Introduction

The recent years have witnessed a significant surge in the emphasis on Environmental, Social, and Governance (ESG) factors, markedly influencing the discourse surrounding environmental issues and governance (Ahmad et al., 2023). This study explores the interplay between public perceptions of air pollution and satisfaction with environmental governance within the ESG framework, focusing on environmental tax as a mediating factor that bridges environmental challenges and governance effectiveness. It also investigates the role of government trust as a moderating variable, essential for enhancing the social aspect of ESG by influencing how public perception impacts satisfaction with governance strategies. By examining these dynamics, the study contributes to a more comprehensive understanding of ESG, highlighting the intricate connections between environmental policies, societal trust, and governance practices. It underscores the importance of understanding public perceptions of air pollution and their satisfaction with governance measures, as these can directly influence a country’s ESG rating (Zhu et al., 2023). Governments play a pivotal role in setting the tone for ESG compliance. Therefore, public satisfaction with environmental governance could reflect the effectiveness of these policies (Ruan et al., 2022), impacting ESG performance. Moreover, this study’s exploration of air pollution perception, environmental tax, government trust, and satisfaction with environmental governance offers a comprehensive view of the ESG framework, underscoring the interconnectedness and impact of environmental, social, and governance factors on overall environmental governance outcomes.

The environmental ecosystem, comprising elements such as water, soil, and air, is complex and expansive. Air pollution, in particular, stands out due to its ubiquity, mobility, and wide-ranging impact, distinguishing it from issues like water contamination and industrial waste. It does not “discriminate” among populations, and people are highly sensitive to air quality (Meng et al., 2022). It is also more readily noticeable and draws more public attention in everyday life and professional settings. The improvement of air quality has significant implications for people’s livelihood. The World Health Organization (2016) has identified air pollution as the most significant environmental threat to health in the 21st century. Therefore, we have selected the public’s personal perception of air pollution as a gauge for the effectiveness of governmental environmental management. However, research on the perceived air pollution’s influence on satisfaction with government environmental governance and its influencing factors remains limited (Wu et al., 2022).

Given the pronounced negative externality feature of environmental contamination, the previous government-led method of environmental management often exhibited instances of “government failure” and “market failure” (Anthoff and Hahn, 2010). Consequently, the Chinese government’s suggestion to build an environmental management system where businesses play a central role represents an initiative that directly engages with the “Governance” component of ESG, with the government leading, businesses playing a central role, and the involvement of social groups and the general public (Li, 2022). This proposes to amplify the eagerness of multiple stakeholders in environmental conservation, thereby enhancing the proficiency of environmental management. The environmental tax, as an essential premise for the formation of a new situation of “everyone governing the environment,” has become a noteworthy issue for its environmental and economic effects assessment (Shen and Zhang, 2022). Existing research has little exploration of whether the environmental tax affects satisfaction with environmental governance. We strive to examine if the environmental tax serves as a mechanistic link between the perception of air pollution and contentment with environmental governance.

According to a 2016 report by the World Health Organization (WHO), a staggering 92% of the world’s population lives in areas where air quality exceeds the WHO’s recommended limits, posing significant public health risks. The report also emphasizes that outdoor air pollution is responsible for approximately three million deaths each year. A substantial number of these deaths occur in Southeast Asia and the Western Pacific regions (WHO, 2016). Air quality, a vital communal asset, not only pertains to public health but also mirrors the government’s proficiency in ecological and environmental governance (Tian et al., 2022). Enhanced governance performance is indicative of the public reaping benefits from policy implementations, meeting their needs, and consequently fostering trust in government authorities. This elevation in public trust can translate into improved life and work satisfaction by diminishing societal transaction costs (Ruan et al., 2022). It explores the role of government trust as a moderating variable between subjective air pollution perception and satisfaction with environmental management initiatives.

This research aims to start from the public’s contentment with governmental environmental management, investigate the influence of air pollution perception on satisfaction with environmental governance, thoroughly scrutinize the factors and mechanisms impacting public satisfaction, and propose policy recommendations for enhancing public contentment with environmental management. In this process, we will focus on the environmental tax, a factor that may mediate between air pollution perception and satisfaction with environmental governance, and will also explore the moderating effect of public trust in this relationship.

In summary, using data from the 2019 National Social Survey (CSS) and matched with provincial-level environmental tax data, we scrutinize the link between subjective air pollution perception and contentment with environmental management. Our focus is on understanding the mechanism and boundaries of the effect of air pollution perception on the public appraisal of governmental environmental efforts. Interestingly, our investigation reveals that an increase in the subjective perception of air pollution results in a more adverse evaluation of governmental environmental governance satisfaction. However, the environmental tax can “neutralize” this negative evaluation, meaning that the environmental tax contributes to the improvement of contentment with governmental governance. Simultaneously, a higher degree of public trust in governmental bodies tends to amplify the positive perception of their environmental endeavors. Our research enriches the field of air pollution perception, broadens our understanding of public satisfaction with environmental governance, and provides valuable references for the government to better use tax measures to manage environmental problems, improve public trust, and thereby enhance the effectiveness of environmental governance.

The organization of this research is outlined as follows: After reviewing the literature, research hypotheses are proposed. Subsequently, the sources of data, variables, and models are elaborated upon. Then, the regression outcomes under the baseline model are presented, followed by the examination of robustness and heterogeneity through additional tests. Next, the paper further explores the mediating effects of environmental taxation. Additionally, the moderating effects of government trust in air pollution perception and satisfaction with environmental governance are discussed from three distinct perspectives: trust in the central level, trust in the county level, and trust in the township level. Finally, research conclusions are given and policy recommendations are proposed.

