Global Warming Intensifies Research Articles

Identification and Analysis of the Superoxide Dismutase (SOD) Gene Family and Potential Roles in High-Temperature Stress Response of Herbaceous Peony (Paeonia lactiflora Pall.).

The herbaceous peony (Paeonia lactiflora Pall.) plant is world-renowned for its ornamental, medicinal, edible, and oil values. As global warming intensifies, its growth and development are often affected by high-temperature stress, especially in low-latitude regions. Superoxide dismutase (SOD) is an important enzyme in the plant antioxidant systems and plays vital roles in stress response by maintaining the dynamic balance of reactive oxygen species (ROS) concentrations. To reveal the members of then SOD gene family and their potential roles under high-temperature stress, we performed a comprehensive identification of the SOD gene family in the low-latitude cultivar 'Hang Baishao' and analyzed the expression patterns of SOD family genes (PlSODs) in response to high-temperature stress and exogenous hormones. The present study identified ten potential PlSOD genes, encoding 145-261 amino acids, and their molecular weights varied from 15.319 to 29.973 kDa. Phylogenetic analysis indicated that PlSOD genes were categorized into three sub-families, and members within each sub-family exhibited similar conserved motifs. Gene expression analysis suggested that SOD genes were highly expressed in leaves, stems, and dormancy buds. Moreover, RNA-seq data revealed that PlCSD1-1, PlCSD3, and PlFSD1 may be related to high-temperature stress response. Finally, based on the Quantitative Real-time PCR (qRT-PCR) results, seven SOD genes were significantly upregulated in response to high-temperature stress, and exogenous EBR and ABA treatments can enhance high-temperature tolerance in P. lactiflora. Overall, these discoveries lay the foundation for elucidating the function of PlSOD genes for the thermotolerance of herbaceous peony and facilitating the genetic breeding of herbaceous peony cultivars with strong high-temperature resistance.

Measuring shaded bike lanes for heat stress mitigation with deep learning: A case study in Amsterdam, Netherlands

As global warming intensifies and heatwaves become more frequent, thermal comfort has emerged as a crucial factor in creating habitable and equitable urban environments. Cities worldwide are promoting sustainable transportation and reducing vehicle usage by enhancing cycling infrastructures. However, the thermal comfort of cyclists has often been neglected, with most research focusing on pedestrians. This study introduces a framework for evaluating shade levels along the bike lanes by incorporating a ‘Shade Index’ that quantifies street shadiness. Utilizing deep learning techniques, the index analyzes street view images from various bike lane locations to evaluate the contribution of trees and buildings in providing shade. The application of this framework is a shade rating map of the bike lanes in Amsterdam, providing cyclists with alternatives that prioritize coolness over the shortest routes typically suggested by map applications, particularly useful during warmer weather. The study identifies significant variability in shade provision, with central urban areas typically more shaded than outlying regions. The workflow can be adapted to other cities to enhance shade provision for cycling infrastructures.

탄소저감 기술동향 분석 및 적용사례 연구 - 공원 및 숲을 중심으로

As the threat of climate change due to global warming intensifies, the world is increasingly experiencing extreme weather phenomena. Consequently, the importance of achieving carbon neutrality is expected to grow. Parks and forests play a crucial role in capturing and storing carbon, offering the most eco-friendly spaces that provide convenience and relaxation for users, as well as resilience for cities. They also serve as essential elements of carbon neutrality with their scenic and touristic value. This study focuses on these aspects, reviewing the trends in existing carbon reduction technologies and investigating carbon dioxide capture and utilization technologies that can increase the amount of carbon that parks and forests can capture. These technologies were classified according to six principles, identifying bioconversion technology as the most applicable and dry capture and mineral carbonation technologies as relatively superior. The study analyzes the current policy foundation and shortcomings for the commercialization and business application of these technologies, along with future improvements that need to be addressed. The purpose of this research is to establish a foundation for creating carbon-neutral parks and forests by identifying applicable technologies, assessing policy hurdles, and suggesting improvements, thereby enabling faster and more efficient carbon absorption and storage. According to the findings of this study, by identifying and expanding the application of technologies suitable for parks and forests and improving policies accordingly, it is expected that a more eco-friendly and efficient reduction of carbon dioxide can be achieved.

