Waste Incineration Power Plant Research Articles

Case Study of Calculating Carbon Credits for Municipal Solid Waste Incineration Power Generation

By replacing landfilling with municipal solid waste incineration, the emission of greenhouse gases (GHGs) generated by sanitary landfilling is avoided. Simultaneously, the thermal energy generated by waste incineration is utilized for power generation, replacing an equivalent amount of electricity generated from fossil fuels, thereby reducing greenhouse gas emissions. Taking a certain municipal solid waste incineration project as an example, relevant methodologies ACM0022 and CM-072-V01 are applied, and simulated calculations of Certified Emission Reductions (CCER) are conducted through national verification. Combined with the current carbon trading prices, additional value-added benefits are calculated, providing a reference for exploring growth opportunities for waste incineration power plants and achieving carbon peak and neutrality targets for the power plants.

Pilot-tests of the coal-fired power plant indirect coupling with multi-source organic solid waste incineration technology

The production of organic solid waste is increasing as the development of society. However, the investment of waste incineration power plant is very high and the thermal efficiency is very low. At the same time, the load of coal-fired power plant is suppressed due to the carbon neutralization policy. Therefore, using the existed coal-fired power plant to co-process the organic solid waste is a feasible method. In this paper, a coal-fired power plant indirect coupling with waste incineration technology based on flue gas circulation was proposed and studied on a 100 kW pilot-test bench. In this technology, the polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) was reduced by a three stages controlling method, which adopts the blending of multi-source organic wastes, high-temperature decomposition and selective catalytic reduction (SCR) catalyst decomposition, simultaneously. The effects of waste incineration coupling, replacement ratio of coal, and flue gas circulation on the combustion and pollutant emission characteristics of the system were studied. The experimental results indicate that the waste incineration coupling has minor influence on the temperature distribution and the toxicity of fly ash of the coal-fired furnace. The NO, HCl, and PCDD/Fs concentrations of flue gas of coal-fired furnace generally decrease as the replacement ratio of coal increases, while the SO2 concentration increases. With the help of three stages controlling method or the flue gas circulation, the PCDDFs concentration of the flue gas of coal-fired furnace can be much lower than 0.1 TEQ ng/Nm3.

Design and evaluation of a municipal solid waste incineration power plant integrating with absorption heat pump

The absorption heat pump can consume a small amount of high temperature heat source instead of electricity to realize the waste heat recovery. It has a potential to be applied in the energy efficiency improvement of municipal solid waste incineration power plant. In this study, a proposed integrated system has been designed, where the sludge heat pump drying system and dump pit heating system are coupled with the absorption heat pumps. The power generation improvement is evaluated through simulation calculation by EBSILON Professional and Aspen Plus. The results show that the power generation of proposed integrated system is 1.21 MW higher than that of reference power plant in winter operating condition. This is mainly due to the reductions of energy loss and exergy loss in incinerator and boiler system according to the energy flow and exergy flow analysis. The extracted steam from turbine is more suitable than the flue gas out of bag filter as the high temperature heat source of heat pump. In addition, the variable operating condition analysis is carried out for the proposed integrated system.

The Effect of Excavation Disturbance on the Stability of Bedding Cataclastic Rock Mass High Slope Containing Multimuddy Interlayers

In China, slope engineering occasionally faces landslides in rocky slopes containing muddy interlayers, primarily triggered by excavation activities. These incidents lead to considerable human casualties and substantial economic losses. However, existing studies predominantly concentrate on the excavation-induced impacts on the stability of rocky slopes characterized by single-layered soft and weak interlayers. Conversely, reports on how excavation influences the stability of bedding cataclastic rock mass high slope containing multimuddy interlayers remain notably absent in the literature. Moreover, unloading due to excavation can swiftly compromise the mechanical integrity and overall quality of the rock mass, consequently impacting the stability of slopes postexcavation. Therefore, this paper modeled the unstable slope excavated at a waste incineration power plant in Yuxi, Yunnan, using the finite element strength reduction method. This approach was employed to comprehensively simulate the entire process of artificial multilevel excavation in a bedding cataclastic rock mass high slope containing multimuddy interlayers. This study investigated the impact of multilevel artificial excavation on slope stability by thoroughly considering factors including alterations in slope morphology, unloading effects, and the degradation of geotechnical parameters. The research yielded the subsequent conclusions. Multimuddy interlayers were the key to the slope’s instability. For slopes subjected to such multilevel excavation, efforts were made to minimize the exposure of muddy interlayers. Slopes above exposed muddy interlayers did not require additional support, while those below needed prioritized reinforcement. The likely instability mode of the actual slope was local destabilization leading to landslides. Furthermore, when using numerical simulation methods to study the impact of excavation disturbances on the stability of such slopes, it was necessary to consider the deterioration of geotechnical parameters to obtain results more reflective of actual conditions. These research findings provided valuable theoretical and empirical support for studies on similar excavated slopes.