Literature review and research hypothesis

Perception of air pollution and satisfaction with environmental governance

The perception of air pollution significantly impacts public satisfaction with environmental governance. Zhu et al. (2023) conducted an extensive study demonstrating that variances in public perceptions about the causes of air pollution and the effectiveness of pollution control measures are closely linked to satisfaction with environmental governance. This finding suggests that as the public’s perception of air pollution severity increases, their satisfaction with existing environmental governance measures tends to decrease. Corroborating this perspective, Sun and Zhu (2023) observed an inverse relationship between public risk perception of outdoor air pollution and their satisfaction with outdoor activities, indicating that heightened perceptions of air pollution risks can adversely affect overall environmental satisfaction. Similarly, Sun et al. (2021) explored public responses to air pollution in Shandong Province using online complaint data, revealing a direct connection between public awareness of air pollution and their reactions towards environmental policies. Furthermore, Ruan et al. (2022) have shown that the perception of environmental pollution plays a crucial role in determining public satisfaction with governmental environmental governance. Their study indicates that higher perceived environmental pollution correlates with lower satisfaction regarding government’s environmental efforts.

In conclusion, the cumulative evidence from these studies supports Hypothesis 1, positing a significant negative relationship between the perception of air pollution and satisfaction with environmental governance. This relationship underscores the importance of addressing public perceptions in environmental policy-making to enhance governance effectiveness.

H1: There is a significant negative relationship between the perception of air pollution and satisfaction with environmental governance.

The study by Ruan et al. (2022) sheds light on the geographic dimension of public satisfaction with environmental governance. It suggests that in the Eastern region, heightened public concern about air pollution correlates with lower satisfaction levels regarding environmental governance. This phenomenon could be attributed to the paradox wherein these economically progressive areas also grapple with significant air pollution challenges, which adversely affecting public satisfaction. Complementing the geographic aspect, Zhu et al. (2023) examine the urban-rural divide in public perception of air pollution. Their research underscores that urban residents may exhibit greater sensitivity to air quality issues, which translates into lower satisfaction levels with environmental governance. This heightened urban sensitivity is likely a consequence of more pronounced air quality issues in urban settings, coupled with lifestyle and work environments that expose residents more directly to these challenges. Addressing age-related differences, the work of Han et al. (2022) indicates that elderly individuals might be more susceptible to the impacts of air pollution, leading to heightened dissatisfaction with environmental governance. This trend can be attributed to increased health vulnerabilities to pollutants among older populations, thereby elevating their expectations for environmental quality.

In conclusion, the reviewed literature collectively highlights the heterogeneity in the negative correlation between air pollution perception and satisfaction with environmental governance. This negativity is more pronounced in the eastern regions, among urban dwellers, and older cohorts. Consequently, the following hypotheses are posited:

H2a: In China’s Eastern region, increased awareness of air pollution is associated with reduced satisfaction.

H2b: Urban residents, upon heightened awareness of air pollution, tend to show lower satisfaction.

H2c: Among the elderly, greater awareness of air pollution correlates with a decrease in satisfaction.

The mediating effect of environmental tax

Environmental taxes, while increasing the financial burden on enterprises, play a crucial role in steering them towards sustainable practices. When businesses face substantial fines for pollution or when pollution control costs surpass these taxes, they are incentivized to undertake industrial upgrading and embrace green innovations (Peng et al., 2021). This transition not only promotes the health and growth of companies and nature but also amplifies social benefits (Fullerton and Metcalf, 2001; Gazzani, 2021).

Environmental taxes have been recognized for their ability to effectively govern environmental pollution (Chien et al., 2021; Li et al., 2021; Țibulcă, 2021), create jobs (Koskela and Schöb,1999; Domguia et al., 2022), stimulate green and technological innovation (Karmaker et al., 2021), enhance productivity (Ekins et al., 2012), and foster a sense of well-being among the populace (Wang et al., 2022; Wang and Tang, 2023).

Importantly, environmental taxes also influence public satisfaction with environmental governance. Studies link environmental regulations and awareness to increased satisfaction (Geng and He., 2021), showing that environmental taxes not only guide enterprises towards greener practices but also enhance overall satisfaction with environmental governance.

In light of the outlined research, it becomes evident that environmental taxes, while initially perceived as a burden, have a transformative impact on enterprise behavior and public perception. This transformation is not limited to corporate practices but extends to influencing public satisfaction with environmental governance. Hence, environmental taxes emerge as a pivotal element in the intricate relationship between air pollution perception and governance satisfaction. Building on this understanding, we propose Hypothesis 3 to delve deeper into the nuanced role of environmental taxes within this dynamic. It examines how environmental taxes, beyond their direct financial implications, serve as a crucial factor in reshaping public perceptions and satisfaction levels in environmental governance.

H3: Within the negative correlation between air pollution perception and environmental governance satisfaction, environmental tax serves as a mitigating factor, reducing dissatisfaction with environmental governance induced by air pollution perception.

The moderating effect of government trust

Zeng et al. (2019) highlight the challenges China faces with severe air pollution amid rapid economic growth, emphasizing the crucial role of public trust in the government’s ability to tackle such pressing issues. Liu et al. (2021) highlights how air pollution impacts mental stress and overall wellbeing, underscoring the public’s reliance on governmental efforts and potentially affecting their satisfaction with environmental governance. Symanski et al. (2020) illustrates a successful model of a collaboration involving government and other stakeholders to improve air quality. This case speaks to fostering trust through cooperative participation, which can correlate to increased satisfaction with environmental governance efforts. Liu et al. (2021) investigates the impact of variable air pollution exposure on happiness over different time frames. Their findings reiterate the importance of effective environmental governance in shaping public perception. Sulistyaningsih et al. (2021) Indonesian study explores a successful model of collaboration between a local government and the tapioca industry in addressing environmental pollution, underscoring the significance of government-industry cooperation in building public trust and satisfaction. Ruan et al. (2022) conduct a study on the impact of trust in government and perception of environmental pollution on satisfaction with environmental governance. Their findings further substantiate the claim that enhancing trust in government can boost the performance of environmental governance.