Weakening of La Niña Impact on Negative Indian Ocean Dipole Under Global Warming

AbstractAs global warming intensifies, the coupling relationship between negative Indian Ocean Dipole (nIOD) and La Niña has substantially changed. However, the characteristics and mechanisms of these changes are not yet fully understood. Here, we find that the impact of La Niña on nIOD has considerably weakened since 1999, with the frequency of nIOD occurrences during La Niña years plummeting to a mere one‐third of the pre‐1999 levels. This is primarily attributed to the early onset of Indian summer monsoon and the decrease in La Niña intensity, while the effect of variations in Bjerknes feedback is relatively minor. Model simulations suggest that the influence of La Niña on nIOD will continue to weaken under future global warming through similar mechanisms as in the observations, increasing the complexity of air‐sea coupling in the Indian Ocean.

Biofuel–Electric Hybrid Aircraft Application—A Way to Reduce Carbon Emissions in Aviation

As global warming intensifies, the world is increasingly concerned about carbon emissions. As an important industry that affects carbon emissions, the air transportation industry takes on the important task of energy saving and emission reduction. For this reason, major airlines have designed or will design different kinds of new-energy aircraft; however, each aircraft has a different scope of application according to its energy source. Biofuels have an obvious carbon emission reduction effect in the whole life cycle, which can offset the drawback of the high pollutant emission of traditional fossil fuels in the preparation and combustion stages. At the same time, a battery has zero emissions in the operating condition, while the low energy density also makes it more applicable to short-range navigation in small aircraft. In this paper, the development direction of a biofuel–electric hybrid aircraft is proposed based on the current development of green aviation, combining the characteristics of biofuel and electric aircraft.

The Impact of High-Temperature Stress on Gut Microbiota and Reproduction in Siberian Hamsters (Phodopus sungorus).

Global warming has induced alterations in the grassland ecosystem, such as elevated temperatures and decreased precipitation, which disturb the equilibrium of these ecosystems and impact various physiological processes of grassland rodents, encompassing growth, development, and reproduction. As global warming intensifies, the repercussions of high-temperature stress on small mammals are garnering increased attention. Recently, research has highlighted that the composition and ratio of gut microbiota are not only shaped by environmental factors and the host itself but also reciprocally influence an array of physiological functions and energy metabolism in animals. In this research, we combined 16S rRNA high-throughput sequencing with conventional physiological assessments, to elucidate the consequences of high-temperature stress on the gut microbiota structure and reproductive capacity of Siberian hamsters (Phodopus sungorus). The results were as follows: 1. The growth and development of male and female hamsters in the high-temperature group were delayed, with lower body weight and reduced food intake. 2. High temperature inhibits the development of reproductive organs in both female and male hamsters. 3. High temperature changes the composition and proportion of gut microbiota, reducing bacteria that promote reproduction, such as Pseudobutyricoccus, Ruminiclostridium-E, Sporofaciens, UMGS1071, and CAG_353. Consequently, our study elucidates the specific impacts of high-temperature stress on the gut microbiota dynamics and reproductive health of Siberian hamsters, thereby furnishing insights for managing rodent populations amidst global climatic shifts. It also offers a valuable framework for understanding seasonal variations in mammalian reproductive strategies, contributing to the broader discourse on conservation and adaptation under changing environmental conditions.

Long-term temporal and spatial divergence patterns of urban heat risk in the Beijing–Tianjin–Hebei urban agglomeration

As urbanization accelerates and global warming intensifies, urban heat risks are increasingly becoming a critical issue and addressing this challenge to foster more harmonious and livable urban environments is essential. In our study, multisource remote sensing and point-of-interest (POI) data were applied to assess the urban heat risks in the Beijing-Tianjin-Hebei (BTH) urban agglomeration from 2001 to 2020. The results indicated that the heat hazard, exposure, and sensitivity were notably greater in the southeastern of the BTH. Conversely, the heat adaptability was lower in the southeast, leading to a severe high heat risk in this region. From 2001 to 2020, the heat risk index (HRI) values for these cities generally displayed an upward trend, peaking in 2015. Among the cities, Handan had the highest heat risk, followed by Baoding and Beijing, with HRIs of 0.32, 0.32, and 0.31, respectively. In urban areas, commercial zones had the highest average HRI at 0.3, while public management zones had the lowest at 0.28. These findings highlight significant variations in heat risk, indicating the need for targeted urban planning and heat mitigation strategies in the most affected areas of the BTH.

