Environmental Protection Research Articles

New urban agenda: sustainable development goals, urban mobility and healthy cities

The trends of modern urban planning are studied, namely two of its urban planning concepts - “Plan for Sustainable Urban Mobility” and “Healthy City”, their theoretical development within the framework of adopted documents, agendas and programs for sustainable development. The goals of sustainable development are studied, the achievement of which is devoted to the documents “New Urban Development Program” and the declaration “Agenda for Sustainable Development for the period up to 2030”. It is concluded that sustainable development considers the integration of goals in territorial planning, environmental protection and public health, achieving social and gender equality, housing policy, and transport development as the basis for unified urban planning.

Atlantic Forest Regeneration Dynamics Following Human Disturbance Cessation in Brazil

The Brazilian Atlantic Forest (BAF) is one of the most important biodiversity hotspots and species-rich ecosystems globally. Due to human activities, it has been significantly reduced and fragmented. This study examined both biotic (floristic composition, diversity, and structure) and abiotic (topographic and soil) factors in BAF fragments undergoing varying levels and durations of human disturbance cessation: approximately 20 years (20 y), ~30 years (30 y), and over 40 years (>40 y). We aimed to understand the recovery dynamics of floristic composition, diversity, and structure in BAF fragments in relation to abiotic factors. Several statistical tools were employed to examine similarities/differences and relationships. Forests of the 30 y group exhibit significantly greater homogeneity in terms of floristic composition, while forests of the 20 y group are characterized by lower species abundance and diversity. The floristic composition was primarily influenced by soil features and the time of disturbance. Under “Environmental Protection Areas”, soil–vegetation recovery can occur more swiftly than usually observed for BAF. A significant BAF recovery was observed approximately 40 years after the end of human disturbance. A partial recovery featured 30 y disturbed areas, while in 20 y forests, recovery is in its early stages. Human-disturbed BAF can gradually rebound when effective management practices are implemented.

A Theoretical Study of the Impact of ESG Performance on the Cost of Corporate Debt Financing

With the increasing global attention to environmental protection, social responsibility and corporate governance (ESG) issues, the ESG performance of enterprises has become an important indicator for creditors to assess their non-financial performance. This paper analyzes the development status quo of ESG ratings in China and the situation of corporate debt financing, combines information asymmetry theory, principal-agent theory, contract theory and other in-depth discussion of the impact of corporate ESG performance on its debt financing costs, so as to put forward targeted recommendations to further enhance the attention of China's listed enterprises to ESG ratings, as well as to reduce the cost of corporate debt financing measures put forward to lay a more solid theoretical foundation, to help enterprises better achieve high-quality and high quality of corporate governance. It lays a more solid theoretical foundation for further improving China's listed enterprises' attention to ESG ratings and proposing measures to reduce the cost of corporate debt financing, and helps enterprises better realize high quality and sustainable development.

Exploiting Legal Reserve Compensation as a Mechanism for Unlawful Deforestation in the Brazilian Cerrado Biome, 2012–2022

This research investigates the illegal Vegetation Suppression Authorization (VSA) for Legal Reserve Compensation (LRC) in Tocantins, Brazil, between 2012 and 2014. The VSA is a license issued by state environmental agencies that authorizes the removal or clearing of native vegetation. This infraction resulted from the state environmental agency’s mistaken interpretation of Resolution 07/2005 of the State Environmental Council and the Native Vegetation Protection Law, which operates nationally and takes precedence over state resolutions and laws. The study area focuses on eight municipalities contained in the Formoso, Pium, and Javaés river basins. The methodology examines irregular VSA-LRC cases through geospatial data analysis, multitemporal analysis using remote sensing data, and economic assessments in both the origin and destination areas of the compensatory reserve. The results showed that among the 217 VSA-LRC applications during the period, 93 had corresponding geospatial data, indicating that 57.1% of the geospatial data were missing. This discrepancy between the authorized area and the available geospatial information restricts the oversight capability of the regulatory agency. A decade-long deforestation analysis of VSA-LRCs using remote sensing data considered three phases: 2012–2014 (application and issuance of VSA-LRCs), 2015–2018 (operational issuance), and 2019–2022 (post-expiration of VSA-LRCs). The results revealed a total VSA-LRC area of 343.291 km2 (34,329.10 ha), with 229.1169 km2 (22,911.69 ha) of deforestation. Notably, 54.877 km2 (5487.70 ha) of this deforestation occurred in 2019–2022, after the VSA-LRC had expired. The analysis of the LRC origin and destination areas demonstrates a unidirectional strategy, from economically more valuable areas to less valuable ones, according to land market dynamics. Therefore, this investigation concludes the need for greater administrative transparency, the development of a reliable geospatial data system for monitoring, and policy changes and actions to enhance environmental protection.

