Average Annual Temperature Research Articles

Critical climate-stress moments for semi-arid farming systems in India

In the face of the increasing frequency of climate stresses, climate change projections can help in adaptation planning and resilience-building. However, typical climate change projections, such as annual average rainfall and temperature increases, are not helpful for farmers in understanding specific climate risks, like crop loss, and making adaptation decisions. Our study aims to identify and characterise context- and time-specific climate stresses in terms of climate conditions of concern to improve the understanding of future climate risks and enhance the climate resilience of semi-arid farming systems in India. Utilising the concept of critical climate-stress moments, we employ an innovative bottom-up methodology integrating insights from focus group discussions with farmers, key informant interviews, and an ensemble of downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP-6) models. Our case studies include (i) a mixed crop-livestock farming system, (ii) a horticulture-based farming system, (iii) a cash crop–dominant farming system, and (iv) a cereal-dominant farming system. The specific climate conditions of concern identified were (i) increasing volume of late-monsoon rainfall, (ii) rising winter temperatures, (iii) increase in the number of days with temperatures exceeding 40 °C, (iv) increase in days with heavy rainfall (> 25 mm), and (v) increasing rainfall during the dry season. Identifying these critical moments improves understanding of both the temporal and spatial variations in climate risks, providing valuable inputs for targeted and implementable climate resilience–building actions. We recommend revising national and state action plans on climate change by utilising such region-specific assessments of critical climate-stress moments.

Land Cover and Land Use Ontology—Evolution of International Standards, Challenges, and Opportunities

Knowledge of land is of central importance to manage the impact of mankind upon the environment. The understanding and treatment of land vary greatly across different regions and communities, making the description of land highly specific to each locality. To address the larger global issues, such as world food production or climate change mitigation, one needs to have a common standardized understanding of the biosphere cover and use of land. Different governments and institutions established national systems to describe thematic content of land within their jurisdictions. These systems are all valid and tuned to address various national needs. However, their integration at regional or global levels is lacking. Integrating data from widely divergent sources to create world datasets not only requires standards, but also an approach to integrate national and regional land cover classification systems. The ISO 19144 series, developed through the collaboration between the Food and Agriculture Organization of the United Nations (FAO) and the International Organization for Standardization (ISO), offers a meta-language for the integration of disparate land classification systems, enhancing interoperability, data sharing, and national to global data integration and comparison. This paper provides an overview of classification system concepts, different stages for the development of standards in ISO and the status of different standards in the ISO 19144 series. It also explores the critical role of the ISO 19144 series in standardizing land cover and land use classification systems. Drawing on practical case studies, the paper underscores the series’ potential to support global sustainable development goals and lays out a path for its future development and application. Using these standards, we gain not only a tool for harmonizing land classification, but also a critical level for advancing sustainable development and environmental stewardship worldwide.

Physiological and antioxidant responses of synthetic hexaploid wheat germplasm under drought

BackgroundAs a result of the world population and climate change impact increases (especially in arid environments), there is a critical need for high-yield, drought-tolerant wheat. Synthetic hexaploid wheat derived lines (SHW-DL), were created artificially by crossing different durum wheat cultivars (AABB) with accessions of Aegilops tauschii (DD), a beneficial source of new genes for common bread wheat (Triticum aestivum L). Here, we studied the response of a panel of 91 SHW-DL for drought tolerance based on physiological, antioxidant enzyme activities, and drought tolerance indices.ResultsA wide range of variation and high values of heritability observed for grain yield, physiological and antioxidant traits indicating that the SHW-DL panel constitutes a valuable gene source for drought tolerance improvement of wheat. Despite decreases in grain yield (YLD), leaf area index (LAI), and relative water content (RWC) an increase in the content of malondialdehyde (MDA) was observed. Moreover, drought streass increased the antioxidant enzyme activities of ascorbate peroxidase (APX), catalase (CAT) and peroxidase (POD), and also photosynthetic pigments, proline (Pro), and MDA content. With higher values of grain yield, physiological and biochemical traits such as photosynthetic pigments, and RWC, and lower content of MDA, and peroxidase (H2O2) activity, SHW-DL performed better compared to common wheat lines under water stress conditions.ConclusionsDifferent responses to water stress within the germplasm and between synthetic and common wheat suggest that selection for adaptive and suitable genotypes is possible for drought tolerance in synthetic wheat germplasm. Genotypes 54, 98, 102, 105, 122, 124, 143, 159, 196, and 198 were identified to be directly used in breeding programs or indirectly by crossing them with other wheat germplasm collections.

