Climate change has emerged as one of the most important environmental issues worldwide. As the world’s biggest developing country, China is participating in combating climate change by promoting a low carbon economy within the context of global warming. This paper summarizes the pathways of China’s low carbon economy including the aspects of energy, industry, low carbon cities, circular economy and low carbon technology, afforestation and carbon sink, the carbon emission trading market and carbon emission reduction targets. There are many achievements in the implementation of low carbon policies. For example, carbon emission intensity has been reduced drastically along with the optimizing of energy and industry structure and a nationwide carbon trading market for electricity industry has been established. However, some problems remain, such as the weakness of public participation, the ineffectiveness of unified policies for certain regions and the absence of long-term planning for low carbon cities development. Therefore, we propose some policy recommendations for the future low carbon economy development in China. Firstly, comprehensive and long-term planning should be involved in all the low carbon economy pathways. Secondly, to coordinate the relationship between central and local governments and narrow the gap between poor and rich regions, different strategies of carbon emission performance assessment should be applied for different regions. Thirdly, enterprises should cooperate with scientific research institutions to explored low carbon technologies. Finally, relevant institutions should be regulated to realize comprehensive low carbon transition through reasonable and feasible low carbon pathways in China. These policy recommendations will provide new perspectives for China’s future low carbon economy development and guide practices for combating climate change.

Groundwater droughts can explain developments and changes in groundwater from a climatological perspective. The North China Plain (NCP) is a typical underground funnel area. Therefore, groundwater drought studies in the NCP can provide better understanding of the local hydrogeological characteristics from new perspectives. In this paper, the GRACE groundwater drought index (GGDI) was used to evaluate groundwater drought events in the NCP. Additionally, a new method was proposed in this study for investigating groundwater drought events at the spatiotemporal scale. On this basis, the centroid theory was used to construct an appropriate groundwater drought migration model for the NCP. The results showed that (1) the groundwater drought frequency in the NCP was 24.54%. In addition, the most severe groundwater drought events in the study occurred in March 2020. (2) In total, 49 groundwater drought events occurred in the NCP over the 2003–2020 period. The most intense groundwater drought event occurred over the June 2018–December 2020 period (DE.49), covering the entire study area. DE.29 was the second most intense groundwater drought event over the August 2012–September 2013 period (14 months), resulting in a maximum arid area of 75.57% of the entire study area. (3) The migration of the groundwater drought events was in the southwest–northeast and northeast–southwest directions, which was consistent with the terrain inclination, while most of the groundwater drought centroids were concentrated in Area II. The groundwater drought event identification method and the groundwater drought migration model were effective and reliable for assessing groundwater drought events in the NCP and provided a better understanding of developments and changes in groundwater droughts, which is of great practical significance and theoretical value for the rational development and use of groundwater resources, as well as for guiding industrial and agricultural activities.

Exploring and predicting the interaction between ecosystem services (ESs) and human well-being (HWB) is essential for understanding Human-Natural system coupling and sustainable development. Existing studies often use a cascading framework to delineate the transmission of ESs system to HWB system, but rarely reveal the interaction between the two systems. In this study, we treated ESs and HWB as two large systems and investigated the interactive coercing relationship in the Yellow River Basin (YRB) from both the system and subsystem levels. Initially, we estimated ecosystem services value (ESV) for each province in the YRB using the revised equivalent factor method, and evaluated the level of HWB by GRA-TOPSIS model. Subsequently, we analyzed the interactive coercing relationship between ESV and HWB utilizing the coupling coordination degree (CCD) model. Finally, we predicted the development trajectory of the coupled system in the next 20 years. From 2000 to 2020, ESV increased in Qinghai, Sichuan, Gansu, Ningxia, Shaanxi and Shandong, but decreased in Shanxi, Henan, and Inner Mongolia. HWB overall showed a positive upward trend. At the subsystem level, regulation service was the dominant function, and the health and safety well-being was lower than other well-being, but the mental fulfillment well-being improving most slowly. System-level CCD between ESV and HWB has been rising and will continue to do so. The relationship between support service and HWB in Shandong deteriorated, and the relationship between the ESV and HWB in Gansu exhibited a serious lag in ESV and will remain in an uncoordinated state for the next 20 years. Our approaches and results have guiding significance for promoting the coordinated development of HWB and ESs and substantiating the SDGs.

