Quantitative assessments of progress towards Sustainable Development Goals (SDGs) and the complex interactions of indicators are critical for monitoring the achievement of SDGs and guiding policymaking and implementation. Based on Big Earth Data and the SDGs global indicator framework, an index system for evaluating progress towards SDGs in frontier, multi-ethnic underdeveloped areas was developed from the perspective of social, economic, and environmental dimensions and included 70 indicators. The study area was the National Innovation Demonstration Zone (Lincang) for the 2030 Agenda for Sustainable Development. The model incorporated regional characteristics and data acquisitioned from Lincang in 2015-2020 through field research. Consequently, we calculated the social, economic, and environmental sub-indices and integrated index of sustainable development of Lincang City from 2015 to 2020, evaluated the progress trend of SDGs and indicators, and proposed key challenges and solutions for the sustainable development of Lincang City. Research shows that the integrated index and the social, economic, and environmental sub-indices of sustainable development have shown an increasing trend from 2015 to 2020. In terms of the SDGs, progress was achieved with respect to all 16 SDGs. The average annual growth rate of SDG 5 was the highest, whereas that of SDG 13 remained unchanged. In addition, 81% of indicators showed acceptable progress. This study provides a reference for sustainable development planning in other typical demonstration areas and underdeveloped mountainous areas in China and worldwide.

The matching of water and land resources often directly affects food production in various regions and is the basis for high-quality economic and social development and modernization of agricultural production. Using nine provinces along the Yellow River as examples, based on the cross-coupling of four elements, such as the natural background of water resources and water resources for total water consumption control, this study constructed a ternary synergistic model of water-cultivated land-grain by cross-coupling. The matching coefficients of water and soil resources from 2010 to 2020 under each scenario were calculated, and the temporal and spatial evolution characteristics of water and soil resources matching along the “province-city” scale of the nine provinces along the Yellow River and the contribution degree of each element were analyzed. The results showed that: \mathrm{①} The matching degree of binary water and soil resources based on the natural background of water resources in the nine provinces was improved as a whole, and the matching pattern of water and soil resources was relatively stable; however, the regional differences are notable and manifested as “high in the west and low in the east.” \mathrm{②} Along the three-way coordinated matching pattern of water-arable land and grain in the nine provinces, from the perspective of the total amount of cultivated land and the amount of irrigated arable land in the natural background of water resources, roughly three distribution patterns were presented: the western and northeastern regions were severely water-deficient areas, the northern and north-central regions typically had varying degrees of water shortage, and the central and eastern regions exhibited a diversified distribution pattern; from the perspective of total water consumption control, a remarkable difference is observed between the total amount of cultivated land and the three-way cooperative matching pattern of irrigated cultivated ground. \mathrm{③} Under the four scenarios, the average contribution rate of water resources were >50%, and the sum of the effective utilization coefficient of irrigation water and the contribution rate of the irrigation quota were >30%, indicating that increasing the effective utilization coefficient and setting a reasonable irrigation quota had a decisive impact on the change in water and soil resource matching. These results improve our understanding of the relationship between water resources and exploitation, cultivated land production capacity, and reclamation, as well as the interdependence and constraints of the grain planting structure.

Severe convective weather systems often cause rainstorms, lightning, gales, hail, and other disasters owing to their small spatial scale and rapid and violent development. Accurate forecasting has always been a difficult and bottleneck problem in the international meteorological field, and it is the focus of disaster prevention and mitigation in Shanghai. This research introduces key technologies developed by the Shanghai Meteorological Department in recent years, such as self-adaptive networking observation of strong convection targets, intelligent identification and prediction of strong convection abrupt structural features, machine learning correction of numerical prediction errors, and system integration. Based on this, an intelligent monitoring and early warning system that can simulate the three-dimensional structure and evolution of a strong convective system is established and applied, which has significantly improved the early warning capability fo severe convection in Shanghai. Relevant technical achievements have provided support for major services such as the China International Import Expo (CIIE) and have been promoted for application in urban disaster prevention and mitigation.