This synthesis of recent research affirms how varied aspects of public perception, trust, and environmental experiences interact to shape satisfaction with environmental governance. Further, these studies imply potential strategies for improving governance satisfaction, such as fostering constructive partnerships, implementing location-specific solutions, and emphasizing trust-building efforts.

Building on Hetherington’s (2005) exploration of political trust and expectation, along with Nabatchi’s (2010) insights into local governance and public participation, this study examines the intricate relationship between public trust at various governmental levels and satisfaction with environmental governance. Hetherington’s framework posits that a higher degree of trust in the central government often translates into heightened expectations. Consequently, individuals with substantial trust may experience a greater decline in satisfaction when facing severe environmental issues, like air pollution, if their expectations are not met. Conversely, Nabatchi’s research underscores the pivotal role of local governance, especially county governments, in addressing environmental concerns. Here, lower trust levels could result in increased dissatisfaction during environmental crises, reflecting skepticism about local governments’ efficacy. Furthermore, incorporating the resource dependence theory by Pfeffer and Salancik (1978), we recognize that village or town governments often operate with limited resources and influence. This theory suggests that such limitations might lead to a relatively stable perception of environmental governance, irrespective of the residents’ trust level, especially in the face of complex challenges like air pollution.

Consequently, the hypotheses are formulated as follows:

H4a: Individuals with higher trust in the central government experience a more significant decline in environmental governance satisfaction under severe air pollution.

H4b: Individuals with lower trust in county governments exhibit a greater decrease in satisfaction with environmental governance when confronted with severe air pollution.

H4c: The level of trust in village or town governments does not significantly influence satisfaction with environmental governance, regardless of air pollution severity.

These hypotheses seek to unravel the layered interaction between governmental trust at different levels and public satisfaction in environmental governance contexts, with a specific focus on air pollution as a prevalent environmental challenge.

In summary, while existing research has extensively focused on air pollution’s impact on health and well-being, there remains a gap in understanding its effects on satisfaction with environmental governance. Similarly, although the environmental tax’s influence on green innovation and ESG compliance is well-documented, its role in enhancing public satisfaction with environmental policies requires further exploration. This study aims to bridge these gaps by investigating the complex interplay between air pollution perception, environmental tax, government trust, and environmental governance satisfaction. The findings are poised to offer significant insights for policymakers, enabling them to formulate more effective and public-centric environmental strategies, particularly in the context of improving ESG outcomes and overall environmental quality. The research logic is illustrated in Fig. 1.

Fig. 1: The research logic diagram.
figure 1

This diagram illustrates the research logic, exploring the relationships among air pollution perception, environmental tax, environmental governance satisfaction, and government trust. Air pollution perception directly influences environmental governance satisfaction (H1) and is moderated by government trust, which includes central, district and county, and township government trust (H4a-c). Environmental tax acts as a mediating variable, linking air pollution perception and environmental governance satisfaction (H3). Additionally, the heterogeneity in the relationship between air pollution perception and environmental governance satisfaction across different contexts, such as urban-rural settings, geographical regions (east, central, west), and age groups (old/young), is also examined (H2a-c).

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Study design

Data information

The data utilized in this research originates from the Chinese Social Survey (CSS) conducted in 2019, a thorough and nationally encompassing survey. The CSS, executed annually by the National Survey Research Center at Renmin University in partnership with the National Bureau of Statistics of China, is dedicated to capturing a wide array of dimensions within Chinese society, with a particular focus on data at the household and individual levels. Its extensive range, encompassing varied themes such as family dynamics and civic engagement, makes it an invaluable resource for profound analysis of societal trends.

The survey boasts an extensive array of topics that include, but are not limited to, family dynamics, living conditions, social assessment, volunteering activities, and social participation. With a vast array of over 2,000 variables, the CSS provides an exceptionally granular depiction of a diverse array of facets of social life in China (Yuan et al., 2021), making it an invaluable resource for any study seeking to provide a holistic analysis of its chosen subject matter within a Chinese context.

In its 2019 iteration, the CSS cast a wide net over China’s population, capturing over 11,000 households across 30 provinces. Excluded from this coverage were Xinjiang and the distinct territories of Hong Kong, Macao, and Taiwan. Out of all the questionnaires disseminated, 10,283 were returned with valid, usable responses. This high response rate underscores the methodological robustness of the CSS as a data collection instrument (Li and Liu, 2023). It’s important to mention that our study also draws upon environmental tax data from the China Statistical Yearbook. This diversified approach of combining datasets allows us to triangulate our findings and better account for potentially confounding factors.

Variable selection

Dependent variable

Environmental governance satisfaction (envg_sat) is measured using the survey item, “How well do you think the government is performing in protecting the environment and addressing pollution?”. The response scale for this item ranged from 1 (very good) to 4 (very poor). The data are inverted for analysis, with higher scores reflecting greater satisfaction with environmental governance.

Independent variable

Air pollution perception (airppp) is assessed based on responses to the question,“Is the air pollution in your current area serious?”. The scale used is as follows: 1 signifies very serious, 2 indicates more serious, 3 represents not too serious, and 4 denotes no such phenomenon. The data are inverted for analysis, with higher scores indicating greater perceived severity of air pollution.

Mediating variable

Environmental Protection Tax (envtax) is considered as a mediating variable. The environmental protection tax comprises six types of levies: urban land usage tax, resource tax, environmental protection tax, arable land occupation tax, vehicle and boat tax, and vehicle purchase tax (Deng and Yang, 2023).

