Reduction Of Pollutant Emissions Research Articles

How effective is the reduction of major pollutants in thermal power plants under the ultra-low emission policy?

In 2015, the Chinese government set ultra-low emission standards for thermal power to alleviate the pressure of increasing total pollutants from energy demand. This paper analyzes the policy effect of ultra-low emission in different regions based on panel data of 1202 thermal power enterprises, and the results of hierarchical linear model show that the total amount of air pollutants emitted by thermal power enterprises showed a decreasing trend during 2017–2021, realizing the dual control of concentration and total amount. Due to the differences in primary energy structure, industrial structure and economic development level of different regions, the total emission reduction of thermal power pollutants is affected differently. First, the proportion of the region's secondary industry in the region's GDP is negatively correlated with the decrease of the total pollutant emission of local thermal power enterprises. Second, the higher the per capita GDP of the region, the more significant the decrease in the total amount of pollutants, economic development is conducive to pollutant emission reduction. Third, the higher the proportion of thermal power in local energy, the more obvious the reduction of total pollutant emissions of thermal power enterprises, indicating that the implementation of ultra-low emission policies in these regions is more thorough. In addition, the environmental protection tax plays a positive role in the total emission reduction, and the higher the sulfur dioxide tax rate, the more significant the reduction of total pollutants of thermal power enterprises. To further reduce the total amount of pollutants in thermal power, more coordinated efforts of environmental and economic policies are needed.

Accelerating zero emission truck adoption in urban applications: Beijing analysis and recommendations

With the complete phase out of national new energy vehicle purchase subsidies, Chinese cities need to explore more policy instruments to simulate the adoption new energy trucks (NETs). The study takes Beijing as an example and aims to address: how Chinese cities can craft policies to further promote NETs, considering different NET models operating in divergent duty cycles by different sizes of operators would have different obstacles with vehicle technologies and costs, to achieve its carbon and air pollutant emission reduction goal, while maintaining the livelihood of small and medium carrier in the freight industry. Based on NET technical performance analysis and surveys WRI conducted on carriers in Beijing, we analyze the technological readiness of NETs and the gaps in total costs of ownership (TCOs) between NETs and ICE trucks for each duty cycle category. The study further identifies the policies that are effective to fill the current (2022—2024) technological and cost gaps of NETs, based on literature review and quantitative analysis.

Investigation on Synergism and Its Influence Parameters between Coal and Biomass during Co-Gasification Based on Aspen Plus

The co-gasification of coal and biomass offers numerous benefits, including improved gasification efficiency, reduced pollution emissions, and the utilization of renewable resources. However, there is a lack of comprehensive research on the synergistic effects of, and influence parameters on, coal–biomass co-gasification. This study employs Aspen Plus simulations to investigate the co-gasification behavior of coal and corn straw, focusing on the synergistic effects and the impact of various operating conditions. A synergistic coefficient is defined to quantify the interactions between the feedstocks. Sensitivity analyses explore the effects of gasification temperature (800–1300 °C), coal rank (lignite, bituminous, anthracite), biomass mass fraction (0–50%), oxygen-to-carbon ratio, and steam-to-carbon ratio on the synergistic coefficients of effective syngas content (CO + H2), specific oxygen consumption, specific fuel consumption, and cold gas efficiency. The results reveal an optimal biomass mass fraction of 10% for maximizing cold gas efficiency, with the syngas primarily consisting of H2 (36.8%) and CO (61.6%). Higher gasification temperatures (up to 1200 °C) improve syngas quality and process efficiency, while higher-rank coals exhibit better gasification performance compared to lignite. Optimal oxygen-to-carbon and steam-to-carbon ratios are identified for maximizing syngas yield and quality. These findings provide valuable guidance for the design and optimization of industrial coal–biomass co-gasification processes, enabling the maximization of syngas quality, process efficiency, and resource utilization.