The aim of this study is to scientifically implement water diversion projects and effectively provide water security for high-quality development and environmental protection. The research progress of water diversion projects is reviewed in terms of industry standards, specifications, and related studies. It was found that water demand prediction tends to be overly high, the integrity of comprehensive benefit evaluation needs to be improved, the standard of ecological compensation mechanism remains incomplete, and post-evaluation and tracking work is insufficient. To support the spatial equilibrium of water resource allocation and the construction of national water networks, future water diversion projects need to strengthen environmental protection and whole-stage follow-up evaluation, perform full cost pricing, perfect the investment and financing system, and improve information and intelligent management.

The upper Yellow River is the most important water conservation area as well as the runoff and confluence area in the Yellow River Basin, and accounts for more than half of the runoff of the entire basin. Therefore, it is of great significance to the ecological protection, water resource security, and food security of the entire Yellow River Basin. Scientifically understanding the change characteristics of natural environmental factors and deeply exploring the coordination problem of natural environmental factors can promote ecological protection and high-quality development of the Yellow River Basin. Based on the macro understanding of the six important characteristics of natural environmental elements, such as climate, hydrology, and ecology, in the upper Yellow River under the background of global warming and the implementation of national ecological protection projects and water resource management policies, this study describes the natural disharmony among hydrology, soil, climate, and ecology in the upper Yellow River. Moreover, from the perspective of the coordination of natural environmental elements, this study puts forward five scientific ideas on how to eliminate the traditional thinking and misunderstanding of ecology and development problems in the upper Yellow River, as well as six scientific suggestions on how to build an ecological protection and high-quality development model with regional characteristics. This study has important guiding significance for the promotion of ecological protection and high-quality development of the upper Yellow River.

Heavy metal migration and enrichment in areas affected by mining and smelting cause severe soil contamination. A thorough understanding of the sources and migration of heavy metals in the soil is the scientific basis for the efficient treatment of soil pollution. In recent years, metal stable isotopes have shown great advantages in identifying sources of soil heavy metal contamination and analyzing heavy metal migration processes, thus acting as powerful tools to trace the environmental behavior of heavy metals. In this paper, we reviewed the analysis technology, tracing principles, and tracing models of metal stable isotopes, determined the isotope fractionations caused by mineral mining and smelting processes (high-temperature smelting, electrochemical processes, and tailing weathering), and discussed the representative applications of metal stable isotopes in the traceability of soil pollution in mining- and smelting-affected areas. The V isotope system is in the initial stages of investigation, and its applications in heavy metal soil source analysis are relatively lacking. Zn, Cd, and Hg isotopes are advantageous for identifying heavy metal contamination sources associated with high-temperature smelting processes. Cu, Tl, and Ni isotopes can directly indicate the ore content of the soil. However, some problems remain, such as the difficulty in analyzing certain systems of metallic stable isotopes, limitations in the application of tracer models, and source uncertainties due to isotope fractionation. Therefore, in the future, it will be necessary to further explore and optimize metal isotope analysis methods, establish more metal stable isotope fingerprints, develop traceability models with stronger applicability and more accurate results, comprehend the characteristics and mechanisms of isotope fractionation in complex interfacial processes and reactions, and strengthen the practical application of metal stable isotopes to trace the history of soil heavy metal pollution.

The inconsistency between the supply and demand of lithium carbonate is becoming increasingly serious. Scientific prediction of the future lithium carbonate demand is of great significance for China’s lithium resource production, import and export arrangements, and national energy policy formulation. Based on a combined model of grey correlation analysis and the ARIMA-GM-BP neural network, data on the driving variables of China’s per capita GDP, industrial structure, urbanization level, grease production, ceramic production, glass production, air conditioning production, lithium-ion battery production, and new energy vehicle production in 2002-2021 were selected to predict China’s lithium carbonate resource demand between 2025 and 2035. The results show that the selected driving variables are highly correlated with China's lithium carbonate resource demand, and the combined model is more accurate than a single model. The predicted average quantity demand for lithium carbonate in 2025, 2030, and 2035 is 0.42 million tons, 0.69 million tons, and 1.03 million tons, respectively. Accordingly, some policy suggestions have been proposed.

