SO2 Emissions Research Articles

Pollutant Emission and Ash Accumulation Characteristics of Tri-Combustion of Coal, Biomass, and Oil Sludge

To study the ash accumulation and pollutant emission characteristics of tri-combustion of coal, biomass, and oil sludge, a fluidized bed and settling furnace system is established for tri-combustion experiments. The effect of blending ratio (the ratio of biomass and oil sludge range from 30% to 50% and 10% to 20%, respectively) and biomass types are examined. The results show that HTB, coal, and oil sludge reach peak NO and NO2 production at approximately 100 s and 200 s of combustion, respectively, with NOx levels returning to zero around 300 s. SO2 peaks around 100 s and then gradually declines. The blending ratio of HTB:oil sludge:coal at 50%:10%:40% demonstrates the most effective control over NOx and SO2 emissions, reducing NO, NO2, and SO2 production by approximately 33%, 20%, and 50%, respectively. In the ash with a ratio of Hutubi (HTB) + 50% oil sludge, the mass fractions of O, Si, Ca, Al, and Fe are approximately 27%, 23%, 20%, 8%, and 12%, respectively. With the increase in the blending ratio of biomass and oil sludge, the mass fraction of Si in the ash rises, while those of Ca, Al, and Fe decrease.

The differences between remote sensing and in situ air pollutant measurements over the Canadian oil sands

Abstract. Ground-based remote sensing instruments have been widely used for atmospheric research, but applications for air quality monitoring remain limited. Compared to an in situ instrument that provides air quality conditions at the ground level, most remote sensing instruments (nadir viewing) are sensitive to a broad range of altitudes, often providing only integrated column observations. These column data can be more difficult to interpret and to relate to surface values and hence to “nose-height-level” health factors. This research utilized ground-based remote sensing and in situ air quality observations in Canada's Athabasca oil sands region to investigate some of their differences. Vertical column densities (VCDs) of SO2 and NO2 retrieved by Pandora spectrometers located at the Oski-Otin site at Fort McKay (Alberta, Canada) from 2013–2019 were analyzed along with measurements of SO2 and NO2 surface concentrations and meteorological data. Aerosol optical depth (AOD) observations by a CIMEL sunphotometer were compared with surface PM2.5 data. The Oski-Otin site is surrounded by several large bitumen mining operations within the Athabasca oil sands region with significant NO2 emissions from the mining fleet. Two major bitumen upgraders that are 20 km south-east of the site have total SO2 and NO2 emissions of about 40 and 20 kt yr−1, respectively. It was demonstrated that remote sensing data from Pandora and CIMEL combined with high-vertical-resolution wind profiles can provide information about pollution sources and plume characteristics. Elevated SO2 VCDs were clearly observed for times with south and south-eastern winds, particularly at 200–300 m altitude (above ground level). High NO2 VCD values were observed from other directions (e.g., north-west) with less prominent impacts from 200–300 m winds. In situ ground observations of SO2 and NO2 show a different sensitivity to wind profiles, indicating they are less sensitive to elevated plumes than remote sensing instruments. In addition to measured wind data and lidar-observed boundary layer height (BLH), modelled wind profiles and BLH from ECMWF Reanalysis v5 (ERA5) have been used to further examine the correlation between column and surface observations. The results show that the height of emission sources (e.g., emissions from high stacks or near the surface) will determine the ratio of measured column and surface concentration values (i.e., could show positive or negative correlation with BLH). This effect will have an impact on the comparison between column observations (e.g., from the satellite or ground-based remote sensing instruments) with surface in situ measurements. This study explores differences between remote sensing and in situ instruments in terms of their vertical, horizontal, and temporal sampling differences. Understanding and resolving these differences are critical for future analyses linking satellite, ground-based remote sensing and in situ observations in air quality monitoring and research.

