Assessing the impact of urban road transport development on haze pollution in the Yangtze River Delta region.

The aim of this paper is to explore whether and how urban road transport (URT) development affects haze pollution. One of the innovations of this paper is that URT development is measured by road accessibility with novel digital elevation model datasets, which have been used by few scholars. The endogenous problem caused by revere causality issue in the relationship between URT development and haze pollution is also considered. Based on the panel data of prefecture-level cities of Yangtze River Delta (YRD) region in China from 2011 to 2018, this paper uses long-lagged values of URT development as the instrumental variable, employing the two-stage least squares (2SLS) method. The study shows that URT development leads to an increase of haze pollution. Moreover, mechanism tests based on moderating and mediating models support the finding that decreasing haze pollution resulted from better connection effects, while rising agglomeration effects tend to bring about increasing haze pollution, and the latter effect is larger in magnitude than the former. Current URT development may have long-term negative consequences for livability of YRD cities, and urban decision makers should reconsider the effectiveness of the current road transport investment and construction.

Cross-sectional analysis of socioeconomic drivers of PM2.5 pollution in emerging SAARC economies.

Within the intricate interplay of socio-economic, natural and anthropogenic factors, haze pollution stands as a stark emblem of environmental degradation, particularly in the South Asian Association for Regional Cooperation (SAARC) region. Despite significant efforts to mitigate greenhouse gas emissions, several SAARC nations consistently rank among the world's most polluted. Addressing this critical research gap, this study employs robust econometric methodologies to elucidate the dynamics of haze pollution across SAARC countries from 1998 to 2020. These methodologies include the Pooled Mean Group (PMG) and Augmented Mean Group (AMG) estimator, Panel two-stage least squares (TSLS), Feasible Generalized Least Squares (FGLS) and Dumitrescu-Hurlin (D-H) causality test. The analysis reveals a statistically significant cointegrating relationship between PM2.5 and economic indicators, with economic development and consumption expenditure exhibiting positive associations and rainfall demonstrating a mitigating effect. Furthermore, a bidirectional causality is established between temperature and economic growth, both influencing PM2.5 concentrations. These findings emphasize the crucial role of evidence-based policy strategies in curbing air pollution. Based on these insights, recommendations focus on prioritizing green economic paradigms, intensifying forest conservation efforts, fostering the adoption of eco-friendly energy technologies in manufacturing and proactively implementing climate-sensitive policies. By embracing these recommendations, SAARC nations can formulate comprehensive and sustainable approaches to combat air pollution, paving the way for a healthier atmospheric environment for their citizens.

Semi-supervised urban haze pollution prediction based on multi-source heterogeneous data.

Particulate matter (PM) is defined by the Texas Commission on Environmental Quality (TCEQ) as "a mixture of solid particles and liquid droplets found in the air". These particles vary widely in size. Those particles that are less than 2.5 µm in aerodynamic diameter are known as Particulate Matter 2.5 or PM2.5. Urban haze pollution represented by PM2.5 is becoming serious, so air pollution monitoring is very important. However, due to high cost, the number of air monitoring stations is limited. Our work focuses on integrating multi-source heterogeneous data of Nanchang, China, which includes Taxi track, human mobility, Road networks, Points of Interest (POIs), Meteorology (e.g., temperature, dew point, humidity, wind speed, wind direction, atmospheric pressure, weather activity, weather conditions) and PM2.5 forecast data of air monitoring stations. This research presents an innovative approach to air quality prediction by integrating the above data sets from various sources and utilizing diverse architectures in Nanchang City, China. So for that, semi-supervised learning techniques will be used, namely collaborative training algorithm Co-Training (Co-T), who further adjusting algorithm Tri-Training (Tri-T). The objective is to accurately estimate haze pollution by integrating and using these multi-source heterogeneous data. We achieved this for the first time by employing a semi-supervised co-training strategy to accurately estimate pollution levels after applying the U-air system to environmental data. In particular, the algorithm of U-Air system is reproduced on these highly diverse heterogeneous data of Nanchang City, and the semi-supervised learning Co-T and Tri-T are used to conduct more detailed urban haze pollution prediction. Compared with Co-T, which train time classifier (TC) and subspace classifier (SC) respectively from the separated spatio-temporal perspective, the Tri-T is more accurate with a and faster because of its testing accuracy up to 85.62 %. The forecast results also present the potential of the city multi-source heterogeneous data and the effectiveness of the semi-supervised learning. We hope that this synthesis will motivate atmospheric environmental officials, scientists, and environmentalists in China to explore machine learning technology for controlling the discharge of pollutants and environmental management.

