Future Changes Research Articles

Mechanisms upholding the persistence of stigma across 100 years of historical text

Today, many social groups face negative stereotypes. Is such negativity a stable feature of society and, if so, what mechanisms maintain stability both within and across group targets? Answering these theoretically and practically important questions requires data on dozens of group stereotypes examined simultaneously over historical and societal scales, which is only possible through recent advances in Natural Language Processing. Across two studies, we use word embeddings from millions of English-language books over 100 years (1900–2000) and extract stereotypes for 58 stigmatized groups. Study 1 examines aggregate, societal-level trends in stereotype negativity by averaging across these groups. Results reveal striking persistence in aggregate negativity (no meaningful slope), suggesting that society maintains a stable level of negative stereotypes. Study 2 introduces and tests a new framework identifying potential mechanisms upholding stereotype negativity over time. We find evidence of two key sources of this aggregate persistence: within-group “reproducibility” (e.g., stereotype negativity can be maintained by using different traits with the same underlying meaning) and across-group “replacement” (e.g., negativity from one group is transferred to other related groups). These findings provide novel historical evidence of mechanisms upholding stigmatization in society and raise new questions regarding the possibility of future stigma change.

Semantic Segmentation for Change Detection in Satellite Imaging

Change detection is a common and actual problem in the field of remote sensing. The classical approaches using raw pixel information are very sensitive to noise. In this study we propose the usage of additional semantic information for change detection. We use the semantic segmentation methods like geospatial Segment Anything Model and encoder based U-Net to evaluate the predictions and tracing the semantic information as well as raw information in change detection. Later the multidimensional time series data is used via the Vector Autoregression model to predict the future changes in the landscape. The observations which fall out of the prediction interval are considered as the changes in the landscape. The proposed method is evaluated on the dataset of the random locations across the Baltic region. The research is accompanied by the data and reproducible code at Github repository.

Remembering for resilience: nature-based tourism, COVID-19, and green transitions

The COVID-19 pandemic had transformative effects on the tourism sector at an unparalleled scale. With the rapid onset of unprecedented travel restrictions, tourists were abruptly confined to experiences in their regional surroundings that led to new and refreshed relationships with local destinations. This paper draws on qualitative interviews with small tourism businesses in two distinct but proximate nature-based destinations in Ontario, Canada and considers how they responded to the COVID-19 pandemic. Findings are positioned within Holling's Adaptive Cycle to consider implications for ongoing resiliency planning for disturbances relating to climate change. Over a 2-year period (2020–2022), SMEs revealed that after an initially turbulent period they quickly adapted to the absence of international long-haul visitors by embracing a surge in domestic demand for nature-based, outdoor experiences. The paper contributes to the literature on tourism SMEs by connecting experiences of COVID-19 to resiliency planning for future predictable disturbances. Two critical lessons for enhancing destination resiliency are identified: engagement of regional tourism demand, and destination level leadership, through investment in infrastructure and partnerships, can both be harnessed to support SMEs and their communities in transitioning toward a more sustainable, resilient and climate-friendly tourism future. Given the growing demand for tourism businesses to transition away from environmentally harmful practices and a longstanding dependency on economic growth, these resources can help destinations enhance preparedness for future changes to tourism flows driven by decarbonization scenarios and increased climatic impacts.

Impacts and State‐Dependence of AMOC Weakening in a Warming Climate

AbstractAll climate models project a weakening of the Atlantic Meridional Overturning Circulation (AMOC) strength in response to greenhouse gas forcing. However, the climate impacts of the AMOC decline alone cannot be isolated from other drivers of climate change using existing Coupled Model Intercomparison Project simulations. To address this issue, we conduct idealized experiments using the EC‐Earth3 climate model. We compare an abrupt 4×CO2 simulation with the same experiment, except we artificially fix the AMOC strength at preindustrial levels. With this design, we can formally attribute differences in climate change impacts between these two experiments to the AMOC decline. In addition, we quantify the state‐dependence of AMOC impacts by comparing the aforementioned experiments with a preindustrial simulation in which we artificially reduce the AMOC strength. Our findings demonstrate that AMOC decline impacts are state‐dependent, thus understanding AMOC impacts on future climate change requires targeted model experiments.