Lakes play an essential role in the evolution of regional water cycles and ecosystems. In previous studies on lake evolution, most lake sediment proxy indicators have been used to reconstruct lake and climate change processes. However, there is a lack of quantitative research on the lake water cycle characteristics. Based on the water balance model for watersheds and lakes in distinct periods and the lake energy balance model based on the simulation of the transient climate, water balance calculations and lake evolution simulations for six typical lakes in the Qinghai-Tibet Plateau and its surrounding areas were carried out in this study. The results showed that the precipitation and evaporation variabilities in Xiao Qaidam Lake and Lop Nur were relatively small during the Holocene. The precipitation and evaporation variabilities in Selinco and Namco were relatively large during the early-middle Holocene, mainly controlled by temperature and net radiation changes. The precipitation and evaporation variabilities in Qinghai Lake and Zhuyeze were close during the early and mid-late Holocene. This study systematically analyzed and calculated the evolution of lake water cycle elements in different climatic regions of the Qinghai-Tibet Plateau during the Holocene, which will help to understand the paleoclimatic mechanism of lake evolution in this region.

Data-driven methods with deep learning as their core have been gradually applied in Earth science; however, challenges remain regarding the interpretability of models and physical consistency. With the background of remote sensing big data, combining deep learning and data assimilation methods to develop new techniques for the simulation and prediction of terrestrial water cycle processes has become an important research direction in Earth science. Τhe progress in deep learning in recent years combines improving the quality of observation data of terrestrial water cycle components and reducing the uncertainty of physical models. Furthermore, the key scientific issues regarding data assimilation in terrestrial hydrology based on deep learning fusing remote sensing big data are classified according to the observations, physical models, and system integration: \mathrm{①} How can the temporal and spatial representativeness of samples be enhanced when deep learning inverts remote sensing products? \mathrm{②} How can a new physics-guided deep learning method be developed within the framework of data assimilation? \mathrm{③} How can the predictability of the terrestrial water cycle be improved through the “data-model” dual drive? Relevant research and exploration should help promote the in-depth application of the “data-model” hybrid modeling method in the field of hydrology and improve the simulation and prediction capacity of the terrestrial water cycle process.

From 2015 to 2017, the Western Cape province in South Africa suffered a severe drought, resulting in an extreme shortage of water resources in the city, making its capital, Cape Town, the first modern city in human history to face the threat of a “Day Zero” disaster (i.e., the day when the city’s water taps are turned off). However, the interaction mechanisms and processes of various disaster-causing factors remain unclear, and how to scientifically cope with the natural precipitation variation mode by man-made water-supply management needs to be further explored. Therefore, this paper explores the key stages, spatial distribution, and management benefits from the three dimensions of meteorological drought, hydrological drought, and urban water supply management. The results show the following: \mathrm{①} The Western Cape experienced a significant increase in the area and intensity of meteorological drought from 2015 to 2017, with the most severe drought conditions occurring in May 2017. Compared with the Standardized Precipitation Index (SPI), the drought detected by Standardized Precipitation Evapotranspiration Index (SPEI) was more significant. \mathrm{②} The hydrological drought conditions in the Western Cape in May 2017 were the most severe. This is broadly consistent with the pattern of spatial and temporal characteristics of meteorological drought, reflecting the rapid spread of meteorological-hydrological drought. Both the Standardized Runoff Index (SRI) results and the change in reservoir water volume reflect water scarcity in the region, indicating that the drought event had a serious impact on the Western Cape, which relies heavily on rainfall and reservoir water supply. \mathrm{③} The Western Cape government adopted different levels of water restrictions and management policies in response to the evolution of this drought, effectively delaying and avoiding a “Day Zero” disaster; however, addressing the political and economic aspects of water inequality is still debatable and worth improving. This paper shows that urban drought problems involve multiple systems and interactions among the meteorology, hydrology, and water supply, and need to be monitored, understood, and mitigated in terms of the spatial and temporal processes.