Examining behavioral strategies of residents and enterprises in the context of subsidy phase-outs for waste incineration power plants

An evolutionary game model was utilized in this study to simulate logical behaviors for bounded rational players in a market-oriented environment, centered on the phasing out of subsidies for waste incineration power plants. The findings reveal that (1) enterprises are willing to leverage market mechanisms to address operational requirements through environmentally conscious innovations. These include reducing carbon footprint, conserving energy, and strictly monitoring pollution emissions. (2) Residents tend to adopt cooperative strategies in the game over the long term, experiencing reduced waste disposal fees and increased overall benefits. The community's support notably increases as the company lowers fees to just 40% of the initial rate. (3) Both players demonstrate marked sensitivity to the corporate revenue augmentation factor; when it surpasses a threshold of 1.025, the company can sustain technological advancements and reach equilibrium. (4) The market-oriented ecological compensation bolsters enterprise-community cooperation, effectively reducing public opposition to waste incineration facilities. An innovative ecological compensation model was established in this study, which integrates positive and negative external influences while balancing the principles of compensating victims and ensuring beneficiaries' contributions.

Emission characteristics and removal of heavy metals in flue gas: a case study in waste incineration and coal-fired power plants.

Heavy metal pollutants such as Hg, As, Pb, Cr, and Cd emitted from coal and waste combustion have received widespread attention. In this study, we systematically investigated the emission characteristics of heavy metals in waste incineration and coal-fired flue gases, focused on testing the removal effect of self-made cold electrode electrostatic precipitator (CE-ESP) on heavy metals in flue gas, and made a comparative analysis with the existing air pollution control devices (APCDs). Test results from waste incineration power plant showed that each APCD showed a certain effect on the removal of heavy metals in condensable particulate matter (CPM), with an average removal efficiency of bag filter was 86%, but its effect on Hg removal was slightly worse. Under the coupled field with electrified cold electrode plate operation mode, the average removal efficiency of CE-ESP on heavy metals in CPM was as high as 93%, including 76% for Hg. The removal efficiency of heavy metals (especially Hg) in CPM increased with the increase of flue gas temperature difference between inlet and outlet of CE-ESP. Test results from this coal-fired power plant showed that heavy metals were enriched in fly ash to a higher degree than in slag, the synergistic control of heavy metals in submicron particulate matter by the dust remover was not obvious, and there was a significant correlation between each heavy metal emission factor and its content in coal. Under the temperature field with non-electric cold electrode plate operation mode, the overall effect of CE-ESP on the removal of gaseous heavy metals was better than that of particulate heavy metals. Under the conventional electric field operation mode, CE-ESP was less effective in removing particulate Cr and gaseous Hg0. Under the coupled field with electrified cold electrode plate operation mode, the average removal efficiencies of CE-ESP for particulate and gaseous heavy metals were 82.37% and 76.16%, respectively.

Bi-level scheduling model for a novel virtual power plant incorporating waste incineration power plant and electric waste truck considering waste transportation strategy

Bi-level scheduling model for a novel virtual power plant incorporating waste incineration power plant and electric waste truck considering waste transportation strategy

Modelling nitrogen oxide emission trends from the municipal solid waste incineration process using an adaptive bi‐directional long and short‐term memory network