Gravel Mulching Significantly Improves Crop Yield and Water Productivity in Arid and Semi-Arid Regions of Northwest China: Evidence from a Meta-Analysis

In the arid and semi-arid regions of Northwest China, periodic rainfall deficits, high field evaporation, limited freshwater resources, and high irrigation costs restrict crop yield and water productivity (WP). Gravel mulching (GM), a traditional agricultural tillage management practice widely used in arid and semi-arid regions, improves crop yield and WP. However, the combined impacts of GM on crop yield and WP are unclear. This study aimed to examine the effects of GM on crop yield and WP under different factors and to find the most critical regional factors and gravel characteristics that affect crop yield and WP. To quantitatively assess the impact of GM on crop yield and WP, this study performed a meta-analysis, a regression analysis, and a path analysis of 185 yield comparisons and 130 WP comparisons from 30 peer-reviewed scientific reports. This study found that GM significantly increased crop yield and WP by an average of 29.47% and 28.03%, respectively. GM was reported with the highest response percentages (I) of crop yield and WP in regions whose average annual precipitation (AAP) was 200–400 mm, average annual temperature (AAT) was 0–9 °C, and altitude (A) was >1000 m. Overall, AAP, AAT, and A had significant effects on the I of crop yield (p < 0.001), but AAT and A had an insignificant impact on the I of crop WP (p > 0.05). Gravel size (GS), the amount of gravel mulching (AGM), the degree of gravel mulching (DGM), and the gravel mulching thickness (GMT) had a significantly positive impact on crop yield and WP (p < 0.05). The stepwise multiple linear regression analysis results indicated that the primary regional factors influencing yield were AAT and A, contributing 43.14% and 53.09%, respectively. GMT and GS were identified as significant gravel characterization factors impacting yield, contributing 82.63% and 17.37%, respectively. AAP and GMT were the main regional factors and gravel characterization factors affecting WP. Furthermore, the I values for cash crop yield and WP were higher than that for food crops, and moderate fertilization and irrigation would increase the I values of yield and WP. The benefits of GM are strongly correlated with the planting year. This study’s results show that GM generally improves crop yield and WP, although the extent of this impact varies based on different conditions. These findings are not only useful in relation to their direct applicability to other countries worldwide but also due to their potential to provide new ideas for agricultural practices in similar crop-growing environments.

Sustainable forest development in the face of global warming: Optimizing Robinia pseudoacacia L. stands to alleviate soil moisture depletion

To foster sustainable forest development amid global warming, it is imperative to enhance the quality of existing forest stands while avoiding excessive depletion of soil moisture. This study established 24 Robinia pseudoacacia L. standard plots (40 × 40 m2) in the Caijiachuan watershed, located in the gully region of the Loess Plateau, Shanxi Province, China, to monitor soil moisture content from 2007 to 2021. Additionally, the study examined the influence of 19 ecological factors, including climate, topography, and stand characteristics, on soil moisture. The findings indicated a sustained decline in soil moisture storage across the 0–200 cm soil profile, with significant depletion at 0–140 cm. The soil moisture content at depths of 80–200 cm was critically low, resulting in a “dry soil layer” during years with low precipitation. Climatic factors (average annual temperature and annual precipitation) and stand factors (uniform angle index, stand density, litter thickness, and Simpson diversity index of the shrubs) emerged as dominant factors impacting soil moisture variations. An increase in average annual temperature due to global warming, compounded by suboptimal stand density, primarily drove soil moisture depletion. Using a multivariate optimization equation to model the relationship between dominant factors and soil moisture storage, this study recommends a dynamic stand management strategy. This strategy involves selective thinning or replanting of Robinia pseudoacacia L. trees, targeting a gradual reduction in optimal stand density from 1500 to 1000 plants·ha−1 over the next two decades. Additionally, transitioning stand spatial arrangements from uniform or clustered to random distributions, maintaining ideal litter thickness (2.43–2.47 cm), and enhancing shrub diversity are advisable. Such measures can alleviate soil moisture deficits in Robinia pseudoacacia L. stands attributable to global warming, thereby promoting the Loess Plateau's sustainable forestry advancement.