Multi-model effective radiative forcing of the 2020 sulfur cap for shipping

Abstract. New regulations of sulfur emissions from shipping were introduced in 2020, reducing emissions of SO2 from international shipping by ∼ 80 %. As SO2 is an aerosol precursor, this drop in emissions over the ocean will weaken the total aerosol effective radiative forcing (ERF) that has historically masked an uncertain fraction of the warming due to the increased concentration of greenhouse gases in the atmosphere. Here, we use four global climate models and a chemical transport model to calculate the ERF resulting from an 80 % reduction in SO2 emissions from international shipping relative to 2019 emission estimates. The individual model means range from 0.06 to 0.09 W m−2, corresponding to the ERF resulting from the increase in CO2 concentration over the last 2 to 3 years. The full uncertainty in the ERF due to the new regulation is not quantified but will very likely be high considering the contribution of uncertainties in shipping SO2 emissions, the sulfur cycle, the modelling of cloud adjustments and the impact of interannual variability on the method for calculating radiative forcing.

Blessing or Curse? Fintech Adoption and Greenhouse Gas Emission Intensity☆

This study investigates the role of fintech adoption in shaping greenhouse gas (GHG) emissions. Exploiting China’s setting and using panel data from 2,400 observations and 281 prefecture-level cities in China from 2011 to 2019, we find that adopting fintech significantly reduces CO2 and SO2 emissions. Further analyses identify the underlying mechanisms as enhanced green innovation and increased fiscal transparency, which strengthen the ability of regions to protect the environment through public governance. To address the potential endogeneity issues arising from non-randomness and the non-exogenous shock of fintech adoption, we employ two novel instrumental variables as the geographical distance of the city to Hangzhou and the number of graduates to re-estimate our baseline results, which yield similar findings. We further find that this effect is more pronounced in regions with better Internet access and less intensive environmental regulations. Moreover, emissions reductions achieved from fintech adoption generate positive economic and social impacts.

Quantifying consumption-based environmental productivity from “Energy-Environment Footprints”

Addressing the challenge of climate change through accounting is crucial for sustainable development, which is influenced by factors such as productivity growth, technical change, efficiency change, and environmental accounting. However, previous studies have predominantly focused on production-based growth accounting, neglecting the significant impact of consumption on growth accounting levels. In response, this study introduces a synthetic index termed as consumption-based environmental productivity. This innovative index utilizes the Luenberger Productivity Index (LPI) and the Logarithmic Mean Divisia Index (LMDI) models, relying on a Multi-regional Input-output (MRIO) footprint instead of direct emissions. Our empirical research found that from 2000 to 2014, certain economies bore a considerable portion of undesirable emissions imported from abroad. This supports the argument that the footprint approach is a valid alternative to direct emissions assessments. Further analysis revealed an overall growth trend in environmental productivity (EP) of 0.79%. Efficiency change (EC) contributed negatively (-0.35%), while technical progress (TP) positively influenced EP by 1.14%. Additionally, our study points out that reductions in NOX and SO2 emissions were primarily due to energy intensity improvements. Conversely, CO2 emissions were driven by individual production factors and economic growth. These results underscore that establishing clear responsibility for emissions is the foundational step in implementing emission reduction policies in an equitable manner. Concurrently, it is crucial to improve the efficiency of energy consumption and mitigate undesirable emissions to significantly enhance productivity, especially for developing economies, policies should prioritize the development of energy cleanliness and energy efficiency. Furthermore, it is imperative for all economies to refrain from pursuing unnecessary economic growth that could lead to excessive emissions.

Impacts of Environmental Conditions on Thermal, Emissions and Economic Performance of Gas Turbine Using Different Types of Fuels: An Experimental Investigation

Gas turbine has been used widely for electrical power generation based on simple cycle system. However, the relatively low thermal efficiency engages the researchers in investigating possible methods to enhance gas turbine performance. In the current study, three different types of fuels were used (crude oil, light oil, and natural gas) to operate the gas power plant in Qayyara, Mosul, Iraq and to evaluate the plant's performance, environmental impact and economic cost. The Aspen Husys package was used for simulation based on data recorded by the control department. Results showed that the software applied was highly valid. The external environmental temperature influenced the performance and efficiency of the station significantly with maximum values obtained for winter by 114MW and thermal efficiency of 32.02% for natural. The emissions of CO2, SO2, and NOX gases are decreased, whereas CO emission is increased when the temperature of the external environment is raised with fewer emissions obtained for natural gas. The cost of three fuels in (summer) is the highest among the four months, with the higher cost for light fuel by 68.2 Iraqi diners/kiloWatt.hour. Therefore, light fuel cannot be used for the permanent operation of gas turbines, and natural gas fuel gives better performance and lower emissions than the other two types of fuels.

