Amount Of CO2 Emissions Research Articles

Using drone soundings to study the impacts and compositions of plumes from a gigantic coal-fired power plant

The immense impacts of coal-fired power plant plumes on the atmospheric environment have caused great concern linked to climate and health issues. However, studies on the field observations of aerial plumes are relatively limited, mainly due to the lack of suitable plume observation tools and techniques. In this study, we use a multicopter unmanned aerial vehicle (UAV) sounding technique to study the influences of the aerial plumes of the world's fourth-largest coal-fired power plant on the atmospheric physical/chemical conditions and air quality. A set of species, including 106 volatile organic compounds (VOCs), CO, CO2, CH4, PM2.5, and O3, and meteorological variables of temperature (T), specific humidity (SH), and wind data, are collected by the UAV sounding technique. The results reveal that the large-scale plumes of the coal-fired power plant cause local temperature inversion and humidity changes, and even affect the dispersion of pollutants below. The chemical compositions of coal-fired power plant plumes are significantly different from those of another ubiquitous vehicular source. High fractions of ethane, ethene, and benzene and low fractions of n-butane and isopentane found in plumes could serve as the key features to help distinguish the influences of coal-fired power plant plumes from other pollution sources in a particular area. By taking the ratios of pollutants (e.g., PM2.5, CO, CH4, and VOCs) to CO2 in plumes and the CO2 emission amounts of the power plant into calculation, we enable the easy quantification of the specific pollutant emissions released from power plant plumes to the atmosphere. In summary, observation by using drone soundings dissecting the aerial plumes provides a new methodology that allows aerial plumes to be readily detected and characterized. Furthermore, the influences of the plumes on the atmospheric physical/chemical conditions and air quality can be assessed rather straightforwardly, which was not easily achievable in the past.

Reducing Iron Oxide with Ammonia: A Sustainable Path to Green Steel (Adv. Sci. 16/2023)

Sustainable Ironmaking In article number 2300111, Yan Ma, Dierk Raabe, and co-workers provide a novel approach to deploying intermittent renewable energy mediated by ammonia and using it for a disruptive technology transition towards sustainable ironmaking. This approach sheds light on future sustainable ironmaking, which is urgently needed to mitigate the gigantic amount of CO2 emissions from the steel industry.

Use of random forest based on the effects of urban governance elements to forecast CO2 emissions in Chinese cities

Chinese cities contributes a large amount of CO2 emissions. Reducing CO2 emissions through urban governance is an important issue. Despite the increasing attention paid on the CO2 emission prediction, few studies consider the collective and complex influence of governance element system. To predict and regulate CO2 emissions through comprehensive urban governance elements, this paper use the random forest model through the data from 1903 Chinese county-level cities in 2010, 2012 and 2015, and establish a CO2 forecasting platform based on the effects of urban governance elements. The results are as follows: (1) The municipal utility facilities element, the economic development & industrial structure element, and the city size &structure and road traffic facilities elements are crucial for residential, industrial and transportation CO2 emissions, respectively; (2) Governance elements have nonlinear relationship with CO2 emissions and most of the relations present obvious threshold effects; (3) Random forest can be used to predict CO2 emissions more accurately than can other predictive models. These findings can be used to conducts the CO2 scenario simulation and help government formulate active governance measurements.

Dye-Sensitized Solar Cell Photoelectrochemical Tandem System Performance Study: TiO<sub>2</sub> Nanotube/N719, BiVO<sub>4</sub>/TiO<sub>2</sub> Nanotube, Ti<sup>3+</sup>/TiO<sub>2</sub> Nanotube for Nitrogen Reduction Reaction to Ammonia

Ammonia is commonly synthesized through the Haber-Bosch process, which produces large amounts of CO2 emissions as it is carried out at extreme temperatures and pressures. An alternative technology is needed to synthesize ammonia which consumes less energy and is environmentally friendly. In this research, a Dye-Sensitized Solar Cell Photoelectrochemical tandem system (DSSC-PEC) was developed for the nitrogen reduction reaction (NRR) into ammonia. PEC cells utilized BiVO4/TiO2 Nanotube (BiVO4/TiO2NT) as a photoanode for water oxidation. BiVO4/TiO2NT was synthesized by the successive ionic layer adsorption and reaction (SILAR) with the cycles variation of 10, 15, and 20 cycles. The optimization method for 20 cycles (20s) gave the highest photocurrent of 0.352 mA/cm2. As a cathode where the nitrogen reduction reaction to ammonia takes place, Ti3+/TiO2NT was used. DSSC based on TiO2NT/N719 with an efficiency of 1.13% was used as an energy booster in the reaction. Using this system with an electrodes area of 3 cm2, under visible light irradiation on photoanode and DSSC while dark at the cathode, the rate of ammonia production, analyzed using the phenate method was 0.022 µmol.h−1.cm−2 with solar to chemical conversion (SCC) efficiency of 0.003%.