Impact of extreme rainfall events on soil erosion on karst Slopes: A study of hydrodynamic mechanisms

As global warming intensifies, frequent extreme rainfall events cause severe soil erosion. ​However, the impact of extreme rainfall on erosion on karst slopes and its hydrodynamic mechanisms are still poorly understood. This study aims to examine how extreme rainfall events and slope gradient affect soil erosion on karst slopes and its underlying dynamic mechanisms. Simulation experiments were performed in a steel tank that mimicked the dual hydrological structure of a karst slope, using various rainfall intensities (50, 105, 115, 125, and 145 mm·h−1) and slope gradients (5°, 15°, and 25°). The results show that in the event of extreme rainfall (105 – 145 mm·h−1), there was a substantial increase in the surface runoff coefficient, rising from 48.85 % to 89.79 %, representing an 83.81 % increase. Surface erosion was found to be the predominant factor on the slope, contributing to 98.74 % to 99.98 % of the overall sediment output, while underground sediment coefficient ranged from only 0.02 % to 1.26 % under same conditions. The unit stream power emerged as the most suitable hydrodynamic parameter for characterizing surface sediment yield (SS), with a critical threshold of unit water flow power for surface erosion identified at 0.006 m·s−1. Constructing a surface erosion model (R2 = 0.969) based on runoff velocity, rain intensity, and slope yields higher accuracy than the model (R2 = 0.966) based solely on runoff modulus, rain intensity, and slope. For the most precise predictions, it is recommended to combine runoff modulus and velocity with rainfall intensity and slope when constructing the surface erosion prediction model(R2 > 0.999). This study enhances understanding of extreme rainfall’s effect on soil erosion in karst slopes and backs the creation of prediction models for such events. Our insights offer fresh perspectives for soil and water conservation, aiding in the formulation of precise erosion control strategies for karst slopes.

Study on Spatial-Temporal Evolution, Decoupling Effect and Influencing Factors of Tourism Transportation Carbon Emissions: Taking North China as an Example

As global warming intensifies, reducing carbon emissions has become a global common mission. Tourism transportation is one of the important sources of carbon emissions, and reducing its carbon emissions is a key part of achieving China’s carbon reduction goals. Based on the panel data of various provinces and cities in North China from 2000 to 2022, this paper calculates the carbon emissions of tourism transportation by using the carbon emission coefficients of different transportation modes in different segments. Moreover, the temporal and spatial evolution of the tourism economy is systematically analyzed. The Tapio decoupling model and LMDI addition decomposition model are used to analyze the relationship between carbon emissions and tourism economic growth and the effects of 11 influencing factors on carbon emissions. The results show that: ① The carbon emission of tourism transportation in North China has experienced four stages: a steady growth period, a transitional adaptation period, a stable equilibrium period, and a drastic decline period. The overall carbon emission level of tourism transportation is as follows: Hebei Province > Shanxi Province > Inner Mongolia Autonomous Region > Beijing City > Tianjin City. ② The decoupling coefficient between tourism traffic carbon emissions and economic development fluctuates but mainly shows a weak decoupling state. ③ In terms of influencing factors, passenger size and passenger density have the greatest impact on the carbon emissions of tourism transportation.