Human dermal exposure to short- and medium-chain chlorinated paraffins: Effect of populations, activities, gender, and haze pollution.

Human dermal exposure to chlorinated paraffins (CPs) has not been well documented. Therefore, hand wipes were collected from four occupational populations to analyze short-chain CPs (SCCPs) and medium-chain CPs (MCCPs) in order to estimate dermal uptake and oral ingestion via hand-to-mouth contact. The total CP levels (∑SCCPs and ∑MCCPs) in wipes ranged from 71.4 to 2310 µg/m2 in security guards, 37.6 to 333 µg/m2 in taxi drivers, 20.8 to 559 µg/m2 in office workers, and 20.9 to 932 µg/m2 in undergraduates, respectively. Security guards exhibited the highest levels of ∑SCCPs among four populations (p < 0.01). In undergraduates engaged in outdoor activities, C13 emerged as the most dominant SCCPs homologue group, followed by C12, C11, and C10. The levels of ∑SCCPs and ∑MCCPs in males in light haze pollution were significantly higher than that in heavy haze pollution (p < 0.05). The median estimated dermal absorption dose of SCCPs and MCCPs via hand was 22.2 and 104 ng (kg of bw)-1 day-1, respectively, approximately 1.5 times the oral ingestion [12.3 and 74.4 ng (kg of bw)-1 day-1], suggesting that hand contact is a significant exposure source to humans.

The environmental consequences of national Audit governance: An analysis based on county-level data in China.

Recent years have witnessed growing public concern over air pollution in China, posing a challenge to the government's environmental management efforts. Empirical evidence indicates that the digital economy contributes to mitigating environmental pollution. Given that national audits are a crucial part of the national oversight system and considering the significant role of digital technology in audit governance, it is relevant to explore how the digital economy can support national audits in enhancing China's environmental quality. This study investigates the environmental impact of national audit governance, utilizing a dataset from 1540 counties in China spanning from 2005 to 2018. The findings reveal that effective national audits contribute to reducing haze pollution (HP) levels, with the digital economy playing a moderating role. The results also demonstrate heterogeneity; national audits are particularly effective in regions characterized by high urbanization rates, severe HP, and stringent environmental regulations. The mechanism analysis suggests that industrial transformation and enhanced government governance are the key mechanisms through which national audits reduce regional HP. Additionally, reforming the audit management system can amplify the effects of national audits on reducing HP.

Benefit of aerosol reduction to winter wheat during China's clean air action: A case study of Henan Province.

A strongly declining aerosol radiative effect has been observed in China since 2013 after implementing the clean air action, yet its impact on wheat (Triticum aestivum L.) production remains unclear. We use satellite measures and a biophysical crop model to assess the impact of aerosol-induced radiative perturbations on winter wheat production in the agricultural belt of Henan province from 2013 to 2018. After calibrating parameters with the extended Fourier Amplitude Sensitivity Test (EFAST) and the generalized likelihood uncertainty estimation (GLUE) method, the DSSAT CERES-Wheat model was able to simulate crop biomass and yield more accurately. We found that the aerosol negatively impacted wheat biomass by 21.87% and yield by 22.48% from 2006 to 2018, and the biomass effects from planting to anthesis were more significant compared to anthesis to maturity. Due to the strict clean air action, under all-sky conditions, the surface solar shortwave radiation (SSR) in 2018 increased by about 7.08% over 2006-2013 during the wheat growing seasons. As a result of the improvement of crop photosynthesis, winter wheat biomass and yield increased by an average of 5.46% and 2.9%, respectively. Our findings show that crop carbon uptake and yield will benefit from the clean air action in China, helping to ensure national food and health security.

Can the construction of a high-speed rail alleviate haze pollution: an empirical analysis based on social networks and dynamic spatial econometric models.

With the increase in haze pollution in Chinese cities, answering the question of whether using a high-speed rail (HSR) as a green and efficient transportation system can alleviate haze pollution in China has become a research hotspot. This study empirically tests the impact of HSR network construction on haze pollution and its spatial spillover effects. (1) The construction of a HSR would have a mitigation effect on haze pollution in node cities and surrounding cities, and the more developed the HSR is, the more significant that this effect would be. (2) Haze pollution persists for a long time, the haze pollution from the previous year may have a positive promoting effect on the haze pollution in the following year. (3) The use of a HSR reduces haze pollution by replacing traditional road transportation and promoting industrial structure upgrading and technological innovation. (4) The inhibitory effect of HSR use on haze pollution varies due to regional differences and variation in city size.