Optimal reliability ensemble averaging approach for robust climate projections over China

AbstractAccurate simulation and reliable projection of temperature and precipitation over China under climate change is important for proposing adaptation measures for future natural ecosystems. This study proposes a novel method to construct an optimal reliability ensemble averaging (REA) subset from the Coupled Model Intercomparison Project Phase 6 (CMIP6) based on their historical performance in simulating temperature and precipitation across different subregions. The optimal REA ensemble outperforms the multi‐model ensemble mean (MMEM) and single optimal model in reproducing the spatial patterns of historical annual mean temperature and precipitation over China from 1985 to 2014. Under the examined Shared Socioeconomic Pathway scenarios (SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5), the REA projects persistent warming and increased precipitation towards the end of the 21st century, intensifying under higher emissions. Nationwide mean temperature rises of 1.39, 2.69 and 5.05°C, and precipitation increases of 9%, 10% and 20% are projected in the long‐term (2081–2100) relative to 1995–2014 under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5 scenarios, respectively. Northwestern China and the Tibetan Plateau are expected to experience amplified warming and precipitation increases, respectively. Compared to the MMEM, the REA generally indicates reduced warming but larger precipitation increases, especially over the Tibetan Plateau under higher‐emissions scenarios. The REA exhibits lower projection uncertainty than the MMEM for both temperature and precipitation, primarily attributed to reduced internal variability. The novel optimal framework for REA shows the potential for extracting robust regional climate information applicable to different subregions of China. This study may contribute to new comprehension of future climate change over China.

Range‐wide intraspecific variation reflects past adaptation to climate in a gypsophile Mediterranean shrub

Abstract Phenotypic differences among populations stem from the interaction between neutral and adaptive processes, and phenotypic plasticity. Although clinal trait variation along climatic gradients often evolves in widely distributed species, it is unknown whether substrate specialization, such as that of Mediterranean gypsum plants, has constrained adaptation to climate. Using a common garden experiment with two contrasting watering treatments, we quantified phenotypic plasticity, assessed evidence for footprints of selection using FST – QST comparisons, and evaluated the ecological factors driving genetically based phenotypic differentiation of 11 populations encompassing the full environmental range of the gypsum shrub Lepidium subulatum. We found evidence for genetic differentiation among populations related to climatic differences, with populations from warmer and drier sites showing lower specific leaf area and leaf N, earlier phenology, greater water use efficiency and greater fitness. Multiple lines of evidence suggest that this differentiation was driven by past divergent selection rather than neutral processes. All populations showed high phenotypic plasticity, indicating that plasticity has not been selected against, even in populations from sites with harsher climatic conditions. Synthesis. Our results indicate that despite strong substrate specialization, adaptive differentiation related to climatic gradients occurs in this species. However, we also found that populations from mesic sites may be particularly vulnerable to future climate change given their relatively lower fitness under both wet and dry conditions.

Emergent constraints on the future East Asian winter surface air temperature changes

Abstract In East Asia, the climate variability in boreal winter is dominated by the East Asian winter monsoon, one of the most energetic monsoon systems that can lead to disasters. The key variable, the East Asian winter surface air temperature (SAT), has significantly changed over the past century and has substantially impacted agriculture, ecosystems, economics, and public health. However, its projections are limited by considerable uncertainties. Here, we identify the first leading mode that explains almost 32.1% of the inter-model spread in future SAT change. Our research delves into the evolution of present-day biases under future scenarios and their consequential impact on the SAT. Models with stronger western currents in the North Pacific exhibit a warmer North Pacific at mid-latitudes during historical periods. Additionally, these models consistently demonstrate stronger western currents in the future, contributing to the amplified warming of the western North Pacific, thereby warming Eurasia via the weakened trough and subtropical jet through barotropic responses to the warm North Pacific. Incorporating observational sea surface temperature (SST) constraints reduces uncertainties by 15.6%, revealing a more reliable SAT change pattern by the end of the 21st century.