Comparison of Carbon-Dioxide Emissions of Diesel and LNG Heavy-Duty Trucks in Test Track Environment

Environmental protection and greenhouse gas (GHG) emissions are getting increasingly high priority in the area of mobility. Several regulations, goals and projects have been published in recent years that clearly encourage the reduction of carbon dioxide (CO2) emission, the adoption of green alternatives and the use of renewable energy sources. The study compares CO2 emissions between conventional diesel and liquefied natural gas (LNG) heavy-duty vehicles (HDVs), and furthermore investigates the main influencing factors of GHG emissions. This study was carried out in a test–track environment, which supported the perfect reproducibility of the tests with minimum external influencing factors, allowing different types of measurements. At the results level, our primary objective was to collect and evaluate consumption and emission values using statistical methods, in terms of correlations, relationships and impact assessment. In this research, we recorded CO2 and pollutant emission values indirectly via the fleet management system (FMS) using controller area network (CAN) messages. Correlation, regression and statistical analyses were used to investigate the factors influencing fuel consumption and emissions. Our scientific work is a unique study in the field of HDVs, as the measurements were performed on the test track level, which provide accuracy for emission differences. The results of the project clearly show that gas technology can contribute to reducing GHG emissions of HDVs, and LNG provides a reliable alternative way forward for long-distance transportation, especially in areas of Europe where filling stations are already available.

Hyperspectral Inversion of Soil Cu Content in Agricultural Land Based on Continuous Wavelet Transform and Stacking Ensemble Learning

Heavy metal pollution in agricultural land poses significant threats to both the ecological environment and human health. Therefore, the rapid and accurate prediction of heavy metal content in agricultural soil is crucial for environmental protection and soil remediation. Acknowledging the limitations of traditional single linear or nonlinear machine learning models in terms of prediction accuracy, this study developed an ensemble learning model that integrates multiple linear or nonlinear learning models with a random forest (RF) model to improve both the prediction accuracy and reliability. In this study, we selected a typical copper (Cu) polluted area in the Pearl River Delta of Guangdong Province as the research site and collected Cu content data and indoor soil reflectance spectral data from 269 surface soil samples. First, the soil spectral data were preprocessed using Savitzky–Golay (SG) smoothing, multiplicative scattering correction (MSC), and continuous wavelet transform (CWT) to reduce noise interference. Next, principal components analysis (PCA) was employed to reduce the dimensionality of the preprocessed spectral data, eliminating redundant features and lowering the computational complexity. Finally, based on the dimensionality-reduced data and Cu content, we established a stacked ensemble learning model, where the base models included SVR, PLSR, BPNN, and XGBoost, with RF serving as the meta-model to estimate the soil heavy metal content. To evaluate the performance of the stacking model, we compared its prediction accuracy with that of individual models. The results indicate that, compared to the traditional machine learning models, the prediction accuracy of the stacking model was superior (R2 = 0.77; RMSE = 7.65 mg/kg; RPD = 2.29). This suggests that the integrated algorithm demonstrates a greater robustness and generalization capability. This study presents a method to improve soil heavy metal content estimation using hyperspectral technology, ensuring a robust model that supports policymakers in making informed decisions about land use, agriculture, and environmental protection.

Fabrication and characterization of foam ceramics from recycled waste concrete powder and waste glass powder

Incorporating multi-solid wastes to prepare foam ceramics has attracted widespread attention due to its excellent characteristics and environmental protection. In this study, foam ceramics were prepared by sintering method using recycled waste concrete powder (RWCP) and waste glass power (WGP) as the major material, Na2CO3 as foaming agent and borax as fluxing agent. The effect of sintering temperature on the physical properties and pore structure of foam ceramics were studied. The phase transformation and reaction mechanism were also discussed. The results reveal that when the RWCP content was 40%, the WGP content was 60% and the sintering temperature was 890 °C, the foam ceramics showed the best overall performance. The compressive strength, bulk density, water absorption and porosity were 2.39MPa, 0.83g/cm3, 8.27% and 66.68%, respectively. At this time, the pore size distribution was optimal, and mesopore occupied the vast majority. The fractal dimension of pore reached the minimum of 1.09. In addition, The XRD results showed that WGP and RWCP gradually depolymerized and reconstructed under the action of flux. Then the foam ceramics with mullite, pyroxene and wollastonite as the main phases were formed. The experimental results showed that it was feasible to prepare foam ceramics using RWCP. This study can provide a new train of thought for the reuse of RWCP.