Could environmental regulation effectively boost the synergy level of carbon emission reduction and air pollutants control? Evidence from industrial sector in China

In response to the pressure of combating climate change and enhancing air quality, China has tightened environmental regulations. In China, reducing carbon emissions and air pollutants together has become a critical target for environmental protection. However, no literature explores the impact of environmental regulation on the synergy level of reducing CO2 and air pollutants in the industrial sector. Therefore, this study explores whether environmental regulation could effectively boost the synergy level of carbon emission reduction and air pollutants control in China's industrial sector. We first construct an evaluation indicator system for synergistic emission reduction of CO2 and air pollutants (SO2, NOx, PM), then employs the coupled coordination model to evaluate the synergy level of emission reduction. Furthermore, we explore the impact pathway of environmental regulation on the synergy level of emission reduction. The results indicate that: (1) On the whole, the synergy level shows a slow upward trend, but remains insufficient from 2011 to 2020. (2) Overall, environmental regulation significantly boosts the synergy level of carbon emission reduction and air pollutants control. Regarding the impact pathway, industrial structure has a completely promoting effect, while technical progress exerts a suppressing effect. (3) In regions with higher economic development, environmental regulation has a greater positive influence on synergy level, and the suppressing effect of technical progress is weaker than in less developed regions. These findings could provide helpful references for policy making on synergistic emission reduction of industrial CO2 and air pollutants in China.

Air quality and heath co-benefits of low carbon transition policies in electricity system: the case of Beijing–Tianjin–Hebei region

Low carbon transition strategies of power plants are crucial to meet China’s ‘Dual Carbon’ targets. While the Beijing–Tianjin–Hebei (BTH) region, the ‘capital economic circles’ of China, is suffering from serious air pollution, air quality co-benefits of low carbon transition policies in electricity system in BTH area remain unclear. Here, we estimate the impacts of low carbon transition policies, including one BAU, six single and five combined scenarios, in electricity system in BTH area on installed power capacity, CO2 emissions, air quality and human health through 2060 based on open source energy modeling system and extend response surface model ERSM models. Results show that the total installed capacity under single and combined scenarios (except RE and Tech single scenarios) fluctuates around the BAU level of 310.5 GW in 2060. While all single and combined scenarios would generally achieve ‘carbon peak’ in BTH electricity system before 2030, only S4 (combining technological progress, renewable energy development and CCUS) and S5 (in additional to S4, including gas-fired power generation instead of coal-fired power generation) scenarios have the potential to realize carbon neutrality by 2060. The magnitude of reductions in air pollutant emissions and improvement in air quality in BTH area from the BAU level in 2060 under combined scenarios, especially S4 and S5, generally exceed that of six single scenarios. Importantly, S5 in 2060 contributes to about 8528 avoided premature mortalities in BTH area, which are more effective than any other scenarios. The results suggest that S5 is a promising low carbon transition policy to achieve environmental improvement and produce health benefits.

Green Fiscal and Tax Policies in China: An Environmental Dynamic Stochastic General Equilibrium Approach

Implementing green fiscal and tax policies for reducing emissions and pollution without negatively impacting economic growth remains a challenge. We aimed to determine whether environmental protection and economic growth can both be attained under a green fiscal and tax policy. Specifically, we created a dynamic stochastic general equilibrium (DSGE) model to explore the environmental, economic, and welfare impacts of green fiscal and tax policies. Additionally, a welfare analysis based on an environmental DSGE (E-DSGE) model was performed. We found that (1) raising the environmental or energy tax rate was beneficial for reducing emissions and environmental pollution. However, this approach inhibited economic growth, an outcome not conducive to improving welfare. (2) Increasing the subsidy rate for emission reduction not only incentivized businesses to reduce emissions but also improved economic growth and welfare. (3) The emission reduction mechanisms of environmental tax policies, energy tax policies, and subsidy policies are different. Among them, the environmental tax policy and the energy tax policy both reduce pollution by forcing businesses to increase their emission reduction efforts, but the former is a tax on pollution emissions, while the latter is a tax on energy consumption. However, emission reduction subsidy policies incentivize companies to increase their emission reduction efforts and reduce pollution emissions by alleviating their financial burden. (4) Increasing government spending on environmental remediation could promote economic growth. However, considering that this does not motivate companies to reduce emissions, increasing their share will lead to a reduction in emission reduction subsidies, ultimately negatively impacting social welfare. (5) An environmental tax would cause greater losses in welfare than an energy tax. These findings will enable policymakers to optimize expenditures and tax systems.