Insurer hedging amidst the interplay of black and green swans toward SDGs 3 and 7

Amid regional conflicts and global warming, the interplay of catastrophic events (black swans) and sustainability issues (green swans) emerges, impacting sustainable insurance and environmental initiatives tied to Sustainable Development Goals (SDGs) 3 (Good Health and Well-being) and 7 (Affordable and Clean Energy). This paper develops a structure-break down-and-out option model to investigate insurer hedging strategies toward SDGs 3 and 7 in the context of sustainable insurance amidst the intertwined dance of black and green swans. There are several main results shown as follows. Enhancing hedging strategies bolsters an insurer's interest margin and mitigates default risk. As the impact of events like regional conflicts and global warming intensifies, the adverse effects of hedging on default risk become clearer, enhancing insurance stability. Both black and green swan events positively affect the insurer's interest margin and default risk. Strict capital regulations are vital for sustainable insurance, safeguarding policyholders and fostering stability during extreme events. In essence, employing robust hedging strategies and adhering to rigorous capital regulations within the framework of sustainable insurance, considering both black and green swan events, proves to be instrumental in advancing toward the achievement of SDGs 3 and 7.

L-arginine alleviates heat stress-induced mammary gland injury through modulating CASTOR1-mTORC1 axis mediated mitochondrial homeostasis

As global warming intensifies, extreme heat is becoming increasingly frequent. These extreme heatwaves have decreased the milk production of dairy animals such as cows and goats and have caused significant damage to the entire dairy industry. It is known that heat stress (HS) can induce the apoptosis and autophagy of mammary epithelial cells (MECs), leading to a decrease in lactating MECs. L-arginine can effectively attenuate HS-induced decreases in milk yield, but the exact mechanisms are not fully understood. In this study, we found that HS upregulated the arginine sensor CASTOR1 in mouse MECs. Arginine activated mTORC1 activity through CASTOR1 and promoted mitochondrial biogenesis through the mTORC1/PGC-1α/NRF1 pathway. Moreover, arginine inhibited mitophagy through the CASTOR1/PINK1/Parkin pathway. Mitochondrial homeostasis ensures ATP synthesis and a stable cellular redox state for MECs under HS, further alleviating HS-induced damage and improving the lactation performance of MECs. In conclusion, these findings reveal the molecular mechanisms by which L-arginine relieves HS-induced mammary gland injury, and suggest that the intake of arginine-based feeds or feed additives is a promising method to increase the milk yield of dairy animals in extreme heat conditions.

Exploring Urban XCO2 Patterns Using PRISMA Satellite: A Case Study in Shanghai

As global warming intensifies, monitoring carbon dioxide (CO2) has increasingly become a focal point of research. Investigating urban XCO2 emission systems holds paramount importance, given the pivotal role of cities as major contributors to carbon emissions. Consequently, this study centers on urban locales, employing Shanghai as a case study for a comprehensive evaluation of regional XCO2 levels. We utilized high spatial resolution imagery from the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite to conduct an XCO2 assessment over the Baoshan District with a 30 m spatial resolution from April 2021 to October 2022. Our XCO2 analysis was conducted in two steps. Firstly, we conducted a sensitivity analysis on key parameters in the inversion process, where cloud cover severely interfered with inversion accuracy. Therefore, we developed the Fmask 4.0 cloud removal and iterative maximum a posteriori differential optical absorption spectroscopy (FIMAP-DOAS) algorithm. This novel integration eliminated cloud interference during the inversion process, achieving high-precision CO2 detection in the region. Secondly, we compared the XCO2 of the region with Level-2 data from carbon monitoring satellites such as OCO-2. The comparison results showed a strong consistency, with a root mean squared error (RMSE) of 0.75 ppm for Shanghai XCO2 data obtained from the PRISMA satellite compared to OCO-2 Level-2 data and an RMSE of 1.49 ppm compared to OCO-3. This study successfully established a high-accuracy and high-spatial-resolution XCO2 satellite monitoring system for the Shanghai area. The efficacy of the FIMAP-DOAS algorithm has been demonstrated in CO2 monitoring and inversion within urban environments, with potential applicability to other cities.

