

The multi-objective optimization of methanol distillation is a critical and complex issue in the methanol industry. The three-column methanol distillation scheme is first simulated with Aspen Plus to provide the initial value of the NSGA-III algorithm. The operating parameters are optimized through the Python-Aspen platform. The total annual cost and CO2 emissions are considered the objective function. A small value of indicator generational distance can be achieved by increasing the number of generations, which is helpful in improving algorithm convergence. The NSGA-III algorithm has good convergence and distribution performance. By comparing the optimized results with the original ones, the total annual cost and CO2 emissions are, respectively, reduced by 5.35% and 12.80% when the operating parameters of the methanol distillation sequence are optimized through NSGA-III. As a result, substantial economic and energy savings can be made, offering great potential to improve the performance of the three-column methanol distillation.

Impacts of land-use change on carbon dynamics in China's coastal wetlands

The impact of land-use and land-cover change (LULCC) on ecosystem carbon (C) dynamics has been previously documented at local and global scales, but uncertainty persists for coastal wetlands due to geographical variability and field data limitations. Field-based assessments of plant and soil C contents and stocks of various LULCC types were conducted in nine regions along the coastline of China (21°–40°N). These regions cover natural coastal wetlands (NWs, including salt marshes and mangroves) and former wetlands converted to different LULCC types, including reclaimed wetlands (RWs), dry farmlands (DFs), paddy fields (PFs) and aquaculture ponds (APs). The results showed that LULCC generally decreased the C contents and stocks of the plant–soil system by 29.6 % ± 2.5 % and 40.4 % ± 9.2 %, respectively, while it slightly increased the soil inorganic C contents and stocks. Wetlands converted to APs and RWs lost greater ecosystem organic C stocks (EOC, sum of plants and top 30 cm of soil organic C stocks) than other LULCC types. The annual potential CO2 emissions estimated from EOC loss depended on the LULCC type, with an average emission of 7.92 ± 2.94 Mg CO2-eq ha−1 yr−1. The change rate of EOC in all LULCC types showed a significantly deceasing trend with increasing latitude (p < 0.05). The loss of EOC due to LULCC was larger in mangroves than in salt marshes. The results showed that the response of plant and soil C variables to LULCC was mainly related to differences in plant biomass, median grain size, soil water content and soil NH4+-N content. This study emphasized the importance of LULCC in triggering C loss in natural coastal wetlands, which strengthens the greenhouse effect. We suggest that the current land-based climate models and climate mitigation policies must account for specific land-use types and their associated land management practices to achieve more effective emission reduction.

Modelling of ship resistance and power consumption for the global fleet: The MariTEAM model

A system that can reliably estimate power consumption based on operational profiles and weather conditions is needed to evaluate global shipping emissions and alternative reduction scenarios. Due to a lack of detailed ship information, uncertainties in collected data, and computing complexity, many prior bottom-up investigations used simplified calculations and empirical equations. Some methodologies offered only approximate estimates that were not enough to capture power consumption trends based on the global fleet’s geographical, seasonal, and operational features. This work intends to develop and implement a power prediction method that can be applied in a bottom-up approach based on fleet composition and trading patterns. We present a comprehensive approach for powering prediction, encompassing data pre-processing, ship resistance estimation, and propulsion efficiency, based on the Maritime Transport Environmental Assessment Model. The model’s predictions match well with full-scale measurements of three operating ships and 2018 EU-MRV (European Union-Monitoring, Reporting, and Verification) data on annual fuel consumption and emissions for ships. The average error with the MRV data on annual CO2 emissions is below the median of 3% and the semi-interquartile range of 14%. Thus, the proposed model can be used to simulate the power performance and energy consumption of worldwide shipping.