Moderating variables

Government trust, assessed via responses to trust in different government levels, acts as the moderating variable. The data regarding government trust is derived from the survey question: “Do you trust the following institutions? 1. Central government 2. District government 3. Township government”. The responses are rated as 1 = total distrust, 2 = less trust, 3 = trust, 4 = total trust. A higher value indicates a higher level of trust.

Control variables

This study include several control variables commonly used in satisfaction analyses: gender, marriage, age, party membership, household registration, region, education level, and income status, and employment status. These variables are consistent with those identified in related research (Levinson, 2012; Liu et al., 2021; Ruan et al., 2022).

Definition and description of the variables

Table 1 presents the definitions and descriptive statistics for the primary variables analyzed in this study, focusing on central tendencies and variability.The dependent variable, environmental governance satisfaction (envg_sat), gauges public approval of governmental environmental protection efforts, rated on a scale from 1 (very poor) to 4 (very good). An average score of 2.94 suggests that respondents generally perceive the government’s performance as between “not so good” and “better,” with a standard deviation of 0.78 indicating moderate diversity in responses.

Table 1 Definition and descriptive analysis of variables.
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The independent variable, air pollution perception (airppp), captures how respondents view the severity of air pollution, with ratings from 1 (no such phenomenon) to 4 (very serious). The mean score of 2.07 implies that most respondents consider air pollution to be “not too serious” to “more serious,” and the standard deviation of 0.92 reflects a broad range of perceptions.

Environmental protection tax (envtax) serves as the mediating variable, encompassing tax amounts from 15.3 to 874.19. The mean tax value stands at 432.98, showing considerable average tax levels, and the standard deviation of 218.5 reveals significant variation among cases.

Government trust, as a moderating variable, is measured across three levels: central (trust_cent), district (trust_dc), and township (trust_town). Trust is rated from 1 (total distrust) to 4 (total trust). Average scores of 3.59 for central government, 3.08 for district government, and 2.94 for township government suggest generally high trust in central authorities and moderate trust in local ones, with standard deviations of 0.61, 0.88, and 1.00 respectively, indicating varying degrees of response variability.

In addition to these primary variables, the study includes several control variables to account for other factors that might influence environmental governance satisfaction. These controls are education level (edu), income (lninc), gender (gender), age (age), marital status (marr), party membership (party), household registration (urban), employment status (work), and region (distr). The descriptive statistics of these control variables provide a comprehensive picture of the sample demographics and socio-economic characteristics, ensuring a robust analysis.

This detailed overview of the sample and key variables ensures a comprehensive understanding of the data’s central tendencies and variability, which is crucial for the robustness of the subsequent analysis.

Model setting

Our regression analysis is structured as follows.

Model (1) - basic regression:

$${\rm{envg}}\_{\rm{sat}}={\alpha }_{0}+{\alpha }_{1}{\rm{airppp}}+{\rm{Z}}+{\varepsilon }_{1}$$
(1)

Where envg_sat is environmental governance satisfaction, airppp is air pollution perception, Z is control variables, α0 is constant term,α1 is coefficient and ε1 is the error term.

The model assesses how perceptions of air pollution affect satisfaction with environmental governance. The coefficient for air pollution perception (airppp) is α1. This means that for every one-unit increase in airppp, it is expected that environmental governance satisfaction will decrease by α1 units, assuming all other variables remain constant. This aligns with our understanding that as air pollution perception increases (i.e., the air pollution becomes more severe), the satisfaction with environmental governance decreases.

Model (2) -Mediation by environmental tax:

In this study, we examine the mediating role of environmental tax (envtax) in the relationship between air pollution perception (airppp) and satisfaction with environmental governance (envg_sat), drawing on the framework proposed by Baron and Kenny (1986). Our model is encapsulated in two equations:

$${\rm{Envtax}}={\beta }_{0}+{\beta }_{1}{\rm{airppp}}+{\rm{Z}}+{\varepsilon }_{2}$$
(2)
$${\rm{envg}}\_{\rm{sat}}={\gamma }_{0}+{\gamma }_{1}{\rm{airppp}}+{\gamma }_{2}{\rm{envtax}}+{\rm{Z}}+{\varepsilon }_{3}$$
(3)

Here, β0 and γ0 represent constant terms, β1, γ1, and γ2 are coefficients, and ε2 and ε3 are error terms. The term Z in both equations refers to control variables.

Our mediation hypothesis posits that while an increase in airppp may reduce envg_sat (as indicated by γ1), the introduction and augmentation of envtax could offset this negative effect. Specifically, Eq. 2 delineates the impact of airppp on envtax, with β1 indicating the responsiveness of envtax to changes in airppp. Equation 3 models envg_sat as influenced by both airppp and envtax, capturing the direct effect of airppp (γ1) and the indirect effect mediated through envtax (γ2).

This model allows for the assessment of the total effect of airppp on envg_sat, which is a composite of its direct impact and the indirect impact through envtax (β1 * γ2). Such a structure facilitates the investigation of a possible “masking effect”, where the environmental tax might obscure the direct negative influence of airppp on envg_sat.

The empirical validation of this model, particularly determining whether it exhibits traditional mediation or a masking effect, will rely on the derived values of γ1 and γ2 from our data analysis.

Model (3) -Moderation by government trust:

This model examines the moderating effect of government trust on the relationship explored in Model (1).

$${\rm{envg}}\_{\rm{sat}}={\lambda }_{0}+{\lambda }_{1}{\rm{airppp}}+{\lambda }_{2}\,{\rm{mod}}\,+{\lambda }_{3}({\rm{airppp}}\times \,{\rm{mod}})+{\rm{Z}}+{\varepsilon }_{4}$$
(4)

Where mod represents government trust at different levels (central, district, township). λ0 is constant term,λ1, λ2, λ3 is coefficient and ε4 is the error term.

