Effect Of Reduction Research Articles

Autonomic modulation with mindfulness-based stress reduction in chronic kidney disease: a randomized controlled trial.

Chronic kidney disease (CKD) is characterized by overactivation of the sympathetic nervous system (SNS) that leads to increased risk of cardiovascular disease. This study was conducted to evaluate the effects of a Mindfulness-Based Stress Reduction (MBSR) programme on SNS activity in CKD patients. Participants with CKD stages III-IV were randomized to the 8week MBSR programme or Health Enhancement Program (HEP; a structurally parallel, active control group). Intraneural measures of SNS activity directed to muscle [muscle sympathetic nerve activity (MSNA)] via microneurography was recorded at rest and during stress manoeuvres (mental arithmetic, handgrip exercise and cold pressor test). Data analyses were performed based on the intent-to-treat principle. In total, 29 participants (64±9years; 86% males) completed the intervention with 17 in the MBSR and 12 in the HEP groups. There was a significant Group (MBSR vs. HEP) by Time (baseline vs. post-intervention) interaction in MSNA reactivity to mental stress (P=0.029), with a significant reduction in the mean ∆MSNA over 3min of mental arithmetic at post-intervention (10.3±4.2-5.9±5.6 bursts/min, P<0.001; Hedges' g=-0.858, 95% confidence interval [-1.578, -0.167]), while no change was observed within the HEP group (P=0.818). Reduced ∆MSNA during handgrip exercise was also observed, while ∆MSNA during the cold pressor test and resting MSNA remained unchanged in both groups from baseline to post-intervention. In this randomized controlled trial, patients with CKD had a reduction of sympathetic reactivity during mental stress and static handgrip exercise following 8weeks of MBSR but not after HEP. Our findings demonstrate that mindfulness training is feasible and may have clinically beneficial effects on autonomic function in CKD. KEY POINTS: Question: Does the Mindfulness-Based Stress Reduction (MBSR) programme reduce sympathetic activity in patients with chronic kidney disease (CKD)? Finding: In this randomized controlled trial including 29 patients with CKD, 8weeks of MBSR decreased sympathetic reactivity to mental stress compared to the control Health Enhancement Program (HEP). Meaning: These finding suggest that mindfulness training may have clinically beneficial effects on autonomic function in CKD.

Hybrid Nanofluids in Solar Thermal Collectors: Size and Cost Reduction Opportunities

Solar thermal collector, an alternative way to harvest renewable solar energy, requires high heat transfer area. Hybrid nanofluid has potential to reduce the size of the collector due to its high thermal conductivity and low specific heat capacity. This study investigates the effects of Multi-Walled Carbon Nanotubes (MWCNT) combine with metal oxides, including Al2O3, CeO2, TiO2, ZnO at the volume ratio of 1:4 between MWCNT and metal oxides with a total of 1 vol.% in water. The investigation focuses on assessing this nanofluids with 1 kg/min mass flow rate for its effect in size and cost reduction. Following the validation of nanofluids properties predictor and the numerical model of flat plate solar collector with experimental data, the effects in terms of size and cost reduction is evaluated. In best case scenario, the use of MWCNT-TiO2 can reduce the size of flat plate solar thermal collector by up to 8.54% and cost by 5.15% compared to using water as the heat transfer fluid.

THE INFLUENCE OF REVERSE GEOMETRIC MODELING TO THE DIMENSIONS AND SHAPE OF THE 3D MODEL

The aim of the study is to investigate the effect of point reduction on the dimensions of a part produced by two different additive technologies, Stereolithography (SLA) and Fused Deposition Modelling (FDM). Also, the effect of polygonization methods on the number of points and file size. For the purpose of the experiment, a part was fabricated which was made up of geometric elements, which served to investigate the influence of the reverse geometric modelling on parameter variation. Subsequently, the model was made into two samples by additive manufacturing FDM and SLA on Stratasys F370 (FDM) and Form 3 (SLA). From the fabricated samples, 3D data was collected on a Metrotom industrial CT 1500, cloud of points was obtained and polygonised in various ways in CAQ software GOM Inspect and CARE software VG Studio MAX. The evaluation as well as the process reverse modelling was performed in Autodesk Powershape software. The results show that different polygonization methods affect the number of polygonal mesh points and the volume of data. It was also found that the reduction of the points by which the polygonal network is formed leads to variations in the dimensions of the geometric features. Another important factor is the method of additive manufacturing of the component, where we have shown point reduction has a different effect for a component manufactured by SLA and a component manufactured by FDM.