Distribution and ecology of shallow-water black corals across a depth gradient on Galápagos rocky reefs

AbstractAntipathes galapagensis is a prevalent habitat-forming black coral in subtidal ecosystems of the Galápagos Marine Reserve (GMR). Despite their ecological importance and status as a CITES-regulated order, little is known about their depth distribution, population structure and ecology in the GMR. Surveys were conducted in 2021 and 2022 at 9 sites in the central Galápagos Archipelago to investigate how black coral densities, occupancy, size, habitat utilization, and epizoan overgrowth varied between 2.0 and 20.0 m depth. The shallowest black corals occurred at 3.4 m depth, one of the shallowest occurrences of an Antipathes spp. in the world. Coral density increased with depth, with a maximum density of 5.2 colonies per m2 observed across the depth range surveyed. Occupancy modeling also yielded curves with increasing probabilities of black coral presence with depth at all sites. Colony height increased with depth at 8 out of 9 sites and was positively correlated with coral density at 6 of 9 sites. Overall, 47% of colonies surveyed occupied cryptic habitats and 53% were attached to exposed substrate, but black coral habitat usage patterns varied with depth at 5 of 9 sites. At these sites, colonies on shallower transects (5.0, 10.0 m depth) more frequently displayed cryptic habitat usage while colonies along the deeper transects (15.0, 20.0 m) were more often exposed. In general, coral density, probability of occupancy, height, and exposed habitat utilization increased with depth, while the average degree of overgrowth and number of epibiont taxa were unrelated to depth. Five hypotheses regarding factors potentially limiting the shallow (upper) depth distribution of A. galapagensis—ranging from negative impacts of the physical environment to high predation on exposed substrates—are presented for future testing. These results provide a comprehensive ecological characterization of Galápagos black coral populations that can be used to assess the impact of future environmental change and applied to management decisions for this key marine foundation species in the GMR.

Dissolved trace elements and nutrients in the North Sea—a current baseline

Primary production is an important driver of marine carbon storage. Besides the major nutrient elements nitrogen, phosphorus, and silicon, primary production also depends on the availability of nutrient-type metals (e.g., Cu, Fe, Mo) and the absence of toxicologically relevant metals (e.g., Ni, Pb). Especially in coastal oceans, carbon storage and export to the open ocean is highly variable and influenced by anthropogenic eutrophication and pollution. To model future changes in coastal carbon storage processes, a solid baseline of nutrient and metal concentrations is crucial. The North Sea is an important shelf sea, influenced by riverine, atmospheric, Baltic Sea, and North Atlantic inputs. We measured the concentrations of dissolved nutrients (NH4+, NO3−, PO43−, and SiO44−) and 26 metals in 337 water samples from various depths within the entire North Sea and Skagerrak. A principal component analysis enabled us to categorize the analytes into three groups according to their predominant behavior: tracers for seawater (e.g., Mo, U, V), recycling (e.g., NO3−, PO43−, SiO44−), and riverine or anthropogenic input (e.g., Ni, Cu, Gd). The results further indicate an increasing P-limitation and increasing anthropogenic gadolinium input into the German Bight.

Coastal Eukaryotic Plankton Diversity of the Southern Adriatic as Revealed by Metabarcoding

Plankton studies serve as a basis for marine ecosystem research, but knowledge of marine plankton is still incomplete due to its extreme taxonomic and functional complexity. The application of metabarcoding is very valuable for the characterisation of the plankton community. The plankton community of the Southern Adriatic is subject to strong environmental fluctuations and changes, which underlines the need for frequent, reliable and comprehensive characterisation of the plankton. The aim of this study was to determine the taxonomic composition and seasonal distribution of eukaryotic plankton in the Southern Adriatic. Plankton samples were collected monthly for one year at the coastal station of the Southern Adriatic and metabarcoding was used for taxonomic identification. The results showed a high taxonomic diversity and dynamic seasonal distribution patterns for both the protist and metazoan plankton communities. Metabarcoding revealed both the core, year-round plankton community and previously unrecorded plankton organisms in the Southern Adriatic. The results provide for the first time a comprehensive overview of the plankton community in this area by metabarcoding. The identified seasonal patterns of plankton genera and species in the Southern Adriatic will contribute to the understanding of plankton interactions and future changes in community diversity characterisation.

Linking Upwelling Dynamics and Subsurface Nutrients to Projected Productivity Changes in the California Current System

AbstractGiven the importance of coastal upwelling systems to ocean productivity, fisheries, and biogeochemical cycles, their response to climate change is of great interest. However, there is no consensus on future productivity changes in these systems, which may be controlled by multiple drivers including wind‐driven and geostrophic transport, stratification, and source water properties. Here we use an ensemble of regional ocean projections and recently developed upwelling indices for the California Current System to disentangle these sometimes‐competing influences. Some changes are consistent among models (e.g., decreased mixed layer depth), while for others there is a lack of agreement even on the direction of future change (e.g., nitrate concentration in upwelled waters). Despite models' diverging projections of productivity changes, they agree that those changes are predominantly driven by subsurface nitrate concentrations, not by upwelling strength. Our results highlight the need for more attention to processes governing subsurface nutrient changes, not just upwelling strength.