AbstractAccurately predicting trends in NOx emission is essential for effectively controlling pollution in municipal solid waste incineration (MSWI) power plants. However, the MSWI process exhibits notable dynamic nonlinearity, time series characteristics, and fluctuations that are distinct from those present in fossil fuel combustion processes. Therefore, the model must possess excellent capabilities in handling time series and nonlinear features while achieving adaptive updates to account for complex working conditions. To address these issues, we have developed a robust prediction model for NOx emission trends using the bi‐directional long short‐term memory (Bi‐LSTM) deep learning algorithm. This model encompasses maximum information coefficient and expert experience for input variables selection, parameter optimization using the linear inertial weight particle swarm algorithm (LDWPSO), and an adaptive update strategy based on probabilistic statistics. The prediction performance of this model was compared to that of the traditional and widely used backpropagation neural network (BPNN), extreme learning machine (ELM), and LSTM. Furthermore, we verified the adaptive update effect of the proposed model using additional data. The results demonstrate that the proposed model exhibits robust prediction and adaptive capabilities. This study's originality is presenting a satisfactory trend prediction for NOx emission from the MSWI process using an adaptive LDWPSO‐(Bi‐LSTM) model. It will be essential for the optimization and control of NOx emissions from the MSWI process.

Application of Multivariate Reinforcement Learning Engine in Optimizing the Power Generation Process of Domestic Waste Incineration

Garbage incineration is an ideal method for the harmless and resource-oriented treatment of urban domestic waste. However, current domestic waste incineration power plants often face challenges related to maintaining consistent steam production and high operational costs. This article capitalizes on the technical advantages of big data artificial intelligence, optimizing the power generation process of domestic waste incineration as the entry point, and adopts four main engine modules of Alibaba Cloud reinforcement learning algorithm engine, operating parameter prediction engine, anomaly recognition engine, and video visual recognition algorithm engine. The reinforcement learning algorithm extracts the operational parameters of each incinerator to obtain a control benchmark. Through the operating parameter prediction algorithm, prediction models for drum pressure, primary steam flow, NOx, SO2, and HCl are constructed to achieve short-term prediction of operational parameters, ultimately improving control performance. The anomaly recognition algorithm develops a thickness identification model for the material layer in the drying section, allowing for rapid and effective assessment of feed material thickness to ensure uniformity control. Meanwhile, the visual recognition algorithm identifies flame images and assesses the combustion status and location of the combustion fire line within the furnace. This real-time understanding of furnace flame combustion conditions guides adjustments to the grate and air volume. Integrating AI technology into the waste incineration sector empowers the environmental protection industry with the potential to leverage big data. This development holds practical significance in optimizing the harmless and resource-oriented treatment of urban domestic waste, reducing operational costs, and increasing efficiency.

Ammonia emission characteristics and ammonia injection control from stationary source in flue gas denitrification system

With the implementation of ultra-low emission of nitrogen oxides, denitrification technologies, such as selective catalytic reduction, selective non-catalytic reduction or selective non-catalytic reduction combined with selective catalytic reduction, have been widely used in gas-fired power plants, cement plants and municipal solid waste incineration power plants. These three denitrification industries have become the main potential fixed sources of ammonia emissions in urban areas, however the studies on ammonia emissions are lacking. In order to study the ammonia emission characteristics and ammonia injection control of gas-fired power plants, cement plants and municipal solid waste incineration power plants, field tests were carried out on five typical denitrification enterprises using three monitoring methods. The multi-form ammonia manual monitoring method proposed in this study distinguished and defined all possible ammonia in the flue gas into filterable ammonia, residual ammonia, condensable ammonia and gaseous ammonia according to the migration and transformation behavior during the collection process. The monitoring results of the multi-form manual monitoring method can more accurately reflect the actual ammonia emission level with the simultaneous collection and monitoring of different ammonia forms. The ammonia emission levels in cement plants (more than 20 mg/m³) were higher than that of gas power plants and waste incineration plants (almost less than 4 mg/m³). The condensed ammonia was the dominant form of ammonia, accounting for 58.4%～88.7%. The humidity and temperature of flue gas at the chimney outlet had significant influence on residual ammonia. For the denitration enterprises using a single denitrification technology, the ammonia emission had a linear negative correlation with that of nitrogen oxide with changing ammonia injection amount, while for that using combined denitrification technology, the degree of collaboration between selective non-catalytic reduction ammonia injection control and selective catalytic reduction ammonia injection control played a decisive role in the control of nitrogen oxide emission and ammonia emission, especially the selective catalytic reduction ammonia injection control.