Challenges and perspectives of air pollution control in China

Air pollution is one of the most challenging environmental issues in the world. China has achieved remarkable success in improving air quality in last decade as a result of aggressive air pollution control policies. However, the average fine particulate matter (PM2.5) concentration in China is still about six times of the World Health Organization (WHO) Global Air Quality Guidelines (AQG) and causing significant human health risks. Extreme emission reductions of multiple air pollutants are required for China to achieve the AQG. Here we identify the major challenges in future air quality improvement and propose corresponding control strategies. The main challenges include the persistently high health risk attributed to PM2.5 pollution, the excessively loose air quality standards, and coordinated control of air pollution, greenhouse gases (GHGs) emissions and emerging pollutants. To further improve air quality and protect human health, a health-oriented air pollution control strategy shall be implemented by tightening the air quality standards as well as optimizing emission reduction pathways based on the health risks of various sources. In the meantime, an “one-atmosphere” concept shall be adopted to strengthen the synergistic control of air pollutants and GHGs and the control of non-combustion sources and emerging pollutants shall be enhanced.

Utilization of RSM to optimize the performance and emissions of a single cylinder diesel engine using waste hazelnut biodiesel

One of the environmentally friendly, biodegradable, and renewable alternative fuels widely used around the world is biodiesel. Among vegetable oils, hazelnut oil has great importance in biodiesel production due to its high content of oleic acid. For this study, it is aimed to determine the optimum mixing ratio of biodiesel, produced from waste hazelnut oil (WHB). The tests were carried out on a diesel engine operated with WHB/diesel mixtures at different loads. By means of the design of experimental method (DOE), three different fuel ratios (WHB0, WHB15 and WHB30) were defined and tests have been performed. The results obtained from the tests were analyzed using the response surface method (RSM). Engine load and mixing ratio were determined as input factors while CO, NOx, smoke, indicated thermal efficiency (ITE), ignition delay (ID) and break specific fuel consumption (BSFC) were determined as output factors. In the mathematical model created, the R2 values were found to be 0.98, 0.95, 0.91, 0.98, 0.99 and 0.90 respectively. The high R2 values indicated a strong correlation between the optimization outputs and the real experiments. By using these performance and emission parameters, optimization was performed to identify the optimum blend ratio and load. Based on the results, the optimum inputs were determined as 8.46 Nm load and 4.86 % blend ratio. As a result, with the optimized fuel blend, BSFC (8.03 %), ID (3.57 %), and NO (2.87 %) increased while ITE (7.7 %), CO (18.37 %), and smoke (26.15 %) decreased comparing to WHB0. Despite the slight increase in consumption, the results showed that this blend could be used in an environmentally efficient manner, thanks to the reduction in pollutant emissions.

Economic Dispatch of Multi Regional Power Systems Based on CMOPSO Algorithm

With the progress of society and the aggravation of environmental pollution, the economic dispatch of the power system is developing towards multiple environmental and economic goals. To improve energy utilization efficiency, this study innovatively proposes a multi-objective particle swarm optimization algorithm based on competitive learning, and uses this algorithm to solve multi regional environmental and economic scheduling problems. In addition, the study solves static and dynamic economic (S-DE) scheduling problems in multiple regions through improved competitive group optimization algorithms. The research results show that under different testing systems, the average distribution uniformity indicators of the research algorithm built on competitive learning are 0.8058 and 0.8457, and the average anti generation distance is 67.6316 and 1664.0978. The improved competitive group optimization algorithm solves the maximum, minimum, and average fuel costs for static economic scheduling in multiple regions, which are 656.2243 $/h, 655.8592 $/h, and 655.9866 $/h, respectively. Thus, the designed algorithm can effectively solve economic scheduling problems, which is of great significance for resource integration, saving power generation costs, and reducing pollution emissions.