Co-firing characteristic prediction of solid waste and coal for supercritical CO2 power cycle based on CFD simulation and machine learning algorithm

The co-firing technology of combustible solid waste (CSW) and coal in the supercritical CO2 (S-CO2) circulating fluidized bed (CFB) can effectively deal with domestic waste, promote social and environmental benefits, improve the coal conversion rate, and reduce pollutant emission. This study focuses on the co-firing characteristics of CSW and coal under S-CO2 power cycle, and simulations are conducted by employing Multiphase Particle-in-cell (MP-PIC) method integrated with the comprehensive chemical reaction models in a 300 MW S-CO2 CFB boiler. Effects of operating parameters including fuel mixture proportion and first stage stoichiometry on the gas emission characteristics are further analyzed. Based on training and testing database based on the simulation results, a novel Improved Whale Optimization Algorithm and Bi-dictionary Long Short-Term Memory (IWOA-BiLSTM) algorithm model is established to predict CFB temperature, NOx emission concentration, and SO2 emission concentration, respectively. Results show that CO and SO2 decrease with the coal mass ratio of the fuel mixture increasing, while NOx increases. With the increase of first stage stoichiometry, CO increases, NOx declines, and the change of SO2 is not obvious. Compared with two other basic algorithm models, the prediction error of the proposed algorithm model for the three targets is minimal with the average relative error of 0.032 %, 0.231 %, and 0.157 %, respectively, which can meet the prediction requirements with acceptable accuracy.

Co-combustion of organic industrial and municipal solid wastes in Shanghai: Evaluation based on energy recovery, thermal behavior and gases pollutants emissions

The imperative for efficient recycling and treatment of organic industrial solid waste (OISW) has spurred the integration of co-combustion strategies with municipal solid wastes (MSW) in recent years in China. Herein, we conducted a detailed analysis of five years data on the production and classification of industrial solid wastes in Shanghai and employed the response surface methodology (RSM) and grey correlation analysis (GCA) to optimizing the blending ratios of five distinct types OISW for their co-combustion with MSW. Proximate and elemental analysis was conducted to analyze the chemical composition of each OISW. The combustion kinetic and typical parameters such as activation energy, ignition and burnout temperatures, comprehensive combustion index of individual OISW and their blending with MSW were examined by Thermogravimetric analysis (TGA). The influences on energy recovery and pollutant gases emissions were assessed and the accuracy was verified by using the Grey artificial neural network (GANN) model. The results indicated that at a 30 % blending ratio of industrial solid waste, the optimal proportions for sewage sludge, waste wood, waste plastic, textile waste, and waste paper were 32.15 %, 5.14 %, 14.32 %, 1.92 %, and 46.47 %, respectively. The optimized blend achieved a significant 29 % decrease in overall carbon emissions and a notable 23 % increase in the energy recovery rate. In this circumstance, the emissions of HCl, SO2 and NOx, were measured at 2.07 mg/m³, 33.46 mg/m³ and 194.81 mg/m³, respectively, all of which are well below the national standards (GB18485—2014) for the emission of flue gas from MSW incineration in China.

Get the real boss in position: Examining the environmental effect of ‘shared environmental accountability’ in China

China implemented the Shared Environmental Accountability between Party Secretaries and Government Officials (SEA) policy in August 2015, aiming to enhance environmental enforcement by holding both the secretaries of the Communist Party of China (Party secretaries) and government officials accountable for environmental issues. This paper examines the environmental effect of the SEA policy, with a particular focus on the role of bureaucrats' personal traits. Based on city-level data from 2011 to 2021, we find that the SEA policy leads to a differential reduction in industrial SO2 emissions and energy consumption by approximately 15.9 % and 32.0 % in cities that have a higher pressure of environmental protection. We also find that the pro-environmental effect of the SEA policy is mainly realized by enhancing energy efficiency and cleaner production. More importantly, we find that the environmental effect of the SEA policy is strengthened by hometown ties if Party secretaries have promotion prospects. Further improvements in emission reduction and energy saving could be achieved if certain countermeasures were undertaken so that Party secretaries, regardless of their promotion potential, are incentivized to faithfully implement environmental regulations.