Optimal planning method of distributed generation in AC/DC microgrid considering power balance

Abstract To optimize AC/DC hybrid microgrid power planning, improve operational efficiency, and balance power distribution, we constructed an optimization model for AC/DC microgrid power generation, covering power, economy, reliability, and environmental protection, and set constraints to solve optimal planning. The experiment shows that this method enhances voltage stability, improves power supply quality, enhances distributed power generation efficiency, and reduces carbon emissions.

Development of Particulate Matter Concentration Estimation Models for Road Sections Based on Micro-Data

With increasing global concerns related to global warming, air pollution, and environmental health, South Korea is actively implementing various particulate matter (PM) reduction policies to improve air quality. Accurate data analysis, including the investigation of weather phenomena, monitoring, and integrated prediction, is essential for effective PM reduction. However, the factors influencing the PM generated from domestic road sections have not yet been systematically analyzed, and currently, no predictive models utilize weather and traffic data. This study analyzed the correlations among factors influencing PM to develop models for estimating fine and coarse PM (PM2.5 and PM10, respectively) concentrations in road sections. Regression analysis models were used to assess the sensitivity of PM2.5 and PM10 concentrations to the traffic volume, whereas machine learning-based models, including linear regression, convolutional neural networks, and random forest models, were constructed and compared. The random forest models outperformed the other models, with coefficients of determination of 0.74 and 0.71 and mean absolute errors of 5.78 and 9.60 for PM2.5 and PM10, respectively. These results indicate that the random forest model provides the most accurate PM concentration estimates for road sections. The practical applications of the developed models were considered to inform effective transportation policies aimed at reducing PM. The developed model has practical applications in the formulation of transportation policies aimed at reducing PM. In particular, the model will play an important role in data-driven policymaking for sustainable urban development and environmental protection. By analyzing the correlation between traffic volume and weather conditions, policymakers can formulate more effective and sustainable strategies for reducing air pollution.

Research on Developing Cyclone Coupling Techniques for Heterogeneous Separators with Design Optimization of Hydrocyclone Separators

Abstract: Hydrocyclone separator is a widely used equipment in the field of liquid-solid separation due to its simple structure, convenient operation, and high separation efficiency. This paper provides a comprehensive review of the working principles, application areas, design optimization, and performance evaluation of hydrocyclone separators, while discussing their future development trends. In addition, particular attention has been given to the aspects related to patents in this study.The focus is on analyzing the structural parameters and flow field characteristics of hydrocyclone separators, as well as the different effects on separation efficiency caused by various hydrocyclone structures and adjustments in hydrocyclone size. The research analysis is conducted on the inlet, cylindrical section, overflow pipe section, cone section, hydrocyclone materials, and other parts, taking into account detailed analysis of operational conditions such as inlet flow rate, pressure drop, separation efficiency, and fluid properties. The future development trend of hydraulic hydrocyclone separators lies in refinement, intelligence, multifunctionality, integration, and energy-saving and environmental protection. In the field of liquid-solid separation, the integration of hydrocyclone separation technology and intelligent devices is becoming increasingly important, and future research will focus on developing new hydrocyclone coupling separation techniques to further improve production efficiency and convenience in daily life. The application prospects are broad, and it is expected to bring significant economic and social benefits to society. It also possesses the potential for patent protection.