Influence of Carbonated Bottom Slag Granules in 3D Concrete Printing.

This study investigates the possibility of utilising bottom slag (BS) waste from landfills, and a carbonation process advantageous for the use of artificial aggregates (AAs) in printed three-dimensional (3D) concrete composites. In general, the main idea of granulated aggregates is to reduce the amount of CO2 emissions of printed 3D concrete objects (wall). AAs are made from construction materials, both granulated and carbonated. Granules are made from a combination of binder (ordinary Portland cement (OPC), hydrated lime, burnt shale ash (BSA)) and waste material (BS). BS is a waste material left over after the municipal waste burning process in cogeneration power plants. Whole printed 3D concrete composite manufacturing consists of: granulating artificial aggregate, aggregate hardening and sieving (adaptive granulometer), carbonation of AA, mixing 3D concrete, and 3D printing. The granulating and printing processes were analysed for hardening processes, strength results, workability parameters, and physical and mechanical properties. Printings with no granules (reference 3D printed concrete) were compared to 3D printed concretes with 25% and 50% of their natural aggregate replaced with carbonated AA. The results showed that, theoretically, the carbonation process could help to react approximately 126 kg/m3 CO2 from 1 m3 of granules.

Analysis of the Influence of the Spark Plug on Exhaust Gas Composition

This paper analyses the influence of the type of electrode in a spark plug on exhaust gas emission. The objects of the research were the following vehicles of different years of production: the Volkswagen Beetle 1300, the Honda Nighthawk 650, the BMW e46 318i, the Hyundai i10, and the Audi A4 B6. The vehicles were powered by petrol and LPG. Spark plugs were selected for the vehicles, with different kinds of construction for the main electrodes and different numbers of poles but with similar heat values. A comparative analysis of the composition of the exhaust gas mixture was performed, depending on the set of spark plugs used. The amount of CO, HC, CO2, and O2 emissions was analysed. The results were compared with the applicable exhaust gas emission standards. Both in the case of E5 95 petrol and LPG gas, lower exhaust gas emissions were observed when iridium spark plugs were used.

Hydrophobic- and fat-dissolved rice straw-C induced equivalent amount of CO2 emission and soil net C balance

Understanding the influences of hydrophobic- and fat-dissolved straw substrates on CO2 emission and soil net C balance is necessary for quantifying soil C storage after the straw return. The straw-driven increase in CO2 emission could dangerously strengthen climate change, and the accompanying uncertainty in soil C sequestration ascribed to the priming effect with different straw-C components application. The mechanism underlying the decomposition of soil organic carbon via the priming effect with different straw-C components amendment still remains insufficiently resolved. Here we evaluated the impact of hydrophobic- (HC) and fat-dissolved C (FC) from rice straw on priming effect using an incubation experiment, which would explain well the observed current variation in CO2 emission and soil C storage in response to straw return. Applying HC and FC to the soil, we found that the emitted CO2 from soil in HC addition treatment was higher than that in FC treatment during first two weeks, thus resulting in a higher cumulative priming effect. The increase in cumulated CO2 emission was ascribed to strong priming effect in HC treatment in the first 14 days, and higher mineralization percentage in FC treatment, separately. In the end, both straw-C addition treatments induced equivalent CO2 emission and increased soil C storage. Our findings suggested that adjusting the driver in controlling the contribution of hydrophobic- and fat-C to CO2 emission was an important strategy to mitigate climate change in response to straw return. Due to the equivalent CO2 emission, the fat-C-derived CO2 emission needs to further study in the future.

Analytical Review of Geopolymer Concrete: Retrospective and Current Issues.

