Pollution Control Costs Research Articles

GREEN ACCOUNTING AND FINANCIAL PERFORMANCE IN NIGERIAN INDUSTRIES: A STUDY OF SELECTED OIL AND GAS FIRMS IN NIGERIA

This study investigated the effect of Green Accounting on the financial performance of selected oil and gas firms in Nigeria. The specific objectives of the study were to: investigate the effect of emission control cost, the effect of renewable energy cost, and the effect of pollution remediation costs control on the financial performance of selected oil and gas firms in Nigeria. The study adopted ex post facto research design and the panel least squares regression technique. The study found that: emission control cost with coefficient (421.2015) and p-value (0.0022) has significant positive effect on the return on capital of selected listed oil and gas firms in Nigeria; pollution control cost with Coefficient of 2.018446 and p-value of 0.0000, has positive significant effect on the return on capital of selected listed oil and gas firms in Nigeria and that renewable cost energy with coefficient (80.40683) and p-value (0.0056) has significant positive effect on the return on capital of selected listed oil and gas firms in Nigeria. The study concluded that Green accounting has significant positive effect on the financial performance of selected oil and gas firms in Nigeria. Based on the findings of the study, the following recommendations were put forward: the oil and gas firms should prioritize Green Accounting as a significant component of their management process, the firms should adopt management practice, and as well adopt the pollution remediation, emission control and renewable energy control costs accounting in their production accounting model.

Carbon risk and investment efficiency: A merger and acquisition perspective

With the increasingly stringent global restrictions on carbon emissions, firms are facing growing carbon risks, which may not only drive up firms' pollution control costs but also force them to improve investment efficiency by optimizing investment and saving costs. Taking the Paris Agreement event as the background and using the data of listed companies in China from 2007 to 2020 and a difference-in-differences model, this paper reveals that the increase in carbon risk can significantly improve the investment efficiency of China's carbon-intensive firms. In addition, we find that the increase in carbon risk can encourage firms to carry out mergers and acquisitions to improve investment efficiency. Our findings provide Chinese evidence for the effective link between carbon risk and firm investment efficiency and may serve as a decision-making reference for carbon-intensive enterprises to improve investment efficiency through merger and acquisition activities in the context of increasing carbon risk.

Characterizing multi-pollutant emission impacts of sulfur reduction strategies from coal power plants

Fuel combustion for electricity generation emits a mix of health- and climate-relevant air emissions, with the potential for technology or fuel switching to impact multiple emissions together. While there has been extensive research on the co-benefits of climate policies on air quality improvements, few studies have quantified the effect of air pollution controls on carbon emissions. Here we evaluate three multi-pollutant emission reduction strategies, focused on sulfur dioxide (SO2) controls in the electricity sector. Traditional ‘add-on’ pollution controls like flue gas desulfurization (FGD) reduce SO2 emissions from coal combustion but increase emissions of nitrogen oxides (NO X ), volatile organic compounds (VOCs), fine particulate matter (PM2.5), and carbon dioxide (CO2) due to heat efficiency loss. Fuel switching from coal to natural gas and renewables potentially reduces all pollutants. We identified 135 electricity generation units (EGUs) without SO2 controls in the contiguous US in 2017 and quantified the unit-level emission changes using pollution control efficiencies, emission rates, fuel heat input, and electricity load. A cost-benefit analysis is conducted, considering pollution control costs, fuel costs, capital and operation and maintenance (O&M) costs, the monetized health benefits from avoided multi-pollutant, and the social cost of carbon as the benefit for carbon reduction. We find that add-on SO2 controls result in an average annual net benefit of $179.3 million (95% CI: $137.5-$221.0 million) per EGU, fuel switching from coal to natural gas, $432.7 million (95% CI: $366.4-$498.9 million) per EGU; and fuel switching from coal to renewable energy sources, $537.9 million (95% CI: $457.1-$618.9 million) per EGU. Our results highlight multi-pollutant emission reduction strategy as a cost-effective way to synergistically control air pollution and mitigate climate change.