How does the adoption of nutritional plans influence the performance of meat quail during the growth phase in hot environments?

The present study aimed to evaluate the effects of different nutritional plans on meat quails subjected to heat stress. A total of 324 quails male European quails (Coturnix coturnix coturnix) were used, with an average initial weight of 121.48 g ± 3.1 g, distributed in a completely randomized design with nine treatments and six repetitions of six birds each. The diets were evaluated from 22 to 42 days of age, according to the following treatments: T1 - Control diet; T2 - Moderate crude protein (CP) reduction, without amino acid supplementation (AA); T3 - Moderate CP reduction with supplementation of methionine (Met) and cystine (Cys); T4 - Moderate CP reduction with Met, Cys, and lysine (Lys) supplementation; T5 - Moderate CP reduction with Met, Cys, Lys, and threonine (Thr) supplementation; T6 - Severe CP reduction, without AA supplementation; T7 - Severe CP reduction with Met and Cys supplementation; T8 - Severe CP reduction with Met, Cys, and Lys supplementation; T9 - Severe CP reduction with Met, Cys, Lys, and Thr supplementation. The room temperature was maintained at 30°C, with relative humidity at 76.42%, and a black globe humidity index (BGHI) of 82.19. No significant (p &amp;gt; 0.05) effect of protein reduction or amino acid supplementation was observed on live weight, feed intake, carcass weight, yield, breast, legs, heart, and gizzard. However, significant effects were observed on weight gain (p &amp;lt; 0.04), feed conversion (p &amp;lt; 0.05), liver weight (p &amp;lt; 0.001), and liver yield (p &amp;lt; 0.001). In hot environments, crude protein in the diet of meat quails can be reduced from 22 to 17.6%, with adequate methionine supplementation to achieve 0.800% digestible Met + Cys during the growth phase (22–42 days). These nutritional strategies may optimize performance, reduce costs, and provide environmental benefits by decreasing nitrogen excretion. Future research should investigate the interactions between diet, heat stress, and quail performance, focusing on different amino acid combinations and their impacts on bird health and productivity under varied thermal conditions.

Distribution dynamics, spatial differences, and convergence of synergistic pollution and carbon reduction in China.

Carbon and pollution reduction are highly synergistic elements of green development, and the detailed derivation of the synergistic relationship is urgently needed. Based on the research perspective of coupling coordination, this paper firstly bases on the research perspective of coupling synergy, takes 30 provinces in China as the research object from 2011 to 2022, and constructs a coupling coordination degree model to measure the synergistic effect of pollution reduction and carbon reduction; secondly, kernel density and Dagum coefficient are used to analyze the spatial and temporal characteristics, spatial differences and sources of differences in the synergistic effects of pollution reduction and carbon reduction in China as a whole, in the three major regions and in each province; finally, the Moran index is applied to test the spatial agglomeration characteristics of the synergistic effect of pollution reduction and carbon reduction, and the spatial panel model is applied to test its β-convergence. The study shows that (1) during the study period, the level of synergistic effect on carbon reduction in China changed from good coordination to good coordination, and the synergistic effect in the western region was significantly better than that in the eastern and central regions; (2) the synergistic effect of pollution reduction and carbon reduction in China as a whole and the three regions showed obvious spatial differences, but the differences were gradually narrowing, and the supervariable density was the dominant factor of the overall differences; (3) as a whole, the synergistic effect of pollution reduction and carbon reduction among provinces has a spatial agglomeration effect, and the level of synergistic effect of pollution reduction and carbon reduction across the country and east and west regions has a significant absolute β convergence trend, while there is a significant conditional β convergence trend across the country and the three major regions, and the eastern and central regions with a low synergy level have a higher convergence rate, indicating that as time goes by, under the influence of various factors, the synergistic effect will converge to the steady state level. The purpose of this paper is to analyze the spatial patterns and regional differences in the synergistic effects of pollution reduction and carbon reduction in Chinese provinces and also to provide a quantitative basis for the full implementation of the synergistic regulation of pollution reduction and carbon reduction.

