The impact of latent policy synergy between cities on air pollution: An empirical analysis from China's 12,764 air policies.

Policy synergy plays a crucial role in managing regional air pollution. However, the current process of formulating collaborative policies often focuses too heavily on achieving optimal emission reduction outcomes, while neglecting the execution costs at the local level. This not only leads to a lack of coordination between existing governance measures and new policies but may also result in inefficient policy implementation and the wastage of administrative resources. To address this issue, we have conducted a thorough analysis of the latent interconnections in local governance and explored the possibility of formulating collaborative policies based on latent policy synergies. Utilizing a dataset of 12,764 policy documents from China spanning from 2000 to 2023, we employed unsupervised learning techniques and panel regression models to investigate the impacts of latent policy synergies among local governments. Our findings reveal that local governments initially relied on rigid command-and-control strategies to address air pollution, which were later enhanced with economic incentives like emissions trading and subsidies, thus broadening the scope of policy tools and improving compliance flexibility. Subsequently, as comprehensive monitoring networks were established, enabling real-time data acquisition and more accurate pollution assessments, the focus of policy efforts shifted towards a more integrated approach to regional air pollution management. This similar evolution facilitated latent policy synergy among local governments, leading to significant reductions in air pollution emissions. Notably, regions such as the Central Plains and coastal cities, characterized by their dense industrial activity and high energy consumption, have shown remarkable potential for collaborative efforts, achieving greater pollution control efficiencies. This study provides a valuable reference for the coordinated governance of air pollution policies.

Green recovery or pollution rebound? Evidence from air pollution of China in the post-COVID-19 era.

Under the strict control measures, China has achieved phased victory in combating with the COVID-19, production activities have gradually returned to normal. This paper examined whether air pollution was rebounded or realized green recovery in the post-COVID-19 era with a dataset of weather normalized pollutant concentrations using difference-in-differences models. Results showed that air pollution experienced a significant decline due to the wide range of control measures. With entering the post-epidemic period, air pollution raised due to the orderly production resumption. Specifically, production resumption increased the PM2.5 concentrations of lockdown cities and non-lockdown cities by 43.2% (22.3 µg/m3) and 35.9% (17.3 µg/m3) compared with that in the period of COVID-19 breakout. Although the economic activities of China have been gradually recovered, PM2.5 concentrations were 8.8-11.2 µg/m3 lower than the level of pre-epidemic period. In addition, the environmental effects varied across cities. With the process of production resumption, the PM2.5 concentrations of cities with higher GDP, higher secondary industry output, more private cars and higher export volume rebounded less. Most developed cities realized green recovery by economy growth and air quality improvement, such as Beijing and Shanghai. While cities with heavy industry reflected pollution rebound with slow economy recovery, such as Shenyang and Harbin. Understanding the environmental effects of control measure and production resumption can provide crucial information for developing epidemic recovery policies and dealing with pollution issues for both China and other countries.

Do environmental taxes reduce air pollution? Evidence from fossil-fuel power plants in China.

Taking environmental protection into consideration, China introduced the new Environmental Protection Tax Law in 2018, which levies taxes for pollutants with higher standards. The vast majority of existing studies have investigated the impacts of environmental taxes (ETs) at the city level or province level. In contrast, we estimate their effects on pollutant reductions for fossil-fuel power plants in 30 provinces in China. Our results show that ETs have positive effects on pollutant emission reductions compared with the pollution discharge fee policy. We provide empirical evidence that sulfur dioxide (SO2), nitrogen oxide (NOx), and dust from fossil fuel power plants significantly decreased by 2.186 (7.7%), 1.550 (6.84%), and 1.064 (16.1%) tons, respectively, after the implementation of the policy. Moreover, there is an inverted U-shape relationship between pollutant emission reductions and tax rates. We offer further evidence that they play a limited role in high environmental regulation regions. Finally, we compare how different types of firms responded to ETs. The results show that ETs have limited effects on pollutant reductions for large state-owned coal power plants, which may have achieved environmental transformation to a certain extent. Therefore, policymakers could consider promoting tax rates in areas with low tax rates and strengthening tax breaks to stimulate firms to achieve pollutant reduction. In addition, local governments should set tax rates taking regional environmental regulation levels and firm heterogeneity into account.