Assessing the effectiveness of PM2.5 pollution control from the perspective of interprovincial transport and PM2.5 mitigation costs across China

Due to the transboundary nature of air pollutants, a province's efforts to improve air quality can reduce PM2.5 concentration in the surrounding area. The inter-provincial PM2.5 pollution transport could bring great challenges to related environmental management work, such as financial fund allocation and subsidy policy formulation. Herein, we examined the transport characteristics of PM2.5 pollution across provinces in 2013 and 2020 via chemical transport modeling and then monetized inter-provincial contributions of PM2.5 improvement based on pollutant emission control costs. We found that approximately 60% of the PM2.5 pollution was from local sources, while the remaining 40% originated from outside provinces. Furthermore, about 1011 billion RMB of provincial air pollutant abatement costs contributed to the PM2.5 concentration decline in other provinces during 2013–2020, accounting for 41.2% of the total abatement costs. Provinces with lower unit improvement costs for PM2.5, such as Jiangsu, Hebei, and Shandong, were major contributors, while Guangdong, Guangxi, and Fujian, bearing higher unit costs, were among the main beneficiaries. Our study identifies provinces that contribute to air quality improvement in other provinces, have high economic efficiency, and provide a quantitative framework for determining inter-provincial compensations. This study also reveals the uneven distribution of pollution abatement costs (PM2.5 improvement/abatement costs) due to transboundary PM2.5 transport, calling for adopting inter-provincial economic compensation policies. Such mechanisms ensure equitable cost-sharing and effective regional air quality management.

Environmental Accounting and Sustainable Development of Firms in Rivers State, Nigeria

Within the scope of the research, environmental accounting and sustainable development were explored in relation to oil and gas firms located in Rivers State, Nigeria. There was a correlational survey research design used for the investigation. A total of six oil and gas businesses that were active in the Rivers State Region of Nigeria were included in the study's research population. For this particular investigation, secondary data served as the instrument. Statistical Package for the Social Sciences (SPSS) Version 22 was used in order to do the analysis on the data. A simple bivariate regression analysis was performed at a significance level of.05. The research issues were evaluated using the mean and standard deviations, and hypotheses were assessed using the analysis. The data indicated that there is no substantial connection between the cost of waste management and the ecologically sustainable growth of oil and gas businesses in Rivers State, Nigeria. Additionally, there is a strong significant association between the cost of pollution control and the development of ecological sustainability, as well as a strong significant relationship between the cost of pollution control and the development of economic sustainability for oil and gas businesses in Rivers State, Nigeria. By adhering to social responsibility in waste management, oil and gas firms should put a premium value on initiatives that are focused towards reducing their ecological footprint and promoting sustainable growth while also reducing their environmental impact.

High organic sulfur coal derived carbon-based sorbent for Hg0 capture from coal-fired flue gas

To develop the high value utilization of high organic sulfur coal instead of combustion as well as save the cost of mercury pollution control, we attempted to transmute the inherent sulfur of high organic sulfur coal, in the case of LF coal (which is from Linfen city, China), to active sulfur species for mercury capture by doping metal oxides, and CuO performed best among various metal oxides. The sorbent (or activated sample) prepared from LF coal with doping CuO is labelled LF+Cu-A, around which a series of experiments were conducted. Firstly, the effects of operational conditions, including GHSV (gas hourly space velocity), temperature and flue components, on the mercury capture performance of LF+Cu-A were thoroughly investigated, and results showed that LF+Cu-A had an excellent mercury capture performance. The average mercury capture efficiency is 97.8 % during a two-hour test under N2+O2+H2O+SO2+NO atmosphere with GHSV of 240000 h−1 and temperature of 120 °C. Secondly, the experimental data were fitted by four kinetic models, and it is found that the mercury adsorption process under low temperatures (60, 90, 120 °C) and high temperature (150 °C) are in the best agreement with the pseudo-first-order model and the intra-particle diffusion model respectively. Last, the mercury capture mechanisms of LF+Cu-A were revealed by Hg-TPD (Hg-temperature programed desorption) experiment, Raman analysis and XPS (X-ray photoelectron spectrometer) spectra, and it is indicated that the multiple sulfur species and Cu2+ play roles in the mercury capture process, during which elemental mercury are oxidized to HgS and fixed on the surface of LF+Cu-A.

