Greening Trend Research Articles

Spatio-temporal coordinated development pattern evolution and driving factors of regional population and green economy: Evidence from Shandong Province in China.

The study of spatio-temporal evolution characteristics and factors affecting the coordinated development of population and green economy (CD_PGE) in Shandong province, China, has significant decision-making implications for promoting high-quality and sustainable regional development. Based on 2001 to 2020 panel data for each city and economic zone in Shandong province, this paper constructs an evaluation model for the CD_PGE systems. Using growth elasticity models, geographic concentration models, kernel density estimation models, spatial autocorrelation, analysis of population and regional green economy development in Shandong Province from the perspective of spatial agglomeration coupling, spatial and temporal coupling coordination patterns, and evolutionary characteristics. In addition, we use the fixed effect models and panel quantile models to empirically test the effects of coordinated demographic and green economy development. The results show that: (1) In terms of demo-graphic and economic development characteristics, Shandong's demographic and green economy development trends are good, but there are still many challenges. (2) According to the time series evolution and spatial distribution characteristics, the degree of CD_PGE in Shandong Province is on the rise, and the level of spatial distribution is distinct. (3) From the spatio-temporal dynamical grid evolution of the degree of CD_PGE, the CD_PGE is characterized by significant spatial clustering, but with large regional differences. (4) From an impact factor perspective, both market mechanisms and government intervention have a significant impact on the degree of CD_PGE, but the direction and extent of the impact vary.

Green bonds and sustainable finance: Performance insights and future outlook

This review paper comprehensively analyses green bonds and their role in sustainable finance. It examines green bonds' definition, characteristics, performance, market trends, challenges, and opportunities. Findings reveal that green bonds offer investors an avenue to align financial objectives with environmental goals while generating competitive returns. However, challenges such as standardised definitions and insufficient investable projects hinder market growth. Implications for investors, issuers, and policymakers are discussed, highlighting the importance of integrating environmental, social, and governance factors into decision-making processes. Recommendations include further research to enhance understanding and stakeholder collaboration to promote transparency and accountability. Ultimately, green bonds promise to advance environmental sustainability and combat climate change in a resilient, low-carbon economy.

Characterizing Vegetation Phenology Shifts on the Loess Plateau over Past Two Decades

Phenology is a critical mirror reflecting vegetation growth and has a major impact on terrestrial ecosystems. The Loess Plateau (LP) is a paramount ecological zone in China that has experienced considerable vegetation changes. However, understanding the dynamics of vegetation phenology is limited by ambiguous vegetation interpretation and anthropogenic-induced forces. This study combined the multi-climatic and anthropogenic datasets to characterize the interactions between phenology shifts and environmental variables. The principal findings were as follows: (1) Phenological shifts exhibit spatial heterogeneity and an interannually increasing trend in greenness (R2 > 0.6, p < 0.05). Notably, SOS (the start of the growing season) advances while EOS (the end of the growing season) delays in both the southeastern and northwestern regions. (2) SOS and EOS, primarily in the range of 100–150 and 285–320 days, respectively. Phenological changes vary depending on vegetation types. The forest has an early SOS, within 80–112 days, and a delayed EOS, within 288–320 days. The SOS of shrub is mainly within 80–144 days. (3) EOS shows a strong response to the preseason of each climate variable. Precipitation (R = 0.76), soil moisture (R = −0.64), and temperature (R = 0.89) are the governing determinants in shaping vegetation phenology. In addition, agriculture and urbanization play a significant role in shaping the spatial variations of SOS. These findings provide a basis for a systematic understanding of the processes that affect vegetation growth, which is crucial for maintaining the health and sustainability of arid and semiarid ecosystems.