Enhancing biomass fuel properties of municipal sewage sludge with carbon-rich and low ash energy crops common reed and miscanthus

Wastewater treatment plant effluents, sewage sludge, and purified water are important resources for producing renewable energy and implementing a carbon-neutral green energy policy due to their richness in organic matter and nutrients for energy crops. In the present study, the biomass energy potential, fuel quality, and combustion emission characteristics of sewage sludge and the energy plants Arundo donax and Miscanthus×giganteus and their mixtures were investigated to improve the combustion properties of sewage sludge. The plant biomass is produced using sewage treatment plant effluent as a nutrient source. The proximate and ultimate analysis results showed that adding plant biomass shifted the fuel value of the mixtures, mainly reducing the ash content and increasing the volatile matter and carbon content in the solid biofuel. The regression analysis showed that heating values of 25, 50, and 75 % biomass in sewage sludge mixtures linearly increased HHV and LHV values. The increase in volatile matter significantly improved the ignitability index of sewage sludge, reaching the optimum value of 35 at 75 % biomass mixtures for both crops. The NOx and SO2 emissions of the mixtures were lower than those of sewage sludge. Overall, the results indicate a synergistic effect between the combustion of biomass from energy crops and sewage sludge. A comprehensive comparison of proximate, ultimate, heating value, fuel indices, and gaseous emissions shows that the mixed fuels of 50 % biomass and 50 % sewage sludge can promote combustion and reduce emissions. Arundo had better biofuel properties than Miscanthus.

Environmental taxes promote the synergy between pollution and carbon reduction: Provincial evidence from China

Since its implementation in 2018, China's environmental tax has become a crucial mechanism in the nation's strategy for reducing environmental pollution. However, its synergistic effect between pollution and carbon reduction has not been adequately focused on and evaluated. This study employs the difference-in-differences (DID) model to analyze the impact of the environmental tax policy on the emissions of pollutant and CO2 as well as the synergistic effect between them. The baseline results reveal that the implementation of environmental taxes significantly reduces the emissions of SO2 and CO2 and enhances the level of synergistic effects. This finding passed a series of robustness tests. Additional analysis reveals that the environmental tax promotes reductions in SO2 and CO2 emissions through adjustments in industrial and energy consumption structures. Furthermore, mechanism analysis from an econometric perspective provides theoretical support for the synergistic effect of pollution reduction and carbon mitigation. In the process of achieving CO2 reduction, SO2 plays a crucial mediating role. The heterogeneity effect suggests that in non-coastal areas and regions with larger governmental scales, the environmental tax exhibits significant emission reduction effects. It is advisable to strengthen the legal safeguard of environmental tax, dynamically adjust tax rates, and timely expand the tax scope to improve the environmental tax system and enhance its policy effects. This study provides empirical evidence and policy insights to optimize the environmental tax, offering valuable references for environmental tax reforms in developing countries.

Energy saving and carbon reduction production process of municipal sludge-based biochar: Optimization, simulation, and techno-economic analysis

The production process of municipal sludge-based biochar is a promising and efficient sludge treatment process. However, inefficient cleaner production and limited resource utilization always caused environmental and cost concerns. Based on the measured data of engineering field operation, the optimized production process of energy saving and carbon reduction is put forward by using the process simulation of Aspen Plus software and economic analysis approach, and the sludge treatment capacity is 300 t/d. The objective of the study is to comparatively evaluate the energy efficiency, carbon emission reduction efficiency, and techno-economic performance of the optimized process. The newly added SNCR and low-temperature SCR units are combined denitration and coupled with a waste heat recovery unit to reduce energy consumption. Meanwhile, reduce carbon emissions and NOx emissions in the whole process. The base case of the optimization process and resource utilization was found to be viable. Compared with the conventional process, the energy efficiency is increased by 8.52 %, the total carbon emission is reduced by 27.41 %, and the total emissions of NOx and SO2 emissions are reduced by 78.11 %, thus reducing the environmental burden of greenhouse gas emissions. The total product cost is reduced by 26.76 %, the annual investment rate of return is increased by 27.45 %, the gross profit rate is increased by 23.78 %, and the internal rate of return is increased by 45.19 %, which has excellent profitability.