Hygrothermal resilience of typical lightweight steel-framed wall assemblies in hot-humid areas under future climate uncertainty

Ensuring the hygrothermal performance of lightweight steel-framed (LSF) wall assemblies is critical for the sustainability of LSF buildings in hot-humid regions; however, climate change poses new challenges. Therefore, this study aimed to bridge the gap in understanding the characteristics of hygrothermal load changes and the hygrothermal resilience of different LSF wall assemblies. Future climate data for each decade of this century (from 2030 to 2090), under various carbon emission scenarios, were generated based on a typical meteorological year (TMY) for hot-humid areas to evaluate the impact of climate change on hygrothermal loads. The hygrothermal resilience of four typical LSF wall assemblies, with either ventilated rainscreen cladding or face-sealed stucco cladding, with or without external insulation, was evaluated through simulation and comparative analysis. The results indicated that the thermal load would increase with increasing carbon emissions and over time, with the annual average external temperature peaking at 25.8 °C by the end of this century. The frequency of months with a high or critical moisture load would increase, although the moisture load may fluctuate across scenarios and years. Consequently, the cooling and dehumidification loads may increase by 52–60 % and 40–88 %, respectively. The hygrothermal risk within the walls may increase, with maximum increases of 2.8–8.0 % in the annual average relative humidity, 2.7–3.0 °C in the annual average temperature, and 10–35 % in the wetness duration. However, the impacts could be reduced by using ventilated rainscreens and external insulation, with further precautions needed to mitigate the increasing hygrothermal risk in areas with thermal bridges and rainwater leakage, as well as at the outer interface of the external insulation. These findings could provide a reference for the design of LSF buildings adapted to climate change in hot-humid areas.

Analysis of Spatiotemporal Evolution Characteristics and Influencing Factors of Vegetation Net Primary Productivity in Shendong Mining Area

Coal plays a key role in the composition of energy production and consumption in China. The mineral is a crucial resource for human economic and social development. The surface subsidence caused by coal mining has attracted disturbance and damage to the surface ecological environments of mining areas. To quantitatively study vegetation carbon sequestration in coal mining areas, this article takes the Shendong mining area as its research object and analyzes the spatiotemporal distribution characteristics and influencing factors of vegetation net primary productivity (NPP). Based on meteorological data, remote sensing images, and land use data in the mining area, this research analyzed the vegetation NPP and its relationship with meteorological factors in the Shendong mining area from 2000 to 2023. The results show that (1) in the past 24 years, the range of NPP variation in the Shendong mining area has been 0–350 gC/m2. The overall NPP shows a fluctuating upward trend. The annual average change in NPP in the mining area is bounded by the two central dividing lines, with a lower value in the central part and a gradually increasing trend in the western and eastern parts. (2) The average vegetation NPP of the Shendong mining area over 24 years was 0–250 gC/m2; after 2011, the annual average NPP of vegetation was higher than this average level, which shows that the ecological environment of the mining area is gradually improving. Coal mining in the mining area has not caused a significant impact on the overall environment of the mining area. (3) There is a significant relationship between NPP and annual cumulative rainfall, average annual temperature, and average annual Normalized Difference Vegetation Index (NDVI). Overall, it is not significantly related to mining factors. The mining factors affect local areas and have a certain correlation.

Climate Change, Biased Technological Advances and Agricultural TFP: Empirical Evidence from China

The impact of climate change on agricultural quality development under the constraint of China’s “Double Carbon” target has been widely discussed by policy practitioners and academic theorists. This paper attempts to deconstruct the logic of how climate change affects agricultural total factor productivity (TFP) in three dimensions—the structure of agricultural input factors, the change in the cropping system, and the stability of crop supply. This paper also reveals the mechanism through which biased technological progress increases agricultural TFP by weakening the magnitude of climate change and empirically tests it by using China’s provincial-level data from 2000 to 2021. This study showed that average annual temperature and annual precipitation had significant negative effects on agricultural TFP, that the number of sunshine hours had a significant positive effect on agricultural TFP, and that obvious regional differences existed in the effect of climate change on agricultural TFP. Further mechanism tests revealed that biased technological progress positively moderated the effect of climate change on agricultural TFP. Based on these findings, the appropriate countermeasures for improving climate early warning mechanisms, promoting the progress of appropriate technology, and fostering new agricultural management bodies.

