Increasing impacts from extreme precipitation on population over China with global warming

Woven Agarose-Cellulose Composite Aerogel Fibers with Outstanding Radial Elasticity for Personal Thermal Management

Aerogel fibers are good thermal insulators, suitable for weaving, and show potential as the next generation of intelligent textiles that can effectively reduce heat consumption for personal thermal management. However, the production of continuous aerogel fibers from biomass with sufficient strength and radial elasticity remains a significant challenge. Herein, continuous gel fibers were produced via wet spinning using agarose (AG) as the matrix, 2,2,2,6,6-tetramethylpiperidine-1-oxyl radical-oxidized cellulose nanofibers (TOCNs) as the reinforcing agent, and no other chemical additives by utilizing the gelling properties of AG. Supercritical drying and chemical vapor deposition (CVD) were then used to produce hydrophobic AG-TOCN aerogel fibers (HATAFs). During CVD, the HATAF gel skeleton was covered with an isostructural silica coating. Consequently, the HATAFs can recover from radial compression under 60% strain. Moreover, the HATAFs have low densities (≤0.14 g cm-3), high porosities (≥91.8%), high specific surface areas (≥188 m2 g-1), moderate tensile strengths (≤1.75 MPa), excellent hydrophobicity (water contact angles of >130°), and good thermal insulating properties at different temperatures. Thus, HATAFs are expected to become a new generation of materials for efficient personal thermal management.

The seasonal variability of future evapotranspiration over China during the 21st century

The evapotranspiration (ET) plays a crucial role in shaping regional climate patterns and serves as a vital indicator of ecosystem function. However, there remains a limited understanding of the seasonal variability of future ET over China and its correlation with environmental drivers. This study evaluated the skills of 27 models from the Six Phase of Coupled Model Intercomparison Project in modeling ET and the Bayesian Model Averaging (BMA) method was employed to merge monthly simulated ET based on the top five best-performing models. The seasonal changes in ET under three climate scenarios from 2030 to 2099 were analyzed based on the BMA-merged ET, which was well validated with observed ET collected from fourteen flux sites across China. Significant increasing ET over China are projected under all seasons during 2030-2099, with 0.05-0.13 mm yr-1, 0.11-0.23 mm yr-1, and 0.20-0.41 mm yr-1 under SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios, respectively. Relative to the historical period (1980-2014), the relative increase in ET over China is highest in winter and lowest in summer. Seasonal ET increases significantly in all seven climate sub-regions under high forcing scenario. Higher ET increase is generally found in southeastern humid regions, while lowest ET increase occurs in northwest China. At the country level, the primary factor driving ET increase during spring, summer, and autumn seasons is the increasing net radiation and warming. In contrast, ET increase during winter is influenced not only by energy factors but also by vegetation-related factors. Future seasonal ET increase is predominantly driven by increasing energy factors in the southeastern humid region and Tibetan Plateau, while seasonal ET changes in the northwest region prevailingly depend on soil moisture. Results indicate that China will experience a "wet season will get wetter, and dry season will become drier" in the 21st century with high radiation forcing scenario.

Exploring changes of precipitation extremes under climate change through global variable-resolution modeling

Understanding the responses of precipitation extremes to global climate change remains limited owing to their poor representations in models and complicated interactions with multi-scale systems. Here we take the record-breaking precipitation over China in 2021 as an example, and study its changes under three different climate scenarios through a developed pseudo-global-warming (PGW) experimental framework with 60-3 km variable-resolution global ensemble modeling. Compared to the present climate, the precipitation extreme under a warmer (cooler) climate increased (decreased) in intensity, coverage, and total amount at a range of 24.3%-37.8% (18.7%-56.1%). With the help of the proposed PGW experimental framework, we further reveal the impacts of the multi-scale system interactions in climate change on the precipitation extreme. Under the warmer climate, large-scale water vapor transport converged from double typhoons and the subtropical high marched into central China, enhancing the convective energy and instability on the leading edge of the transport belt. As a result, the mesoscale convective system (MCS) that directly contributed to the precipitation extreme became stronger than that in the present climate. On the contrary, the cooler climate displayed opposite changing characteristics relative to the warmer climate, ranging from the large-scale systems to local environments and to the MCS. In summary, our study provides a promising approach to scientifically assess the response of precipitation extremes to climate change, making it feasible to perform ensemble simulations while investigating the multi-scale system interactions over the globe.