An efficient minimum cost battery charging and discharging scheduling scheme for electric vehicle using hybrid energy valley-pathfinder algorithm

ABSTRACT Emission pollution is one of the major issues in many growing cities. To overcome the problem and to prevent pollution, “Electric Vehicle (EV)” is one of the best solutions. Moreover, it has both economic and environmental benefits. To increase network reliability and quality, distribution companies contribute effective assistance. The major challenge met by this network is choosing an applicable connecting point for the bi-directional operation in a distribution network. Other issues the network faces are the performance and quality of the distribution network, cost reduction, and geographic location. The system’s stability is affected by connecting to the grid for charging EVs. Therefore, the optimal charging process is needed for the EVs. This paper proposes developing an optimal charging system without damaging the stability of the power system. This optimization is carried out by combining two algorithms and developing a new algorithm called “Final Position of Energy Valley and Pathfinder Algorithm (FP-EVPA).” This algorithm minimizes overall system operating costs. Also, it helps to reduce pollution emissions, grid losses, environmental pollution, nodal offset voltage, peak valley difference of load, charging, and operating costs. The optimized method maintains the quality of the power grid and system stability. It is also helpful for the users for minimal charging costs. The empirical findings of the model are better than 0.19%, 0.2%, 0.18%, and 0.07% of GEO, EOO, EVO, and PFA algorithms in terms of median. The developed FP-EVPA was compared with other traditional algorithms with different test functions to examine the effective achievement of the developed method.

Impact of aerosol concentration changes on carbon sequestration potential of rice in a temperate monsoon climate zone during the COVID-19: a case study on the Sanjiang Plain, China.

The emission reduction of atmospheric pollutants during the COVID-19 caused the change in aerosol concentration. However, there is a lack of research on the impact of changes in aerosol concentration on carbon sequestration potential. To reveal the impact mechanism of aerosols on rice carbon sequestration, the spatial differentiation characteristics of aerosol optical depth (AOD), gross primary productivity (GPP), net primary productivity (NPP), leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FPAR), and meteorological factors were compared in the Sanjiang Plain. Pearson correlation analysis and geographic detector were used to analyze the main driving factors affecting the spatial heterogeneity of GPP and NPP. The study showed that the spatial distribution pattern of AOD in the rice-growing area during the epidemic was gradually decreasing from northeast to southwest with an overall decrease of 29.76%. Under the synergistic effect of multiple driving factors, both GPP and NPP increased by more than 5.0%, and the carbon sequestration capacity was improved. LAI and FPAR were the main driving factors for the spatial differentiation of rice GPP and NPP during the epidemic, followed by potential evapotranspiration and AOD. All interaction detection results showed a double-factor enhancement, which indicated that the effects of atmospheric environmental changes on rice primary productivity were the synergistic effect result of multiple factors, and AOD was the key factor that indirectly affected rice primary productivity. The synergistic effects between aerosol-radiation-meteorological factor-rice primary productivity in a typical temperate monsoon climate zone suitable for rice growth were studied, and the effects of changes in aerosol concentration on carbon sequestration potential were analyzed. The study can provide important references for the assessment of carbon sequestration potential in this climate zone.

The role of political party in firm environmental governance: evidence from China

ABSTRACT The importance of corporate environmental governance and compliance in China is on a noticeable rise. Meanwhile, as the sole governing entity, the Chinese Communist Party’s involvement in the business landscape has sparked extensive interest. In this paper, we use the difference-in-difference framework and show that the mandatory requirement to establish a Communist Party branch within a firm after 2018 significantly reduces the likelihood of receiving environmental penalties. Furthermore, our findings indicate heterogeneous effects across firms as the results are more pronounced for firms that belong to heavily polluted industries, operate in regions with low air quality, or have CEOs and executives without green experience. Additionally, we provide evidence that green innovation can serve as a strategy for firms to enhance their environmental initiatives, consequently leading to a reduction in the penalties they incur. Finally, we demonstrate that firms with Party branches undergo a simultaneous decrease in government environmental subsidies and a reduction in both air and water pollutant emissions after 2018, a series of parallel outcomes attributable to enhanced governance brought about by the Party branch. Our study offers valuable insights into the considerable influence the government has on corporate decision-making and contributes to the emerging literature on environmental compliance.