Enhanced photocatalytic hydrogen evolution via yolk–heteroshell TiO2@TiO2/SiO2 nanoreactor with confined Pt nanoparticles

The upper limit of photocatalytic efficiency is largely determined by the light-harvesting capability of a semiconductor. To address this challenge, we developed a yolk-heteroshell TiO2@TiO2/SiO2 (T@T/S) nanoreactor, leveraging a novel design based on an in-depth understanding and innovative utilization of light-matter interactions. The T@T/S nanoreactor significantly enhances solar light capture and utilization efficiency through total internal reflection mechanisms facilitated by the heterogeneous shell. This heteroshell, consisting of an outer SiO2 shell an inner monolayer of TiO2 nanoparticles, maximizes light confinement due to the different refractive indices of SiO2 and TiO2, while also minimizing mass transfer resistance due to the thin inner shell layer. These unique structural features result in high photocatalytic activity under simulated solar light. Additionally, we successfully applied a “ship-in-a-bottle” strategy for the confined growth of platinum nanoparticles within T@T/S nanoreactor. The Pt0.5-T@T/S nanoreactors demonstrated excellent hydrogen production, achieving a hydrogen evolution rate of 24.43 mmol g−1h−1 under simulated sunlight and an apparent quantum efficiency (AQE) of 7.8 % at 350 nm. This study highlights the importance of nano-engineered designs in optimizing semiconductor photocatalysts and shows the significant potential of our approach for sustainable energy conversion and environmental protection.

Environmental Justice Specialization and Corporate ESG Performance: Evidence from China Environmental Protection Court

In order to implement the dual-carbon strategy and achieve sustainable economic development, it is essential to guarantee environmental protection through the establishment of an effective environmental rule of law. This study employs a quasi-natural experiment, namely the establishment of environmental protection courts in China’s intermediate people’s courts, to investigate the impact on the ESG performance of A-share listed companies from 2010 to 2022. A double-difference model is utilized for this purpose. This study reveals that the specialization of environmental justice is an effective means of promoting the ESG performance of enterprises. The results of mechanism tests indicate that the specialization of environmental justice has a positive impact on the ESG performance of enterprises, primarily by enhancing external supervision and garnering greater media attention and analyst interest. Furthermore, heterogeneity analysis reveals that the influence of environmental justice specialization on corporate ESG performance is particularly pronounced in eastern regions, contexts characterized by high environmental uncertainty and heavily polluting enterprises. These findings offer invaluable insights into the development of environmental justice and the advancement of sustainable economic growth.

Machine Learning Based Prediction of Compressive and Flexural Strength of Recycled Plastic Waste Aggregate Concrete

In the last 50 years, the use of plastics has increased significantly due to advances in technology, population growth and increasing needs. However, this trend has led to the accumulation of large amounts of plastic waste. Numerous studies have been conducted on the use of recycled plastic materials in concrete production as a means of recycling and environmental protection. This study aims to predict the 28-day cylinder compressive and flexural strength of concretes using Polyethylene Terephthalate (PET), Phenolic Formaldehyde (PF), Polypropylene (PP), Polycarbonate (PC), Polyvinyl Chloride (PCV), High-Impact Polystyrene (HIPS) and High-Density Polyethylene (HDPE) plastic waste as aggregates. In this scope, a comprehensive database was created using experimental results obtained from the literature. Then, this study used six ML models, including Support Vector Regressor (SVR), Random Forest Regressor (RFR), Gradient Boosting Regressor (GBR), XGBoost Regressor (XGR), LightGBM Regressor (LGR), Bagged Decision Trees Regressor (BDTR), to predict the compressive and flexural strength of recycled plastic waste aggregate concrete (RPWAC). From the experimental database, 253 data points with strength between 6.00-70.05MPa were identified to estimate the compressive strength (CS) and 175 data points with strength between 1.21-7.96MPa were identified for flexural strength (FS). Cross-validation was used for six ML models and hyperparameter fine-tuning was performed. The results showed that six different ML models predicted the compressive and flexural strengths of RPWAC with high accuracy. The XGR model predicted CS and FS better than the other five different models with R2 values of 0.931 and 0.999, respectively. The three main properties effecting the CS of RPWAC were plastic waste content, water/cement ratio and concrete specific gravity, while the three main properties affecting the FS of RPWAC were cement specific gravity, plastic waste content and cement CS.

MXene/TiO2 NAs on CC flexible electrode for electrocatalytic tigecycline degradation: Performance, Mechanistic insights, and toxicological assessment