The Probability of Ship Collision during the Fully Submerged Towing Process of Floating Offshore Wind Turbines

As global warming intensifies, the development of offshore wind farms is swiftly progressing, especially deep-water Floating Offshore Wind Turbines (FOWTs) capable of energy capture in deep-sea regions, which have emerged as a focal point of both academic and industrial interest. Although numerous researchers have conducted comprehensive and multifaceted studies on various components of wind turbines, less attention has been paid to the operational stage responses of FOWTs to wind, waves, and currents and the reliability of their structural components. This study primarily employs a theoretical analysis to establish mathematical models under a series of reasonable assumptions, examining the possibility of collisions between FOWT transport fleets and other vessels in the passage area during the towing process. Using the model, this paper takes the Wanning Floating Offshore Wind Farm (FOWF) project, which is scheduled to be deployed in the South China Sea, as its research object and calculates the probability of collisions between FOWTs and other vessels in three months from the pier near Wanning, Hainan, to a predetermined position 22 km away. The findings of the analysis indicate that the mathematical model developed in this study integrates the quantities and velocities of navigational vessels within the target maritime area as well as the speeds, routes, and schedules of the FOWT transport fleet. By employing statistical techniques and geometric calculations, the model can determine the frequency of collisions between various types of vessels and the FOWT transport fleet during the transportation period. This has substantial relevance for future risk assessments and disaster prevention and mitigation measures in the context of FOWT transportation.

Balancing thermal comfort and energy efficiency in high-rise public housing in Hong Kong: Insights and recommendations

As global warming intensifies, passive design for public housing in hot and humid climates has become a pressing issue. Achieving a balance between thermal comfort and energy conservation is particularly challenging in low-income public rental housing, where residents may endure extended periods of uncomfortable and unhealthy thermal conditions without resorting to air conditioning. In this study, EnergyPlus simulations are employed in combination with a novel thermal-comfort-based HVAC control approach to evaluate the performance of 14 Passive Cooling Strategies (PCS) in optimizing thermal comfort and energy conservation in high-rise public apartments of various sizes and orientations in Hong Kong, particularly under extreme summer conditions. The results reveal that, during extreme summer weather, the implementation of PCS primarily enhances thermal comfort conditions in May and September, while facing challenges in creating comfortable conditions during peak summer months. Most PCSs struggle to improve indoor comfort while simultaneously reducing energy consumption, with two exceptions: 1) Cross-ventilation-based designs enhance thermal comfort without increasing cooling energy consumption. 2) With energy-saving HVAC and opening control behavior, coupled with the use of fans for improving indoor thermal comfort, all PCSs can achieve a simultaneous improvement in thermal comfort and a reduction in cooling energy consumption. This results in a reduction in summer air-conditioning operation time of up to 50% and a decrease in air-conditioning cooling energy consumption of up to 30%. Regarding the impact of building size and orientation: 1) Small apartments show a heightened sensitivity to PCSs, particularly concerning indoor temperature, thermal comfort, and cooling energy consumption. 2) The influence of building orientation on cooling and comfort time in any PCS varies by less than 10% of its average and is even lower in PCSs with lower internal heat gain.

Susceptibility analysis of glacier debris flow by investigating glacier changes based on remote sensing imagery and deep learning: A case study

Glacier debris flow is becoming increasingly severe as global warming intensifies. To minimize the catastrophic losses caused by glacier debris flow, it is essential to analyze the susceptibility of glacier debris flow. In this study, we employed remote sensing with deep learning methods to investigate glaciers changes, evaluating the susceptibility of glacier debris flow in Zelongnong ravine, Southeast Tibet. First, we utilized Landsat optical remote sensing imageries to obtain the semantic segmentation dataset and trained a deep learning model to automatically extract the glacier boundary in Zelongnong ravine. Second, by pre-processing the DEMs (Digital Elevation Model) and integrating them with the glacial boundaries, the volume of glacier ablation was measured. Eventually, according to the glacier ablation, the correction coefficient was determined, which modified the geomorphic information entropy theory, and further analyzed the susceptibility of glacier debris flow in Zelongnong ravine. The research results of the study present that the evaluation indices of the deep learning model that extracted glacier boundaries are over 90%. Moreover, the study results confirm the accuracy of the modified susceptibility evaluation method for glacier debris flows, and the susceptibility of glacier debris flows in Zelongnong ravine generally ranges between high and very high. This study reveals the feasibility and progress of using remote sensing and deep learning in glacier boundary extraction, providing a promising reference for the evaluation of the susceptibility and prediction of glacier debris flow in similar high mountainous areas as well.

Climate change and fluid status in children: early education as one response to an emerging public health problem.