The Role Of Hydrogen In Future Climate-neutral Economy

Global annual CO2 emissions have increased more than 16 times in 2021 compared to 1990 and are expected to keep growing. Renewable energy is a critical way to reduce the impact on the climate. However, renewable energy production’s power output does not necessarily match the demand. The intermittent character of renewable electricity generation requires the storage of produced energy. Green hydrogen production via electrolysis is an opportunity to increase the integration of renewable energy sources and move hard-to-decarbonize sectors to climate neutrality. This research aims to assess the potential role of hydrogen in decarbonizing the energy sector in Latvia in the long term. Latvia’s energy system is modeled using the input/output deterministic energy system analysis model EnergyPlan. The model includes all the primary energy demand sectors, energy production, and storage, and allows the analysis of the impact of different strategies on the total costs and emissions of the system by 2050. The results show that the production potential of green hydrogen will increase significantly by 2030, taking into account the existing plans for the installation of 800 MW of wind and solar generating capacity on a national scale. The most significant potential is associated with using hydrogen in the transport sector in vehicles and in producing alternative fuels. Other uses include the decarbonization of the natural gas sector. In these scenarios, it is possible to reduce CO2 emissions while annual system costs increase.

Techno-Economic Analysis of a Hydrogen-Based Power Supply Backup System for Tertiary Sector Buildings: A Case Study in Greece

In view of the European Union’s strategy on hydrogen for decarbonization and buildings’ decarbonization targets, the use of hydrogen in buildings is expected in the future. Backup power in buildings is usually provided with diesel generators (DGs). In this study, the use of a hydrogen fuel cell (HFC) power supply backup system is studied. Its operation is compared to a DG and a techno-economic analysis of the latter’s replacement with an HFC is conducted by calculating relevant key performance indicators (KPIs). The developed approach is presented in a case study on a school building in Greece. Based on the school’s electricity loads, which are calculated with a dynamic energy simulation and power shortages scenarios, the backup system’s characteristics are defined, and the relevant KPIs are calculated. It was found that the HFC system can reduce the annual CO2 emissions by up to 400 kg and has a lower annual operation cost than a DG. However, due to its high investment cost, its levelized cost of electricity is higher, and the replacement of an existing DG is unviable in the current market situation. The techno-economic study reveals that subsidies of around 58–89% are required to foster the deployment of HFC backup systems in buildings.

Investigating energy saving and climate mitigation potentials in cement production – A case study in Ethiopia

The cement industry is one of the most energy and emission-intensive sectors, accounting for approximately 7% of total-industrial energy use and 7% of global CO2 emissions. This study investigates the potential energy savings and CO2 abatement in the cement plants of Ethiopia. A Benchmarking and Energy Saving Tool for Cement is used to compare the energy use performance of the individual cement plants to best practices. The study reveals that all the surveyed plants are less efficient, with an average energy saving potential of 36% indicating a significant potential for energy efficiency improvement. Then, twenty-eight energy efficiency measures are identified and analyzed using a bottom-up energy conservation supply curve model. The results show that the cost-effective electrical energy and fuel-saving potentials of these measures are estimated to be 99 Gigawatt hours per year which is about 11.5% of the plants’ annual electrical energy consumption and, 2.7 Petajoules per year which is to be 12.5% of the plants’ annual fuel consumption, respectively. The cost-effective fuel measures have an annual average CO2 emission reduction potential of 254 kilo-tonnes per year which covers about 5% of the total CO2 emission. Sensitivity analysis is conducted using the key parameters that show some discrepancy in the base case results. This study could be used as a reference for policymakers to understand the potential for energy savings and CO2 abatement. It could also be used to design policies in improving energy efficiency in the cement sector.

Effects of Precipitation Variation on Annual and Winter Soil Respiration in a Semiarid Mountain Shrubland in Northern China