In this study, a composite electrode (MXene/TiO2 NAs@CC) based on TiO2 nanotube arrays (NAs) and two-dimensional MXene-coated carbon cloth (CC) was prepared. The electrode greatly improved the catalytic activity by capturing protons through the abundant active sites of TiO2 nanotube arrays and promoting proton reduction with the high conductivity of MXene. Moreover, the composite electrode possessed the largest specific surface area (9.1660 m2·g−1) according to the results of the BET test. Under optimal conditions, the composite electrode degraded tigecycline (TGC) up to 86.66 % in 20 min. Furthermore, the electrocatalytic performance was not affected after 10 cycling experiments and 60 days of exposure to air, indicating its excellent stability. In addition, the cathodic co-catalytic reaction mechanism involving anode ·OH, HClO, and cathode H* was proposed. The degradation pathways of TGC and the toxicity of possible intermediates were also analyzed. Finally, a two-stage continuous wastewater reactor with high efficiency and low consumption (90.46 % removal rate, 0.061 kWh/m3) was designed. This study provides a new idea for designing an electrocatalytic reactor with high efficiency, stability, and low consumption, enriching the field of electrocatalytic treatment strategies for antibiotic wastewater. It is of great significance for the protection of the water environment and human health.

Environmental Protection for Bureaucratic Promotion: Water Quality Performance Review of Provincial Governors in China

We show including quantitative environmental targets for bureaucratic promotion incentivizes government officials to enforce environmental regulation but at significant economic costs. Taking advantage of the gradual expansion of China’s water quality performance review (WQPR) over time and space, we find that WQPR significantly reduced ambient concentrations of criteria pollutants, digestive cancer mortality, and GDP growth rate. WQPR’s effects are more pronounced along provincial borders, which are targeted by WQPR, and when provincial governors have more promotion potential. An important mechanism is investment in wastewater treatment facilities. There is evidence that WQPR passed the benefit-cost test, especially in rural areas.

Mineral pollutants and coliform contamination in groundwater pose health risks to consumers: a spatiotemporal study in a mining-impacted area

The presence of mineral pollutants, combined with bacterial contamination, has significantly impacted groundwater quality and led to various health-related issues in mining-impacted areas. Therefore, we measured the concentration of fluoride (F-), phosphate (PO43-), sulphate (SO42-), ammonium (NH4+), nitrate (NO3-), the total coliforms (TCs), and physiochemical characteristics in groundwater samples of South Khorasan, Eastern Iran. For this, we collected water samples from 100 wells in spring and autumn across this mining-impacted area. We then measured the concentrations of mineral pollutants and assessed their associated health risks to children and adults using the Environmental Protection Agency (EPA) models and spatiotemporal zoning maps in ArcGIS. The concentrations of PO43-, NH4+, SO42-, NO3-, and F- were 0.70 ± 0.34, 0.82 ± 0.9, 175.45 ± 123, 15.26 ± 9.41, and 0.53 ± 0.68 mg/L in spring, and 0.71 ± 3.18, 4.68 ± 31, 306.72 ± 615.80, 19.30 ± 15.61, and 0.72 ± 0.65 mg/L in autumn, respectively. PO43-, NH4+, and SO42- exceeded both the World Health Organization (WHO) and EPA, but NO3- exceeded only EPA standards. TCs in both seasons exceeded the standards set by the EPA and WHO. The hazard quotient (HQ) values indicated non-carcinogenic risks for F⁻ and NO3⁻, while posing no risks NH4⁺ and PO43⁻ in both adults and children during autumn and spring.Hazard index (HI) was greater than 1 for all minerals in both children and adults in autumn and spring. No correlation was observed between mineral compounds and TCs in the study area, yet the water samples were highly contaminated by coliform with a significant risk to adults and children. In essence, both mineral pollutants and TCs potentially pose serious risks to human, and more efforts are required to improve the quality of water in this area.

Rights for nature or protecting people’s rights?: The operationalization of rights of nature in non-indigenous communities in the United States

As the Rights of Nature movement gains political traction globally, researchers must examine how this transnational movement to extend rights to nature or natural entities is being operationalized in place. Proponents of the rights of nature contend transferring rights to nature constitutes a paradigm shift in human-environment interactions and will lead to solutions directed at the root causes of environmental problems. Critics contend that these rights-based governance structures have the potential to do more harm than good for environmental protection depending on the cultural and legal frameworks within which rights of nature are enacted. In this paper, I examine how rights of nature have been operationalized in non-Indigenous communities in the United States through an analysis of rights of nature ordinances passed in these communities between 2006 and 2020. Drawing on theoretical engagements with rights I demonstrate how the reliance on universalizing human rights frameworks and anti-corporation rhetoric both distinguish these ordinances from the broader rights of nature movement and center the rights of people to have access to a clean environment rather than the intrinsic rights of nature. In conclusion, I explore alternatives to how rights of nature are currently operationalized in non-Indigenous communities in the United States and call for increased research on the implications and impacts of rights of nature ordinances to assess whether they achieve their stated goals.