As global warming intensifies, residents of temperate regions will also face heat waves in the near future. Food habits are one component in addressing the global challenge of climate change. However, water, the most important food for humans, has not been adequately addressed. For this commentary, on the one hand, publications on the increasing heat stress of children were consulted. On the other hand, publications on the special demands of children's temperature regulation in hot environments on fluid balance were analysed. The situation of young children in care facilities on days with heat stress is presented as a scenario. In this way, the effects of climatic changes on fluid balance can be estimated and measures to reduce heat stress and stabilise the fluid balance of children can be developed. For this analysis, first, infants will be considered in order to identify their specific fluid needs. Second, the possibilities for caregivers to improve fluid intake and train appropriate drinking habits already in infancy will be highlighted. Climate change should be included in recommendations on hydration for children. The need to adapt drinking habits requires educational approaches to weather and water - starting in early childhood care. In the face of rapid climate change, countries must act now by protecting, preparing and prioritising the high-risk group of children. Particular focus should be placed on supporting adequate hydration.

Improved Drought Characteristics in the Pearl River Basin Based on Reconstructed GRACE Solution with Enhanced Temporal Resolution

As global warming intensifies, the damage caused by drought cannot be disregarded. Traditional drought monitoring is often carried out with monthly resolution, which fails to monitor the sub-monthly climatic event. The GRACE-based drought severity index (DSI) is a drought index based on terrestrial water storage anomalies (TWSA) observed by the gravity recovery and climate experiment (GRACE) satellite. DSI has the ability to monitor drought effectively, and it is in good consistency with other drought monitoring methods. However, the temporal resolution of DSI is limited by that of GRACE observations, so it is necessary to obtain TWSA with a higher temporal resolution to calculate DSI. We use a statistical method to reconstruct the TWSA, which adopts precipitation and temperature to obtain TWSA on a daily resolution. This statistical method needs to be combined with the time series decomposition method, and then the parameters are simulated by the Markov chain Monte Carlo (MCMC) procedure. In this study, we use this TWSA reconstruction method to obtain high-quality TWSA at daily time resolution. The correlation coefficient between CSR–TWSA and the reconstructed TWSA is 0.97, the Nash–Sutcliffe efficiency is 0.93, and the root mean square error is 16.57. The quality of the reconstructed daily TWSA is evaluated, and the DSI on a daily resolution is calculated to analyze the drought phenomenon in the Pearl River basin (PRB). The results show that the TWSA reconstructed by this method has high consistency with other daily publicly available TWSA products and TWSA provided by the Center for Space Research (CSR), which proves the feasibility of this method. The correlation between DSI based on reconstructed daily TWSA, SPI, and SPEI is greater than 0.65, which is feasible for drought monitoring. From 2003 to 2021, the DSI recorded six drought events in the PRB, and the recorded drought is more consistent with SPI-6 and SPEI-6. There was a drought event from 27 May 2011 to 12 October 2011, and this drought event had the lowest DSI minimum (minimum DSI = −1.76) recorded among the six drought events. The drought monitored by the DSI is in line with government announcements. This study provides a method to analyze drought events at a higher temporal resolution, and this method is also applicable in other areas.

Potential Carbon Sequestration and Economic Value Assessment of the Relict Plant Ginkgo biloba L. Based on the Maximum Entropy Model

