Is the sky of smart city bluer? Evidence from satellite monitoring data

Emission control status and future perspectives of diesel trucks in China

Chinese diesel trucks are the main contributors to NOx and particulate matter (PM) vehicle emissions. An increase in diesel trucks could aggravate air pollution and damage human health. The Chinese government has recently implemented a series of emission control technologies and measures for air quality improvement. This paper summarizes recent control technologies and measures for diesel truck emissions in China and introduces the comprehensive application of control technologies and measures in Beijing-Tianjin-Hebei and surrounding regions. Remote online monitoring technology has been adopted according to the China VI standard for heavy-duty diesel trucks, and control measures such as transportation structure adjustment and heavy pollution enterprise classification control continue to support the battle action plan for pollution control. Perspectives and suggestions are provided for promoting pollution control and supervision of diesel truck emissions: adhere to the concept of overall management and control, vigorously promote the application of systematic and technological means in emission monitoring, continuously facilitate cargo transportation structure adjustment and promote new energy freight vehicles. This paper aims to accelerate the implementation of control technologies and measures throughout China. China is endeavouring to control diesel truck exhaust pollution. China is willing to cooperate with the world to protect the global ecological environment.

China's endeavor to reduce energy intensity: Does the green financial reform and innovation pilot zones policy matter?

The implementation of green financial reform and innovation pilot zones is a pivotal initiative aimed at directing financial resources more effectively towards green transformation and national sustainable development strategy. To this end, this study adopts a dual machine learning model to examine the effect of this pilot policy on energy intensity and the underlying mechanisms, drawing upon data from 254 cities in China spanning from 2006 to 2019. The conclusions obtained confirm that the establishment of these pilot zones has exerted a substantial impact on mitigating energy intensity. This inhibitory effect is particularly evident in cities with lower administrative levels, cities in western regions, smaller and medium-sized cities, and cities dominated by the secondary industry. It should be emphasized that the reduction in energy intensity is achieved through fostering green technology innovation and enhancing green financial development. The results not only provide empirical evidence for the effectiveness of green finance pilot policies in reducing energy intensity, thereby enriching the inclusive impact of financial innovation, but also offer practical insights for strengthening the green financial system and replicating and expanding the pilot zones.

A significance of smart city pilot policies in China for enhancing carbon emission efficiency in construction

The Chinese government seeks to promote economic growth and sustainable development while achieving carbon neutrality by establishing phased smart city pilots. Therefore, it is important to study whether smart city pilots can promote carbon emission efficiency (CEE). This paper constructs a multi-period difference-in-difference (DID) model based on panel data from 241 prefecture-level cities in China from 2007 to 2019, aiming to investigate the mechanism of the impact of smart city pilot policies (SCPP) on CEE and whether there is a rebound effect. The study found that smart city construction (SCC) significantly improves carbon efficiency, with pilot cities increasing their CEE by 1.4% compared to non-pilot cities. The conclusions remain robust under a variety of scenarios including the introduction of placebo tests, counterfactual tests, sample data screening, and omitted variable tests. The results of the mechanism test show that although the rebound effect can inhibit the improvement of CEE, the environment can be improved and the CEE can be enhanced through green technology innovation, industrial structure upgrading, energy structure optimization, environmental regulation effect, information technology support, and resource allocation effect. The heterogeneity results indicate that the SCPP is more effective in promoting CEE in cities in the eastern region, southern cities, environmentally friendly cities, large cities, and medium-sized cities. This study contributes to the existing literature in clarifying the environmental benefits of SCPP and provides valuable policy insights for cities to address climate change and sustainable development.