Bayesian Network Analysis: Assessing and Restoring Ecological Vulnerability in the Shaanxi Section of the Qinling-Daba Mountains Under Global Warming Influences

Human activities, especially industrial production and urbanization, have significantly affected vegetation cover, water resource cycles, climate change, and biodiversity in the Qinling-Daba Mountain region and its surrounding areas. These activities contribute to complex and lasting impacts on ecological vulnerability. The Qinling Mountain region exhibits a complex interaction with human activities. The current research on the ecological vulnerability of the Qinling Mountain region primarily focuses on spatial distribution and the driving factors. This study innovatively applies the VSD assessment and Bayesian networks to systematically evaluate and simulate the ecological vulnerability of the study area over the past 20 years, which indicates that the integration of the VSD model with the Bayesian network model enables the simulation of dynamic relationships and interactions among various factors within the study areas, providing a more accurate assessment and prediction of ecosystem responses to diverse changes from a dynamic perspective. The key findings are as follows. (1) Areas of potential and slight vulnerability are concentrated in the Qinling-Daba mountainous regions. Over the past 20 years, areas of extreme and high vulnerability have significantly decreased, while areas of potential vulnerability and slight vulnerability have increased. (2) The key factors impacting ecological vulnerability during this period included industrial water use, SO2 emissions, industrial wastewater, and ecological water use. (3) Areas primarily hindering the transition to potential vulnerability are concentrated in well-developed small urban regions within basins. Furthermore, natural factors like altitude and temperature, which cannot be artificially regulated, are the major impediments to future ecological restoration. Therefore, this paper recommends natural restoration strategies based on environmental protection and governance strategies that prioritize green development as complementary measures. The discoveries of the paper provide a novel analytical method for the study of ecological vulnerability in mountainous areas, offering valuable insights for enhancing the accuracy of ecological risk prediction, fostering the integration of interdisciplinary research, and optimizing environmental governance and protection strategies.

The Impact of Carbon Emissions Trading Policy on Regional Economy and Pollution Reductions in Chinese Provinces

Carbon emissions trading policy is an important tool to achieve carbon peaking and carbon neutrality goals. In order to explore the effectiveness of carbon emissions trading policy, this paper adopts the difference-in-differences model to analyze the effects of China’s pilot policy on regional economic development and pollution reductions. The results show that carbon trading policy can significantly promote economic development and reduce total carbon emissions, industrial SO2 emissions and solid wastes production of pilot regions. Further research finds that there is significant regional difference in policy effectiveness, with the policy more effective in western areas. In addition to direct effects, carbon trading policy could exert an indirect effect on carbon emissions, air quality, industrial solid wastes and regional economic development by optimizing energy consumption structures and industrial structures and increasing technological investment. This result verifies the “Porter hypothesis”. China should improve the construction of national carbon trading markets, covering more industries, considering the regional differences and negative spillover effect.

The Impact of Firework Ban Relaxation on Variations in SO2 Emissions in China During the 2023 Chinese New Year

During the 2023 Chinese New Year (CNY), many city governments temporarily relaxed firework restrictions, leading to increased sulfur dioxide (SO2) emissions from the combustion of sulfur-containing fireworks. This study employed the four-dimensional variational (4DVar) assimilation system to examine variations in SO2 emissions in China by assimilating hourly ground-based observations. Two experiments were conducted during CNY in 2022 and 2023 to quantify the variations in SO2 emissions. On CNY’s Eve in 2023, following the relaxation of the firework ban, SO2 emissions surged by 8.22 Gg nationwide compared to the previous day with significant increases in the Energy Golden Triangle (2.037 Gg), the North China Plain (1.709 Gg), and northeast China (0.945 Gg). Emissions peaked on CNY’s Eve and rapidly declined in the following two days but remained elevated compared to the pre-CNY period, indicating lingering effects of firework burning. Compared to the forecasts using the prior emissions, the optimized emissions markedly improved the model forecasts of SO2 during the 2023 CNY period, with an increase in the correlation coefficient (R) from 0.13 to 0.64 and a reduction in the root mean square error (RMSE) by 49.2%, demonstrating the effectiveness of the optimized emissions. These findings will be useful for local governments in formulating strategies for firework burning during CNY.