The moderation effect is represented by λ3, the coefficient of the interaction term (airppp×mod). This concept elucidates the variable impact of perceptions of air pollution on satisfaction with environmental governance, contingent on varying degrees of trust in government. A notable λ3 value indicates the extent to which trust in government modifies the intensity or nature of the correlation between perceptions of air pollution and satisfaction with environmental governance. A positive and significant λ3 suggests that elevated trust in government heightens the influence of air pollution perceptions on satisfaction levels. In contrast, a negative λ3 would imply that increased government trust mitigates this impact. Hence, the influence of air pollution perception on satisfaction with environmental governance is dynamic and shifts based on the prevailing level of trust in government.

In summary, this model posits that government trust plays a crucial role in moderating the relationship between individuals’ perception of air pollution and their satisfaction with environmental governance. The significance and value of λ3 would provide empirical evidence for this moderating effect.

Empirical tests

Baseline regression results

OLS regression

In the regression analysis, multicollinearity among variables is assessed using the variance inflation factor (VIF) method. The mean VIF stands at 1.46, with all individual VIFs remaining below the threshold of 2, indicating a lack of significant multicollinearity (Hair et al., 2017). This step is essential to maintain the validity of our results. Moreover, the selection of control variables such as gender, education, and income, follows their proven impact on satisfaction in existing literature (Levinson, 2012; Ruan et al., 2022), allowing a more nuanced understanding of factors influencing satisfaction with environmental governance.

Given that most variables in this study are ordered discrete, the estimation is conducted using an Ordered Probit (Oprobit) model (Lu, 1999). We first use the Ordinary Least Squares (OLS) model to do the baseline regression. Then the mediating and moderating effects research will be discussed later and the Ordered Probit (Oprobit) will be used for robustness testing.

Table 2 outlines the outcomes of the regression analysis using OLS to explore the relationship between perceived air pollution and satisfaction with environmental governance. The results reveal a significant negative correlation between individuals’ perception of air pollution and their satisfaction with environmental governance, both with and without control variables. This finding supports H1, indicating that as the public’s perception of air pollution severity increases, their satisfaction with the government’s environmental governance decreases.

Table 2 Basic regression results.
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In the model without control variables (Column 1), the coefficient for air pollution perception is −0.2650, indicating a significant negative association at the 1% significance level. When control variables are included (Column 2), the coefficient slightly changes to −0.2605, still showing a significant negative relationship at the 1% significance level. This consistency across both models indicates that as the public’s perception of air pollution severity increases, their satisfaction with the government’s environmental governance decreases, thus corroborating H1.

The inclusion of control variables in Column 2 accounts for potential confounding factors such as education, income, gender, age, marital status, party membership, urban residence, employment status, and region. The robustness of the negative correlation between air pollution perception and satisfaction with environmental governance, even with these controls, underscores the validity of H1. It suggests that perceived air pollution is a significant and independent predictor of satisfaction with environmental governance.

Robustness test

Four distinct approaches are employed to validate the robustness of the findings. First, we substituted the OLS method with the Ordinal Probit (Oprobit) method, as the dependent variable (environmental governance satisfaction) is ordinal. The Oprobit method, designed for ordinal multicategory dependent variables, may handle this type of data more accurately, as shown in Table 3 (1). Second, we replaced air pollution perception with water pollution perception, as detailed in Table 3 (2). Third, we matched the objective Air Quality Index (AQI) published by each province with residents’ perceptions, using AQI as a proxy for objective air pollution perception (Falzone and Romain, 2022). A higher AQI value indicates worse air pollution quality, as evidenced in Table 3 (3). Lastly, we integrated province-level control variables in our analysis to eliminate potential confounding effects stemming from geographical, economic, and social differences (Gong et al., 2019), as illustrated in Table 3(4). All of the outcomes uniformly indicate a substantial negative correlation between the independent and dependent variables, thereby affirming the robustness of our research conclusions.

Table 3 Robustness test.
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Heterogeneity test

Table 4 reveals a significant negative correlation between air pollution perception and environmental governance satisfaction across various demographics, including urban-rural, regional, and age groups. However, the Bdiff test results show no considerable variance between urban and rural residents (p = 0.44). This indicates that hypothesis H2b, predicting lower satisfaction among urban residents as their perception of air pollution severity increases, is not supported. The rapid urbanization process in China may explain this lack of significant differences. Urbanization has gradually transformed many rural areas into urbanized regions, potentially leading to a convergence of environmental governance measures. The government may have implemented similar policies in both urban and rural areas, ensuring improved environmental quality across regions. Additionally, factors such as differing expectations and the influence of socioeconomic backgrounds may also play a role. Further research is required to validate and explore these factors comprehensively.

Table 4 Heterogeneity test.
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In contrast, significant differences are observed between residents of the eastern region and those in the central-western regions (p = 0.02), supporting hypothesis H2a. In the eastern regions, characterized by higher levels of economic development, increased pollution levels likely result in greater dissatisfaction with environmental governance among residents. Additionally, significant differences among different age groups (p < 0.001) support hypothesis H2c. Older individuals are more sensitive to the severity of air pollution compared to younger individuals, leading to a higher level of dissatisfaction with environmental governance during severe pollution episodes.

In-depth analysis

Analysis of marginal effects

The Ordered Probit model’s parametric implications provide significant insights into the relationship between independent and dependent variables, highlighting their significance and direction. However, to understand the precise quantitative relationship, conducting a marginal effects analysis is crucial. Marginal effects illustrate how changes in exogenous variables influence the probability of specific outcomes for the dependent variable, assuming all other variables are at their mean values (Mize et al., 2019). Table 5 presents the marginal effect coefficients of air pollution perception on satisfaction with environmental governance. When all variables are at mean values, a 1% increase in perceived air pollution leads to a 10.8% decrease in the likelihood of a “very good” rating for environmental governance. This reaffirms the inverse relationship between perceived environmental pollution and governance satisfaction.