The impact of smart city construction (SCC) on pollution emissions (PE): evidence from China

Based on panel data from 210 prefecture-level cities in China from 2003 to 2021, this study employs the Time-Varying Differences-in-Differences (Time-Varying DID) approach to systematically examine the impact of smart city construction on pollution emissions and its underlying mechanisms. Additionally, the Propensity Score Matching-Differences-in-Differences method is employed for further validation. The research findings indicate that Smart City Construction (SCC) significantly reduces urban Volume of Sewage Discharge (VSD), sulfur dioxide emissions (SO2), and Emissions of Fumes and Dust (EFD), thereby mitigating pollution emissions (PE) and enhancing environmental quality. Mechanism analysis reveals that SCC achieves these effects through scale effects, structural effects, and technological effects. City heterogeneity analysis shows that provincial capital cities exhibit a stronger suppression effect on pollution emissions compared to non-provincial capital cities. Moreover, cities with lower levels of education attainment demonstrate a stronger ability to curb pollution emissions, while larger cities exhibit a more pronounced impact on mitigating pollution emissions. The marginal contributions of this study mainly consist of three aspects: Firstly, it enriches the literature on environmental impact factors by assessing, for the first time, the influence of SCC on PE. Secondly, a comprehensive approach is employed, integrating VSD, EFD, SO2 data, and economic and pollution data at the city level. Time-Varying DID is used to evaluate the policy effects of SCC. Finally, the study analyzes the impact mechanisms of SCC policy on environmental emissions from various perspectives.

Analysis on the impact of smart city construction on urban greenness in China's megacities

Urban greenness serves as a key indicator of sustainable urban development, with smart city construction emerging as a primary strategy for its enhancement. However, there is little empirical evidence considering multi-dimension between urban greenness and smart city construction on the city level. This study focuses on the impact on urban greenness of smart city construction in megacities, using the difference-in-differences regression model to evaluate the impact based on urban development conditions in various aspects from 2010 to 2021 in 10 megacities in China. The results of panel data of different indicator samples show unique conclusions. First, smart city pilot policy in megacities has significant impact on urban greenness, primarily due to demographic and economic developments. Second, the impact is different between the megacity and national level, and different factors of urban greenness have different effects on smart city construction. Third, the effects are time-lagged and lasted for years, and regional heterogeneity divided by building climate zones is existed, where the effect is more obvious in city agglomeration. These findings of smart city construction reveal the unique influences on megacity greenness, and can be generalized to cities with similar characteristics accordingly.

A study on identifying synergistic prevention and control regions for PM2.5 and O3 and exploring their spatiotemporal dynamic in China

Air pollutants, notably ozone (O3) and fine particulate matter (PM2.5) give rise to evident adverse impacts on public health and the ecotope, prompting extensive global apprehension. Though PM2.5 has been effectively mitigated in China, O3 has been emerging as a primary pollutant, especially in summer. Currently, alleviating PM2.5 and O3 synergistically faces huge challenges. The synergistic prevention and control (SPC) regions of PM2.5 and O3 and their spatiotemporal patterns were still unclear. To address the above issues, this study utilized ground monitoring station data, meteorological data, and auxiliary data to predict the China High-Resolution O3 Dataset (CHROD) via a two-stage model. Furthermore, SPC regions were identified based on a spatial overlay analysis using a Geographic Information System (GIS). The standard deviation ellipse was employed to investigate the spatiotemporal dynamic characteristics of SPC regions. Some outcomes were obtained. The two-stage model significantly improved the accuracy of O3 concentration prediction with acceptable R2 (0.86), and our CHROD presented higher spatiotemporal resolution compared with existing products. SPC regions exhibited significant spatiotemporal variations during the Blue Sky Protection Campaign (BSPC) in China. SPC regions were dominant in spring and autumn, and O3-controlled and PM2.5-dominated zones were detected in summer and winter, respectively. SPC regions were primarily located in the northwest, north, east, and central regions of China, specifically in the Beijing-Tianjin-Hebei urban agglomeration (BTH), Shanxi, Shaanxi, Shandong, Henan, Jiangsu, Xinjiang, and Anhui provinces. The gravity center of SPC regions was distributed in the BTH in winter, and in Xinjiang during spring, summer, and autumn. This study can supply scientific references for the collaborative management of PM2.5 and O3.