Experimental study on adsorption of PbCl2 and CdCl2 on kaolin modified by leachates from municipal solid waste incineration power plant

Six kinds of waste liquids produced in the treatment process of leachate in a waste incineration plant were used to improve the adsorption effect of raw kaolin on heavy metal chloride. The capture performances of these modified kaolin on PbCl2 and CdCl2 vapor were investigated in a two-stage fixed bed combustor. The results indicated that the adsorption effects of raw kaolin on PbCl2 and CdCl2 were improved in some experimental groups, main effective component was Na+ in the leachate, but the influences did not change regularly with the increase in the concentration of Na + introduced into kaolin. The adsorbents formed by modifying 10 g kaolin with 21.25 ml leachate 2 were the best adsorbents for PbCl2 and CdCl2. The capture efficiencies of PbCl2 and CdCl2 can reach 95% and 63.88%, with the increase of 36% and 53%, respectively. Using leachate as modifying agent had the same effect as directly using Na+. Adsorptions of PbCl2 and CdCl2 were still mainly chemical adsorptions. After adsorption of PbCl2, the modified kaolin not only generated PbA12Si2O8, but also produced other chemical compounds. The adsorption of CdCl2 by modified kaolin did not generate CdAl2Si2O8, but other chemical reactions occurred to generate CdAl2O4 and Pb8Cd (Si2O7)3.

Research on Deformation Failure Mechanism and Stability of Bedding Cataclastic Rock Slope Containing Multi-Muddy Interlayers

Based on the excavated slope of a waste incineration power plant in Yuxi, Yunnan Province, China, the finite element strength reduction method was used to investigate the variation rules of the safety factor, displacement, and deformation of the bedding cataclastic rock slope containing multi-muddy interlayers under the different conditions of number of muddy interlayers n, inclination angle θ, cohesion c, and angle of internal friction φ. Moreover, the deformation failure mechanism and stability of bedding cataclastic rock slope containing multi-muddy interlayers were revealed. The results showed that, as n increased, the maximum horizontal displacement of the slope increased, the factor of safety decreased, and the key influence on the stability of the slope was the muddy interlayers through the toe of the slope. As θ increased, the horizontal displacement of the slope first increased, then decreased, and then increased again, the safety factor first decreased, then increased, and then decreased again, and the stability of the upright laminar slope was slightly larger than that of the horizontal laminar slope. When the slope angle β was 45°, with the increase in θ, the failure mechanism of the slope manifested as a compression-shear failure, traction-sliding failure, traction-sliding-bending-shear failure, flexural deformation, and bending-buckling-collapse failure in sequence. As c increased, the slope evolved from traction-sliding failure to traction-sliding-bending-shear failure; the stability of the slope increased as c and φ increased.

Feasibility of thermal disposal masks in domestic waste incinerators: a study on the combustion characteristics, gaseous pollutant emissions characteristics and control of masks

ABSTRACT Discarded disposable medical masks generated due to the COVID−19 epidemic are overwhelming the current medical waste disposal facilities. Thermal disposal masks in domestic waste incinerator can both utilize the heat energy released by their combustion and dispose of the headache-inducing masks in a harmless manner. The masks are divided into 6 parts: white inside (WI), filter (FI), blue outside (BO), bonding of 3 parts (BP), ear strap (ES) and nose wire (NW). The highest burnout temperature (Tb) of each part of the mask was only 481.2°C and had a high HHV of 40.47 MJ/kg, which has a high energy potential as an energy source. The NOx, SO2, and HCl emission characteristics of each part of the masks were evaluated in a fixed-bed reactor. BP, BO, and ES contradict SO2 and HCl emission limits in China. The SO2 and HCl emission peaks of the masks with the addition of 10 wt% Ca(OH)2 did not exceed 60 mg/m3, which made the combustion emissions of the masks comply with GB 18,485–2014. Considering subsidies for disposal of masks and power generation, blending masks with a 1%−5% ratio enhances the subsidy revenue of waste incineration power plants by 12.63%−63.13%.