Optimizing Energy and Reserve Minimization in a Sustainable Microgrid with Electric Vehicle Integration: Dynamic and Adjustable Manta Ray Foraging Algorithm

The growing presence of EVs in regional microgrids introduces increased variability and uncertainty in the areas’ load profiles. This paper presents a novel approach for optimizing energy and reserve minimization in a sustainable integrated microgrid with electric vehicles (EVs) by the use of the dynamic and adjustable Manta Ray Foraging (DAMRF) algorithm. The DAMRF algorithm harnesses the inherent flexibility of EVs as controllable loads and develops a comprehensive dispatch model for a large-scale EV response. The model takes into account the management, operational, and environmental costs associated with load fluctuations in the microgrid. Simulation evaluations conducted based on a practical microgrid environment validate the effectiveness of our wind–solar energy storage and management strategy. The results showcase significant improvements in energy and reserve minimization, highlighting the potential advantages of integrating EVs into sustainable microgrid systems. In addition, the DAMRF algorithm achieves lower environmental pollution control costs (USD 8000) compared to the costs associated with the Genetic Algorithm (GA) (USD 8654.639) and PSO (USD 8579.546), emphasizing its ability to effectively control and minimize environmental pollution. In addition, the DAMRF algorithm offers a more cost-effective solution for managing the power grid, and the shorter solution running time of the DAMRF is almost the same as PSO’s quicker decision-making and response times, enhancing the overall responsiveness and adaptability of the power grid management system.

How to optimize dust pollution control in opencast coal mines: Analysis of a joint social regulation model based on evolutionary game theory.

The carbon peaking and carbon neutrality goals drive innovation in pollution governance systems, unleashing the potential of social supervisory forces to achieve coordinated governance by multiple stakeholders. In order to improve dust pollution control in opencast coal mines, this study combines prospect theory with evolutionary game theory, analyzing the evolutionary game process of coordinated governance activities of coal mining enterprises, local regulators, and social camps in the management of dust pollution against the backdrop of national supervisions. The research indicates that the perceived value of dust pollution has a significant impact on the strategic choices of the three agents involved in the game. Coal mining enterprises tend to be risk averse, and by reducing the cost of dust pollution control and increasing the additional benefits of pollution control, it can promote pollution control behavior by coal mining enterprises. Local regulators are also risk averse, but not sensitive to risk benefits. Strengthening pollution subsidy incentives and environmental fines can help promote dust pollution control behavior by coal mining enterprises. However, increasing the strength of the rewards strategy is not conducive to local regulators' own regulatory responsibilities, and environmental fines have limited binding effects. The strategic choices of social camps' supervision have a restrictive effect on the strategic choices of coal mining enterprises and local regulators, promoting the evolution of equilibrium results in the direction of maximizing social benefits. When coal mining enterprises actively governance pollution, local regulators strictly regulated, and social camps do not monitor, the system reaches its optimal equilibrium state. The research results clarify the mechanism and specific effects of social supervision of opencast coal mine dust pollution control, guide the participation of the public in dust pollution control, and regulate the behavior strategies of coal mining enterprises and local regulators, providing the scientific basis for management.

Improving Sparrow Search Algorithm for Optimal Operation Planning of Hydrogen–Electric Hybrid Microgrids Considering Demand Response

Microgrid operation planning is crucial for ensuring the safe and efficient output of distributed energy resources (DERs) and stable operation of the microgrid power system. The integration of hydrogen fuel cells into microgrids can increase the absorption rate of renewable energy, while the incorporation of lithium batteries facilitates the adjustment of microgrid power supply voltage and frequency, ensuring the three-phase symmetry of the system. This paper proposes an economic scheduling method for a grid-connected microgrid that considers demand response and combines hydrogen and electricity. Based on the operating costs of renewable energy, maintenance and operation costs of nonrenewable energy, interaction costs between the microgrid and main grid, and pollution control costs, an optimization model for dispatching a hydrogen–electric hybrid microgrid under grid-connected mode is established. The primary objective is to minimize the operating cost, while the secondary objective is to minimize the impact on the user’s power consumption comfort. Therefore, an improved demand response strategy is introduced, and an enhanced sparrow search algorithm (ISSA) is proposed, which incorporates a nonlinear weighting factor and improves the global search capability based on the sparrow search algorithm (SSA). The ISSA is used to solve the optimal operation problem of the demand-response-integrated microgrid. After comparison with different algorithms, such as particle swarm optimization (PSO), whale optimization algorithm (WOA), sooty tern optimization algorithm (STOA), and dingo optimization algorithm (DOA), the results show that the proposed method using demand response and ISSA achieves the lowest comprehensive operating cost for the microgrid, making the microgrid’s operation safer and with minimum impact on user satisfaction. Therefore, the feasibility of the demand response strategy is demonstrated, and ISSA is proved to have better performance in solving optimal operation planning problems for hydrogen–electric hybrid microgrids.