Trends and factors of green regional economy development: theoretical-research aspect

With the deepening of industrialization, modernization and urbanization, global environmental and resource problems are becoming more and more serious, and the development of a green economy is becoming an important global trend that is also reflected at the regional level. The goal of the study is to analyze the key factors determining green economic trends and to attempt to determine the future directions of these trends themselves. The methodological basis of the study was formed by analytical and comparative methods, as well as relevant works of scientists devoted to the study of trends and factors of green economy development, primarily in the regional context. The results of the analysis show that, firstly, the connotation of the essence of the green economy is constantly evolving and becoming broader. The Sustainable Development Goals perspective emphasizes that a green economy is a low-carbon, environmentally friendly and sustainable model of the dynamic trajectory. Secondly, the system of relevant tools for assessing and indi-cating the trends of the green economy is becoming increasingly multidimensional in terms of reflecting the parametric characteristics of environmentally oriented development of the regional economy. Thirdly, there is a gradual transformation in the methods of researching the factors of impact on the green economy development, expressed in the transition from unilinear causal analysis to multidimensional non-linear network one, covering not only explicit but also implicit factors. It is shown that future research in this area will be increasingly interdisciplinary, practically orientated towards the development of regional green policies.

Urban dynamics and their implication on greenness trends: A 25-year retrospective study of the changing face of tokyo metropolitan area

Global metropolises and their needs for green space are rising due to demographic urbanization. Some phenomena contradicted to prevailing understanding have been observed in metropolises, such as the “sprawl shrinkage” associated with the increasing built-up area despite declining populations, and the positive relationship between population and greenness. To study these storylines, we conceptualized and mapped 5 urban dynamics by cross-referencing the“increase, stable, and decrease”of built-up area and population density based on threshold values of an introduced Normalized Difference Index (NDI). Furthermore, Kruskal-Wallis H Test was used to analyze the influence of different urban dynamic patterns on 3 greenness trends (greening, browning, and stable greenspace). From 1995 to 2021, Tokyo Metropolitan Area (TMA) gradually transited from intense urban expansion to a stabilization of built-up area and population density in the city center, declining urbanization in the peri-urban areas, and “sprawl shrinkage” in the far-outskirts. Moreover, compared to other urban dynamics, the pattern of built-up areas increases with a population density reduction of over 5% were conducive to maintaining NDVI values of 0.75 or higher. In the future, the ongoing demographic urbanization is highly likely to further exacerbate the phenomenon of urban-suburban disparity and intra-suburban differentiation. We propose that Asian metropolises should enhance regional cooperation and public-private partnerships to address potential regional ecological imbalances. Additionally, it is necessary to maximize the greenness within the given urban dynamics through figuring out the spatial impact mechanisms of urban development on greenness change from a long-term perspective.

A Bibliometric Analysis Of Green Accounting Research

The primary goal of green accounting is to address social issues impacting global sustainable development and to influence corporate actions towards social and environmental concerns. This research aims to map the concept of green accounting and describe its impact on science. This research is a literature review using bibliometrics. Bibliometrics helps map research related to developing green accounting research trends published by leading journals from 1992 to 2023, which have been indexed by Scopus as many as 233 articles, using VosViewer software. The analysis is focused on keyword trends, authors, and institutions. The results show that the number of articles discussing the theme of green accounting has been increasing yearly, which aligns with the development of economics and the environment. The most popular keywords are sustainable development, environmental management, and environmental economics. The most published writer is Markandya. Meanwhile, the most popular organization is Fondazione Eni Enrico Mattei (FEEM). This study provides valuable insights for researchers focusing on green accounting. Therefore, this theme has the potential to be further developed in the future.

China's Green Finance Development History and Trends

China's Green Finance Development History and Trends

Recent Water Constraints Mediate the Dominance of Climate and Atmospheric CO2 on Vegetation Growth Across China

AbstractMultiple lines of evidence confirm a widespread increase in vegetation growth across China over the past few decades. The relationship between vegetation growth and water availability is thought to be becoming stronger under climate change, that is, water constraints on vegetation growth have been increasing. However, our understanding of how water constraints have influenced these vegetation greening trends, especially those climate change‐driven ones, remains limited. Here, we conduct a comprehensive evaluation of recent water constraints and their implications for vegetation growth in China between 1982 and 2015. By analyzing the spatiotemporal patterns of the relationship between vegetation growth and water availability, we reveal recent water constraints and their changes hidden within an overall greening trend in China. Further analysis demonstrates that two climate change‐related categories, defined broadly as “climate” (e.g., air temperature, precipitation, and so on) and “CO2” (i.e., atmospheric carbon dioxide), have exerted varying levels of importance in regulating vegetation growth across different water constraints. With increasing water constraints, the proportion of the climate‐dominated area has significantly risen, while that of the CO2‐dominated area has sharply declined. Our findings highlight that water constraints can mediate the dominance of climate and atmospheric CO2 on vegetation growth. This has the great potential to exacerbate the uncertainty surrounding current and future sustainable vegetation greening trends.