Asymmetric pre-growing season warming may jeopardize seed reproduction of the sand-stabilizing shrub Caragana microphylla

Our current understanding of the processes and mechanisms by which seasonal asymmetric warming affects seed reproduction in semiarid regions, which are essential in preserving the stability of both vegetation ecosystem structure and function, remains poorly understood. Here, we conducted a field warming experiment, including pre-growing season warming (W1), in-growing season warming (W2), and combined pre- and in-growing season warming (W3) treatments, to investigate the seed reproductive strategy of Caragana microphylla, an important sand-stabilizing shrub, from the perspective of reproductive phenology, reproductive effort, and reproductive success. Results show that the warming treatments advanced the initial stages of reproductive phenology, prolonged its duration, and decreased its synchrony (magnitude = W3 > W2 > W1). Additionally, flowering phenology was more sensitive to warming than podding phenology. The W1 treatment inclined seed reproduction towards the conservative strategy with low reproductive effort and success. The W3 treatment tended to increase seed reproductive effort and success. While the W2 treatment did not affect reproductive success, it did increase reproductive effort. Changes in reproductive phenology explained 20 % of the variation in reproductive effort and 38 % of the variation in reproductive success. However, these changes also directly hindered reproductive success (direct effect = -0.57) while indirectly promoting reproductive success (indirect effect = 0.27) by increasing reproductive efforts. Our results reveal that the seasonal asymmetry of warming altered the seed reproduction strategy of sand-stabilizing shrubs, with warmer winters and springs before the growing season decreasing seed fecundity.

Population Exposure Changes to Mean and Extreme Climate Events Over Pakistan and Associated Mechanisms

The increasing prevalence of warmer trends and climate extremes exacerbate the population's exposure to urban settlements. This work investigated population exposure changes to mean and extreme climate events in different Agro-Ecological Zones (AEZs) of Pakistan and associated mechanisms (1979-2020). Spatiotemporal trends in mean and extreme temperatures revealed significant warming mainly over northern, northeastern, and southern AEZs. In contrast, mean-to-extreme precipitation changes showed non-uniform patterns with a significant increase in the northeast AEZs. Population exposure to mean (extreme) temperature and precipitation events increased two-fold during 2000-2020. The AEZs in urban settlements (i.e., Indus Delta, Northern Irrigated Plain, and Barani/Rainfall) show a maximum exposure to extreme temperatures of about 70-100 × 106 (person-days) in the reference period (1979-1999), which increases to 140-200 × 106 person-days in the recent period (2000-2020). In addition, the highest exposure to extreme precipitation days also increases to 40-200 × 106 person-days during 2000-2020 than 1979-1999 (20-100 × 106) person-days. Relative changes in exposure are large (60%-90%) for the AEZs across northeast Pakistan, justifying the spatial population patterns over these zones. Overall, the observed changes in exposure are primarily attributed to the climate effect (50%) over most AEZs except Northern Irrigated Plain for R10 and R20 events, where the interaction effect takes the lead. The population exposure rapidly increased over major AEZs of Pakistan, which could be more vulnerable to extreme events due to rapid urbanization and population growth in the near future.

Microbiological risks increased by ammonia-oxidizing bacteria under global warming: The neglected issue in chloraminated drinking water distribution system

A rising outbreak of waterborne diseases caused by global warming requires higher microbial stability in the drinking water distribution system (DWDS). Chloramine disinfection is gaining popularity in this context due to its good persistent stability and fewer disinfection byproducts. However, the microbiological risks may be significantly magnified by ammonia-oxidizing bacteria (AOB) in distribution systems during global warming, which is rarely noticed. Hence, this work mainly focuses on AOB to explore its impact on water quality biosafety in the context of global warming. Research indicates that global warming-induced high temperatures can directly or indirectly promote the growth of AOB, thus leading to nitrification. Further, its metabolites or cellular residues can be used as substrates for the growth of heterotrophic bacteria (e.g., waterborne pathogens). Thus, biofilm may be more persistent in the pipelines due to the presence of AOB. Breakpoint chlorination is usually applied to control such situations. However, switching between this strategy and chloramine disinfection would result in even more severe nitrification and other adverse effects. Based on the elevated microbiological risks in DWDS, the following aspects should be paid attention to in future research: (1) to understand the response of nitrifying bacteria to high temperatures and the possible association between AOB and pathogenic growth, (2) to reveal the mechanisms of AOB-mediated biofilm formation under high-temperature stress, and (3) to develop new technologies to prevent and control the occurrence of nitrification in drinking water distribution system.