Performance audit evaluation of marine development projects based on SPA and BP neural network model

Abstract Accurately grasping the comprehensive cost-benefit and influencing factors of various marine development projects is of great significance to the promotion of high-quality marine development. This work screened and constructed the performance audit evaluation index system of comprehensive cost-benefit of marine development projects from the four aspects including society, economy, resources, and environment. The entropy weight set pair analysis (SPA) was used to audit and evaluate the comprehensive cost-benefit of 15 marine development projects during the construction and operation period. The back propagation (BP) neural network model was used to test the results. The main influencing factors were analyzed by the grey relational analysis (GRA) model. It was found that the comprehensive cost-benefit performance audit evaluation index of the six projects of marine protected area and offshore wind power were higher than the other nine projects of mariculture, sewage dumping, and port industry. The main influencing factors were economic net income, loss of wetland ecological service value, environmental pollution prevention and control cost, new addition employment rate, etc. The countermeasures suggestions were put forward.

Prediction of air quality index based on the SSA-BiLSTM-LightGBM model

The air quality index (AQI), as an indicator to describe the degree of air pollution and its impact on health, plays an important role in improving the quality of the atmospheric environment. Accurate prediction of the AQI can effectively serve people’s lives, reduce pollution control costs and improve the quality of the environment. In this paper, we constructed a combined prediction model based on real hourly AQI data in Beijing. First, we used singular spectrum analysis (SSA) to decompose the AQI data into different sequences, such as trend, oscillation component and noise. Then, bidirectional long short-term memory (BiLSTM) was introduced to predict the decomposed AQI data, and a light gradient boosting machine (LightGBM) was used to integrate the predicted results. The experimental results show that the prediction effect of SSA-BiLSTM-LightGBM for the AQI data set is good on the test set. The root mean squared error (RMSE) reaches 0.6897, the mean absolute error (MAE) reaches 0.4718, the symmetric mean absolute percentage error (SMAPE) reaches 1.2712%, and the adjusted R2 reaches 0.9995.

Opportunities and constraints for cleaner production policy in the developing world: a case study of Sindh Region, Pakistan.

The current industrial and economic activities in Sindh Province, Pakistan, polluted the region's water, air, soil, and marine resources. However, there is a rising demand for eco-friendly production, and it is important to develop new policies and tools to combat environmental degradation and enhance economic development. Cleaner Production (CP) provides opportunities to address many of these issues. Employed method for this study was based on three approaches: a literature review and stakeholder mapping; a collection of data and information from key stakeholders through focal group discussions, consultative workshops, and one-on-one meetings; and analysis and synthesis of data that were gathered from different sources. The analysis of collected information provides an overview of CP strategies moving forward. Participant workshops gave in-depth information on policy implementation, technological impediments to methods that have been employed elsewhere, and needed capacity building as well as financial consequences of policy implementation. Through increasing financial resources and institutional resources, the expansion of CP will help to replace the conventional methods of waste treatment with an eco-efficiency approach to preventing pollution at the source, thus reducing the need for expensive pollution control and management costs for environmental compliance. Experiences, achievements, and implementation pitfalls from this study can provide a lesson to other developing countries to improve their economic and environmental sustainability.

Study of an Optimized Micro-Grid’s Operation with Electrical Vehicle-Based Hybridized Sustainable Algorithm

Recently, the expansion of energy communities has been aided by the lowering cost of storage technologies and the appearance of mechanisms for exchanging energy that is driven by economics. An amalgamation of different renewable energy sources, including solar, wind, geothermal, tidal, etc., is necessary to offer sustainable energy for smart cities. Furthermore, considering the induction of large-scale electric vehicles connected to the regional micro-grid, and causes of increase in the randomness and uncertainty of the load in a certain area, a solution that meets the community demands for electricity, heating, cooling, and transportation while using renewable energy is needed. This paper aims to define the impact of large-scale electric vehicles on the operation and management of the microgrid using a hybridized algorithm. First, with the use of the natural attributes of electric vehicles such as flexible loads, a large-scale electric vehicle response dispatch model is constructed. Second, three factors of micro-grid operation, management, and environmental pollution control costs with load fluctuation variance are discussed. Third, a hybrid gravitational search algorithm and random forest regression (GSA-RFR) approach is proposed to confirm the method’s authenticity and reliability. The constructed large-scale electric vehicle response dispatch model significantly improves the load smoothness of the micro-grid after the large-scale electric vehicles are connected and reduces the impact of the entire grid. The proposed hybridized optimization method was solved within 296.7 s, the time taken for electric vehicle users to charge from and discharge to the regional micro-grid, which improves the economy of the micro-grid, and realizes the effective management of the regional load. The weight coefficients λ1 and λ2 were found at 0.589 and 0.421, respectively. This study provides key findings and suggestions that can be useful to scholars and decisionmakers.