Green Banking Trends in Islamic Bank: Gen Z’s Awareness and Knowledge

Green Banking Trends in Islamic Bank: Gen Z’s Awareness and Knowledge

Financial resilience and sustainability: examining green innovation trends post-stock price crashes in China

The primary objective of this study is to uncover whether the occurrence of stock price crash (SPCR) influences firms’ engagement in green innovation (GI) and change in GI activities. Using data for China’s A-share listed firms from 2009 to 2022, our initial findings reveal that firms increase their investments in GI after SPCR occurrence and this effect is consistent with a change in GI. The mechanism analysis shows increased financial constraints prompting firms to adopt GI to alleviate the strain on financing, thereby enhancing overall financial stability. Additionally, the impact of SPCR on GI is more prominent in state-owned enterprises and in those with politically connected CEOs. Moreover, heterogeneity analysis shows that firms located in high-tech regions and those with low levels of bank competition tend to invest more in GI activities after the occurrence of SPCR. Overall, the findings are robust and remain valid after using propensity score matching and system generalized method of moments models.

GREEN MARKETING: A MEANS FOR SUSTAINABLE DEVELOPMENT

Marketers are continually trying to recognize the new opportunities and risks given by the marketing environment, while also understanding the significance of regularly monitoring and adjusting to it. Marketers must think imaginatively about how to meet the requirements of the global population while promoting sustainable development. Green Marketing has developed as a new idea to capitalize on growing opportunities and ensure a higher standard of living through sustainable development. Green marketing is a philosophy that is primarily concerned with sustainable development. Recognizing the importance of people's concern for a healthy environment to live in and their preference for environmentally friendly products and services to consume, marketers are now attempting to capitalize on this to ensure sustainable development and are incorporating these concepts into their strategy development. This document tries to explain the words and concepts of green marketing. The study attempts to illustrate why green marketing is critical in the current environment. This report attempts to describe the fundamental challenges linked with green marketing and propose solutions. This study also discusses current green marketing trends and how green marketing can be used to promote sustainable development.

Regional divergent evolution of vegetation greenness and climatic drivers in the Sahel-Sudan-Guinea region: nonlinearity and explainable machine learning

IntroductionThe vegetation dynamics of the Sahel-Sudan-Guinea region in Africa, one of the largest transition zones between arid and humid zones, is of great significance for understanding regional ecosystem changes. However, a time-unvarying trend based on linear assumption challenges the overall understanding of vegetation greenness evolution and of tracking a complex ecosystem response to climate in the Sahel-Sudan-Guinea region.MethodsThis study first applied the ensemble empirical mode decomposition (EEMD) method to detect the time-varying trends in vegetation greenness based on normalized difference vegetation index (NDVI) data in the region during 2001–2020, and then identified the dominant climatic drivers of NDVI trends by employing explainable machine learning framework.ResultsThe study revealed an overall vegetation greening but a significant nonlinear spatio-temporal evolution characteristic over the region. Trend reversals, i.e., browning-to-greening and greening-to-browning, were dominant in approximately 60% of the study area. The browning-to-greening reversal was primarily observed in the southern Sahel, Congo Basin north of the Equator, and East Africa, with a breakpoint around 2008, while the greening-to-browning reversal was mainly observed in West Africa, with a breakpoint around 2011. The sustained greening primarily took place in northern Sahel, Central African Republic and South Sudan; while sustained browning clustered in central West Africa and Uganda, mainly in agricultural lands. Furthermore, the combination of Random Forest (RF) algorithm and the SHapley Additive exPlanations (SHAP) method could robustly model and reveal the relationships between the observed trends in NDVI and in climatic variables, also detected by applying EEMD. The results suggested that air temperature and precipitation were the most important climatic drivers controlling the NDVI trends across the Sahel-Sudan-Guinea region. The NDVI trends were more likely to have negative correlations with solar radiation and vapor pressure deficit in arid areas, while they could have positive correlations in humid areas. The study also found that large-scale climate changes induced by sea surface temperature (SST) anomalies had strong relationships with trend reversals in vegetation greenness at a sub-continental scale. These findings advanced the understanding of the impacts of climatic drivers on vegetation greenness evolution in the Sahel-Sudan-Guinea region.