Exploration of the utilization of a new land degradation index in Lake Ebinur Basin in China

Land degradation significantly impacts regional economic development and food security, particularly in arid river basins where soil and water conservation is crucial. Understanding the extent and causes of land degradation is pivotal for effectively prevention and management. This study employs the soil adjusted vegetation index (SAVI), the temperature vegetation dryness index (TVDI), and the salinization detection index (SDI), combined with the analytic hierarchy process and the entropy weight method, to construct a comprehensive land degradation index (LDI). Sen’s slope trend analysis and the Mann-Kendall significance test were used to analyze land degradation trends in the Ebinur Lake watershed from 2002 to 2022. Additionally, the optimal parameters-based geographical detector was used to examine the underlying mechanisms of land degradation. The results indicate the following: (1) From 2002 to 2012, the degree of land degradation in the Ebinur Lake watershed worsened, particularly in the eastern and southeastern parts, as well as in the southern region of Toli County. From 2012 to 2022, land degradation significantly improved, with a notable reduction in degraded land area. (2) Over the period of 2002-2022, 93.08%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$93.08\\%$$\\end{document} of the land in the research region exhibited a declining LDI trend, 3.95%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$3.95\\%$$\\end{document} showed no change, and only 2.96%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2.96\\%$$\\end{document} showed an increasing LDI trend. (3) Moderate, severe, and very severe degradation mainly occurred on grassland and unused land, while light degradation and non-degradation primarily occurred on forest land and cultivated land. (4) Unreasonable land use and overgrazing were identified as the primary factors influencing land degradation, with elevation being a secondary factor. The interaction between land use and other factors was found to be most significant, followed by the synergistic effects of grazing quantity with elevation, annual average temperature, gross domestic product, soil moisture, and elevation with annual average precipitation, and temperature. The results of this study offer an empirical basis and taking decisions assistance for land degradation control in the Ebinur Lake Basin, as well as examples and references for assessing land degradation in other places.

Влияние абиотических факторов весенне-летнего периода на формирование хозяйственно ценных признаков у сортов черешни (Сerasus avium L.) в условиях юга России

Abstraсt. This paper shows a variation in the yield of 11 studied sweet cherry varieties from a minimum value of 5 kg/tree in 2020 (Dar izobilya variety) to a maximum of 65.0 kg per tree in 2021 (Kavkazskaya variety), which was more dependent on the weather conditions of the growing season. In this regard, the aim of the research is to study the biological features of the formation of indicators of yield and quality of fruits of Russian and introduced varieties of sweet cherries, and related weather and climatic factors. By means of statistical evaluation, the coefficient of variation was established, which was high for all varieties – from 63.1 % to 97.3 %, which indicates strong fluctuations in yield during the study period (2019-2023). The indicator "fruit weight" is a varietal feature, therefore it does not vary much by year of observation within each variety. Thus, the coefficient of variation in the studied varieties ranged from 2.7 % (Sashenka variety) to 15.8 % (Kavkazskaya variety). By varieties, this indicator varied quite strongly from the lowest value in 2022 of 4.3 g (Kavkazskaya variety) to the highest 10.3 g in 2022 (Krupnoplodnaya variety). According to the results of the study, the varieties that are least affected by climatic factors were identified, which had an average yield of 31.5-35.2 kg per tree over 5 years of study, subject to the almost complete absence of fruits in 2020 these include – Alaya, Volshebnitsa and Dar Isobiliay. A correlation has been established between the studied breeding-valuable indicators and various abiotic factors influencing their formation. The yield index had a high correlation with the average annual air temperature R2 = 0.60 and the amount of precipitation in April – R 2 = 0.60. The fruit weight indicator was most dependent on the average monthly temperature in June, in this case the correlation coefficient was – R 2 = 0.80, as well as the amount of precipitation for the year – R 2 = 0.54. Keywords: variety, sweet cherry, abiotic factors, yield, productivity, fruit weight. Financing source: The research was carried out within the State Task of Ministry of Science and Higher Education of the Russian Federation for the FSBSI NCFSCHVW.