Impact of next-generation Artificial General Intelligence (AGI) on international relations

The new generation of artificial intelligence technologies occurrence represented by ChatGPT is the beginning of the Artificial General Intelligence (AGI) era. In contrast to the impact of weak AI technologies on international relations discussed in the previous era, AGI is no longer just a tool in the traditional sense. The human-computer integration facilitated by AGI technology will rapidly and deeply penetrate into all areas of social policy and economy. It also may change the mode of social production and economic development, influence international relations and geopolitics by transforming the comprehensive state capacity, and simultaneously force new challenges in global governance. The acknowledgement of a new generation of AGI technological qualitative changes’ impact on future changes in international relations is no longer the fantasy; the underlying AGI changes in labour productivity will certainly lead to a disruptive reconfiguration of future international relations.

Anthropogenic forcings reverse a simulated multi-century naturally-forced Northern Hemisphere Hadley cell intensification

The Hadley circulation plays a central role in determining the location and intensity of the hydrological cycle in tropical and subtropical latitudes. Thus, the human-induced historical and projected weakening of the Northern Hemisphere Hadley circulation has considerable societal impacts. Yet, it is currently unknown how unparalleled this weakening is relative to the response of the circulation to natural forcings in past centuries. Here, using state-of-the-art climate models, we show that in contrast to the recent and future human-induced Hadley circulation weakening, natural forcings acted to intensify the circulation by cooling the climate over the last millennium. The reversal of a naturally-forced multi-centennial trend by human emissions highlights their unprecedented impacts on the atmospheric circulation. Given the amplifying effect of natural forcings on the Hadley circulation, our analysis stresses the importance of adequately incorporating natural forcings in climate model projections to better constrain future tropical climate changes.

Performance evaluation of varies climate models using observed and regional climate models for the Katar Watershed, Ethiopia

Climate models are fundamental tools to estimates the reliable future climate change and its effects on the water resources and agriculture in basins. However, all climate models are not equally performed for all areas. Therefore, determining the most appropriate climate models for a specific study area is essential. The focus of this study was to evaluate the performance of the regional climate models with regard to simulating precipitation, and temperatures at Katar watershed. This study examines the performance of fourteen CORDEX-AFRICA-220 Regional Climate Models (RCMs) for the period of 1984–2005 using statistical metrics such as Pearson correlation coefficient (R), mean absolute error (MAE), root mean squared error (RMSE), and bias. The findings indicated that GERICS-MPI was better performed in representing Areta, and Bokoji station, GERICS-IPSL was better representing in Assela, Ketergenet, and Sagure station, CCCma-CanESM2-AFR22, and RCA4-ICHEC performed relatively better in representing the mean annual observed rainfall at the Kulumsa, and Ogolcho station respectively. However, RCA4-CSIRO performed weakly in estimation of annual rainfall at all stations. RCM model such as GERICS-MPI was relatively better than the others in replicating the annual pattern of the maximum temperature at Areta, Bokoji, and Ketergenet stations. Similarly, GERICS-IPSL were relatively better in replicating the annual maximum temperature at Assela, and Sagure stations, CCCma-CanESM2-AFR22 at Kulumsa station, and RCA4-ICHEC at Ogolcho station performed well in capturing the observed and simulated annual maximum temperature. Better performance was observed on minimum temperature at CCCma-CanESM2-AFR22 at Areta, Assela, and Ketergenet stations, GERICS-MOHE-AFR-22 at Bokoji station, GERICS-MPI at Kulumsa, and Ogolcho stations, RAC4-NOAA-2G at Sagure stations. However, weak performance was observed RCA4-CSIRO at all stations. RCM models of GERICS-MPI, and CCLM4-NCC-AFR-22 performed better than the other RCM models for correction of annual rainfall in Katar watershed. However, poor performance was observed at RCA4-ICHEC model on Katar watershed. The GERICS-MPI model performed well. However, poor performance was observed at RCA4-ICHEC on maximum temperature, and GERICS-NOAA-2M on minimum temperature in Katar watershed.