Cataclastic Characteristics and Formation Mechanism of Dolomite Rock Mass in Yunnan, China

The dolomite rock mass on the slope of the Yanhe domestic waste incineration power plant was used as the research object. The macro- and micro-structural characteristics of intact rock blocks and rock discontinuities were analyzed qualitatively and quantitatively using in-hole television, wave velocity testing, three-dimensional laser scanning techniques, photogrammetry, image processing techniques, and scanning electron microscopy (SEM). The study shows that the degree of fracturing generally decreases with depth over the exposed borehole depth range, and the rock masses are generally very fractured. The wave velocity of dolomite generally increases with the depth of the borehole, and the integrity of the dolomite is either broken or extremely broken. The excavation profile reveals six sets of discontinuities and joints that are straight, smooth, interconnected, and largely unfilled. The angles of the structural bodies of different grain sizes are sharp, with roundness being angular and sharp-angled. The smaller the blocks, the more complex the surface morphology. SEM observations show that the ultramicroscopic fractures are not flat and smooth, and the fractures are folded. Fracturing mainly occurs along intercrystalline and crystal interfaces. These fracture features suggest that the fracturing of dolomite is mainly related to the original sedimentary construction and tectonism.

Tracking the life-cycle greenhouse gas emissions of municipal solid waste incineration power plant: A case study in Shanghai

Municipal solid waste incineration (MSWI) has become the predominant waste-to-energy technology in China. The present work addresses an onsite greenhouse gas (GHG) emissions accounting approach for MSWI plants. A comprehensive life-cycle GHG emissions assessment model was developed and applied to a case study in Shanghai. Different methods (Method 1: CO2 concentration measurement-based method; Method 2: O2 concentration measurement-based method; and Method 3: Intergovernmental Panel on Climate Change (IPCC) 2006 guidelines-based method) were compared for calculating the fossil CO2 emissions (FCO2E) originating from waste incineration. The results indicate that the deviations of FCO2E among different methods could be effectively reduced by modifying the dry matter (DM) content since the waste in China is commonly featured by high moisture content. Moreover, the life-cycle GHG emissions of MSWI in each month ranged from 11.2 to 622.4 kg CO2-eq/t MSW, in which FCO2E yielded the most significant impact. The seasonal characteristics of GHG emissions were directly related to variations in the waste components. In particular, a high plastics fraction in the waste streams after source separation contributed to high levels of GHG emissions originating from Chinese MSWI plants. It was demonstrated that GHG emissions increased by approximately 12.1 kg CO2-eq/t MSW with a 1% increase in the plastics fraction. Therefore, properly increasing the recycling rate of plastics and improving the power generation efficiency could effectively reduce the GHG emissions associated with MSWI.

Gradient boosting decision tree in the prediction of NO[formula omitted] emission of waste incineration

This paper investigates the real-time prediction of nitrogen oxides (NOx) emission by using around 17000 samples involved in a collection of three-day real data from a waste incineration power plant. To disclose the relationship between the ammonia (NH3) ejection and NOx emission, we choose the NOx reduction from inlet to outlet rather than the NOx concentration monitored by continuous emission monitoring system (CEMS). A hybrid procedure is developed to select appropriate features from the large and unsynchronized data, with which we establish a model based on the gradient boosting decision tree (GBDT) for the prediction. Computational experiments demonstrate that, with root mean square error (RMSE) values being 1.851 and 3.593 for training and test data, respectively, GBDT outperforms its two popular counterparts, supporting vector regression (SVR) and long short-term memory (LSTM). Shapley additive explanations (SHAP) is also conducted for analysis.

Characteristics, secondary transformation and odor activity evaluation of VOCs emitted from municipal solid waste incineration power plant

Volatile organic compounds (VOCs) emitted from municipal solid waste incineration power plant (MSWIPP) plays a significant role in the formation of O3 and PM2.5 and odor pollution. Field test was performed on four MSWIPPs in an area of the North China Plain. Nonmethane hydrocarbons (NMHCs) and 102 VOCs were identified and quantified. Ozone formation potential (OFP), secondary organic aerosol formation potential (SOAFP), and odor activity of the detected VOCs were evaluated. Results showed that the average concentration of NMHCs and VOCs were 1648.6 ± 1290.4 μg/m3 and 635.3 ± 588.8 μg/m3, respectively. Aromatics (62.1%), O–VOCs (16.0%), and halo hydrocarbons (10.0%) were the main VOCs groups in the MSWIPP exhaust gas. VOCs emission factor of MSWIPP was 2.43 × 103 ± 2.27 × 103 ng/g-waste. The OFP and SOAFP of MSWIPP were 960.18 ± 2158.17 μg/m3 and 1.57 ± 3.38 μg/m3, respectively. Acrolein as the dominant VOC species was the major odor contributor with a percentage of odor contribution of 65.9%. Benzene and 1,2,4-trimethylbenzene as the dominant VOC species were the main contributors of O3 formation potentials, in which 1,2,4-trimethylbenzene was also the main contributors of SOA formation potential.