Comprehensive Assessment of Heavy Metal Contamination in Soil-Plant Systems and Health Risks from Wastewater-Irrigated Vegetables

A research study examined the origins, human health impacts, and risks associated with pollutants in vegetables grown in soil irrigated with wastewater. The study analyzed 164 samples from water sources, irrigated soil, and harvested vegetables for eight heavy metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) using atomic absorption spectrophotometry. The focus was on the potential health effects of consuming heavy metal-contaminated vegetables grown in wastewater-irrigated soil. The findings revealed significant accumulation of heavy metals in soil and plants from Mianwali, Pakistan, posing potential health risks to consumers. When compared to vegetables produced with freshwater irrigation, the concentration levels of heavy metals in the soil irrigated with untreated wastewater were significantly greater (P≤0.001) and above the recommended limits set by the World Health Organization (WHO). The results showed that heavy metals in the soil had significantly increased, and crops had subsequently absorbed these metals. Produce raised in soil watered with wastewater showed higher levels of heavy metals than the US Environmental Protection Agency (EPA) and the WHO recommended. Among the veggies, lead (Pb) and cadmium (Cd) were found to have higher Hazardous Quotient Indices (HRIs) than one. This indicates that both adults and children may have been exposed to dangerous levels of these metals. Additionally, for Brassica oleracea, Raphanus sativus, and Spinacia oleracea, nickel (Ni) surpassed HRIs larger than 1, indicating a significant health risk connected to these veggies' ingestion.

Multidimensional structural racism and estimated cancer risk from traffic-related air pollution.

Traffic-related air pollutants have been associated with a variety of adverse human health impacts, including cancers. In the United States, numerous studies have documented racial inequities in neighborhood exposures to traffic-related air pollution. Emerging evidence suggests that structural racism may influence neighborhood exposures to air pollutants. However, existing research has largely focused on residential racial segregation, one indicator of structural racism. This study developed a multidimensional measure of structural racism to examine the relationship between structural racism and estimated cancer risk from air pollutants in Georgia. Carcinogenic air toxics data were obtained from the US Environmental Protection Agency's 2019 Air Toxics Screening Assessment and sociodemographic data from the American Community Survey. Guided by stakeholder input, county-level data on residential segregation, education, employment, incarceration, economic status, political participation, and homeownership were used to create a multidimensional county-level structural racism index. Relative risks (RRs) were estimated for associations between structural racism and elevated (top 10% in Georgia) estimated cancer risk from air toxics. Multilevel analyses revealed a significant association between multidimensional structural racism and exposure to carcinogenic traffic-related air pollutants. Neighborhoods in the highest quartile of structural racism exhibited an elevated cancer risk from traffic-related air pollutants (RR,7.84; 95% CI,5.11-12.05) compared to neighborhoods with lower levels of structural racism. Multidimensional structural racism was associated with estimated cancer risk from traffic-related air pollution in Georgia. Findings can inform future studies and policy interventions that address racial inequalities in exposure to traffic-related air pollution.

Synthesis of CuOQDs/g-C3N4/C Composites Via Stem Template Induction and their Photocatalytic Properties

Introduction: The synthesis of bio-templated porous CuOQDs/g-C3N4/C composites with controllable morphology and suitable energy band structure was successfully carried out via a simple thermal condensation and hydrothermal method. Method: Dicyandiamide and cadmium chloride were selected as starting materials, while Hollyhock stem was chosen as the biological template. The results indicated that, in comparison to pure g-C3N4, g-C3N4/C had a rich porous structure and better-photogenerated carrier separation efficiency. The CuOQDs were anchored evenly on the surface of the g-C3N4, thus resulting in the formation of a greater number of reactive sites. Results: The type-Z heterojunction formed between the CuOQDs and g-C3N4/C reduced the energy required for electron transition, thereby facilitating the separation of photo-generated electronhole pairs. The highest photocatalytic degradation efficiency of CuOQDs/g-C3N4/C for tetracycline (TC) was 65.1%, which was 3.3 times that of pure g-C3N4. Conclusion: In the photocatalytic process, the main reactive species is O2−. The CuOQDs/g- C3N4/C synthesized by stem induction in multi-phase heterojunction form has a stable microstructure to improve the charge separation efficiency. Further, it represents practical photocatalytic environmental protection.