Double-deck programming method for areal energy optimal allocation in active distribution network

With the problem of worldwide energy and environment become more and more serious, the method that increasing power sources and the investment of substation construction is difficult to meet the rapidly growing power demand. From the theory of comprehensive resource strategic planning and the perspective of the whole society, consider the generalized power supply such as the photovoltaic power supply and interruptible load, establish double-deck programming model for areal energy optimal allocation in active distribution network. The upper planning takes the construction of generalized power supply and the minimizing the total cost of power generation and pollution control as target, improve installed volumn of various power supplies; The lower target is minimizing the net loss, and select address and determine capacitance for generalized power supply. In result, this paper use simplex method and improving PSO algorithm to calculate it. The result of a 33 bus system’s simulation say that the method has the more obvious effect of energy conserving and emissions reducing than the traditional method.

Clean energy-based rural low carbon transformation considering the supply and demand of new energy under government participation: A three-participators game model

Since the 20th century, human society has developed rapidly, and with the continuous development of urbanization, serious environmental pollution problems have followed. Actively studying the development of new energy industry has become an important issue around the world. Rural energy is an important foundation of rural economic and development. Promoting green energy transformation and development in rural areas is an inherent requirement to meet people’s needs for a better life and an important part of building a modern energy system. This study constructs a tripartite evolutionary game model of the government, new energy enterprises and farmers, and analyzes the evolutionary path and stable strategy of the three participants in the process of energy industry transformation. The results show that (1) moderate or high level of government subsidies for farmers use of new energy can promote the development of new energy industry, while low level of subsidies is not conducive to the development of rural new energy industry. (2) When the government’s investment in new energy infrastructure construction is low, farmers will choose to use new energy passively. When the government’s investment in new energy infrastructure construction is moderate or high, farmers will choose to actively use new energy, and new energy enterprises will evolve to actively produce new energy under the circumstance of active use by farmers. (3) Under the current development situation of rural new energy industry, the smaller the proportion coefficient of pollution control costs borne by new energy enterprises formulated by the government, the more conducive the evolution of new energy enterprises to actively produce new energy. Perfect farmers use of new energy countermeasures for the benign development of new energy industry is of great significance. Therefore, from the perspective of evolutionary game, we should promote the transformation of environmental governance to public governance mode. A basic framework for a tripartite coordination mechanism among farmers, the government and enterprises will be established. At the same time, the establishment of specific systems and policies will guide the interests of farmers, the government and new energy enterprises, so as to truly realize the positive development of the new energy industry driven by the participation of three parties.

A Study on Inter-Provincial Environmental Pollution Movement in China Based on the Input–Output Method

In China, environmental pollution responsibilities are divided according to administrative regions. However, because of the strong externality of environmental pollution, the movement of environmental pollution undoubtedly increases the complexity of pollution governance. To divide the responsibility of environmental pollution governance in each province, we effectively quantify the unequal relationship between environmental pollution costs and economic benefits in each province to understand the mechanism and characteristics of inter-provincial environmental pollution movement. Based on the regional input–output model and an inventory we compiled of sulfur dioxide(SO2) emissions of air pollutants in 2012, we calculate the implied inter-provincial environmental pollution emissions and economic benefits from trade, based on production and consumption (supply-side and demand-side). In addition, the movement relationship is explored, and the cost and economic value-added indexes of air pollution control are further constructed to provide effective evidence for a reasonable division of responsibility for environmental pollution control. The results show that there are obvious environmental inequities in the regional trade process in each province, indicating that environmental pollution has been moved. Developed provinces have more economic benefits but pay less in the process of trading goods with less-developed provinces due to the advantages of their industrial structure, while the opposite is true for less-developed provinces. Finally, we propose corresponding policy recommendations to change this condition.