An Efficient Water Quality Prediction and Assessment Method Based on the Improved Deep Belief Network—Long Short-Term Memory Model

The accuracy of water quality prediction and assessment has always been the focus of environmental departments. However, due to the high complexity of water systems, existing methods struggle to capture the future internal dynamic changes in water quality based on current data. In view of this, this paper proposes a data-driven approach to combine an improved deep belief network (DBN) and long short-term memory (LSTM) network model for water quality prediction and assessment, avoiding the complexity of constructing a model of the internal mechanism of water quality. Firstly, using Gaussian Restricted Boltzmann Machines (GRBMs) to construct a DBN, the model has a better ability to extract continuous data features compared to classical DBN. Secondly, the extracted time-series data features are input into the LSTM network to improve predicting accuracy. Finally, due to prediction errors, noise that randomly follows the Gaussian distribution is added to the assessment results based on the predicted values, and the probability of being at the current water quality level in the future is calculated through multiple evolutionary computations to complete the water quality assessment. Numerical experiments have shown that our proposed algorithm has a greater accuracy compared to classical algorithms in challenging scenarios.

American Presidential Elections 2024: The Core Point of Future Geopolitical Changes

Purpose: This research is focused on the ongoing Russia – Ukraine military conflict, which has already caused some significant changes in foreign policy priorities of major players of international political system. Objective: The objective of this study is to investigate the impact of U.S. 2024 elections to the Russia – Ukraine military conflict outcomes with the aim of analyzing different foreign policy philosophies the two potential candidates have, that can have an effect not only on current Russo-Ukrainian conflict but on the whole global geopolitical situation in the current world. Theoretical Framework: realism as an international relations theory with the system level analysis is used to explain current global geopolitical issues. Method: The issue of methodology is decided according to the necessities of tasks of this article and is mostly based on data analyses, comparison of similarities or differences and case study. Results and Discussion: the current work claims that the major war on the European continent disrupts the core security arrangements which has a shattering effects of unipolar liberal order and how much will this order be changed, is mainly depended on the dedication to it by the U.S.A, European union countries and their liberal democratic allies around the globe. Research Implications: the research findings contribute in raising awareness of the current Ukraine conflict and accumulate the type of knowledge that enriches the political science with theoretical and practical value.

Seasonal Scale Climatic Factors on Grassland Phenology in Arid and Semi-Arid Zones

Influenced by climate change, significant alterations in vegetation phenology have been observed globally. Grassland phenology is highly sensitive to climate change. However, research on the variations in grassland phenology and its responses to seasonal climatic changes in arid and semi-arid regions remains scarce. This study, utilizing Solar-Induced Chlorophyll Fluorescence (SIF) data, meteorological station data, and grassland type data, employs trend analysis and time series analysis to explore the trends of seasonal climatic variability and the sensitivity response of grassland phenology in Xinjiang to seasonal climates. The findings reveal the following: (1) The region experiences more pronounced warming in winter and spring than in summer and autumn, with ground temperature increments outpacing those of air temperatures. The summer season registers the peak in precipitation volume and rate of increase, where mountainous zones accrue more rainfall compared to basins and plains. The distribution of sunshine duration is characterized by higher values in eastern areas than in the west and more in the plains than in mountainous regions, potentially due to escalating cloudiness, which has contributed to a diminishing trend in sunshine hours across Xinjiang over the past 20 years. (2) Over the past two decades, the perennial greening phase of Xinjiang grasslands has predominantly occurred in early May, showing an overall trend of occurring earlier by approximately 5.47 days per decade, while the yellowing phase mainly occurs at the end of September and the beginning of October, demonstrating a delaying trend (6.61 days/decade). The average length of the growing season is 145 days, generally showing a slightly increasing trend (11.97 days/decade). (3) In spring, the rise in air and ground temperatures, along with increased sunshine duration, all promote grassland growth, leading to an earlier greening phase. Conversely, in autumn, increases in air temperature, ground temperature, and sunshine duration can inhibit grassland growth, resulting in an earlier yellowing phase. Increased precipitation in summer and autumn can delay the yellowing phase and extend the length of the grassland growing season. This research provides new insights into the factors influencing large-scale grassland phenology and offers references for grassland adaptation to future climate changes.