The Nexus of Artificial Intelligence and Green Innovation: a Cross-Density Analysis at the Country Level

AbstractThis study explored the synergistic effects of artificial intelligence (AI) on green innovation at the national level by identifying three core activities in green innovation: entry, exit, and sustained specialization in green technologies. Employing a comprehensive three-way fixed-effects panel model, we analyzed green innovation trends in 139 countries over a 30-year period. Our findings emphasize that technological capability, especially in green and AI technologies, is more pivotal than economic wealth in securing comparative advantages in green technologies. One notable observation is the path-dependent development of green technology, which suggests a propensity for nations to build new technologies based on existing strengths. A key contribution of this study is the development of the “AI-Green Cross-Density” model. This innovative method quantifies the interactions between green and AI technologies and highlights the role of AI in promoting green innovation. The influence of AI on the introduction of new green technologies has become more pronounced in recent years, particularly in economically less-developed countries. Our findings indicate that the integration of modern AI can significantly enhance green technology sectors in mid-to-low-income countries, providing vital insights for policymakers striving to foster a sustainable and technologically advanced future.

Hydrological Factor and Land Use/Land Cover Change Explain the Vegetation Browning in the Dosso Reserve, Niger

The West Sahel is facing significant threats to its vegetation and wildlife due to the land degradation and habitat fragmentation. It is crucial to assess the regional vegetation greenness dynamics in order to comprehensively evaluate the effectiveness of protection in the natural reserves. This study analyzes the vegetation greenness trends and the driving factors in the Dosso Partial Faunal Reserve in Niger and nearby unprotected regions—one of the most important habitats for endemic African fauna—using satellite time series data from 2001 to 2020. An overall vegetation browning trend was observed throughout the entire region with significant spatial variability. Vegetation browning dominated in the Dosso Reserve with 17.7% of the area showing a significant trend, while the area with significant greening was 6.8%. In a comparison, the nearby unprotected regions to the north and the east were found to be dominated by vegetation browning and greening, respectively. These results suggest that the vegetation protection practice was not fully effective throughout the Dosso Reserve. The dominant drivers were also diagnosed using the Random Forest model-based method and the Partial Dependence Plot tool, showing that water availability (expressed as soil moisture) and land use/land cover change were the most critical factors affecting vegetation greenness in the study region. Specifically, soil moisture stress and specific land management practices associated with logging, grazing, and land clearing appeared to dominate vegetation browning in the Dosso Reserve. In contrast, the vegetation greening in the central Dosso Reserve and the nearby unprotected region to the east was probably caused by the increase in shrubland/forest, which was related to the effective implementation of protection. These findings improve our understanding of how regional vegetation greenness dynamics respond to environmental changes in the Dosso Reserve and also highlight the need for more effective conservation planning and implementation to ensure sustainable socio-ecological development in the West Sahel.

Asymmetric warming has different impacts on vegetation growth across various vegetation types on the Tibetan Plateau

ABSTRACT Global warming could affect vegetation growth, while land surface temperature has exhibited an asymmetric warming pattern over the past 50 years. The Tibetan Plateau, known as “the roof of the world,” experiences the surface warming almost twice as high as the global average. However, previous research has largely overlooked the impacts of this asymmetrical warming on vegetation growth and the temporal changes in these impacts. In this study, we assess the effects of asymmetric warming on vegetation growth at regional and different vegetation types by using partial correlation analysis, and reveal the temporal changes of impacts strength using time moving window. The results showed that there had been a significant greening trend (1.01 × 10−3 yr−1, p < 0.01) in the Normalized Difference Vegetation Index (NDVI) during the growing season, as well as significant warming trends in both maximum temperatures (Tmax, 0.0354°C yr−1, p < 0.01) and minimum temperatures (Tmin, 0.0333°C yr−1, p < 0.01) during 2000–2021. Under the background of asymmetric warming, the grassland showed stronger impacts of Tmin than Tmax on NDVI, while the opposite effects were observed for forests. Over time, the response of NDVI to Tmax and Tmin has intensified. This study highlights importance of asymmetric warming in the projection of climate change on vegetation in similarly vulnerable ecosystems worldwide.