The concept of sustainable development provides for the search for environmentally friendly alternatives to traditional materials and technologies that would reduce the amount of CO2 emissions into the atmosphere, do not pollute the environment, and reduce energy costs and the cost of production processes. These technologies include the production of geopolymer concretes. The purpose of the study was a detailed in-depth analytical review of studies of the processes of structure formation and properties of geopolymer concretes in retrospect and the current state of the issue. Geopolymer concrete is a suitable, environmentally friendly and sustainable alternative to concrete based on ordinary Portland cement (OPC) with higher strength and deformation properties due to its more stable and denser aluminosilicate spatial microstructure. The properties and durability of geopolymer concretes depend on the composition of the mixture and the proportions of its components. A review of the mechanisms of structure formation, the main directions for the selection of compositions and processes of polymerization of geopolymer concretes has been made. The technologies of combined selection of the composition of geopolymer concrete, production of nanomodified geopolymer concrete, 3D printing of building structures from geopolymer concrete, and monitoring the state of structures using self-sensitive geopolymer concrete are considered. Geopolymer concrete with the optimal ratio of activator and binder has the best properties. Geopolymer concretes with partial replacement of OPC with aluminosilicate binder have a denser and more compact microstructure due to the formation of a large amount of calcium silicate hydrate, which provides improved strength, durability, less shrinkage, porosity and water absorption. An assessment of the potential reduction in greenhouse gas emissions from the production of geopolymer concrete compared to the production of OPC has been made. The potential of using geopolymer concretes in construction practice is assessed in detail.

CO2 Emission Contribution Analysis of Rice Distribution Channels in Indonesia

According to Horrigan (2002), the food industry accounts for 10% of all fossil fuel consumption in the United States. Based on this, an effective rice distribution effort is needed as an effort to achieve food security. Moreover, the effective distribution channels will reduce the impact of CO2 emissions in the air. This study examines how the rice distribution channels in Indonesia and the amount of CO2 emissions resulting from these activities. This study using substitution analysis technique based on equation and conversion value of CO2 residue based on the type of transportation mode. The results show that the total emissions from rice distribution activities are 36.007,97 tons km or 0,026% of the total emissions generated by transportation activities

Low-carbon transformation of ethylene production system through deployment of carbon capture, utilization, storage and renewable energy technologies

Ethylene industry contributes significantly to the world economy, but the conventional steam cracking based production process generates huge amount of CO2 emissions due to massive use of fossil fuels for power and heat supply. Deploying technologies of carbon capture, utilization and storage (CCUS) and renewable energy is urgently necessary to steer the emission-intensive ethylene industry towards carbon neutrality. To attain this goal, this paper proposes a low-carbon ethylene production system with the joint deployment of CCUS, wind turbine, solar heat collector, electric boiler and thermal energy storage technologies. Energy, economic and CO2 generation/reduction performance models of each equipment are developed first. Based on which, a mixed-integer liner programming framework is constructed to find the optimal capacity configuration and coordinated operation scheme of the multiple devices, laying a foundation for the reliable, economical and low-carbon operation of the integrated system. Case studies on a practical ethylene production system demonstrate that the proposed low-carbon retrofit leads to 57.50% CO2 reduction at the expense of 15.92% total annual cost increase. Discussions are then carried out to investigate the effects of different decarbonization routes, the impact of carbon emission trading price, the approach to promote the deployment of CO2 hydrogenation to methanol, and the advantage of taking carbon capture as flexible load, through which, broader insights are provided for the low-carbon transformation of the ethylene industry.

Long-term outdoor performance of grid-connected photovoltaic power plant in a desert climate

In this paper, a 2.25 kWp grid integrated with the tied solar park has been implanted in the Renewable Energy Applied Research Unit (URAER) in a dry and harsh desert region. The PV plant uses micromorph thin-film solar modules (a-Si/μc-Si) technology. The photovoltaic module systems (PVS) were evaluated from May 2015 to December 2020 (around five and a half years of operation), and the electricity was injected into the internal network of the low-voltage power supply. Performance evolution has been conducted in this work as stated by the IEC61724 guideline. The monthly and annual performance indicators analyzed and assessed consist of reference yield, array yield, final yield, system losses, capture losses, PV module efficiency, system efficiency, inverter efficiency, capacity factor, and performance ratio. The annual electricity production is 3688.28 kWh, 3188.25 kWh, 3306.28 kWh, 3136.05 kWh, and 2952.81 kWh for 2016, 2017, 2018, 2019, and 2020 operating periods, respectively. The solar park's total produced energy yield over the monitored period and the quantity of CO2 emissions avoided are 16,271.67 kWh and 14.17 tons, respectively, which can significantly contribute to and help in purifying the environment from pollution. In addition, the energy results produced by the PVS were compared to those found by the four widely used PV simulation tools (PVsys, PVGIS, NREL's PVWatts® Calculator and Solar Med-Atlas). Furthermore, this work investigates and quantifies the degradation phenomenon of solar PVS power output after five years and a half years of outdoor exposure. There is around 0.22 % degradation per year. When this rate was compared to other studies conducted worldwide, it was shown to be highly appropriate. Technical-economic research was also conducted, revealing that the system's PVS period, which establishes its sustainability, is between 9 and 12 years. The results demonstrate that micromorph thin-film modules perform better and are more efficient under harsh real-world outdoor environmental conditions. Inventux modules preserve most of their better performance even with increasing module temperature. This kind of PV module technology is low-insensitive to the highest PV module temperature. Compared to the literature, micromorph thin-film technologies are better and preferable than crystalline modules under desert environmental conditions. The results also indicate that grid-connected solar park plants using this kind of technology are feasible in the hot arid climate to produce electricity and may participate in future energy projects in the country.