Synergistic Emission Reduction of Carbon Dioxide and Atmospheric Pollutants Under Different Low-carbon Development Scenarios of the Power Industry in Jiangsu Province

The power industry is the main source of carbon dioxide （CO2） emissions in Jiangsu Province and also an important source of sulfur dioxide （SO2）, nitrogen oxides （NOx）, and particulate matter （PM）. In order to address climate change and contribute to the goal of "carbon peaking and carbon neutrality," Jiangsu Province has implemented a series of low-carbon development policies in the power industry. These policies not only reduce carbon emissions but also have important synergistic emission reduction benefits for atmospheric pollutants. Based on the low-carbon development plan for electricity in Jiangsu Province, a baseline scenario （BAU） and four low-carbon development scenarios have been constructed： current policy scenario （CLE）, IEA target scenario （IEA）, accelerated coal-fired power phaseout scenario 1 （STE1）, and scenario 2 （STE2）. An econometric model was used to predict the future electricity demand in Jiangsu Province, and the greenhouse gas-air pollution interactions and synergies （GAINS） model was employed to quantitatively analyze the impact of low-carbon policies in the power sector on the emissions of CO2, SO2, NOx, and PM, which are the major air pollutants in the region. The results showed that the electricity demand in Jiangsu Province has been increasing year by year, with an annual growth rate of approximately 4.01%. Under the BAU scenario, carbon emissions were projected to peak around 2030, with a peak carbon emission level of 462.03 Mt. Under the IEA scenario, it should reach its peak around 2028, with a peak emission level of 380.27 Mt. Under the CLE scenario, the peak would be expected to occur around 2026 at 353.46 Mt. In both STE1 and STE2 scenarios, carbon emissions had reached their peak and were continuously declining after 2020. In all scenarios, the replacement of conventional coal-fired power plants with natural gas （GAS）, nuclear power （NUC）, solar photovoltaic （SPV）, and wind power （WND） showed high synergistic benefits in pollution reduction and carbon reduction. The deployment of biomass energy （OS1） and non-renewable waste energy （OS2） will result in a significant increase in SO2 emissions. Carbon capture and storage （CCS） transformation of coal-fired power only showed significant synergistic benefits after 2035. The development of OS1 and OS2 fuel substitutes in power plants should focus more on reducing SO2 emissions, while upgrading and retrofitting CCS technology should prioritize the reduction of particulate matter emissions. The research findings provide a reference and decision-making basis for the synergistic efficiency of pollution reduction and carbon reduction in the power industry in Jiangsu Province.

Sustainable Solutions in Gas Separation: Exploring the Potential of Deep Eutectic Solvents

In the face of escalating environmental concerns, particularly related to greenhouse gas emissions, this study delves into the potential of Deep Eutectic Solvents (DESs) as a sustainable alternative in gas separation technologies. Focusing on the significant emissions of CO2, SO2, and H2S from industrial processes, this work reviews the application of DESs for their capture and separation. We investigate the physical properties of DESs, such as solubility and viscosity, which are crucial for their efficacy as sorbents. This review includes a comprehensive analysis of various DES formulations, exploring their roles in CO2 absorption, SO2 removal, and the separation of other gases like H2S. Additionally, we extend our examination to the applicability of DESs in the oil and gas industry, highlighting their effectiveness in removing sulfur and nitrogen impurities, and their potential in the extraction of organic constituents. The study reveals that DESs, characterized by their biodegradability and environmental sustainability, offer promising performance in gas separation, aligning with the principles of green chemistry. However, challenges such as high viscosity and the need for further understanding of their solubility dynamics under different conditions are addressed. This work underscores the importance of DESs as novel sorbents for gas purification and sets a foundation for future research aimed at enhancing their application on a broader industrial scale.

Intelligent Optimization and Impact Analysis of Energy Efficiency and Carbon Reduction in the High-Temperature Sintered Ore Production Process.