Vegetation browning trend progressively leading to forest degradation in eastern himalaya in response to climatic and anthropogenic drivers

Vegetation is a major natural resource that plays an important role in maintaining ecological balance. Vegetation in the eastern Himalaya has experienced severe consequences owing to deforestation, fragmentation, land use land cover (LULC) conversion and climate change. Disturbances in vegetation have a close connection to browning trend because they modify the terrestrial ecosystems. Remote sensing derived vegetation indices and the availability of long-term satellite data allowed us to infer greening and browning tendencies across the Northeast Region (NER) of India. The present study has employed almost four decades (1982–2020) of satellite data (i.e. NDVI and LAI) and climate data (precipitation, soil moisture, temperature, solar radiation) to deduce the spatial pattern of greening and browning trends over major vegetation ecosystems, namely forest, grassland and cropland. Statistical metrics such as the Mann–Kendall test (τ) and the Theil–Sen median trend were computed to understand the greening and browning including vegetation degradation. The key findings exhibited that a noticeable large-scale greening trend of forests persisted in the first period (1982–2000) and switched to browning in the latest period (2000–2020). The statistically significant areas of browning trends over forest regions in NER was 5.6% which increased to 10.7–15.6%. The browning trends over grassland were more pronounced in the southernmost part of NER. Such changes were ascribed mostly to persistent warming and declining soil moisture. This was further exacerbated by human-induced LULC change. Over croplands, greening was prominent in Assam in the latest period, whilst other regions switched to browning. Trend analysis gives critical information on temperature-induced moisture stress leading to browning that might have potential implications for the forest, grassland and agriculture ecosystems. Specifically, the areas at Ziro Valley of Arunachal Pradesh showed high risk of forest degradation (i.e. 19% of the total forest area of 1816.54 km2), whereas areas around the Loktak Lake in Manipur exhibited high risk of cropland degradation. The states in the southernmost part of NER showed high risk of grassland degradation. Nearly 20–27% of the areas were identified as high risk of degradation. The study underscores the potential areas of NER where land management strategies need attention in the context of complex climatic factors along the side of anthropogenic influences.

Research on the Evolution of the Spatial Association Network Structure and Driving Factors of China’s Agricultural Green Development

Against the backdrop of global environmental challenges and sustainable development goals, this paper pioneers the application of social network analysis to the study of spatial associations in China’s agricultural green development. It not only enhances the understanding of the spatial interconnectivity and network structural characteristics of agricultural green developments, but also captures the complex dependencies and interactions among provinces through a network lens, offering a fresh perspective on regional agricultural cooperation and competition. The study reveals: (1) The spatial network of China’s agricultural green development displays strong overall connectivity and enhanced stability, with regional green development trends becoming increasingly interlinked and interdependent. (2) The network exhibits a clear hierarchical and core-periphery structure which, over time, shows signs of diminishing, indicating a narrowing of developmental disparities among regions. (3) Significant shifts in the roles and positions of provinces within the network occur due to the relocation of industrial focal points and adjustments in development strategies, highlighting the complexity of dynamic changes among regions. (4) The spatial association network can be divided into four main clusters: Net spillover block, Bidirectional spillover block, Net beneficial block, and Broker block, with significant gradient characteristics in the relationships between these clusters, suggesting directional and differential flows and exchanges of resources and information among regions. (5) Geographic proximity, economic development level, informatization, and agricultural technological advancement significantly influenced the development and structural evolution of the network.