The Northwest region of China is a major battlefield and an important ecological and environmental security barrier to China’s western development. Flourishing the Belt and Road Initiative, climate change in this region has a direct impact on water resources, ecology, and environmental security. In the context of global climate change, Northwest China has shown an obvious and rapidly developing warming-wetting trend, which has resulted in increasingly prominent environmental and public security risks that are seriously affecting the sustainable development of the regional economy and society. This poses new challenges for climate change responses, water resource management, and disaster prevention and mitigation in this region. Research on the evolution characteristics, causes, and physical mechanisms of warming-wetting as well as its future trends and possible risks were reviewed. It further summarizes the current scientific consensus and existing problems, and finally looks forward to the key directions of future scientific research. A systematic review of the trend, causes, and future projection of climate warming-wetting in Northwest China will have important scientific implications for further research on this issue.

Climate extremes threaten human health, economic stability, and the safety of both natural and built environments. Compound extreme events are combinations of multiple climate drivers and/or hazards that contribute to societal or environmental risks, and their impacts on human society and natural ecosystems are often more serious and destructive than those of a single extreme event. Understanding the changes in compound extreme events is important for adaptation, mitigation strategies, and disaster risk management. Here, the definitions and connotations of compound extreme events are briefly discussed, including preconditioned, multivariate, temporal, and spatial compounding events. Subsequently, the progress in compound extreme event research is discussed in terms of temporal and spatial evolution characteristics, influencing factors, and future scenario projections. Given the problems in current research, we suggest that future studies should focus on studying compound extreme events regarding variable/index selection and threshold determination, dependence and interaction analysis among drivers and/or hazards, simulation performance evaluation and future projections, and their dynamic processes and disaster-causing mechanisms. Compound extreme events are expected to increase in frequency and intensity in a warming world, and many regions are projected to experience an increase in the probability of compound events with greater global warming. Therefore, we must improve our understanding of the causes and drivers of compound and cascade events.

The Diurnal Cycle of Precipitation (DCP) is the result of various dynamic and thermodynamic processes in the climate system and is closely related to the water cycle and land-atmosphere interactions. In North China, the DCP is influenced by factors such as valley wind circulation, boundary layer inertial oscillations, and sea-land breeze circulation, exhibiting two peaks during the early morning and afternoon. In addition, the DCP in North China is influenced by anthropogenic aerosol emissions. This study introduces the fundamental characteristics and factors influencing the DCP in North China and summarizes recent research on the connection between the DCP and land-atmosphere coupling in North China, the modeling of the DCP, and the influence of aerosols on the DCP. The existing scientific knowledge is synthesized, and its shortcomings and challenges are outlined. Overall, investigating the DCP and its influencing factors can help us better understand the mechanisms of precipitation formation and evolution. This provides scientific support for enhancing the accuracy of fine-scale precipitation forecasting.