The coordinated optimization of energy conservation, efficiency improvement, and pollution reduction in the sintering production process is vital for the efficient and sustainable development of the sintering department. However, previous studies have shown shortcomings in the multi-objective collaborative optimization of sintering systems and the quantification of pollutant impacts. To address these, this paper proposes a multi-objective optimization method integrated with the NSGA-III algorithm and establishes an integrated system optimization model for sintered ore production and high-temperature waste heat recovery. The results demonstrate significant improvements: energy utilization efficiency increased by 0.67%, energy consumption decreased by 17.3 MJ/t, production costs were reduced by 11.45 CNY/t, and the emissions of CO2, SO2, and NOx were reduced by 0.464 kg/t, 0.034 kg/t, and 0.008 kg/t, respectively. Additionally, the study identified optimal configuration parameters and analyzed the quantitative impact of several key factors on multiple indicators. The results also show that reducing the water content of the mixture, decreasing the middling coal content in the fuel, and increasing the thickness of the material layer are effective strategies to reduce energy consumption and pollutant emissions in the sintering process. Overall, implementing these optimizations can bring significant economic and environmental benefits to the steel industry.

Displacement Factors for Aerosol Emissions From Alternative Forest Biomass Use

ABSTRACTSubstituting alternative materials and energy sources with forest biomass can cause significant environmental consequences, such as alteration in the released emissions which can be described by displacement factors (DFs). Until now, DFs of wood‐based materials have included greenhouse gas (GHG) emissions and have been associated with lower fossil and process‐based emissions than non‐wood counterparts. In addition to GHGs, aerosols released in combustion processes, for example, alter radiative forcing in the atmosphere and consequently have an influence on climate. In this study, the objective was to quantify the changes in the most important aerosol emission components for cases when wood‐based materials and energy were used to replace the production of high‐density polyethylene (HDPE) plastic, common fossil‐based construction materials (concrete, steel and brick), non‐wood textile materials and energy produced by fossil fuels and peat. For this reason, we expanded the DF calculations to include aerosol emissions of total suspended particles (TSP), respirable particulate matter (PM10), fine particles (PM2.5), black carbon (BC), nitrogen oxides (NOx), sulphur dioxide (SO2) and non‐methane volatile organic compounds (NMVOCs) based on the embodied energies of materials and energy sources. The DFs for cardboard implied a decrease in BC, SO2 and NMVOC emissions but an increase in the other emission components. DFs for sawn wood mainly indicated higher emissions of both particles and gaseous emissions compared to non‐wood counterparts. DFs for wood‐based textiles demonstrated increased particle emissions and reduced gaseous emissions. DFs for energy biomass mainly implied an increase in emissions, especially if biomass was combusted in small‐scale appliances. Our main conclusion highlights the critical need to thoroughly assess how using forest biomass affects aerosol emissions. This improved understanding of the aerosol emissions of the forestry sector is crucial for a comprehensive evaluation of the climate and health implications associated with forest biomass use.

The benefits and burdens of wind power systems in reaching China's renewable energy goals: Implications from resource and environment assessment

Recognizing the economy's growing reliance on global energy landscape transformation on wind power deployment, as well as the general reality that renewable facilities require lower operational but higher up-front inputs than fossil-based power systems, this paper focuses on the life-cycle burdens of wind power systems and their substitution benefits compared with coal-fired power systems. The estimation considers the consumption of nonrenewable sources of energy, emissions of greenhouse gases, and other environmental resource factors that have received significantly less research attention, such as industrial land use, water use, PM2.5, SO2, NOX, and Hg emissions. The scope of this study differs from earlier ones in that it includes a comprehensive description of all the equipment, materials, and services used, as opposed to earlier studies that either omit crucial supporting infrastructure or just focus on the plant's physical structure as its primary materials. Results based on a typical plant in China show that the state-of-the-art onshore wind power systems can provide significant reductions in nonrenewable energy use (9.2 MJ/kWh) and GHG emissions (782.8 GtCO2/kWh). To produce an equivalent amount of electricity, wind power systems require more than three times industrial land use and almost one-third of industrial water use of that for traditional coal-fired power systems. The avoided SO2, Hg, PM2.5, and NOX emissions per unit of electricity generation account for 60.6%–89.3% of the total air pollution emissions induced by supercritical coal-fired power systems. By integrating 3797 operating plant-specific data and fixed-point wind energy information, this study scales up results of the single plant to a country level. The macro picture implies different opportunities born by wind power systems in easing multiple resource and environmental pressures, highlighting the significance of designing hierarchical strategies to improve penetration levels of wind power. By 2050, cumulative climate benefits obtained from onshore wind power technology are predicted to reach 74.2 Gt CO2, achieving around 17.2%–45.5% of the national carbon-neutral goal.