The Role of the Accounting Profession in Controlling Environmental Pollution According to Requirements of Social Responsibility in Industrial Companies

Accounting as an information system is not only affected by the environment, but also affects it through its active role in making and implementing decisions, and this important role is achieved through information related to the environmental activities performed by the economic unit, and for the purpose of performing its mentioned role, it is necessary to strengthen accounting with procedures and treatments that can keep pace with the developments taking place. In the environment surrounding the economic unit, and be able to explain the economic phenomena that it performs, and this requires an effort from researchers and specialists in this field. Preparing the methodology is the first important step in the preparation of scientific research, through which the problem, its importance and the hypotheses on which it is based will be determined to reach the goal of the research, and then the methodology and sample of the research will be determined. In this aspect, the researcher relied on several means to obtain data and information related to the topic of research, which are laws, instructions and legislation related to environmental activity, financial statements and reports issued by the Federal Financial Supervision Bureau in Iraq, reports issued by the Oil Industry Company, personal interviews with employees, and the use of statistical methods in Calculation of pollution rates One of the results of the research is that industrial companies do not respond to performing their role in controlling pollution in an effective manner, unless there is a legal obligation that other industrial companies do the same work. Descriptively and financially, as well as the need for the organization to include pollution control within the structure of its objectives, and then the costs of pollution control should be included within the framework of its planning budget.

The dilemma for China’s national carbon trading market: minimizing carbon abatement costs or maximizing net social benefits?

After a decade of planning and trials, China officially launched a national carbon trading in July 2021. Using a standard economic model, this study shows that an unconstrained carbon trading market would face a dilemma between minimizing pollution control costs and maximizing social benefits. We further show that this would be a significant challenge in China. Our results show that areas with higher population densities also would have higher costs for carbon reduction, and hence the polluters in those areas would be net buyers in the national market. Moreover, our analysis indicates a significantly high correlation between carbon dioxide emissions and other local pollutants. Therefore, cross-regional transactions may result in more emission of other pollutants in areas with higher population density under the unconstrained national cap-and-trade system and cause larger losses in social benefits. We call for more studies to address the issue.

Environmental Information Disclosure, Fiscal Decentralization, and Exports: Evidence From China

We take the “Environmental Information Disclosure Measures (Trial)” implemented in China as a quasi-natural experiment and use the difference-in-difference (DID) method to identify the impact of environmental information disclosure (EID) on local exports. Additionally, we further investigate the impact of fiscal decentralization on local governments’ performance of this centrally mandated environmental information disclosure policy. Our results suggest that EID significantly hinders local exports, and such an inhibition effect exhibits obvious regional and stringency heterogeneity. Furthermore, the degree of fiscal decentralization is positively related to the enthusiasm of local governments in implementing the EID policy, thus strengthening EID’s inhibitory impact on local exports. As for the mechanisms behind, we verify that EID activates the “cost effect” and increases the cost of local pollution control. However, it cannot stimulate local innovation at the same time, and the “innovation effect” does not work, which ultimately results in a decrease in local exports; for cities with a high degree of fiscal decentralization, local governments tend to actively implement the centrally-mandated environmental protection policy by increasing investments in environmental pollution control and stimulating the innovation vitality of local enterprises. But the benefits from the innovation improvement cannot fully offset the negative impact of the increase in environmental costs in the short term, and local exports are further reduced.

Analyzing the Water Pollution Control Cost-Sharing Mechanism in the Yellow River and Its Two Tributaries in the Context of Regional Differences

A river basin is a complex system of tributaries and a mainstream. It is vital to cooperatively manage the mainstream and the tributaries to alleviate water pollution and the ecological environment in the basin. On the other hand, existing research focuses primarily on upstream and downstream water pollution control mechanisms, ignoring coordinated control of the mainstream and tributaries, and does not consider the impacts of different environmental and economic conditions in each region on pollution control strategies. This study designed a differential game model for water pollution control in the Yellow River and two of its tributaries, taking regional differences into account and discussing the best pollution control strategies for each region under two scenarios: Nash noncooperative and cost-sharing mechanisms. Furthermore, the factors influencing regional differences in pollution control costs are analyzed, and their impacts on the cost-sharing mechanism of pollution control are discussed. The results show that: (1) The cost-sharing mechanism based on cooperative management can improve pollutant removal efficiency in the watershed and achieve Pareto improvement in environment and economy. (2) The greater the economic development pressure between the two tributaries, the fewer the effects of the cost-sharing mechanisms and the higher the proportion of pollution control costs paid by the mainstream government. (3) Industry water consumption, the proportion of the urban population to the total population at the end of the year, the value-added of secondary sectors as a percentage of regional GDP, the volume of industrial wastewater discharge, and granted patent applications all influence industrial wastewater pollution treatment investment. (4) The greater the coefficient of variation in pollution control costs between the two tributary areas, the less favorable the solution to water pollution management synergy. These findings can help governments in the basin regions negotiate cost-sharing arrangements.