Characteristics of Carbon Emissions of a Hospital in Beijing and the Measures to Cut Carbon Emissions Under Carbon Peaking and Carbon Neutrality Goals

Healthcare-related carbon emissions are an important contributor to global warming, and "Carbon Peaking and Carbon Neutrality" is a major strategy being implemented in China. In this context, strengthening energy conservation and reducing carbon footprint of hospitals is crucial to help achieve the Carbon Peaking and Carbon Neutrality goals is a problem that hospital managers must consider and address. In this study, a general hospital in Beijing was taken as a case study, and its carbon emissions were calculated from 2019 to 2023 to analyze emission characteristics, identify key factors affecting carbon emissions through multiple linear regression models, evaluate the carbon reduction effects of energy-saving and low-carbon projects or measures implemented by the hospital, and propose measures to be adopted in the future.

Seagrasses under stress: Independent negative effects of elevated temperature and light reduction at multiple levels of organization

Seagrasses under stress: Independent negative effects of elevated temperature and light reduction at multiple levels of organization

Measures and effects on soil Cd remediation and safe rice production: a meta-analysis of 10-year Chinese patents

Rice is the staple food for 1/3 of the world’s population, but soil pollution with cadmium (Cd) is harmful to rice production and human health. Therefore, how to reduce the Cd content in rice grains is a hot topic worldwide. However, so far, little is known about Cd remediation technologies for paddy soils from the perspective of patents. Therefore, a meta-analysis was performed to assess the effects of measures based on 1402 observations from 336 patents from 2011 to 2021. The spatio-temporal analysis showed that the number of patents was positively related to the general economic development of the country, but hardly related to the regional economy or the level of provincal Cd pollution. The meta-analysis showed that the overall effect of Cd reduction was slightly higher for combined technologies (59%) than for single technologies (57%). Among all technology classifications, soil applications, which are mainly based on nutritional elements, were the most commonly used technology that could reduce the Cd content in rice grains by 57%. The plant biotechnology was the most effective and could reduce Cd content in rice grains by 76%. Further analysis showed that macronutrients (calcium, phosphorus, and sulfur) were preferred in soil amendments, while micronutrients (silicon, zinc, and selenium) were preferred in foliar amendments. NRAMP5 and HMA3 were the most important genes for manipulating Cd uptake in rice, while Bacillus and Pseudomonas were the most important bacterial taxa for bioremediation of Cd. Overall, this study compiled data on Cd remediation of paddy soil from 10 years of Chinese patents, providing a theoretical basis for better production of low Cd crops and protection of human health.

Migration and catalytic viscosity reduction of biochar-based catalyst fluid in heavy oil reservoir pores

The method for reducing heavy oil viscosity through catalysts has remained experimental. Catalyst aggregation in reservoirs is a challenging issue. This study prepares catalyst fluids with both hydrophilic and oleophilic properties and uses dispersants to inhibit aggregation. Stability is assessed using direct observation and an ultraviolet-visible spectrophotometer, with results showing that a dispersant concentration of 0.05 wt. % stabilizes catalyst fluids. Micromodel experiments are conducted to investigate the catalytic performance and dispersion characteristics of catalyst fluids under various conditions. A post-processing method based on the hue, saturation, and value color space for image recognition and error calculation is proposed to analyze the migration and sweeping effects of catalyst fluids. This method involves identifying images captured by a digital camera, calculating area ratios, and determining recognition errors. The results show that catalyst fluids exhibit the best viscosity reduction ratio (80.0%) and the largest dispersion area ratio (55.7%) when the catalyst concentration is 4 wt. %, the injection velocity is 0.01 ml/min, the reaction temperature is 200 °C, and the reaction time is 24 h. With the increase in injection velocity, the viscosity reduction effect becomes worse. The viscosity reduction effect is improved with the increase in reaction temperature. With the growth of reaction time, the viscosity reduction effect increases and then becomes gentle. The combined mechanism of catalytic viscosity reduction and sweeping effects of catalyst fluids in porous media is proposed. This study provides a theoretical foundation for the large-scale development of heavy oil catalytic viscosity reduction.