The effect of haze pollution on rural-to-urban migrants' long-term residence intentions.

Severe haze pollution in China threatens human health, and its negative effect hampers rural-to-urban migrants' settlement intentions in destination cities. Using the 2017 China Migrants Dynamic Survey Data (CMDS), the satellite data of PM2.5, and city-level data, this study investigates the impact of haze pollution on rural migrants, long-term residence intentions in Chinese context with IV-probit model, and mediating effect model. Overall, we find an inverted U-shaped relationship between the level of haze pollutants and rural migrants' long-term settlement intentions. Robustness check using multi-measures and thermal inversion as the instrumental variable supports this conclusion. The mediating effect model shows haze pollution plays its role through two opposite mechanisms: signal effect and health effect. When the size of signal effect is larger than health effect, rural migrants are inclined to settle down in their host cities; otherwise, they show lower settlement willingness. The turning point appears when PM2.5 concentration reaches 38.5 µg/m3; migrants have the highest long-term residence intentions. Currently, the national average PM2.5 concentration is 40.98 µg/m3, indicating that China is at the stage where the health effect of haze pollution holds a dominant position. Haze pollution has heterogeneous impacts on migrants' residence intentions. From the individual level, the younger generation, female, and higher-educated migrants have a higher tolerance for polluted air. From the city level, migrants who work in the city with 5 to 10 million dwellers have the highest long-term residence intention and are less sensitive to haze pollution. Thus, we propose stringent environmental regulations and more inclined public service policies to migrants.

Is air pollution joint prevention and control effective in China-evidence from "Air Pollution Prevention and Control Action Plan".

This paper examined the effect of air pollution joint prevention and control on pollution emissions in China. Specifically, based on the panel data of 290 cities from 2007 to 2021, taking the implementation of the "Air Pollution Prevention and Control Action Plan" as a natural experiment, the difference-in-difference-in-difference (DDD) model was used to explore the effect of air pollution joint prevention and control on haze pollution. Results show that air pollution joint prevention has a significant impact on pollutant emissions either as a whole or as a single pollutant. In terms of individual urban agglomeration, whether the Yangtze River Delta or the Pearl River Delta urban agglomerations, the air pollution joint prevention and control policy has a significant impact not only on the overall reduction of pollutant emissions but also on the reduction of single PM2.5 or industrial sulfur dioxide emissions alone. Environmental regulations have also achieved the effect of haze control in general and have a significant impact on the reduction of PM2.5 or industrial sulfur dioxide emissions. Environmental regulations also significantly reduced PM2.5 emissions in these three urban agglomerations. These findings provide a scientific basis and essential reference for understanding the implementation effect of regional joint prevention and control policies comprehensively and objectively.

[Characteristics and Generation Mechanism of Secondary Inorganic Ions in PM2.5 in Changsha-Zhuzhou-Xiangtan City Group].

Secondary inorganic ions, the main components of atmospheric PM2.5, are a dominant contributor to haze formation. The detailed characteristics and main generation mechanism of secondary inorganic ions in PM2.5 are still unclear in the Changsha-Zhuzhou-Xiangtan City Group, which is suffering from severe haze pollution, particularly in the autumn and winter seasons. For our study, we collected PM2.5 samples in November 2020 and January 2021 from four urban sites in the Changsha-Zhuzhou-Xiangtan City Group. Secondary inorganic components such as SO42-, NO3-, and NH4+ in PM2.5 were quantified. The average values(µg·m-3) of ρ(SO42-), ρ(NO3-), and ρ(NH4+) in autumn and winter were(5.2±2.5) and(7.9±4.8),(4.1±2.2) and(7.2±4.2), and(17.1±10.5) and(7.8±5.2), respectively. During the heavy haze pollution events in winter, the sum of ρ(SO42-), ρ(NO3-), and ρ(NH4+)(SNA) contributed 72.7% to the growth of PM2.5 mass concentration, and ρ(NO3-) accounted for 41.2%. This result suggested that the generation of NO3- was the key factor leading to the formation of winter haze pollution. In the polluted stage, high aerosol water content(AWC) promoted the rapid secondary generation of SNA, whereas adverse meteorological conditions also led to the accumulation of pollutants. The values of sulfur oxidation rate(SOR) and nitrogen oxidation rate(NOR) were still high in the dissipation stage. It indicated that the PM2.5 concentration fell due to the reduction in primary emissions and favorable weather conditions in dissipation, instead of the weakening of secondary generation of SNA. Compared to that in autumn, the higher AWC concentration, pH value, and lower temperature in winter were the main factors for the higher ρ(NO3-)/ρ(PM2.5) and NOR values in the Changsha-Zhuzhou-Xiangtan City Group. At the same time, the heterogeneous reaction was the main generation pathway of NO3-, when the AWC concentration was high in winter. Affected by aerosol pH value and generation rate, the liquid-phase oxidation reactions of H2O2 and SO2 were the main generation pathways of SO42- in autumn and winter in the Changsha-Zhuzhou-Xiangtan City Group. Compared to that in autumn, the higher AWC was more conducive to forming SO42-, which led to higher SOR in winter.