Utilizing Multi-Source Datasets for the Reconstruction and Prediction of Water Temperature in Lake Miedwie (Poland)

Water temperature is a fundamental parameter of aquatic ecosystems. It directly influences most processes occurring within them. Hence, knowledge of this parameter’s behavior, based on long-term (reliable) observations, is crucial. Gaps in these observations can be filled using contemporary methodological solutions. Difficulties in reconstructing water temperature arise from the selection of an appropriate methodology, and overcoming them involves the proper selection of input data and choosing the optimal modeling approach. This study employed the air2water model and Landsat satellite imagery to reconstruct the water temperature of Lake Miedwie (the fifth largest in Poland), for which field observations conducted by the Institute of Meteorology and Water Management—National Research Institute ended in the late 1980s. The approach based on satellite images in this case yielded less accurate results than model analyses. However, it is important to emphasize the advantage of satellite images over point measurements in the spatial interpretation of lake thermal conditions. In the studied case, due to the lake’s shape, the surface water layer showed no significant thermal contrasts. Based on the model data, long-term changes in water temperature were determined, which historically (1972–2023) amounted to 0.20 °C per decade. According to the adopted climate change scenarios by the end of the 21st century (SSP245 and SSP585), the average annual water temperature will be higher by 1.8 °C and 3.2 °C, respectively. It should be emphasized that the current and simulated changes are unfavorable, especially considering the impact of temperature on water quality. From an economic perspective, Lake Miedwie serves as a reservoir of drinking water, and changes in the thermal regime should be considered in the management of this ecosystem.

Changes in Snow Cover and Its Surface Temperature across the Tibetan Plateau Region from 2000 to 2020

Currently, the global climate system is complex and ever-changing, with multiple factors influencing climate change. The Qinghai–Tibet Plateau, known as the “Third Pole” of the Earth, is particularly sensitive to global climate change. Without timely and scientific research on the ecological environment of the Qinghai–Tibet Plateau and without summarizing relevant adaptive strategies, global climate change will impact the sustainable development of the plateau. This study utilized Landsat remote sensing images from 2000 to 2020 to extract the snow cover area and snow temperature of the Qinghai–Tibet Plateau using the snow frequency threshold method. The study analyzed the spatiotemporal characteristics of snow cover and temperature over the 20-year period and investigated some of the climate and topographical driving factors influencing their changes. The results showed that from 2000 to 2020, the permanent snow cover area in the Qinghai–Tibet Plateau region showed a fluctuating decreasing trend, reducing from approximately 12.34 thousand km2 to around 9.01 thousand km2; the permanent snow temperature showed an initial increase followed by a decrease during the same period. The highest annual average snow temperature was approximately −3.478 °C, while the lowest annual average temperature was around −8.150 °C. Over the 20-year period, the snow cover area in the plateau was negatively correlated with temperature and precipitation, while snow temperature was positively correlated with temperature and precipitation. The snow cover in the weak wind areas of the plateau showed a significant reduction. Areas with higher average wind speeds, such as shaded slopes and semi-shaded slopes, had larger snow cover areas. These research findings provide important insights into the protection and management of the ecological environment of the Qinghai–Tibet Plateau.