The impact of precipitation changes on the safety of railway operations in China under the background of climate change

Global climate change has intensified the water cycle, leading to frequent extreme precipitation events, posing a significant threat to railway infrastructure and safety operations. Based on the analysis of past and future precipitation changes in China, this study investigates the impact of climate change on railway safety operations. The study reveals the following findings: (1) Under the influence of the intensified East Asian summer monsoon and the northward shift of the subtropical high during the 2017–2021 compared to the 2012–2016, precipitation has significantly decreased (120 mm) in the regions south of the Yangtze River and South China, while it has increased (60 mm) in the regions from the eastern of Northwest China to the middle and lower reaches of Yangtze River; The operational precipitation risk has decreased for Urumqi, Lanzhou, Qinghai-Tibet Group, Xi’an, and Wuhan railway bureaus (abbreviated as Bureau), while it has increased for Nanchang, Chengdu, Zhengzhou, Shanghai, and Shenyang Bureaus. Particularly noteworthy is that despite a decrease in total annual precipitation for Nanchang bureau (15.3 mm/a), the frequency of intense precipitation events has increased, leading to an increased operational precipitation risk. (2) During the 21st century, under high (SSP5-8.5), medium (SSP2-4.5), and low (SSP1-2.6) forcing scenarios, all projections indicate that most of the China will experience an increasing trend in precipitation, with significant increases in precipitation observed in the regions south of the Yangtze Rive, South and Southwest China. The higher the greenhouse gas emissions, the more pronounced the increasing trend in precipitation. (3) Compared to the 20th century, under high (SSP5-8.5), medium (SSP2-4.5), and low (SSP1-2.6) forcing scenarios, all projections indicate that the total annual precipitation hours, railway inspection, speed limit, and closure risk hours have all increased on a national scale during the 21st century. The operational precipitation risk for railways has also increased. The higher the alert level for railway precipitation (precipitation < inspection < speed limit < closure), the higher the proportion of risk hours compared to the 20th century. By the late 21st century, the railway inspection, speed limit, and closure risk hours have increased by 175%, 463%, and 647%, respectively, compared to the 20th century.

Inventory Management System

Inventory management systems cater to the demands of businesses by providing efficient inventory operations via user-friendly interfaces for supplier administration, product categorization, inventory tracking, and transaction recording. This web application facilitates online stock and inventory management for a particular business or retailer. The project makes it simple for the management of the company to keep track of, record, and maintain its goods inventory. The system will have a modular architecture to enable future improvements and changes, with a focus on scalability, security, and user-friendliness. It will also include strong search and filtering capabilities, role-based access control, and support for many transaction types. It guarantees dependability and efficiency, includes extensive testing and documentation, and finally gives companies a strong instrument to streamline inventory procedures and enhance overall operations. The Inventory Management System will include cutting-edge capabilities such inventory Management Systems, with features like automated stock replenishment, real-time inventory synchronization across multiple locations or warehouses, and integration, represent a substantial investment in raising a company's competitiveness through cost savings, improved customer satisfaction, and optimized inventory processes

Historical and Future global warming under different RCP emission scenarios

Understanding the relationship between carbon emissions and climate change has become increasingly urgent amidst the universal endorsement of sustainable development and the establishment of net-zero carbon emission target (The Paris Agreement). In this study, model projections based on Coupled Model Intercomparison Project Phase 5 (CMIP5) are used to examine future climate change under different representative concentration pathway (RCP) emission scenarios till 2300. Besides analysis of future global average temperature change under the emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP 8.5, historical data is first collected during the past three decades (1990-2021). The results show that the simulated global warming ranges from 0.9 to 1.3 between 1990 and 2021, consistent with the observations (0.93). Carbon emissions in China arose mostly from manufacturing and construction, electricity and heat and transport. Emissions from electricity, heat and transport increase by a high ratio of 7.7 and 3.5 times due to industry development. Under different RCP scenarios, the global surface temperature anomaly will increase by 0.2-1.0, 1.2-2.0, 3.5-4.3 and 3.0-8.5 , respectively. The surface temperature anomaly values under RCP8.5 are much higher than those under other emission scenarios. Only in the RCP2.6 scenario (sustainability), the surface warming in all simulations stays below a 2 threshold at the end of the 21st century. To attain net zero emissions, it is highly demanded to develop strict emission policies, chart a course toward decarbonization, and institute effective measures aimed at realizing net zero emissions within the short to medium term. Concurrently striving for economic objectives, managing the equilibrium between economic growth and environmental sustainability emerges as a critical imperative.