Nonlinear effects of socio-economic factors on urban haze in China: Evidence from spatial econometric smooth transition autoregressive regression approach.

In recent years, China has achieved numerous economic miracles but it has also been plagued by severe air pollution. The frequent hazy weather has severely restricted China's sustainable development. To investigate the nonlinear threshold effect of socio-economic factors on urban haze in China, this study constructs a spatial econometric Smooth Transition Autoregressive Regression (STAR) model based on the STIRPAT theory by using the remote sensing inversion PM2.5 data of 223 prefecture-level and above cities in China mainland during 2004-2016. In this study, the ARAR-STAR model is estimated by quasi-maximum likelihood estimation, and the accuracy of parameter estimation is verified by Monte Carlo simulation, which proves that the ARAR-STAR model constructed in this study is robust. It is concluded that: there is a complex spatial nonlinear relationship between socio-economic factors such as economic development level, population density, advanced industrial structure, energy consumption, opening-up, and haze pollution. The effect of socio-economic factors on haze emission reduction under the spatial influence has complex heterogeneity with the smooth transition between high and low regimes with economic development. The ARAR-STAR model constructed in this paper, which has both individual fixed effects and time fixed effects, expands the form of existing spatial panel nonlinear models and enriches and implements the application of spatial panel smooth transfer threshold models in the environmental field. Not only can it provide policy recommendations for China to achieve "coordinated efficiency in pollution reduction and carbon reduction" as soon as possible, but it also contributes to China's plan to address global climate change and promote global sustainable development.

Towards sustainable development: what carbon trading pilot policy has been done for mitigating carbon emissions and air pollution?

This study examines the impact of carbon trading pilot policy (CTPP) on carbon emissions (CO2) and air pollution (Ap) using the difference in differences method (DID) utilizing panel data from 30 Chinese areas spanning from 2008 to 2020. The results indicate that CTPP implementation can effectively decrease CO2 and Ap. CTPP can reduce CO2 and Ap through positive incentive effects that promote industrial structure upgrading and drive technological progress. Moreover, CTPP exhibits significant regional variation, with CTPP significantly reducing CO2 in both the eastern and central and western regions. CTPP do not show an effective reduction in Ap in eastern region, while effectively reduce Ap in central and western regions.

How does the opening of China's high-speed rail affect the spatial mismatch of haze pollution and economic growth?

A better reconciliation of haze pollution and economic growth has become the social consensus in China. The development of China's economy and air quality will be significantly impacted by its efforts to create high-speed rail (HSR). Based on panel data from 265 prefecture-level cities in China from 2003 to 2019, this paper investigates how the opening of HSR affects the spatial mismatch of haze pollution and economic growth by using the spatial mismatch index model, multi-period difference-in-differences (DID) model, and intermediary effect model. We find that the spatial mismatch in China has an overall decreasing trend. And its spatial agglomeration is dominated by low levels. Further empirical analysis shows that HSR opening can effectively restrain the spatial mismatch. Even after some robustness tests and endogenous treatment, the conclusion is still valid. In addition, population density, FDI, and industrial structure are also explicit factors affecting the spatial mismatch. Second, there is significant heterogeneity in the impact. This is reflected in the fact that HSR opening can suppress the spatial mismatch of service-oriented cities and the eastern region, while other cities and regions have no noticeable effect. Third, spatial transfer of haze pollution (STHP) and balanced development of economic growth (BEG) are two important conduction paths for the opening of HSR to affect the spatial mismatch. Specifically, HSR opening can constrain the spatial mismatch by inhibiting STHP and BEG. Based on the above findings, recommendations related to promoting a better harmony between haze pollution and economic growth are proposed.