Contrasting environmental impacts of nano-biochar and conventional biochar on various organisms

The environmental hazards of nanobiochar (n-BC) require attention due to limited knowledge. This study is the first to explore the effects of biochar size reduction across various organisms, including bacteria (Allivibrio fischeri), plants (Lemna minor, Lepidium sativum), and invertebrates (Daphnia magna, Folsomia candida). Bulk biochar (b-BC) and n-BC were applied in both liquid and solid-phase tests to assess their ecotoxicity. The resulting leachates were tested at concentrations of 2, 10, and 100 mg/L on organisms such as Daphnia magna and Lemna minor. In the solid-phase tests, b-BC and n-BC were added to the OECD soil at concentrations of 1 % and 5 % to evaluate toxicity in Folsomia candida and at concentrations of 1 % to evaluate toxicity in Lepidium sativum. We found n-BC to be significantly more toxic (by 18 % to 2886 %) to A. fischeri than b-BC, with toxicity increasing over time. Low doses (1 %) of both b-BC and n-BC did not cause mortality or inhibit reproduction in F. candida, though b-BC enhanced reproduction (by 30 % to 56 %) compared to n-BC. At a 5 % dose, both b-BC and n-BC inhibited reproduction F. candida, with n-BC being 0.5 to 1.8 times more toxic. Neither b-BC nor n-BC immobilized D. magna, but both inhibited reproduction (by 28 % to 35 %). The nanoscale dimensions of n-BC facilitated bioaccumulation in D. magna, leading to adhesion on the organism's body. The n-BC had a greater impact on plants, both b-BC and n-BC were non-toxic to L. minor, but all n-BC inhibited root growth in L. sativum. These findings highlight the importance of considering biochar size, feedstock, and pyrolysis conditions when evaluating environmental risks, ensuring safe use in sustainable agriculture.

The effect of weight reduction on the diabetes foot: A scoping review and clinical implications

The effect of weight reduction on the diabetes foot: A scoping review and clinical implications

An evaluation method for synergistic effect of air pollutants and CO2 emission reduction in the Chinese petroleum refining technology

The screening and evaluation of co-control technologies for pollution reduction and carbon mitigation represent a crucial prerequisite for researching pathways toward pollution and carbon reduction within petroleum refining industry. A systematic assessment method for technology synergies in pollution reduction and carbon mitigation remains deficient in China. In this study, we propose a method for evaluating the synergistic effects of technologies in pollution reduction and carbon mitigation in the petroleum refining industry. This model evaluates the synergistic control efficacy of technologies from multiple perspectives, including pollution-carbon synergy, synergistic reduction of pollutant-carbon emissions, cost-benefit analysis, and environmental benefits. The developed methodology is validated through its application to typical petroleum refining technology. The results confirm the synergistic benefits of pollution and carbon reduction through five petroleum refining technologies. With the increase in carbon trading prices, bio-jet fuels (T1) and microalgae carbon sequestration (T5) technologies have greater application potential. This study provides a scientific basis and theoretical support for the realization of collaborative control of carbon pollution in the petroleum refining industry.

Surmounting scaling relationship on Cu-base diatomic catalysts by geminal-site-induced synergistic effect for high-selectivity CO2 electrochemical reduction to CO

Cu-based nanomaterials are regarded as the most promising alternatives for catalyzing electrochemical CO2 reduction reactions (ECO2RR). However, its development is impeded by the low selectivity. Improving the selectivity of ECO2RR plays a key role in the commercialized progress of Cu-based nanomaterials. Herein, we screened out the most potential diatomic site from representative Cu-based diatomic catalysts (DACs) and their responsive single-atomic catalysts through theoretical calculations and experiments. The theoretical calculations revealed that the synergistic effect between the diatomic sites in Cu-Mn and Cu-Fe DACs can assist them to break through the limit of scaling relationship and realize the high-selectivity ECO2RR to CO. This was verified by the electrochemical measurements that the as-synthesized nitrogen-doped carbon-supported Cu-Mn and Cu-Fe DACs (Cu-Mn/NC and Cu-Fe/NC) delivered high Faraday efficiency of CO (FECO >90%) at a wide potential range. Furthermore, the Cu-Mn/NC displayed remarkable mass activity of 1760 A g‒1, which is about 27.3 times of a Cu single-atom catalyst, and catalytic stability that goes through a 30-hour electrolytic process without current attenuation at ‒0.6 V. Our work suggests that this synergistic effect can be used as a viable and general strategy to design DACs with high-selectivity ECO2RR for desired products.