In response to global climate change, future precipitation changes are expected to profoundly influence soil respiration in arid and semiarid areas. However, few studies focus on CO2 emissions from soils undergoing precipitation changes in semiarid mountain shrublands in winter. A precipitation-manipulation experiment with three levels of precipitation (30% decreased precipitation (DP), ambient precipitation (AP), and 30% increased precipitation (IP)) was performed to examine the effects of variable precipitation on soil respiration (SR) and wintertime contributions to annual SR emissions in Vitex negundo var. heterophylla shrub ecosystems located on the Middle Taihang Mountain in Hebei Province, northern China. The results showed that the average annual SR rates and winter SR rates ranged from 1.37 to 1.67 μmol m−2 s−1 and 0.42 to 0.59 μmol m−2 s−1 among the different precipitation treatments. The model based on soil moisture better represented the soil-respiration rates, suggesting that the variable precipitation extended the water’s limitation of the soil’s CO2 emissions. The cumulative annual soil CO2 emissions were 523, 578, and 634 g C m−2 in response to the DP, AP, and IP treatments, respectively. The ratio of the soil CO2 emissions in winter to the annual CO2 emissions varied from 7.6 to 8.8% in response to the different precipitation treatments. Therefore, ignoring the soil CO2 emissions in winter leads to the underestimation of the carbon losses in semiarid shrublands. Our results highlight that variable precipitation significantly influences soil-respiration rates, and soil CO2 emissions in winter must not be ignored when predicting the future feedback between SR and climate change in semiarid regions.

Investigating the Cost-Effectiveness of Solar Electricity Compared to Grid Electricity in the Capitals of Middle Eastern Countries: A Residential Scale Case Study

Despite of being rich in fossil fuels, the Middle East is currently the main energy consumer and is projected to have the highest growth in energy demand in the world. Due to its great potential in the Middle East, solar energy can play an important role in the plans of energy decision-makers in the region. According to the studies done so far, no study has been done to show the potential benefit of using home-scale solar systems in the Middle East. Therefore, in this work for the first time, the potential of solar electricity production in the capitals of Middle Eastern countries has been studied using HOMER V2.81 software. The investigations are technical, economic, energy, and environmental, and the studied solar system is connected to the national electricity grid. The results showed that in Nicosia, due to the sale of electricity to the grid, the levelized cost of electricity (LCOE) is equal to -0.759 $, which is the lowest price for produced electricity and leads to a return on investment time of 5.69 years for this system. The solar fraction for the Nicosia station is 92%, which prevents the emission of more than 8 tons of CO2 pollutants during the year. The highest value of LCOE with the amount of $0.25 is related to Sana’a, whose investment return time, solar fraction, and annual CO2 emission prevention amount are 14.1 years, 53%, and 1162 kg, respectively. Ranking analysis was done on the results of 5 outputs of the HOMER software as well as 3 other influential parameters using 4 multicriteria decision-making (MCDM) methods. TOPSIS, GRA, WSM, and AHP methods were used, and the final ranking of each station was considered the average of the 4 methods. According to the results, Cyprus and Kuwait stations were the best and worst, respectively.

Techno-economic design of a solar combisystem in a residential building

A solar combisystem is utilized to supply domestic hot water (DHW) and heat a residential building. This system decreases the fossil fuel consumption and, hence, reduces air pollution and global warming. This paper proposes an innovative method to design and optimize a suitable solar combisystem for a residential building with respect to technical and economic parameters. First, different configurations of solar combisystems, including various components, are considered. Then, the optimum design variables are determined for each configuration using Grouped Method of Data Handling (GMDH) type of Artificial Neural Network (ANN) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II). Total Solar Fraction (TSF) and Life Cycle Cost (LCC) are considered as objective functions. Finally, the optimum design is chosen for the solar combisystem. Typically, researchers have focused on evaluating the performance of a single solar combisystem configuration in each study. However, this research takes a different approach by optimizing multiple configurations, resulting in a significant improvement in the total solar fraction by 7.3%. This is the main novelty of this paper. Based on the results, the optimum configuration of the solar combisystem includes 17.91 m2 of evacuated-tube collectors with a tilt angle of 50°. Also, the volume of the hot water tank and heating buffer tank are, respectively, equal to 204 and 500 L (L). In this system, solar energy provides 94% of the required energy for supplying DHW and 23% of the energy for heating the building. Moreover, reduction of annual CO2 emissions is 1806 kg. This paper presents a guideline to design solar systems for the residential buildings considering technical and economic aspects.