Does the low-carbon city pilot contribute to the blue sky defense? Evidence from China.

China's goal of ecological civilization construction simultaneously faces the dual strategic tasks of pollution control and carbon reduction (PCCR). In addition to carbon reduction, does the low-carbon city pilot (LCCP) further contribute to the blue sky defense? This study investigates the impact of the LCCP on air pollution by employing a multiperiod difference-in-differences (DID) model based on data from 276 Chinese cities. The results show the following: (1) Compared with nonpilot areas, the LCCP reduces PM2.5 levels in pilot areas by approximately 1.50% on average, which is achieved by "industrial restructuring", "government investment in science and technology (S&T)", and "green lifestyle". (2) The LCCP has heterogeneous effects on air quality across cities with different resource endowments and industrial attributes, showing a greater air quality improvement in nonresource-based cities (NREB cities) and old industrial base cities (OIB cities) than in other city types. (3) The positive impact of the LCCP on air improvement in the pilot areas is derived from "pollution control effects" rather than "pollution transfer effects". This study provides useful policy implications for the comprehensive green transition and exploration of synergistic governance for PCCR in China.

Haze pollution and urbanization promotion in China: How to understand their spatial interaction?

Can promoting urbanization and controlling haze pollution result in a win-win situation? Based on panel data from 287 prefecture-level cities in China, this paper uses the three-stage least-squares estimator method(3SLS) and generalized space three-stage least-squares estimator method (GS3SLS) to study the spatial interaction between haze pollution and urbanization. The results show the following: (1) There is a spatial interaction between haze pollution and urbanization. On the whole, haze pollution and urbanization have a typical inverted U-shaped relationship. (2) Haze and urbanization show different relationships in different regions. The haze pollution in the area left of the Hu Line has a linear relationship with urbanization. (3) In addition to haze, urbanization also has a spatial spillover effect. When the haze pollution in the surrounding areas increases, the haze pollution in the area will also increase, but the level of urbanization will increase. When the level of urbanization in the surrounding areas increases, it will promote the level of urbanization in the local area and alleviate the haze pollution in the local area. (4) Tertiary industry, greening, FDI and precipitation can help alleviate haze pollution. FDI and the level of urbanization have a U-shaped relationship. In addition, industry, transportation, population density, economic level and market scale can promote regional urbanization.

Interaction mechanism and spatial effect of cross-regional haze pollution based on a multisectoral economy-energy-environment (3E) model and the evidence from China.

The transboundary characteristics and multisectoral factor interaction mechanism of haze pollution have aroused widespread attention but remain understudied. This article proposes a comprehensive conceptual model that clarifies regional haze pollution, further establishes a theoretical framework on a cross-regional, multisectoral economy-energy-environment (3E) system, and attempts to empirically investigate the spatial effect and interaction mechanism employing a spatial-econometrics model based on China's province-level regions. The results demonstrate that (1) regional haze pollution is a transboundary atmospheric state formed by the accumulation and agglomeration of various emission pollutants; moreover, there is a "snowball" effect and a spatial spillover effect. (2) The formation and evolution of haze pollution are driven by the multisectoral factors of 3E system interaction, and the findings still hold after theoretical and empirical analysis and robustness tests. (3) Significant spatial autocorrelation exists for the 3E factors, presenting different clustering modes with a dynamic spatiotemporal evolution, particularly in the high-high (H-H) mode and low-low (L-L) mode. (4) Significant heterogeneous impacts of economic and energy factors on haze pollution are identified, namely, an inverted "U-shaped" relationship and a positive linear association, respectively. Further spatial analysis demonstrates a strong spatial spillover and obvious path dependence among local and neighboring regions. Policymakers are advised to consider multisectoral 3E system interaction and cross-regional collaboration. Integr Environ Assess Manag 2023;19:1525-1543. © 2023 SETAC.

The effect of natural and socioeconomic factors on haze pollution from global and local perspectives in China.