Table 5 Marginal effect of air pollution perception on environmental governance satisfaction.
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The accompanying marginal effects plot (Fig. 2) offers a more dynamic representation of this relationship. It visually depicts how worsening air pollution perception correlates with a decline in high ratings for environmental governance satisfaction.

Fig. 2: Conditional marginal effects of air pollution perception on environmental governance satisfaction.
figure 2

This figure displays the marginal effects of air pollution perception (airpp) on environmental governance satisfaction (envg_sat) across different levels of satisfaction. The y-axis represents the effects on probability, while the x-axis shows the levels of environmental governance satisfaction. The plot reveals how the perception of air pollution influences satisfaction with environmental governance at varying levels, illustrating a non-linear relationship where the marginal effect initially increases before declining. These findings underscore the significant impact of public perception of air quality on their satisfaction with environmental policies, highlighting the importance for policymakers to proactively address public concerns to maintain or enhance satisfaction with environmental governance.

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These findings underscore the significant impact of public perception of air quality on their satisfaction with environmental policies. They suggest a need for policymakers to proactively address public concerns about air quality to maintain or enhance satisfaction with environmental governance.

Analysis of the mediating effect of environmental tax

To verify the mediating effect of environmental tax on the relationship between air pollution perception and satisfaction with environmental governance, we first employed the mediation model based on the framework proposed by Baron and Kenny (1986). The results are presented in Table 6.

Table 6 The mediating effect of environmental tax.
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Table 6(2) highlights a significant positive correlation between perceived air pollution and environmental tax (r = 8.6427, p < 0.01), suggesting that higher air pollution perception leads to increased environmental tax imposition. Table 6(3) reveals a notable positive association between environmental tax and satisfaction with environmental governance, indicating that higher environmental tax enhances satisfaction. The environmental tax serves as a mitigating factor, reducing the negative impact of air pollution perception on governance satisfaction by 0.82%, thus supporting Hypothesis 3 (H3). The significance of environmental tax, although modest in proportion, is crucial as it represents a national strategy of engaging governments, businesses, and the public in environmental preservation through taxation mechanisms. The enactment of China’s Environmental Protection Tax Law in 2018 reinforces this strategy, legally mandating pollution control and environmental conservation in businesses. The environmental tax’s role in enhancing satisfaction with environmental governance is expected to amplify in the future.

To further substantiate the mediating effect of environmental tax on the relationship between air pollution perception and environmental governance satisfaction, we employed the Karlson, Holm, and Breen (KHB) method (Breen et al., 2021). The KHB approach provides a straightforward method for assessing total, direct, and indirect effects without the need for manual computation, as shown in Table 7.

Table 7 Total, direct, and indirect effects of environmental tax mediation.
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Our study distinctly demonstrates the mediating role of environmental tax as evidenced in our results. According to Table 7, the total effect of air pollution perception on environmental governance satisfaction is quantified at −0.261, with a direct effect of −0.263, and an indirect effect via environmental tax at 0.00213. These findings corroborate the results presented in Table 6, highlighting the neutralizing role of environmental tax between air pollution perception and satisfaction with environmental governance. This indicates that environmental tax not only contributes to pollution management but also plays a significant role in enhancing public satisfaction with governmental environmental efforts.

The application of the KHB method lends additional support to our analysis, affirming the pivotal role of environmental tax in moderating the impact of air pollution perception on environmental governance satisfaction. This method allows us to quantify and understand the critical function of environmental tax in environmental governance, and how it influences public approval and satisfaction with government environmental policies. This aspect of our study brings forth a nuanced understanding of the dynamics between environmental taxation, public perception, and governmental effectiveness in environmental management.

Analysis of the moderating effect of government trust

In exploring the nuanced relationship between public trust at various government levels and satisfaction with environmental governance, especially under the pressure of severe air pollution, this section aligns closely with theoretical frameworks and recent research findings. Table 8 and Figs. 3–5 offer a detailed depiction of this intricate dynamic.

Table 8 The moderating effects.
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Fig. 3: The role of trust in the central government as a moderating factor.
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This figure demonstrates the significant moderating effect of central government trust on the relationship between air pollution perception and environmental governance satisfaction. The plot reveals that individuals with high trust in the central government experience a more pronounced decline in satisfaction when air pollution perception is high. This finding suggests that heightened expectations associated with high central government trust can lead to greater dissatisfaction under severe pollution conditions, thus supporting hypothesis H4a.

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Fig. 4: The role of trust in the district government as a moderating factor.
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This figure illustrates how trust in district governments influences the relationship between air pollution perception and environmental governance satisfaction. The results indicate that lower trust in district governments exacerbates dissatisfaction during periods of severe air pollution, as evidenced by the steeper decline in satisfaction levels among individuals with low district government trust. This supports hypothesis H4b by underscoring the critical role that trust in local governance plays in shaping public satisfaction under adverse environmental conditions.

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Fig. 5: The role of trust in the township government as a moderating factor.
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This figure depicts the stabilizing effect of township government trust on environmental governance satisfaction in the context of air pollution perception. Unlike central and district government trust, township government trust shows a more consistent influence on satisfaction, regardless of pollution levels. This relative stability suggests that the limited resources and influence associated with township governments may result in a less variable public response to environmental challenges, providing additional evidence for hypothesis H4c.

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From Table 8, we can observe several key patterns in how trust at different government levels impacts satisfaction with environmental governance:

Hierarchical trust pattern

A critical observation from Table 8 is the hierarchical pattern in the impact of trust on environmental governance satisfaction. This pattern demonstrates that trust in the central government has the most substantial influence, followed by township and then district governments. This hierarchy signifies varying degrees of public expectations and perceptions of each government level’s capabilities and responsibilities in managing environmental issues (Tang et al., 2023).