GHG Savings Calculation: Switch from Electricity Production to Biomethane. Case Study

Carbon dioxide is one of the main components of greenhouse gases. The amount of anthropogenic CO2 emissions in the atmosphere reached 37.9 Gt, which is 60 % more than in 1990. The use of CO2 in the production of valuable products can help to reduce the amount of CO2 in the atmosphere. Biomethane fuel production could be a successful solution in Latvia as well. The work includes a case study of a Latvian biogas production facility Agro Iecava with a switch from biogas to biomethane production. All calculations are made according to REDcert rules. For biofuel production the Plant uses 13 types of substrates, which is also reflected in the calculation. The work shows a step-by-step algorithm for research and analysis. The experience can be used at other biogas production stations, regardless of its location. The analysis of the Plant shows that switching to biomethane production saves up to 80.34 % of GHG emissions (with an estimated loss during transportation in the network of 1 %). In the worst-case scenario, this amount is 76.34 % (loss from transportation is 5 %), which is also above the minimum indicated in the Renewable Energy Directive.

Green Transformation of Scrap Metal. MCDA and SWOT Analysis of Metal Melting Methods: Case Study of Latvia

Metal is one of the most used materials in the world. It was an important impetus in technological development during the industrial age and is still pushing us forward to this day. Along with the growth of metal consumption, the amount of scrap metal also increases. The correct use of this kind of waste plays an important role in reducing the negative impact of the metalworking industry on the environment. Replacing raw metal with scrap metal can reduce the amount of electricity consumed by up to 10 times and the amount of CO2 emissions created by up to 30 times. The choice of the optimal scrap metal processing technology also plays an important role. The metal melting furnace can be considered the backbone of the industry, and the environmental indicators of the entire scrap metal melting process depend on its efficiency. In this paper, 8 metal melting furnaces are analysed according to 11 natural criteria. In addition, a SWOT analysis is carried out to determine the efficiency of the metal smelting process in Latvian metalworking enterprises and the possibility of expanding enterprises in the future.

Application of Artificial Intelligence to Predict CO2 Emissions: Critical Step towards Sustainable Environment

Prediction of carbon dioxide (CO2) emissions is a critical step towards a sustainable environment. In any country, increasing the amount of CO2 emissions is an indicator of the increase in environmental pollution. In this regard, the current study applied three powerful and effective artificial intelligence tools, namely, a feed-forward neural network (FFNN), an adaptive network-based fuzzy inference system (ANFIS) and long short-term memory (LSTM), to forecast the yearly amount of CO2 emissions in Saudi Arabia up to the year 2030. The data were collected from the “Our World in Data” website, which offers the measurements of the CO2 emissions from the years 1936 to 2020 for every country on the globe. However, this study is only concerned with the data related to Saudi Arabia. Due to some missing data, this study considered only the measurements in the years from 1954 to 2020. The 67 data samples were divided into 2 subsets for training and testing with the optimal ratio of 70:30, respectively. The effect of different input combinations on prediction accuracy was also studied. The inputs were combined to form six different groups to predict the next value of the CO2 emissions from the past values. The group of inputs that contained the past value in addition to the year as a temporal index was found to be the best one. For all the models, the performance accuracies were assessed using the root mean squared errors (RMSEs) and the coefficient of determination (R2). Every model was trained until the smallest RMSE of the testing data was reached throughout the entire training run. For the FFNN, ANFIS and LSTM, the averages of the RMSEs were 19.78, 20.89505 and 15.42295, respectively, while the averages of the R2 were found to be 0.990985, 0.98875 and 0.9945, respectively. Every model was applied individually to forecast the next value of the CO2 emission. To benefit from the powers of the three artificial intelligence (AI) tools, the final forecasted value was considered the average (ensemble) value of the three models’ outputs. To assess the forecasting accuracy, the ensemble was validated with a new measurement for the year 2021, and the calculated percentage error was found to be 6.8675% with an accuracy of 93.1325%, which implies that the model is highly accurate. Moreover, the resulting forecasting curve of the ensembled models showed that the rate of CO2 emissions in Saudi Arabia is expected to decrease from 9.4976 million tonnes per year based on the period 1954–2020 to 6.1707 million tonnes per year in the period 2020–2030. Therefore, the finding of this work could possibly help the policymakers in Saudi Arabia to take the correct and wise decisions regarding this issue not only for the near future but also for the far future.