Research on controlling measures of snowdrifts around Arctic ground-based buildings through shape optimization

Elevated structures in the Arctic region have proven effective in mitigating surrounding snowdrifts by enhancing the airflow beneath, and serve as a preferred architectural form. However, ground-based buildings still occupy the dominant position due to the constraints posed by construction costs and foundation conditions. One of the effective measures to reduce and prevent snowdrifts around such buildings is to modify their aerodynamic shapes. Therefore, this research endeavors to explore measures for controlling snowdrifts around ground-based buildings through shape optimization. Initially, the predictive accuracy of a refined Mixture model for simulating snowdrifts around ground-based structures was checked against wind tunnel test results. Based on the validated numerical model and representative Arctic meteorological conditions, the snowdrift controlling effects by changing the overall and local building shapes were investigated separately. Overall, the snow reduction and prevention effects can be effectively achieved for ground-based buildings with smoother sidewalls, such as those featuring a circular plane. Conversely, for traditional rectangular ground-based buildings, a larger downwind aspect ratio and a more inclined windward surface can significantly diminish peak snow depth. Additionally, the measures by adding windward side chamfering can effectively manage the locations of snow erosion areas, thereby enabling flexible placement of entrances and exits.

Optimal Dispatch of Coal-fired Power Units with Carbon Capture Considering Peak Shaving and Ladder-type Carbon Trading

In the context of the low-carbon transformation of the power system, carbon markets, and carbon capture technologies have become important means to promote energy conservation and emission reduction. The rapid development of renewable energy poses a challenge to the regulation capability of the power system, and energy storage technology is currently an important means to enhance the regulation capability of the power grid. To reduce the carbon emission level of the power system, improve the system economy and the ability to consume renewable energy, this paper proposes a multi-energy complementary system (MECS) with carbon capture power plant (IFCCPP) considering ladder-type carbon trading (LCT) and energy storage. The optimal dispatch model was developed with the objective of minimizing the overall operating cost. The results indicated that the integration of IFCCPP and LCT has better economic and environmental benefits than separate applications. The integration of the two modes can reduce the total cost by 504.33 k$ and carbon emission by 39232.63 t, which verifies the rationality of integrating the two modes. The LCT produces more significant emission reduction effects due to its higher benefits when carbon emissions are lower. The traditional carbon trading mechanism reduces 4779.88 t of carbon emissions, and LCT reduces 38574.45 t.

Modeling ground vibration excited by a high-speed train running along a viaduct railway using a new structure-soil interaction method

Ground vibrations generated by high-speed trains running along railways either at grade or on viaduct bridges, are greatly concerned by the railway industry. Considering the train-track-bridge-abutment-pile-soil interactions involved, modeling the problem in an analytical manner is almost impossible, while conventional numerical methods struggle to accurately simulate the dynamic properties of infinitely large soils. Therefore, this study introduces a new substructure methodology for train-track-bridge-abutment-pile-soil interactions that leverages an ingenious combination of the 2.5-dimensional finite element-boundary element method (2.5D FE-BE) for dynamics of infinitely long periodic structures, and a local 3-dimensional finite element model for pile-soil interaction. This innovative method allows for the consideration of detailed pile-soil coupling using a local finite element model, all while retaining the ability to account for the infinite size of the soil structure using the 2.5-dimensional finite element-boundary elements. After a comparison between model prediction and field measurement, the model is employed to explore the environmental vibration characteristics of on-viaduct high-speed railways and analyze the vibration reduction effects of various measures, including rail fasteners, track slab pads, and bridge bearings.

Assessment of individual external exposure doses based on environmental radiation in areas affected by the Fukushima Daiichi Nuclear Power Station accident

Assessing individual external exposure doses from ambient dose equivalents is valuable for predictive and retrospective purposes when personal dosimeters are impractical. This study developed a model to assess individual external exposure doses from ambient dose equivalents, considering daily life patterns (location and time spent in various places), and evaluated parameters associated with individual external exposure doses, such as the reduction effects of radiation due to buildings and vehicles. The model parameters were evaluated using the robust datasets of environmental radiation measured in areas affected by the Fukushima Daiichi Nuclear Power Station (FDNPS) accident. The effective dose estimated by the model was compared to 106 daily personal dose equivalents measured using personal dosimeters in the residents’ living environments near the FDNPS. The estimated effective dose well consists with the measured personal dose equivalents, particularly when considering natural radiation in indoor dose estimation. This model is adequate for radiation protection, enabling the predictive and retrospective estimation of individual external exposure doses using environmental radiation monitoring data.