ФАКТОРЫ ОКРУЖАЮЩЕЙ СРЕДЫ И ЗАРАЖЕННОСТЬ ЛОШАДЕЙ ЖЕЛУДОЧНО-КИШЕЧНЫМИ ГЕЛЬМИНТАМИ В ГОРНОМ АЛТАЕ

The aim of the study is to conduct a comparative assessment of the infestation of horses with intestinal helminths in various administrative districts and to characterize the patterns of the relationship between abiotic and anthropogenic environmental factors and the rates of infestation of horses with intestinal helminths in the Gorny Altai. Based on long-term (2019–2023) ovoscopic examinations of 1.2 thousand horses from 10 districts of the region, the infestation of animals with helminths of the gastrointestinal tract was characterized. Correlation analysis was used to characterize the relationship between the level of infestation of animals with helminths, the number of parasites with abiotic and anthropogenic environmental factors in the context of farms and districts of the Gorny Altai. Horses are mostly infected with helminths in the Chemalsky District, where the prevalence of infestation is 95.8 %, and the infection intensity is 458.3 eggs per gram of feces. The lowest prevalence of helminths in animals was recorded in the Ust-Kansky District – EI 56.3 %, with IIs – 186.7 specimens. g/f. The prevalence of infestation in animals is significantly lower in areas characterized by low temperatures and precipitation, and significantly higher in warmer and more humid areas of the region. The prevalence of infestation in horses is 84.6 %, with IIs – 337.5 specimens. g/f. The most significant factors influencing the infection of animals with intestinal helminths (EI, % and IIs) in farms are the long-term average annual precipitation (r = 0.42 and 0.52) and the degree of anthropogenic pressure (r = –0.55 and –0.63), in the context of regions, long-term average annual temperatures (r = 0.55 and 0.65) and long-term average precipitation (r = 0.69 and 0.65).

The possibilities of GIS technologies for assessing and monitoring the climatic conditions of the Makazhoy Fepression (Chechen Republic, Russia)

Modeling based on a digital relief model of the spatiotemporal change in the amount of total solar radiation and the assessment of the contribution of locations to the distribution of meteorological elements.DEM analysis was conducted in a GIS environment to assess the spatial and temporal distribution of total solar radiation, and statistical analysis of retrospective climatic and actual (2023) meteorological data was conducted.Based on a digital model of the relief of average spatial resolution in a GIS environment, changes in the spatial and temporal magnitude of solar radiation were estimated. A prospective analysis of climatic conditions made it possible to assess the general features of the climate of the Makazhoy basin Field observations made it possible to characterize modern climatic conditions, as well as to calculate gradients.Depending on the locations, it was determined that the amount of total solar radiation in the Makazhoy basin varies by almost 3 times. Within the same altitude intervals, the difference between the slopes of the southern and northern exposures reaches up to 50 %. The smallest differences in the amount of radiation were observed on the days of the summer solstice, and the largest on the days of the winter solstice. The average annual air temperature in the altitude range of 1960–2264 m in 2023 varied from 8.6 to 5.8°, and the amount of precipitation – from 481 to 525 mm, respectively. The intra‐annual course of meteorological parameters (air temperature and leaf surface, precipitation and relative humidity) within the meteorological transect has been revealed. The data obtained make it possible to proceed to the formation of a GIS system for monitoring the climatic conditions of the carbon landfill of the Kadyrov Chechen State University.

Climate state of the Three Gorges Region in the Yangtze River basin in 2022–2023

Based on daily observation data of the Three Gorges Region (TGR) of the Yangtze River basin and global reanalysis data, the climate characteristics, climate events, and meteorological disasters of the TGR in 2022 and 2023 were analyzed. For the TGR, the average annual temperature for 2022 and 2023 was 0.8 °C and 0.4 °C higher than normal, respectively, making them the two warmest years in the past decade. In 2022, the TGR experienced its warmest summer on record. The average air temperature was 2.4 °C higher than the average, and there were 24.8 days of above-average high temperature days during summer. Rainfall in the TGR varied significantly between 2022 and 2023. Annual rainfall was 18.4 % below normal and drier than normal in most parts of the region. In contrast, the precipitation in 2023 was considerably higher than the long-term average, and above normal for almost the entire year. The average wind speed exhibited minimal variation between the two years. However, the number of foggy days and relative humidity increased in 2023 compared to 2022. In 2022–2023, the TGR mainly experienced meteorological disasters such as extreme high temperatures, regional heavy rain and flooding, overcast rain, and inverted spring chill. Analysis indicates that the abnormal western Pacific subtropical high and the abnormal persistence of the eastward-shifted South Asian high were the two important drivers of the durative enhancement of record-breaking high temperature in the summer of 2022.摘要基于长江三峡地区观测资料和全球再分析资料, 分析了该地区 2022–2023年气候特征, 酸雨状况以及主要天气气候事件. 2022 年和2023年三峡地区平均气温分别较常年偏高0.8 °C和0.4 °C, 是近十年来最暖的两年, 特别是2022年夏季出现破记录极端高温; 2022年三峡地区降水量较常年偏少18.4 %, 2023年降水量转为偏多15.3 %. 在这两年中该地区主要出现了极端高温, 区域性暴雨洪涝, 连阴雨和倒春寒等气候事件. 分析表明, 西太平洋副热带高压和南亚高压协同异常是2022年夏季极端高温维持的两个重要因素.