The Anthropocene Working Group (AWG) of the International Commission on Stratigraphy voted that the Anthropocene should be defined by a Global boundary Stratotype Section and Point (GSSP or ‘golden spike’) as a formal chronostratigraphic unit. Increasing evidence has shown that human activities have drastically intensified since the mid-twentieth century, altering the original rate and direction of Earth’s evolution, triggering a profound impact on Earth’s environment, and leaving their imprint on geological records through physical, chemical, and biological markers. Consequently, the 1950s was assumed to be the ideal onset of the Anthropocene. Currently, 12 candidate sites for the GSSP of the Anthropocene have been proposed for consideration by the AWG. Chinese researchers have made outstanding progress in recent years regarding the establishment of a system of proxies for human activities and the global comparison of the candidate sites for the GSSP of the Anthropocene. These proxies, including anthropogenic radioactive isotopes, microplastics, δ¹³C, δ¹⁵N, and diatoms, have great potential as markers of human activities. These proxies recorded in the sediments of Sihailongwan Maar Lake, which is far away from cities and less affected by human activities, indicate that this site is sensitive to global change. The concentrations of ^{239, 240}Pu have drastically increased since 1953 CE in the sediment profile collected from Sihailongwan Maar Lake. as Additionally, other proxies such as PAHs, ¹²⁹I, soot ¹⁴C, SCP (spheroidal carbonaceous particles), DNA, δ¹³C, and Pb exhibit synchronous changes near 1953 CE, indicating the onset of Anthropocene. Two sediment stratotype profiles collected from Sihailongwan Maar Lake and Beppu Bay, Japan, were selected by the AWG as auxiliary sections for the GSSP of the Anthropocene. The ultimate goal of Anthropocene science should be to deepen the theory and technological innovation of sustainable development of the Earth-humans system and adaptation based on clarifying the impact of human activities on the Earth system.

N₂O is an important greenhouse gas that also damages the ozone layer. N₂O emissions have been observed during microalgae cultivation and in microalgae-based ecosystems, such as eutrophic lakes. However, little has been reported on the important role of the N₂O balance in algae and the potential algal N₂O production pathways. A review of recent relevant studies on N₂O synthesis and fixation by algae shows that the studies mainly focus on the relationship between algae and N₂O emissions, several possible pathways of N₂O production and consumption in algae, the influence of the algal microenvironment on the distribution pattern of N₂O, and the potential impacts on global climate change. However, the Intergovernmental Panel on Climate Change currently does not consider the possible N₂O emissions during algal blooms or algal aquaculture; hence, it is necessary to intensify experimental studies related to algal N₂O production globally to take important steps towards a comprehensive clarification of the important roles of algae in N₂O emission and fixation and a comprehensive assessment of greenhouse gas emissions from aquatic ecosystems.

Global warming caused by human activities has resulted in significant changes in the climate system, including changes in the regional climate, extreme events, snow, ice, vegetation, air quality, water cycle, and responses and feedbacks among various components of the climate system. The land surface is where water, energy, and geochemical transports to and from the atmosphere occur, hydrological processes occur, and vegetation grows. Hence, the land surface is sensitive to climate change. Climate change affects the hydrological processes not only directly but also indirectly by affecting the vegetation structure and physiology. Land surface models are useful for studying climate change and its impacts on the land surface by modeling the relevant responses and feedbacks. There are three types of land surface models that simulate the mass and energy exchange between the land surface and atmosphere: the global land surface process model, global hydrological model, and global dynamic vegetation model. These three types of models focus on different specific components of the land surface. Since the 1990s, various land surface comparison projects have revealed many problems and shortcomings in land surface models and have furthered their development. However, various issues with these models still need to be addressed. For example, one major problem with the global hydrological model is that it does not incorporate dynamic vegetation growth; hence, it cannot project long-term vegetation change impacts on the hydrological processes—let alone extreme hydrological events such as flooding and drought—and cannot be useful with respect to future water resource management. Incorporating dynamic vegetation growth into hydrological models is a frontline research topic in hydrology. Moreover, many land surface models represent soil textures and heat exchanges among soil liquids, solids, and gases on the Tibetan Plateau insufficiently. This aspect requires improvement by enhancing the observations, understanding the relevant mechanisms, and realizing the mechanisms and processes in the land surface models. The Tibetan Plateau provides fresh water to the surrounding regions and forms and modulates climate and weather both regionally and globally; thus, it is dubbed the Asian Water Tower. Improving the land surface model capability of the plateau will improve the understanding of climate change and its impacts, both regionally and globally.