Investigating the performance of ternary cementitious systems incorporating wollastonite powder and lime sludge in concrete

The production of cement results in a significant amount of energy consumption and CO2 emissions, which are major contributors to environmental pollution. Researchers have developed a ternary blended mix concrete to address these concerns by partially substituting cement with a combination of lime sludge (LS) and wollastonite powder (WP). This study investigated the mechanical properties (compressive strength, spilt tensile strength, and flexural strength) of a ternary blended concrete mix with a grade of M30. 180 specimens, including 60 cubes, 60 cylinders, and 60 prisms, were prepared for testing. The blended concrete mix was produced using different percentages of cement replacement by LS (5%, 10%, 15%) and WP (10%, 15%, 20%). The compressive strength for the ternary mix at 10% LS and 15% WP was 44.78% higher than the conventional mix, the flexural strength ternary mix at 10% LS and 15% WP was 25.46% higher than the conventional mix, and spilt tensile strength ternary mix at 10% LS, and 15% WP was 27.30% higher than the conventional mix at 28 days and trend is almost same for 7,56 and 90 days . The results showed that a ternary mix containing 75% cement, 10% LS, and 15% WP exhibited the best mechanical properties.

Measuring carbon emissions performance of Japan's metal industry: Energy inputs, agglomeration, and the potential for green recovery reduction

This study measures the total factor carbnon dioxide (CO2) emissions performance of the metal industry, iron and steel, nonferrous metal, and metal processing industries in 39 Japanese prefectures from 2008 to 2019. The true fixed-effects panel stochastic frontier model identifies regional carbon efficiency as well as the inefficiency determinants. The main results are as follows. First, a decrease in the coal ratio and an increase in the electricity ratio in total energy consumption improves efficiency. This result suggests that electrification in the metal industry, especially conversion from blast furnaces to electric furnaces in the iron and steel industry, contributes to reducing carbon emissions. Second, industrial agglomeration improves carbon emissions performance in the metal industry. This implies that agglomeration and decarbonization policies focusing on there are more effective, rather than a uniform national policy. Third, compared to the cumulative CO2 emissions over the sample period, 49,017 × 103 tons, the cumulative CO2 mitigation potential is 29,703 × 103 tons, indicating that CO2 emissions can be reduced by 60.6% without affecting the output. Forth, to examine the green economic recovery with efficiency in Japan's metal industry after COVID-19, we present a simple scenario analysis where a k% replacement coal ratio with an electricity ratio in total energy consumption, assuming that each prefecture will achieve the maximum CO2 emission amount during the sample period. By replacing 10% of the coal ratio with the electricity ratio, CO2 emissions can be reduced by 23.0%. In the case of a 20% replacement, CO2 emissions can be reduced by 33.0%. Our results show that Japan's targets in the post-COVID-19 green recovery process should be a decrease in coal consumption, an increase in electricity, and industrial agglomeration.