Economic assessment of the impact of climate change on agriculture in Albania and Ukraine

This study aimed to provide a comparative analysis of the impacts of climate change on the agricultural sector in Albania and Ukraine, with a focus on identifying key challenges and opportunities for adaptation. The study analysed statistical data from 2010 to 2023 on climate change and its impact on agriculture and assessed the consequences. The results of the study showed that changes in temperature regimes are a key factor that directly affects agriculture. An increase in average annual temperatures leads to a change in the growing season of plants, which has both positive and negative consequences. Changes in precipitation patterns are another key mechanism of climate change impact on agriculture. Reduced precipitation and frequent droughts can lead to significant crop losses, requiring the introduction of irrigation systems and other water-saving technologies. Economic risks associated with climate change are a serious challenge for agriculture. Reduced yields, higher production costs and the need to adapt to new conditions can threaten the stability of farms, especially small ones. The analysis for Albania showed that rising temperatures and decreasing precipitation pose challenges for agriculture, particularly for cereal and vegetable production. In Ukraine, with its large area of arable land, there is scope to compensate for the decline in yields by expanding the area under cultivation, but investment in new irrigation technologies and agronomic practices is needed to improve efficiency. Both countries face the need to introduce new plant varieties, modernize irrigation systems, and develop agricultural innovation and precision farming. Effective adaptation strategies, including international cooperation and support for research, are key to ensuring the sustainability of the agricultural sectors in both countries. The findings of the study can be applied in practice to government agricultural support programmes and international climate change adaptation projects

Enterprise Digital Transformation and Environmental Performance

The need to improve corporate environmental performance has emerged as a crucial and urgent study topic as the world's pollution and climate challenges get worse. This trend has taken on new meaning and importance in light of the expanding digital economy and digital transformation. Using financial and associated data from 2009 to 2021 as the sample, this research empirically studies the link between digital transformation, green innovation, and environmental performance with a focus on China's A-share listed enterprises. According to the study's findings, digital transformation may improve a company's environmental performance by strengthening its capacity for green innovation. Furthermore, heterogeneity analysis shows that the effect of digital transformation in enhancing environmental performance is more prominent in high-tech enterprises, non-heavy polluting companies, and organizations with a greater percentage of party members in senior management.

Carbon capture and storage at Malaysia power plants: Evaluation of its feasibility and requisite enablers

Rapidly growing GHG emissions are significantly altering the world climate, necessitating a global decarbonization efforts to avert irreversible catastrophic failure of the world ecosystem. Malaysia is pledging to achieve carbon neutrality by 2050 and has subsequently identified Carbon Capture and Storage (CCS) as one of the solutions for carbon removal from its energy sector by 2050. However, the implementation of CCS presents formidable challenges, encompassing both technical and commercial complexities, especially for a nation like Malaysia, which has limited experience in large-scale CCS deployment. This study evaluates the feasibility of CCS implementation in Malaysia's fossil fuel power plants by conducting a comprehensive techno-economic assessment, taking into considerations the prevailing energy landscape of the country. This assessment is very crucial to demonstrate the feasibility of this plan within the timeframe, considering the limited research have been done to assess a national-scale implementation, as well as to provide the important insights for future policy implication to promote CCS adoption. The CCS scenarios are assessed through an analytical approach, and comparative analyses are conducted between alternative paths. The result shows that a large-scale implementation of CCS at Malaysia's fossil fuel power plant to achieve net-zero emission by 2050 are feasible given a strong enforcement on emission policy and establishment of CCS legal framework. CCS can potentially reduce 60% of Malaysia's energy sector total emissions, and a solar-supported CCS helps to reduce it further. Levelized Cost of Electricity analysis reveals that the implementation of CCS leads to only a minimal increase between pre- and post-CCS LCOE when carbon price is considered. A SWOT-PESTLE analysis was also conducted to identify gaps in regulatory framework, financial and social aspects. It can be concluded that CCS is a techno-economically viable solution, however Malaysia's readiness for CCS implementation is still at a very novice stage, and aggressive actions are needed to enable a successful full-scale implementation.