Feasibility assessment of Japan’s fertilizer reduction target: A meta-analysis and its implications for nitrogen waste

Reducing synthetic nitrogen fertilizer (SNF) use is critical for mitigating environmental nitrogen (N) pollution caused by excessive reactive nitrogen and lowering the cost of chemical N fertilizer inputs in agricultural management. In response, Japan has set a national target to reduce chemical fertilizer inputs, with a goal of 30% reduction in SNF use. To assess the feasibility of this target, we collected ca. 1700 records from domestic SNF reduction experiments and conducted a meta-analysis to examine the effects of SNF reduction on crop yield. Using a linear plateau response model of yield to SNF application in the experiments, we assumed that the conventional SNF rates used in control plots were sufficient to reach maximum yield. Our meta-analysis indicates that a 30% SNF reduction in SNF is achievable without significant yield loss on average. This reduction can be facilitated through the use of functional fertilizers and replacement of SNF with organic materials. Additionally, we evaluated changes in nitrogen waste from domestic cropland under the new national target using simple scenarios. Our results show that a 30% SNF reduction, without substituting by organic materials, would only decrease N waste by 8.8%. However, our meta-analysis finds that greater reductions in nitrogen input are possible, indicating potential for further optimization of N management, including the use of organic amendments.

Cooperative Innovation Under the “Belt and Road Initiative” for Reducing Carbon Emissions: An Estimation Based on the Spatial Difference-in-Differences Model

The Belt and Road Initiative holds significant importance for achieving the United Nations’ Sustainable Development Goals, particularly Goals 9 and 17. Drawing on data from the Web of Science database, the BRI database, and the World Bank database, this study explores the potential carbon emission reduction effects that cooperative innovations may bring to participating countries under the Belt and Road Initiative. The study constructs variable endogenous spatio-temporal weight matrices based on initial spatial weight matrices and, drawing on trends in co-authored publications, innovatively establishes time dummy variables and event dummy variables in a difference-in-differences (DID) model. This approach fully considers the interconnected, shared model of the Belt and Road Initiative and the spatial effects of policy implementation. A spatial DID model was established for 106 BRI participating countries and regions from 2005 to 2021. The results reveal the following: first, cooperative innovation under the BRI significantly reduces carbon emission intensity in participating countries. Second, the BRI primarily achieves carbon reduction through investment, innovation, and trade mechanisms. Third, the results of the global SDID model indicate that cooperative innovation with China negatively impacts carbon emission intensity. Also, this effect exhibits spatial spillover, suggesting that there is a policy spillover effect. Fourth, the decomposition of local policy shock effects indicates that the influences of cooperative innovation exhibit spatial heterogeneity, with varying degrees of direct and indirect effects on carbon emission intensity across different countries.

Synergistic effect evaluation method of atmospheric emission reduction based on deep learning fusion model

Currently, the absence of a nonlinear response between air quality and industrial emissions, which accurately captures the complex relationship between pollution levels and emission sources, poses a significant challenge in the formulation of effective control policies. For the purpose of effectively managing industrial emissions and mitigating severe pollution peaks, a new method for evaluating the synergistic effects of atmospheric emission reduction was proposed. The objective of this method is to simulate the impact of emissions on air quality. In particular, we have developed a deep learning fusion model, GR-BILSTM, which integrates a generative adversarial network for data enhancement and a ResNet-BILSTM model to effectively address the issue of gradient disappearance in deep networks and capture high-dimensional data features, thereby improving the model's prediction accuracy. This model is used to study the relationship between emissions and air pollution. Subsequently, a perturbation analysis method is employed to provide a quantitative assessment of the impact of varying types and scales of industrial park emissions on PM2.5 concentrations. By modifying the emission reduction ratio, the PM2.5 concentration in the subsequent moment is predicted, and the correlation between the predicted value and the measured value is examined. This provides a vital point of reference for the formulation of targeted emission policies in industrial parks. In comparison to the LSTM, BILSTM, and CNN-BILSTM models that are commonly employed in this field, the GR-BILSTM model has been demonstrated to exhibit superior performance in terms of fitting accuracy. Our research indicates that the greatest contributions of SO2, NOx, and TSP to PM2.5 pollution in industrial parks are 16 %, 15 %, and 18 %, respectively.