Does target-based performance evaluation system reduce pollution emissions? Firm-level evidence from China

This paper sheds light on the effectiveness of a concrete target-based performance evaluation system (TPES) for localities in enhancing local environmental enforcement in China. We conduct a difference-in-differences (DID) specification and exploit unique firm-level data to investigate the effects of the TPES on SO2 emission reduction through the Two control Zones (TCZ) policy. The results suggest that the TPES significantly reduces SO2 emissions of firms located at the TCZ cities, both in extensive and intensive margins. We also find that the treatment effects vary largely across enterprise sizes, ownership types, and local economic development. Our findings further verify how the long-standing distortions in the decentralized implementation of nationwide environmental regulations in China are remedied with a proper performance evaluation system.

Implementation of european trends regarding the reduction of air pollutants in Ukraine

The paper analyses European trends in reducing emissions of harmful substances and carbon dioxide. Today, the problem of increasing CO2 is an acute one, and thus the task of decarbonising the planet is an important task for the global community. Along with this, the negative impact of other pollutants, such as NOx and SO2, on the environmental situation in Ukraine and the world as a whole is also important.In order to reduce the amount of polluting gases in the air of Ukraine, it was decided to turn to the experience and practice of the European Union (EU) countries and analyse what has already been done, as well as what is planned to be done in this direction in the coming decades. To this end, we analysed the actual data on the reduction of CO2, NOx, and SO2 emissions by European countries and compared their plans for further emission reductions in the coming years.The theoretical data of the study on the actual reduction of air pollutant and carbon dioxide emissions by European countries, as well as their plans for further reduction of these emissions, are of practical importance, as they show global trends in this problem of global importance and should be applied in all future energy plans both in Ukraine and other countries where this is not taken into account. Therefore, an effective and scientifically based plan for energy saving, clean energy production, and diversification of energy resources is needed to accelerate the transition to clean energy, increase energy independence from unreliable suppliers and unstable supplies of imported fossil fuels (in particular, accelerated phase-out of russian fossil fuels by 2030, which are used by the aggressor as an economic and political weapon), and help solve the climate crisis.

Dynamic evaluation of China's atmospheric environmental pressure from 2008 to 2017: Trends and drivers

Evaluating the pressure of atmospheric pollutant emissions on the atmospheric environment is crucial for effective pollution control and emission reduction policies. This study introduces a novel Atmospheric Environmental Pressure Index (AEPI) and employs a dynamic comprehensive method to evaluate China's Atmospheric Environmental Pressure (AEP) across 31 provinces from 2008 to 2017. The drivers of AEP were analyzed using a spatial panel data model, uncovering the integral role of pollution reduction policies, particularly the Air Pollution Prevention and Control Action Plan, which led to a 25% reduction in AEP during its enforcement. Our findings reveal significant spatial disparities in AEP, with higher levels in the Beijing-Tianjin-Hebei and Yangtze River Delta regions. The regression analysis identifies economic development, industrial structure, energy efficiency, environmental regulations, and urbanization as key influencing factors, though their impacts vary across different regions, suggesting the need for region-specific pollution control policies. Furthermore, the shift in the AEP gravity center from 2008 to 2017 indicated a southeastward movement, suggesting the necessity to focus air pollution control efforts on the southeast provinces. In conclusion, the AEPI developed in this study enables comparative analysis of AEP across different regions and facilitates the monitoring of long-term trends, which is valuable in guiding regional air pollution control in China.