Conflicting Changes of Vegetation Greenness Interannual Variability on Half of the Global Vegetated Surface

AbstractChanges in the interannual variability (IAV) of vegetation greenness and carbon sequestration are key indicators of the stability and climate sensitivities of terrestrial ecosystems. Recent studies have examined the changes in the vegetation IAV using atmospheric CO2 observations and dynamic global vegetation models (DGVMs), however, reported different and even contradictory IAV trends. Here, we investigate the changes in the IAV of vegetation greenness, quantified as coefficient of variability (CV), over the past few decades based on multiple satellite remote sensing products and DGVMs. Our results suggested that, on half of the global vegetated surface (mostly in the tropics), the CV trends detected by different satellite remote sensing products are conflicting. We found that 22.20% and 28.20% of the global vegetated surface (mostly in the non‐tropical land surface) show significant positive and negative CV trends (p ≤ 0.1), respectively. Regions with higher air temperature and greater aridity tend to have increasing CV trends, whereas greater vegetation greening trend and higher nitrogen deposition lead to smaller CV trends. DGVMs generally cannot capture the CV trends obtained from satellite remote sensing products, while the inconsistency among satellite remote sensing products is likely caused by their process algorithms rather than the sensors utilized. Our study closely examines the changes in the IAV of global vegetation greenness, and highlights substantial uncertainty when using satellite remote sensing to study the response of terrestrial ecosystems to climate change.

Prevalence of vegetation browning in China’s drylands under climate change

Vegetation greening has long been acknowledged, but recent studies have pointed out that vegetation greening is possibly stalled or even reversed. However, detailed analyses about greening reversal or increased browning of vegetation remain scarce. In this study, we utilized the normalized difference vegetation index (NDVI) as an indicator of vegetation to investigate the trends of vegetation greening and browning (monotonic, interruption, and reversal) through the breaks for the additive season and trend (BFAST) method across China’s drylands from 1982 to 2022. It also reveals the impacts of ecological restoration programs (ERPs) and climate change on these vegetation trends. We find that the vegetation displays an obvious pattern of east-greening and west-browning in China’s drylands. Greening trends mainly exhibits monotonic greening (29.8 %) and greening with setback (36.8 %), whereas browning shows a greening to browning reversal (19.2 %). The increase rate of greening to browning reversal is 0.0342/yr, which is apparently greater than that of greening with setback, 0.0078/yr. This research highlights that, under the background of widespread vegetation greening, vegetation browning is progressively increasing due to the effects of climate change. Furthermore, the ERPs have significantly increased vegetation coverage, with the increase rate in 2000–2022 being twice as much as that of 1982–1999 in revegetation regions. Vegetation browning in southwestern Qingzang Plateau is primarily driven by adverse climatic factors and anthropogenic disturbances, which offset the efforts of ERPs.

Wetting or greening? Probing the global trends in Vegetation Condition Index (VCI)

Vegetation Condition Index (VCI), as a widely used drought index for monitoring vegetation drought stress and estimating drought trends, is constructed by normalizing the long-term satellite-based Normalized Difference Vegetation Index (NDVI) data. However, under global greening, vegetation across different regions has shown an increasing trend in greenness, which may cause VCI to inherit the greening trend in NDVI and further hamper its ability in drought trend analysis. Therefore, this study quantitatively explored the underlying relationship among VCI, global greening, and drought from 2001 to 2021 to examine the utility of VCI in a changing environment. Multi-source indicators were employed as surrogates for vegetation greenness and drought, respectively. Particularly, the Leaf Area Index (LAI) and Net Primary Production (NPP) were used as proxies for vegetation greenness while the Root-Zone Soil Moisture (RZSM), Palmer Drought Severity Index (PDSI), and Standardized Precipitation-Evapotranspiration Index (SPEI) were used for drought indices. Based on Sen’s slope estimator, Mann-Kendall (MK) test, and partial correlation analysis, our results show that the proportion of pixels with an increasing trend in VCI is approximately 38.5%, which is similar to the greenness-related indices (i.e., NPP [26.47%] and LAI [59.14%]), and is significantly higher than the other drought indices (i.e., RZSM [19.83%], PDSI [10.38%], and SPEI [9.32%]). Furthermore, our results demonstrate that the VCI, as a drought index, exhibits a closer correlation with greenness-related indicators (LAI and NPP) than other drought indices (RZSM, PDSI, and SPEI). These results reveal the potential limitations in the practical applications of VCI and could enhance our understanding of vegetation dynamics and drought trends, especially in the current greening globe. Additionally, this study serves as a cautionary note for the scientific community involved in drought monitoring, emphasizing that the VCI may not be a suitable tool for evaluating long-term trends in drought impacts on vegetation.