Ozone is among the most important trace gases in Earth’s atmosphere and plays a crucial role in both climate change and ecology. Tropospheric ozone is an important component of photochemical smog, and its variations are closely related to human activity. Monitoring of tropospheric ozone based on satellite remote sensing can help us better understand and quantitatively explain the characteristics of tropospheric ozone changes in different seasons, times, and regions, and explore the mechanism of ozone generation in the troposphere. With the comprehensive development of satellite remote sensing techniques, ozone remote sensing products (e.g., total ozone, profiles, etc.) have improved significantly in terms of accuracy and spatiotemporal resolution. However, the accuracy of tropospheric ozone products is still not sufficient for the current scientific application of the atmospheric composition of the troposphere due to the weak satellite signals and complexity of the subsurface. This review focuses on satellite remote sensing of tropospheric ozone. It outlines and analyzes the development history and current status of ozone satellite remote sensing payloads and discusses the characteristics and applicability of remote sensing retrieval algorithms based on different technologies (direct and indirect retrieval, multiband joint retrieval, collaborated nadir-limb retrieval, and innovative algorithms based on machine learning techniques). It further discusses the application of satellite remote sensing for the provision of reliable tropospheric ozone observation data at the global and regional scales. Overall, this review envisions the application of satellite remote sensing for providing reliable tropospheric ozone observations at the global and regional scales.

As computing power continues to improve, the horizontal grid resolution of numerical weather prediction models has reached the kilometer-to-sub-kilometer scale. This grid scale is comparable to the characteristic turbulent scales in the convective boundary layer, allowing the numerical models to resolve the organized convective structures. The assumptions of traditional one-dimensional boundary layer parameterization schemes (suitable for horizontal resolutions of several kilometers or coarser) and large eddy simulation three-dimensional turbulent closure schemes (suitable for horizontal resolutions below several tens of meters) do not hold at this scale, which is referred to as the gray zone. This study discusses the applicability and limitations of traditional parameterization methods and introduces the gray zone of the convective boundary layer from three perspectives: theory, methodological approaches, and impact. It summarizes the characteristics of the simulation methods at the CBL gray zone scale developed over the past two decades and explores the impact of the boundary layer process simulation at this scale on other physical processes (e.g., shallow/deep convection) in numerical models. Further, we anticipate future research directions and approaches.

Sea-Level Rise (SLR) directly changes the hydrology and salinity of estuarine tidal wetlands and is one of the primary drivers of global change that significantly impacts ecosystem processes. Herein, various methodologies and experimental facilities (marsh organs, weirs, and flow-through mesocosms) for manipulating SLR are systematically reviewed. This study provides a comprehensive summary of the effects and mechanisms associated with SLR regarding the fluxes and production rates of CH₄ and CO₂, and the pathways and rates of soil organic carbon mineralization from the perspectives of SLR-saltwater intrusion and inundation increase. Saltwater intrusion due to SLR notably decreases CH₄ production rates and fluxes. It induces a shift in the pathways of soil organic carbon mineralization, transitioning from CH₄ production to microbial SO{}_{\mathrm{4}}^{\mathrm{2}-} reduction in tidal freshwater marshes. The main mechanism reducing saltwater intrusion-induced CH₄ flux is the increased presence of the electron acceptor SO{}_{\mathrm{4}}^{\mathrm{2}-}, which hinders soil CH₄ production. The impact of SLR through saltwater intrusion on CO₂ emissions in tidal freshwater marshes exhibits distinct uncertainty. Owing to the inherent challenges in experimentally manipulating SLR in situ, few reports concerning the effects of SLR-related inundation on CH₄ and CO₂ fluxes and production rates exist. However, some studies have suggested that an increase in inundation height leads to a reduction in CO₂ emissions. Additionally, this study consolidates information surrounding electron acceptors and microbial mechanisms associated with SLR that influence the pathways and rates of soil organic carbon mineralization in coastal tidal wetlands. Finally, this study outlines the specific domains that warrant further exploration in future research on the impact of SLR on the production and emission of carbon greenhouse gases in estuarine tidal marshes.