Land-use simulation for synergistic pollution and carbon reduction: Scenario analysis and policy implications

Simulations of sustainable land use and management are required to achieve targets to reduce pollution and carbon emissions. Limited research has been conducted on synergistic pollution and carbon reduction (SPCR) in land-use simulations. This study proposed a framework for land-use simulation focused on SPCR. The non-dominated sorting genetic algorithm (NSGA-Ⅱ) and the entropy weight-based technique for order of preference by similarity to an ideal solution (TOPSIS) were used to optimize the land-use structure according to minimum net carbon, nitrogen, and phosphorus emissions. The cellular automata (CA) Markov model was then utilized to simulate the land-use spatial pattern according to the optimal conditions. The proposed framework was applied to the Dongjiang River Basin, South China, and three other scenarios (natural development (ND), carbon minimization (CM), and pollution minimization (PM)) were designed to validate the effectiveness of pollution and carbon emissions reduction under the SPCR scenario. The land-use structure and the pollution and carbon emissions in the scenarios were compared. The results showed the following. (1) The proportions of cultivated land, woodland, grassland, water, and construction land In the SPCR scenario accounted for 14%, 72%, 4%, 3%, and 7% of the total area, respectively. The carbon, nitrogen, and phosphorus emissions were 42.4%, 6.6%, and 7.8% lower, respectively, in the SPCR scenario than in the ND scenario, demonstrating the advantages of simultaneous pollution and carbon reduction. (2) The kappa coefficient of the CA-Markov model was 0.8729, indicating high simulation accuracy. (3) The simulated land-use spatial patterns exhibited low spatial heterogeneity under the CM, PM, and SPCR scenarios. However, there were significant disparities between the ND and SPCR scenarios. The cultivated and construction land areas were significantly smaller in the SPCR scenario than in the ND scenario. In contrast, the woodland and grassland areas were larger, with most differences in the central and southwestern regions of the Dongjiang River Basin. The results of the current study can be used to formulate effective land use policies and strategies in the Dongjiang Basin and similar areas to achieve the Coupling coordination between pollution reduction and carbon reduction. Policy recommendations include increasing the proportion of woodland and grassland, implementing reasonable constraints on expanding cultivated and construction lands, and establishing farmland red lines to promote synergistic pollution and carbon reduction.

Heterogeneous relations among environmental regulation, technological innovation, and environmental pollution

In this study, interprovincial panel data of China from 2011 to 2020 are selected and empirically examined to determine the effects of three types of environmental regulation tools: command-and-control, market-incentive, and public-participation types. Then, hierarchical regression analysis and instrumental variables are used to analyze and verify the mediating role of technological innovation. Results show no significant relationship between command-and-control regulation and environmental pollution, while market-incentive and public-participation regulations have a significantly negative inhibitory effect on environmental pollution and contribute to pollution reduction. In addition, product and process innovations play partially mediating roles between market-incentive regulation and environmental pollution and between public-participation regulation and environmental pollution, respectively, thus indicating that technological innovation is an effective way to reduce pollutant emissions. Compared with product innovation, process innovation has a better effect on pollution emission reduction but a smaller incentive effect under environmental regulation. This finding indicates that enterprise technology innovation and environmental regulation fail to achieve a suitable match for maximizing environmental benefits. Further analysis shows that the effects of the three types of environmental regulation tools on reducing pollution emissions vary in different periods and show significant changes around 2010. The effects of command-based regulation weaken, while those of the pollution abatement of market-incentive and public-participation regulations increase.