Effects of the joint prevention and control of atmospheric pollution policy on air pollutants-A quantitative analysis of Chinese policy texts.

Joint prevention and control of atmospheric pollution (JPCAP) policies play a vital role in alleviating regional pollution. Based on Latent Dirichlet Allocation (LDA) model, we construct two policy strength measures of effectiveness and number, and investigate the effects of policy strength on air pollutant emissions for four types of JPCAP policies. The results show that the effects of economic incentive policy tools and supporting policy tools on emission reduction deviate significantly from policy preferences. Economic incentive policy tools are the most effective in promoting emission reductions in SO2, NOx and dust, but their effectiveness are the lowest in reality. Supporting policy tools, with the highest strength, have little effect on emission reduction. Command-control policies and persuasion policies are both relatively high in quantity and effectiveness. In addition, policy strength plays a more important role in reducing air pollutants in key regions than in non-key regions. JPCAP policies have gradually changed from a single policy tool to multiple policy tools, and the government shifted its attention to improving the legal effectiveness of policies after 2015. Finally, we propose some policy implications to optimize JPCAP policies and address regional air pollution problem.

Spatial spillover effects of environmental regulations on air pollution: Evidence from urban agglomerations in China.

Environmental regulations affects the environmental quality of not only local areas but also surrounding regions. It remains unknown whether the effect of environmental regulations on the surrounding regions is free riding or pollution shelter. Based on the data from 2006 to 2018, the spatial correlation of PM2.5 in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) urban agglomerations in China was examined in this study. In addition, the spatial spillover effects of environmental regulation on PM2.5 concentrations were explored while the socio-economic driving factors of the heterogeneity of pollution spillover were identified via SDM based STIRPAT framework. Results showed that the characteristics of PM2.5 concentrations spatial correlations varies from one urban agglomeration to another. This study revealed that the air pollution is affected by not only local environmental regulations, but also regulations implemented in surrounding cities. The PM2.5 concentration of BTH, YRD and PRD increased by 0.76, 0.147 and 0.109 for each unit increase in environmental regulation of surrounding cities, respectively. In fact, cities with loose regulation become the pollution shelters. The spatial spillover effects offset the improvement effects of local environmental regulations on the air quality. Furthermore, the comparison amongst three urban agglomerations showed that the spatial spillover effects of PM2.5 concentration in BTH and YRD are higher than that of PRD. This is attributed to differences in industrial structure, population density, economic development, FDI and geographical location. Therefore, the spatial spillover effects should be taken into consideration and joint regulation should be strengthened to address air pollution issues in urban aggregations.

Understanding the external pressure and behavior of commercial banks' environmental risk management: an empirical study undertaken in the Yangtze River delta of China.

The present study employed a quantitative survey to ascertain whether the external pressure of environmental risk management (ERM) on commercial banks was a contributing factor to their ERM behavior. Data was obtained using questionnaires from 204 branches of commercial banks located in the Yangtze River Delta of China. The relationship between external pressure and behavior was tested using a linear structural relations model through path analysis. The results revealed that external pressure of ERM was significantly and positively related to the behavior and that pressure from governmental regulations was the most important contributing factor in the passive feedback behavior and preventive behavior of commercial banks. The pressure from markets was the most important contributing factor in banks' active participation behavior; the pressure from community and NGOs was the most important contributing factor in their enthusiastic behavior.

[ECG signal preprocessing based on morphological filtering].

Electrocardiogram (ECG) signals are usually interfered by noises and base-line drift. A morphological filtering approach is put forward to remove the noise of the ECG signals and to calibrate the base-line drift in this paper. Different sizes of structuring elements were used to process the signals for different properties of ECG signal and noise. The morphological filtering approach is simple, fast and real-time in processing the signals, and it keeps the ECG signal shape unchanged while removing the noise. An experiment was carried out to simulate the morphological filtering approach with LabVIEW, and it was shown that this approach was effective in removing noise and in calibrating the base-line drift.