Analyzing the factors that cause haze and the regional differences in the influence of factors on haze is the premise and critical to precise prevention and control of haze pollution. This paper explores the global effects of haze pollution drivers and the spatial heterogeneity of factors on haze pollution using global and local regression models. The results show that, from a global perspective, a 1 µg/m3 increase in the average PM2.5 concentration of a city's neighbors will increase the city's PM2.5 concentration by 0.965 µg/m3. Temperature, atmospheric pressure, population density, and green coverage of built-up areas are positively associated with haze, while GDP per capita is the opposite. From a local perspective, each factor has different influencing scales on haze pollution. Specifically, technical support is on a global scale, and for every 1 unit increase in technical support level, the PM2.5 concentration will decrease by 0.106-0.102 µg/m3. The influencing scales of other drivers are local. In southern China, the concentration of PM2.5 decreases by 0.001-0.075 µg/m3 for every 1 °C increase in temperature, while in northern China, the concentration of PM2.5 increases by 0.001-0.889 µg/m3. In the region around the Bohai Sea in eastern China, the concentration of PM2.5 will decrease by 0.001-0.889 µg/m3 for every 1 m/s increase in wind speed. Population density positively impacts haze pollution, and the impact intensity gradually increases from 0.097 to 1.140 from south to north. For every 1% increase in the proportion of the secondary industry in southwest China, the PM2.5 concentration will increase by 0.001-0.284 µg/m3. For cities in northeast China, for every 1% increase in the urbanization rate, the PM2.5 concentration will decrease by 0.001-0.203 µg/m3. These findings help policymakers develop targeted joint prevention and control policies for haze pollution, considering regional differences.

Research on the Heterogeneity Threshold Effect of Foreign Direct Investment and Corporate Social Responsibility on Haze Pollution.

Carrying out environmental protection and governance in the process of using foreign capital to develop the economy is a realistic problem that China needs to solve urgently. In order to reduce environmental pollution, all enterprises are called upon by the local government to fulfil CSR and improve the quality of FDI use. However, previous studies have rarely explored the threshold effect of FDI and CSR on haze pollution. This paper employs the threshold effect model to explore the above problem based on panel data of 30 provinces in China from 2009 to 2018. The empirical study found the following: (1) FDI has a significantly positive double-threshold effect on haze pollution. Meanwhile, the promotion effect of FDI on haze pollution is the strongest in the two threshold ranges. (2) CSR has a significantly negative single-threshold effect on haze pollution; that is, the increase in CSR intensity inhibits haze pollution. Such a negative effect shows the characteristics of increasing marginal efficiency. (3) In addition, the provinces in different thresholds display obvious geographical distribution characteristics. Through the above analysis, it can be observed that FDI and CSR have distinct impacts on haze pollution. Thus, the country and the government can reduce haze pollution by improving the investment structure, using environmentally friendly technology, guiding enterprises to abide by business ethics and promoting social responsibilities fulfilment.

Is the development of digital finance conducive to reducing haze pollution? Empirical evidence from 284 cities in China.

Using the panel data of 284 cities from 2011 to 2020 in China, this research statistically tests the direct impact and internal mechanism of digital finance on urban haze pollution. The results show the following: (1) the development of digital finance can significantly inhibit the concentration of urban haze, and there is a stronger inhibitory effect in areas where the government pays more emphasis to haze pollution and in cities with high levels; (2) after mechanism inspection, it is found that digital finance can indirectly promote urban haze pollution by influencing green innovation, cooperative innovation, industrial structure upgrading, and producer service agglomeration; (3) the results of the spatial econometric analysis show that digital finance can suppress the haze concentration in the region and simultaneously inhibit the neighboring areas through spillover effects; (4) further inspection shows that the spatial spillover effect of digital finance on haze pollution has an obvious spatial attenuation feature, demonstrating that a dense area of spatial spillover is within 310 km. The spillover effect gradually disappears when the threshold is exceeded.

How does haze pollution affect green technology innovation? A tale of the government economic and environmental target constraints.

Numerous studies have revealed that developing green technology innovation is extremely important for minimizing haze pollution. However, limited by serious endogenous problems, research rarely focuses on the effect of haze pollution on green technology innovation. Based on a two-stage sequential game model including both production and government departments, this paper mathematically deduced the effect of haze pollution on green technology innovation. Then China's central heating policy is considered a natural experiment in our study to verify whether haze pollution is the key factor affecting the development of green technology innovation. The result that haze pollution significantly inhibits green technology innovation is confirmed, and this negative impact is mainly concentrated on substantive green technology innovation. Robustness tests have been performed, and the conclusion is still valid. Moreover, we find that government behavior can significantly affect their relationship. Specifically, the government's economic growth target will increase the haze pollution's ability to block the development of green technology innovation. However, if the government has a clear environmental target, their negative relationship will weaken. Based on the findings, targeted policy insights are presented in this paper.