Quantitative Estimation of the Impacts of Precursor Emissions on Surface O3 and PM2.5 Collaborative Pollution in Three Typical Regions of China via Multi-Task Learning

The coordinated control of PM2.5 and O3 pollution has become a critical factor restricting the improvement of air quality in China. In this work, precursors and related influencing factors were utilized to establish PM2.5 and O3 estimation models in the North China Plain (NCP), the Yangzi River Delta (YRD), and the Pearl River Delta (PRD) using a multi-task-learning (MTL) model. The prediction accuracy of these three MTL models was high, with R2 values ranging from 0.69 to 0.83. Subsequently, these MTL models were used to quantitatively reveal the relative importance of each factor to PM2.5 and O3 collaborative pollution simultaneously. Precursors and meteorological factors were the two most critical influencing factors for PM2.5 and O3 pollution in three regions, with their relative importance values larger than 29.99% and 15.89%, respectively. Furthermore, these models were used to reveal the response of PM2.5 and O3 to each precursor in each region. In the NCP and the YRD, the two most important precursors of PM2.5 pollution are SO2 and HCHO, while the two most critical factors for O3 pollution are HCHO and NO2. Therefore, SO2 and VOC emissions reduction is the most important measure for PM2.5 pollution, while VOC and NO2 emission reduction is the most critical measure for O3 pollution in these two regions. In terms of the PRD, SO2 and NO2 are the most important precursors of PM2.5 pollution, while the most important precursors for O3 pollution are HCHO and SOX, respectively. Thus, NO2, SO2, and VOC emission reduction is the most critical measure for PM2.5 pollution, while VOC and NO2 emission reduction is the most critical measure for O3 pollution in the PRD. Overall, this study provides clues and references for the control of PM2.5 and O3 collaborative pollution in the NCP, the YRD, and the PRD.

Effects of contaminant diffusion on the fresh air inlets of a clean room workshop

In this study, a clean workshop is the subject of our research study, and computational fluid dynamics methods are applied to investigate the effect of exhaust pipe height, exhaust velocity, barrier structure, and wind direction on contaminant diffusion from the clean workshop. Results show that an increase in exhaust pipe height and exhaust velocity or a decrease in barrier height can effectively reduce the pollutant concentration at each fresh air inlet (FAI). Along the wind direction, the contaminant concentration initially increases and then decreases as distance increases. When the height of the exhaust pipe reaches 45 m, the effect of pollutants on the FAI is insignificant. When the exhaust velocity reaches 12 m/s, the effect of pollutants on the FAI weakens as the emission speed of flue gas increases. Reducing the height of the barrier to 29–31 m can effectively improve the concentration of pollutants at each FAI. Practical implications The mechanism by which the exhaust pipe height, exhaust velocity, barrier structure, and wind direction affect pollutant diffusion from a clean room workshop is systematically investigated by combining the CFD methods with an actual clean workshop as the research object, and the optimal pollutant reduction conditions are presented, thus providing scientific guidance for the construction of clean plants and the reduction of pollutant emissions.

Synthesis of Fe(III)-g-C3N4 and Applications of Synergistic Catalyzed PMS with Mn(VII) for Methylene Blue Degradation

Refractory organic pollutants pose a great threat to public health in water bodies due to their toxicity and low biodegradability. Developing a method of activating persulfate efficiently and in an environmentally friendly way has become a popular topic of research in current advanced oxidation water treatment technologies. Fe(III)-g-C3N4 was prepared by the calcination method. Fe(III) was anchored on the framework of g-C3N4. The characterization analysis indicated that Fe(III) was successfully loaded on g-C3N4. The best effect for MB degradation was Fe(III)-g-C3N4 (0.1 g/L) dosed with 30 µmol/L KMnO4 for synergistic catalyzed PMS (0.1 g/L), where the degradation rate could reach 95.4%. The optimum temperature for MB degradation was determined to be 10 °C. The optimum pH range of Fe(III)-g-C3N4/Mn(VII) synergistic catalyzed PMS for MB degradation was pH 4.4–6.6 under acidic conditions, and the optimum pH range for MB degradation was pH 8–10 under alkaline conditions. The Fe(III)-g-C3N4/Mn(VII) synergistic catalyzed PMS system was also tested for the degradation of methyl orange and rhodamine b, and good degradation results were obtained with the degradation rates of 87.37% and 84%, respectively. It facilitates the reduction in pollutant emissions, improves water quality and will have a positive impact on the sustainability of the environment.