The popularization of smart phones and the large-scale application of location-based services (e.g., exercises, traveling and food delivery via cycling) have resulted in the emergence of massive amounts of personalized cycling trajectory data, spurring the demand for map navigation based on cycling trajectories. Therefore, in the current paper, we propose a cycling trajectory-based navigation algorithm without the need for road network data support. The proposed algorithm focuses on extracting navigation information from a given trajectory and then guiding others to the destination along the original trajectory. In particular, the algorithm analyzes the coordinate and azimuth angle data collected by the built-in positioning and direction sensors of mobile smart phones to identify several turning modes from the provider’s cycling trajectory. In addition, the interference of the traffic conditions during data collection is considered in order to improve the recognition accuracy of the turning modes. The turning modes in the trajectory are subsequently transformed into navigation information and shared with users, so as to realize the shared navigation of the cycling trajectory. Experimental results indicate that the algorithm can accurately extract the turning feature points from cycling trajectory data, recognize various turning modes and generate correct navigation messages, thereby guiding users to arrive at the destination safely and accurately along the original trajectory. The algorithm is independent of electronic map platforms and does not require road network data support.

In this study, a TEC variation window value was selected based on the wavelet power spectrum method to analyze the seismic–ionospheric coupling relationship. In the full-time domain, a 27-day periodicity of the wavelet power spectrum was obtained that passed the 95% significance test. The sliding interquartile range method was used to analyze earthquakes above Mw6.5 in Japan from 2011 to 2022, excluding the hybrid effects between earthquakes close to one another. The sunspot number (SSN), 10.7 cm radio flux (F10.7), total solar irradiance (TSI), solar wind velocity (Vsw), geomagnetic activity index in the equatorial region (DST), and global geomagnetic activity index (KP) were used as indices representing solar and geomagnetic activity. After removing solar and geomagnetic interference from ionospheric anomaly changes using the sliding interquartile range method, the TEC anomaly changes before the earthquake were verified as being caused by the earthquake and analyzed. The statistical analysis of ionospheric total electron content (TEC) anomalies showed that earthquake magnitude was positively correlated with the amplitude of TEC anomalies but not linearly. The occurrence time of ionospheric anomalies lagged behind to some extent with the increase in earthquake magnitude. Additionally, abnormal changes on the 29th day (15 February 2022) before the 20th earthquake did not conform to previous research rules. According to the lithosphere–atmosphere–ionospheric coupling (LAIC) mechanism and global ionospheric map (GIM) studies, the TEC anomaly was consistent with the vertical projection of the epicenter with obvious regularity. The results show that these TEC anomalies may be related to earthquakes.

Extreme precipitation is one of the most prevalent meteorological disasters occurring today. Its occurrence not only causes significant social and economic losses but also indirectly affects surface deformation, creating safety hazards for diverse ground features. Although there are presently high-precision, comprehensive tools such as continuous scattering interferometry to observe surface deformation, it takes a long time to locate potentially vulnerable objects. A monitoring scheme for surface deformation anomalies was devised to address the timeliness issue of identifying sensitive surface features under extreme rainfall conditions. An SAR image of Sentinel-1A is used to derive the surface deformation in three years before and after a rainstorm in the main urban area of Zhengzhou, and the anomaly surface deformation objects after extreme precipitation are screened to determine the surface deformation-sensitive objects. The results indicate that, in the past three years, a 22.14 km² area in Zhengzhou City has experienced a settlement speed greater than 10 mm/yr. Under the influence of the “7–20” rainstorm in the main urban area of Zhengzhou City, among them, the area of highly sensitive agricultural land for deformation is 2,581,215 m², and there are 955 highly sensitive houses for deformation, with an excellent recognition effect. This method is effective in rapidly locating surface deformation-sensitive or potentially damaged features; it can provide a reference for the vulnerability and risk assessment of buildings.