Representation of Climate Change in the Documentary Film Ano Bulan Balong (Semiotic Analysis of Roland Barthes)

Climate change is a condition characterized by changes in world climate patterns which result in erratic weather phenomena. Climate change occurs due to changes in climate variables, such as air temperature and rainfall, which occur continuously. In this research, film is the subject, film is a mass communication tool that is packaged with characters, plot and messages in it, provides information to the audience through the storyline that is conveyed and has a strong influence on issues that are developing in society, the unit of analysis of this research contains "Semiotic Analysis of Roland Barthes' Representation of Climate Change in the Documentary Film Ano Bulan Balong". The aim of this research is to determine the representation of climate change in the film Ano Bulan Balong based on Roland Barthes' stereotypes. This research uses Roland Barthes' semiotic theory, where the researcher looks for the meaning of Denotation, Connotation and Myth in several scenes in the film Ano Bulan Balong. . The results of research on the documentary film Ano Bulan Balong can be linked to environmental issues, namely climate change. Researchers group and categorize messages to convey meaning in the film Ano Bulan Balong, including; environmental message, Through semiotic analysis, Roland Barthes in this film shows that the problem currently being faced by Sumbawa is unrest triggered by environmental problems which are a factor in climate change, forest lands full of trees are starting to disappear, replaced by corn plants. Critical trees resulting from deforestation will cause extreme natural disasters.

A preliminary integrated analysis of regional paleoclimate variations in China over the past ∼ 21 ka

In this study, we employ biological, geochemical and mineral, and physical proxies to quantitatively and semi-quantitatively reconstruct regional paleoclimate variations in China over the past ∼21 thousand years (ka). We have constructed state-of-the-art transfer functions between proxies and climatic variables in East Asia, revealing substantial paleoclimate variability, and demonstrate significant diversity of paleoclimate variations in regions of China over the past ∼21 ka. Compared with observational data between 1961 and 1990, averaged mean annual temperature (MAT) was ∼5 °C (3–8 °C) lower during the Last Glacial Maximum (LGM, ∼21 ± 3 ka), and ∼ 2 °C (1–3 °C) higher during Holocene Optimum (HO, ±9 ka) in China; while averaged mean annual precipitation (MAP) and averaged summer precipitation varied between 30 and 150%, with enhanced seasonality during the warmer Holocene (8–5 ka). Our quantitative and semi-quantitative paleoclimate reconstructions reveal both similarities and contrasts with previous studies of regional temperature and precipitation variability. The most remarkable paleoclimate variability is recorded in the transitional zone between the humid monsoon and arid desert regions of central and northern China. We conducted a dynamic downscaling paleoclimate simulation with a regional climate model (RegCM4), using the output from the fully-forced transient simulation of the global climate (TraCE-21 K) as the prescribed boundary conditions, to simulate regional climate changes at high spatial resolution in China over the past ∼21 ka. The results improve paleoclimate simulations at regional scales, but reveal differences in comparison with TraCE-21 K, thereby highlighting uncertainties in the simulation modeling. Moreover, we compare proxy-based paleoclimate reconstructions and the output of TraCE-21 K to identify inconsistencies in relation to regional paleoclimate variations, and confirm a generally consistent warming trend in MAT from the LGM to the HO followed by a cooling trend during the late Holocene. An overall increase in both annual and summer precipitation is observed from LGM to Holocene. This general paleoclimate pattern is likely to have been driven by northern hemisphere ice volume and atmospheric greenhouse gas concentrations (GHGs) during the last deglaciation, and boreal summer insolation during the Holocene. This study represents the first attempt to use multi sources and large datasets of proxy reconstructions and numerical simulations to evaluate regional paleoclimate variability in China since the LGM. Our research provides a comprehensive overview of climate change over the past 21 ka and underscores the critical importance of conducting high-resolution simulations and quantitative paleoclimate studies. This approach is essential for deciphering patterns of paleoclimate change that are currently poorly defined.