Long-term forecast of electrical energy consumption with considerations for solar and wind energy sources

The long-term goals achievement of sustainable development based on consumption of electrical energy is possible through the use of renewable energy sources. The objectives of this study include (a) long-term forecasting of Electrical Energy consumption (EEC) for sample countries with developed and developing economies, and (b) analyzing of different scenarios based on the use of solar and wind energy sources with 1%, 2% and 3% of the EEC. Artificial neural network (ANN) modeling with socio-economics data of the energy balance sheet last 30 years (1990–2019) as input data contain Gross Domestic Product (GDP), Population (POP), Import (IMP), Export (EXP), and EEC are used in order to forecast the EEC in the long-term (2020–2050). The United States and the OECD as developed economies and China, India, and Iran as developing economies are the countries under study. The structure of ANN is optimized for long-term EEC forecasting based on PSO and E-PSO algorithms. For both types of inputs and economies, the results demonstrate that E-PSO – ANN model can be used by SRE-3% scenario, which finally leads to a reduction of 55% and 54% in the EEC and amount of CO2 emissions in average according to the Paris Agreement (PA) goals, respectively.

Why PV panels must be recycled at the end of their economic life span? A case study on recycling together with the global situation

The use of solar energy as a renewable energy source has been increasing in recent years. Photovoltaic (PV) panel technology is an important alternative to fossil fuels for the future energy needs of the world. PV panels, which have a lifespan of about 25–30 years, have a potential for photovoltaic waste in the coming years due to the increase in their production. There is a remarkable difference between the amount of CO2 emissions generated during the production of a PV panel and the amount of CO2 emissions generated during its recycling. When recycled, the environmental damage of PV panels is significantly reduced. Recycling also helps economically recover materials some of which are rare in nature. In this study, the structures of the components that compose PV panels are emphasized. The estimated waste projection of the PV for the world, Turkiye and, as a case study, Karapinar Solar Power Plant was analyzed until 2050. The harms of PV panels to the environment, people's health and their recycling potential were scrutinised. Furthermore, the carbon dioxide emissions and economic costs of the PV panels produced by recycling and the panels produced without recycling are compared.

Incentive policy optimization of scientific and technological talents and low-carbon economy analysis from the perspective of public health.

In the face of multiple challenges in stabilizing economic growth, improving people's living quality, and limiting the total amount of CO2 emissions, firstly, this study analyzes the incentive and optimization policies of scientific and technological (S&T) talents from four aspects: incentive, cultivation, flow, and evaluation. Moreover, practical suggestions are put forward. Secondly, an optimization model of China's low-carbon economy (LCE) is implemented. The Matlab software can be adopted to solve the economic output of each department in the expected year and obtain the overall economic indicators for 2017 and 2022. Finally, the output influence and CO2 emission influence of each industry are analyzed. The research results are as follows. (1) From the viewpoint of public health (PH), the countermeasures and suggestions of the S&T talents policy mainly include four parts: building a complete S&T talents policy system, expanding the coverage group of the policy, strictly implementing the policy of evaluating S&T talents, and improving the guarantee mechanism of relevant talents introduction policy. (2) In 2017, the primary industry, agriculture, forestry, animal husbandry, and fishery, accounted for 5.33%; the secondary industry, the energy sector accounted for 72.04%, and the tertiary industry (service industry) accounted for 22.63%. In 2022, the primary, secondary, and tertiary industry accounted for 6.09%, 68.44%, and 25.47%. (3) From the perspective of the industrial influence coefficient, the coefficient of all sectors is stable during 2017-2022. From the standpoint of CO2 emission, China's total CO2 emission shows rapidly increasing trend during the same period. This study has vital practical significance and theoretical value for realizing the sustainable development (SH) and transformation of the LCE.

Properties and Uses of Biochars Incorporated into Mortars

The construction industry is responsible for a large amount of CO2 emissions and an intensive energy consumption. Cement production is the third largest source of anthropogenic CO2 emissions and is responsible for about 1.8 Gt of CO2 emissions into the atmosphere. The use of waste materials to replace a fraction of cement in the mortar makes it more economically and ecologically friendly. In this work, the main objective was to test incorporations of biochar produced at temperatures of 300, 350, and 400 °C, as a partial replacement for cement in the production of mortar. The materials used for the tests were residual lignocellulosic biomass (WBL) and electrical cable insulation waste (WIEC) mixed in a ratio of 1:1. The biochars produced were crushed and sieved after production to reduce the particles. A sample of biochar was used and tested under these conditions and another sample was washed in water and dried before being incorporated; all tests were carried out with a 5% replacement. Waste recovery tests were also carried out without thermochemical treatment. The specimens were studied for compressive strength and water absorption by immersion. All tests were replicated and were analyzed and compared with a control mixture with no incorporation of biochar in the mixture. It was possible to observe that the tests with the incorporation of biochars at 400 °C showed better results, with only a 24% reduction in resistance to compression.