As global warming intensifies, plant carbon sequestration is becoming increasingly important. Studies have shown that Ginkgo biloba L. is a kind of tree with a high carbon sequestration capacity and is one of the dominant tree species suitable for urban ecosystems. Predicting the changes in the potential suitable areas, carbon sequestration amount and carbon sink value of G. biloba under current and future climate change will provide some references for the resource utilization of urban green tree species and the realization of carbon sink value. In this study, we used ‘kuenm’, an R package that uses MaxEnt, as a modeling algorithm to predict the potential suitable areas of G. biloba under nine climate scenarios, and the carbon sequestration and the carbon sink values under the fair-value measurement model were calculated. We found that: (1) the optimized MaxEnt model improved the prediction accuracy (AUC = 0.97 ± 0.004) significantly. (2) The total current potential suitable area of G. biloba was 175.11 × 104-km2, representing 21.63% of China’s total territorial area, and the highly suitable area was 26.86 × 104-km2, accounting for 2.83% of China’s total territorial area, concentrated primarily in the regions of Sichuan and Chongqing, southern Jiangsu, and Zhejiang Province. (3) The eight future climate scenarios predict that the suitable area of G. biloba will initially decrease and then increase, and the newly expanded area will be distributed primarily in the middle and upper reaches of the Yangtze River as well as near the estuary of the Yangtze River, while the region suffering losses will move from Sichuan and Chongqing to Hunan, Jiangxi and Zhejiang Province as well. Hf and bio2 are the major factors affecting the distribution of G. biloba. (4) The total annual carbon sequestration of G. biloba was 1.60 × 106-t, 1.50 × 106-t and 1.57 × 106-t under different environmental conditions in the present, the 2050s and the 2090s, respectively. Over these three time periods, we obtained total carbon sequestration values of 5.63 × 107 CNY, 5.28 × 107 CNY and 5.53 × 107 CNY.

Effects of heat wave on development, reproduction, and morph differentiation of Aphis glycines (Hemiptera: Aphididae).

As global warming intensifies, heat waves occur frequently in the summer and autumn in Heilongjiang Province, northeast China. The soybean aphid, Aphis glycines Matsumura, is an important pest of soybean in the region, which faces great survival pressure due to high temperature. In this study, A. glycines fed soybean (AgFS) and wild soybean (AgFW) were exposed to diurnal 35 °C for 7 days begin at different developmental stages, and the development, reproduction, and morph differentiation were studied. When AgFS were exposed to heat waves from the second stadium to the adult stage, they performed worse in adult lifespan and fecundity than the control. When AgFW were exposed to heat waves begin at different developmental stages, the adult lifespan and reproduction period were shortened and reproduction ability decreased. When exposed to heat waves, the adult fecundity and intrinsic rate of increase in AgFW were lower than those of AgFS. Lower proportion of males were deposited on day 13, when AgFS and AgFW were exposed to diurnal 35 °C begin at different developmental stages. The results showed that heat waves lasting for 7 days were likely to be useful in the management of A. glycines, which reduced adult reproduction ability and male differentiation proportion in the offspring and significantly affected AgFW compared to AgFS. These results are important for predicting the dynamics of A. glycines in Heilongjiang, northeast China, where the local environmental temperature is increasing and heat waves occur frequently.

Anthropogenic emissions and land use/cover change contributions to extreme temperature changes over China

Extreme weather and climate events tend to increase and strengthen as global warming intensifies, which severely affect human life and sustainable economic development. Therefore, based on the Detection and Attribution Model Intercomparison Project (DAMIP) and the Land Use Model Intercomparison Project (LUMIP) provided by the Coupled Model Intercomparison Project phase 6 (CMIP6), the optimal fingerprinting method is applied to quantify the greenhouse gases (GHG), aerosols (AA), natural forcing (NAT), and land use/cover change (LUCC) contributions to the intensity, frequency, and duration of extreme temperatures in China during 1960—2020. The results show that GHG is the main driver of extreme temperature changes in China, except for ice days (ID0) and cold spells (CSDI). GHG causes an increase in warm spells (WSDI) by about 10 days and an extension of the growing season length (GSL) by 6 to 8 days. The Tibetan Plateau is the region with the strongest extreme temperature changes influenced by GHG. AA forcing has a cooling effect that partially offsets the warming effect of GHG, especially in southeastern China. It should be pointed out that AA forcing is also the main driver for the changes in diurnal temperature range (DTR) in southeastern China, which exceeds the GHG contribution. Additionally, LUCC has greater impact in nighttime extreme temperature indices changes than the regional AA, and becomes the second dominant factor beside GHG. LUCC leads to an attributable cooling contribution of 0.34 °C for the maximum of daily minimum temperatures (TNx). Spatially, the LUCC effects on extreme temperature changes are stronger in western China than in eastern China. The more robust estimation of the GHG, AA, NAT, and LUCC contributions over distinct regions provides an advanced understanding of anthropogenic impacts on regional extreme temperatures, which is expected to be an important reference for regional climate change adaptation and mitigation.