The cost of (Un)regulation: Shrinking Earth's orbits and the need for sustainable space governance

Outer space is infinite, useable planetary orbits are not. This makes the Earth's orbit a unique case of an Area Beyond National Jurisdiction (ABNJ) complex to address, difficult to use in a sustainable and equitable way and almost intractable to regulate at an international level. As of 2023, we remain far from attaining a sustainable orbital environment, and future uses of the Earth's orbits for new satellites constellations appear now increasingly at risk. Adopting a probability-based empirical model to project the growth trajectory of objects in space, this article argues that the sector will cross a 'critical density' threshold within the upcoming years unless strong remedial actions to clear up the orbits are implemented and estimates the potential costs of active debris removal measures. Our findings suggest that orbital sustainability is unlikely to come from technology alone, no matter how advanced or ground-breaking. A long-term solution will necessarily require a radical rewriting of the outdated, often conflicting international regulatory framework, which contributed to creating this debris crisis in the first place, shrinking the Earth's orbit to (almost) the point of no return.

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.

The effectiveness of smart city policy on pollution reduction in China: new evidence from a quasi-natural experiment

Based on panel data of 285 prefecture-level and above cities in China from 2003 to 2020, this study has explored the impacts of smart city policy (SCP) on environmental pollution by utilizing the difference-in-differences (DID) model and its derived models. The results indicate that SCP can significantly reduce environmental pollution, and this conclusion still holds after passing numerous robustness tests, such as the propensity-score-matching difference-in-differences (PSM-DID) test, the placebo test, all independent variables lagging one period test, the policy interference test, and the instrument variable (IV) test. Moreover, the heterogeneity analysis shows that the effect of reducing environmental pollution of SCP is heterogeneous. Furthermore, the results of the spatial difference-in-differences (SDID) model show that SCP has a "beggar-thy-neighbor" effect among the pilot cities, and there is no spillover effect of SCP on pollution reduction in neighboring non-pilot cities. Finally, the analysis of moderating effect reflects that the government intervention plays a negative inhibition role in the process of SCP affecting environmental pollution, while the market competition plays a positive catalytic role in the process of SCP reducing environmental pollution.

Spatial Effect of Digital Economy on Particulate Matter 2.5 in the Process of Smart Cities: Evidence from Prefecture-Level Cities in China

During the COVID-19 pandemic, the digital economy has developed rapidly. The airborne nature of COVID-19 viruses has attracted worldwide attention. Therefore, it is of great significance to analyze the impact of the digital economy on particulate matter 2.5 (PM2.5) emissions. The research sample of this paper include 283 prefecture-level cities in China from 2011 to 2019 in China. Spatial Durbin model was adopted to explore the spatial spillover effect of digital economy on PM2.5 emissions. In addition, considering the impact of smart city pilot (SCP) policy, a spatial difference-in-differences (SDID) model was used to analyze policy effects. The estimation results indicated that (1) the development of the digital economy significantly reduces PM2.5 emissions. (2) The spatial spillover effect of the digital economy significantly reduces PM2.5 emissions in neighboring cities. (3) Smart city construction increases PM2.5 emissions in neighboring cities. (4) The reduction effect of the digital economy on PM2.5 is more pronounced in the sample of eastern cities and urban agglomerations.

The impact of industrial robots application on air pollution in China: Mechanisms of energy use efficiency and green technological innovation

The battle against air pollution in China persists, and haze remains over cities. Whether industrial robots, as the core technology of intelligent manufacturing, can improve city air quality in the process of production has not been determined. Using the International Federation of Robotics data and Chinese city air pollution data (2013-2018), this study finds that industrial robots significantly reduce city air pollution levels (PM2.5, PM10, and SO2), which remains robust after addressing endogeneity. The mechanism of action lies in the synergistic benefits of industrial robots in reducing city air pollution levels by effectively improving energy use efficiency and promoting green technological innovation. Heterogeneity analysis suggests that industrial robots, as the incarnation of green technology, can be an effective alternative tool to green policies, such as low-carbon piloting, resource planning, and environmental regulation. This study empirically confirms that industrial robots are environment-friendly technologies that can provide new policy ideas to promote air pollution prevention and control in the industrialization process.