Central government trust

The significant negative interaction term (airppp#trust_cent) in Table 8 supports H4a, indicating that individuals with higher trust in the central government experience a more pronounced decline in satisfaction under severe air pollution. This finding aligns with Hetherington’s theory of political trust, suggesting heightened expectations from higher trust levels.

District government trust

In contrast, the positive interaction term (airppp#trust_dc) in Table 8 supports H4b. This reflects that lower trust in district governments correlates with increased dissatisfaction during severe air pollution, underscoring the importance of trust in local governance as per Nabatchi’s insights.

Township government trust

The non-significant interaction term (airppp#trust_town) in Table 8 supports H4c, aligning with the resource dependence theory. It suggests that trust in township governments, often limited by resources, does not significantly impact satisfaction levels in the context of air pollution.

Moving from the tabular data to the visual representations, we provide a more intuitive understanding of these complex interactions in the next section.

Figures 3–5 visually depict how varying levels of trust in different government levels modulate public satisfaction under different air pollution scenarios.

Figure 3 demonstrates the role of trust in the central government as a moderating factor, highlighting the significant negative impact of high central government trust on satisfaction during severe air pollution, further supporting H4a. Figure 4 illustrates the impact of trust in district governments, showing how lower trust exacerbates dissatisfaction in severe pollution conditions, which reinforces H4b. Figure 5 depicts the relative stability of trust in township governments, indicating that their limited resources and influence result in a more consistent perception of environmental governance, providing additional evidence for H4c.

In conclusion, this section not only provides a nuanced analysis of how government trust at various levels affects public satisfaction with environmental governance but also emphasizes the importance of aligning public expectations with the capabilities and actions of governments at different levels. These insights are crucial for developing effective strategies to enhance environmental governance and public trust, especially in the face of environmental challenges such as air pollution. The theoretical underpinnings of this research, drawn from political trust and resource dependence theory, offer valuable directions for policymakers in understanding and addressing the complexities of public trust and satisfaction in environmental governance.

Treatment of endogeneity

To address the potential endogeneity issue between satisfaction in environmental governance and air pollution perception, we adopt a Two-Stage Least Squares (2SLS) instrumental variable approach. Our instrumental variable is constructed as the cubic deviation from the mean of air pollution perception (airpppgap3). This choice of instrument is inspired by econometric methods that utilize non-linear transformations of variables as instruments. The 2SLS method, a well-established technique in econometrics for dealing with endogeneity, is applied to isolate the causal impact. While the use of such transformed variables as instruments is consistent with advanced econometric practices, it is not a methodology uniquely attributable to any single study, including Mogstad et al. (2018). Our application of this approach aims to robustly address the endogeneity concerns in our analysis.

The initial regression stage, as shown in Table 9(1), indicates a significant positive correlation between airpppgap3 and air pollution perception (airppp). Furthermore, the robustness of the instrumental variable is confirmed by a high F-statistic (1818.85), indicating no issues with weak instrumental variables (Stock et al., 2002).

Table 9 Outcomes obtained using the 2SLS instrumental variable approach.
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Table 9(2) details the second stage of regression analysis, presenting further outcomes. There is a notable inverse relationship between air pollution perception and satisfaction with environmental governance, as observed in the analysis. This suggests that, while controlling for other variables, a one-unit increase in air pollution perceptions leads to a decrease of 0.259 units in environmental governance satisfaction, indicating a significant negative impact of perceived air pollution on satisfaction.

Table 9(3) presents the regression results of the semi-simplified equation. The inclusion of the instrumental variable in the regression equation demonstrates that its coefficient in relation to environmental governance satisfaction does not refute the null hypothesis. This indicates a lack of correlation between the instrumental variable and the error term in the regression, satisfying the exclusion restriction (Sovey and Green, 2011).

In conclusion, the application of the 2SLS method using airpppgap3 as an instrumental variable provides robust evidence for the significant inverse relationship between air pollution perception and satisfaction with environmental governance. This analysis confirms the validity of our approach in addressing the endogeneity issue and underscores the importance of considering such methodological nuances in environmental governance research.

Findings and discussion

In our empirical investigation utilizing 2019 CSS data and environmental tax data, we sought to evaluate the influence of perceived air pollution on environmental governance satisfaction, as well as to examine the underlying mechanisms and contributing factors. Our primary research findings are as follows:

Impact of air pollution perception: The regression analysis revealed a substantial and adverse effect of air pollution perception on satisfaction with environmental governance. This finding aligns with the research of Ruan et al. (2022) and Zhu et al. (2023). Additionally, subgroup evaluations based on age and region substantiate variations in the influence of environmental pollution perception on governance satisfaction. Notably, older individuals and those from eastern regions are more adversely affected compared to other groups. This is consistent with the findings of Ruan et al. (2022) and Han et al. (2022) However, contrary to Zhu’s study (2023), our research did not observe heterogeneity in satisfaction levels between urban and rural residents.

Environmental tax as a mediating Factor: Our study identifies environmental tax as a mediating variable between air pollution perceptions and environmental governance satisfaction. The implementation of environmental taxation not only effectively manages air pollution but also enhances satisfaction with environmental governance. This role of environmental tax in governing environmental pollution is supported by studies from Chien et al. (2021), Li et al. (2021), and Liu, Liu (2022). However, the aspect of environmental tax elevating governmental governance satisfaction emerges as a novel insight, not extensively covered in previous literature.