Research and analysis of environmental legal compensation mechanisms related to waste incineration in the context of “double carbon”

In the context of “double carbon,” waste disposal has become a critical issue so far, and how to deal with it is the key to ensuring compliance with the double carbon target, the most practical treatment is still incineration, and how to establish the site selection and legal compensation mechanism is crucial. This paper establishes an environmental dynamic monitoring system for waste incineration power plants based on the Gaussian model and successfully solves the health risk of surrounding residents. Regarding the economic compensation issues, we first applied the AHP to analyze the pollutants comprehensively, constructed the judgment matrix, and conducted a consistency test, determined the weight of each index, and integrated various emissions into one pollutant, which is convenient for the concentration of pollutants. Then, by taking into account the effects of wind direction, rainfall, topography, and other factors on the diffusion of pollutants, we calculated the pollutants around the waste incineration power plant site based on the “elevated continuous point source” “diffusion model.” To obtain the concentration distribution, monitoring points were set up at representative locations, and the environmental monitoring system of the waste incineration power plant was established. Finally, Matlab software was used to draw the contour map of pollutant concentration, and the concentration level of pollutants was divided according to waste incineration. Given the income of the power plant, the economic level of the surrounding residents, the amount of compensation from the local government, and the pollution level, economic compensation plans for the surrounding residents were developed. Through analyzing the proposed compensation scheme, it can be known that the compensation scheme can satisfy the surrounding residents. The highlights of this paper can be described as follows: First, the analytic hierarchy process is used to comprehensively consider the pollutants, simplifying the establishment process of the model. Second, the pollutant concentration is graded, and the concentration equivalent map is drawn to make the monitoring point layout more representative. The economic compensation plan is more reasonable and more convincing to the public.

Comparison of property price development in regions affected by mining with other regions of the CR

The property market has experienced a sharp increase in prices recently, which indicates a different nature of the Covid 19 downturn of the economy compared with usual economic crises. This paper identifies key features of the property market which may help understand why the property market performs differently from other markets. A number of factors play an important role in shaping real estate prices, some of which can and cannot be influenced. The quality of the environment is often one of the main important factors, which is also presented by air pollution values. Apart from transport, waste incineration and thermal power plants, the most common causes of air pollution include the mining industry's activities. We aim to explain why property prices do not converge across regions, but prices in expensive regions experience an even stronger price dynamics, a recent phenomenon. We argue that the price dynamics have been predominantly demand-driven in a market with an unelastic and lacking supply of new properties. The real estate market was also significantly affected by the monetary and fiscal policies of individual states. It has been found that money, which has been invested on a large scale in all sectors of the economy in order to limit the negative effects of pandemic measures, has often found its way to investing in assets of all kinds. As a result, real estate prices are rising sharply, especially in richer areas with minimal unemployment. This article aims to offer a deeper insight into the relationship between flats/house prices and variables that proved to be significantly correlated to prices in regional decomposition. Finally, we suggest ways for sustainable future development of the property market.

Intelligent Modeling of the Incineration Process in Waste Incineration Power Plant Based on Deep Learning

The incineration process in waste-to-energy plants is characterized by high levels of inertia, large delays, strong coupling, and nonlinearity, which makes accurate modeling difficult. Therefore, an intelligent modeling method for the incineration process in waste-to-energy plants based on deep learning is proposed. First, the output variables were selected from the three aspects of safety, stability and economy. The initial variables related to the output variables were determined by mechanism analysis and the input variables were finally determined by removing invalid and redundant variables through the Lasso algorithm. Secondly, each delay time was calculated, and a multi-input and multi-output model was established on the basis of deep learning. Finally, the deep learning model was compared and verified with traditional models, including LSSVM, CNN, and LSTM. The simulation results show that the intelligent model of the incineration process in the waste-to-energy plant based on deep learning is more accurate and effective than the traditional LSSVM, CNN and LSTM models.