Government trust as a moderator: Government trust significantly moderates environmental governance satisfaction, with a higher trust in the government correlating with improved satisfaction. The trust level of the central government is observed to be much higher than that of local government, presenting a “differential government trust” pattern, akin to findings by Jing et al. (2012) and Li (2004). However, when government trust functions as a moderator, its role in adjusting the relationship between air pollution perception and public governance satisfaction varies according to different levels of government trust. Specifically, individuals with greater trust in the central government may experience a more pronounced decrease in satisfaction when perceiving severe air pollution, while those with higher trust in county governments may exhibit increased satisfaction with environmental governance. Notably, no significant differences in governance satisfaction were observed between individuals with high or low trust in village or town governments. This finding is unique to our study. This nuanced understanding of government trust’s moderating effect underscores the complexity of how varying degrees of trust in different government levels influence public perceptions and satisfaction in environmental governance.

This research significantly enriches the understanding of the dynamics between air pollution perception and environmental governance satisfaction, offering unique insights into how environmental policies and public trust interact to shape public perception and satisfaction.

Conclusions and recommendations

Conclusions

This study reveals a significant inverse correlation between public perception of air pollution and satisfaction with environmental governance. Notably, older individuals and residents of eastern regions exhibit a more pronounced impact of pollution perception on their satisfaction levels. Environmental tax serves as a mediating mechanism between air pollution perception and governance satisfaction, effectively managing pollution and enhancing public contentment with environmental policies. Furthermore, varying degrees of government trust influence satisfaction levels, with higher trust in central government correlating with decreased satisfaction amidst severe pollution, while greater trust in county governments may augment satisfaction.

This research substantially enriches the domain of air pollution perception by meticulously examining the determinants that shape the connection between air pollution perception and satisfaction towards environmental governance, as well as exploring their fundamental processes. The findings offer valuable practical insights for the government. The implementation of environmental taxes can effectively manage pollution issues, leading to enhanced public satisfaction with environmental governance. Additionally, increasing public trust in the government can significantly enhance satisfaction with environmental management efforts, thereby promoting the advancement of our nation’s ecological and environmental governance system.

Policy recommendations

The ecological environmental management holds a crucial position within the national governance framework, and evaluating government environmental governance efforts requires considering public satisfaction as a crucial aspect. To further enhance the government’s ecological environmental management level and improve public satisfaction with environmental governance work, we propose the following policy recommendations: (1) Enhance the development and execution of ecological policies. To ensure the scientific and effective nature of environmental policies, the government should adopt a collaborative approach involving multiple disciplines and departments. Thorough investigations and research on the causes and impacts of environmental issues should be conducted to formulate practical and feasible policies. Additionally, strict adherence to policy requirements by government departments at all levels should be ensured during policy implementation, with regular evaluation and adjustment of policy effects. (2) Enhance government governance capacity. The government should increase investment in environmental pollution control, including funding, personnel, and technology. Introducing advanced environmental protection technologies and equipment can improve the effectiveness of environmental governance. Additionally, strengthening the training and education of environmental protection personnel will enhance their professional expertise, enabling them to effectively address various environmental problems. (3) Enhance government credibility. The government should promptly disclose environmental information, including environmental quality data and pollution source monitoring data, to enable the public to understand the environmental situation. Furthermore, actively promoting the achievements of environmental governance will allow the public to witness the government’s efforts and effectiveness. Such transparent information dissemination plays a crucial role in enhancing public trust in the government. (4) Establish a robust system of supervision and accountability for environmental issues. The government should establish a well-functioning mechanism to supervise and hold accountable government departments and enterprises that fail to fulfill their environmental protection responsibilities. For instance, an independent environmental protection supervision agency can be established to conduct regular inspections of polluting enterprises and government departments, promptly address any issues identified. Additionally, a reporting system should be put in place to foster public participation in environmental protection supervision and crackdown on illegal and irregular activities. (5) Enhance environmental tax policies. The government can incentivize enterprises to reduce pollution emissions by revising tax policies. For instance, it can raise the level of environmental taxes imposed on enterprises with high pollution and high energy consumption, while offering tax benefits to those adopting clean production technologies and promoting low-carbon development. Moreover, establishing a dedicated environmental protection fund and utilizing the collected environmental taxes for environmental governance and ecological restoration can be considered. (6) Promoting public engagement in environmental decision-making: Enhance public participation in the development and implementation of environmental policies. This can be achieved by establishing platforms for public consultation and feedback, particularly on issues related to air pollution and environmental taxation. Such engagement not only increases transparency and trust in government actions but also aligns with the Environmental and Governance aspects of ESG by ensuring that policies are reflective of public perception and concerns. This approach could lead to more effective and accepted environmental strategies, thus improving overall satisfaction with environmental governance.

By comprehensively implementing the aforementioned five measures, we anticipate enhancing the government’s effectiveness in environmental governance and increasing public satisfaction with environmental initiatives. This, in turn, will enable us to simultaneously drive economic development, safeguard the ecological environment, and achieve sustainable development.

Research shortcomings and future prospects

Future research should aim for a comprehensive analysis that incorporates both dynamic panel data and in-depth exploration of government trust. This approach should involve:

(1) Longitudinal policy impact analysis: Employ dynamic panel data to assess the evolving impact of specific policies like the Environmental Protection Tax Law of 2018, focusing on changes in pollution control and public satisfaction over time. (2) Transparency and public perception: Investigating the roles of environmental information transparency, government reputation, and public awareness in shaping the public’s perception of environmental policies and their trust in government. (3) Cultural and social contexts of government Trust: Expanding the analysis of government trust to include its stability and origins across different cultural and social contexts. This should also consider the influence of policy transparency and public participation in shaping trust. (4) Internet utilization and environmental consciousness: Examining how internet access and public environmental awareness moderate perceptions of environmental pollution and evaluations of government governance. (5) Panel data comparative study: Employing panel data for comparative analysis across different regions and time periods, to understand the dynamic nature of public perception and satisfaction with environmental governance.

By integrating these approaches, future research can offer a more nuanced and comprehensive understanding of the effectiveness of environmental governance and policy, taking into account both temporal changes and the multifaceted nature of government trust and public perception.