Herders' adaptation strategies and animal husbandry development under climate change: A panel data analysis

The frequent occurrence of extreme climate events has become an indisputable fact. However, the role of adaptation to extreme climate change in the development of livestock husbandry is still insufficiently understood. This study empirically analyzed the impact of herders' adaptation strategies to extreme drought on livestock husbandry development and aimed to explore the optimal grassland management path under continuous climate change. A panel dataset of surveyed herders from the Xilingol League, a traditional pastoral area in China, was used. The results indicated that the average frequency of extreme drought in the Xilingol League from 1980 to 2020 was 4.94 months/year, and the occurrence of extreme drought showed a slightly upward trend. The average technical efficiency of livestock husbandry was 0.721, which can still be improved. Hay purchases can effectively promote livestock technical efficiency (p<0.01) and is the main adaptation strategy of herders to extreme drought. Further analysis showed that non-farming and pastoral employment has a positive regulatory effect in the impact of purchased hay on livestock technical efficiency. The results of this study deepen the understanding of effective adaptation to extreme weather events in pastoral areas due to climate change and provide useful information to policymakers engaged in grassland management.

Increased impact of heat domes on 2021-like heat extremes in North America under global warming

During summer 2021, Western North America (WNA) experienced an unprecedented heatwave with record-breaking high temperatures associated with a strong anomalous high-pressure system, i.e., a heat dome. Here, we use a flow analog method and find that the heat dome over the WNA can explain half of the magnitude of the anomalous temperature. The intensities of hot extremes associated with similar heat dome-like atmospheric circulations increase faster than background global warming in both historical change and future projection. Such relationship between hot extremes and mean temperature can be partly explained by soil moisture-atmosphere feedback. The probability of 2021-like heat extremes is projected to increase due to the background warming, the enhanced soil moisture-atmosphere feedback and the weak but still significantly increased probability of the heat dome-like circulation. The population exposure to such heat extremes will also increase. Limiting global warming to 1.5 °C instead of 2 °C (3 °C) would lead to an avoided impact of 53% (89%) of the increase in population exposure to 2021-like heat extremes under the RCP8.5-SSP5 scenario.

Future Projection of Extreme Precipitation Indices over the Qilian Mountains under Global Warming

The Qilian Mountains are a climate-sensitive area in northwest China, and extreme precipitation events have an important impact on its ecological environment. Therefore, considering the global warming scenario, it is highly important to project the extreme precipitation indices over the Qilian Mountains in the future. This study is based on three CMIP6 models (CESM2, EC-Earth3, and KACE-1-0-G). A bias correction algorithm (QDM) was used to correct the precipitation outputs of the models. The eight extreme precipitation indices over the Qilian Mountains during the historical period and in the future were calculated using meteorological software (ClimPACT2), and the performance of the CMIP6 models to simulate the extreme precipitation indices of the Qilian Mountains in the historical period was evaluated. Results revealed that: (1) The corrected CMIP6 models could simulate the changes in extreme precipitation indices over the Qilian Mountains in the historical period relatively well, and the corrected CESM2 displayed better simulation as compared to the other two CMIP6 models. The CMIP6 models performed well while simulating R10mm (CC is higher than 0.71) and PRCPTOT (CC is higher than 0.84). (2) The changes in the eight extreme precipitation indices were greater with the enhancement of the SSP scenario. The growth rate of precipitation in the Qilian Mountains during the 21st century under SSP585 is significantly higher than the other two SSP scenarios. The increment of precipitation in the Qilian Mountains mainly comes from the increase in heavy precipitation. (3) The Qilian Mountains will become wetter in the 21st century, especially in the central and eastern regions. The largest increase in precipitation intensity will be observed in the western Qilian Mountains. Additionally, total precipitation will also increase in the middle and end of the 21st century under SSP585. Furthermore, the precipitation increment of the Qilian Mountains will increase with the altitude in the middle and end of the 21st century. This study aims to provide a reference for the changes in extreme precipitation events, glacier mass balance, and water resources in the Qilian Mountains during the 21st century.

Radiative cooling for passive thermal management towards sustainable carbon neutrality

Photonic structures at the wavelength scale offer innovative energy solutions for a wide range of applications, from high-efficiency photovoltaics to passive cooling, thus reshaping the global energy landscape. Radiative cooling based on structural and material design presents new opportunities for sustainable carbon neutrality as a zero-energy, ecologically friendly cooling strategy. In this review, in addition to introducing the fundamentals of the basic theory of radiative cooling technology, typical radiative cooling materials alongside their cooling effects over recent years are summarized and the current research status of radiative cooling materials is outlined and discussed. Furthermore, technical challenges and potential advancements for radiative cooling are forecast with an outline of future application scenarios and development trends. In the future, radiative cooling is expected to make a significant contribution to global energy saving and emission reduction.

Applying deep learning-based regional feature recognition from macro-scale image to assist energy saving and emission reduction in industrial energy systems

INTRODUCTION

Image recognition technology has immense potential to be applied in industrial energy systems for energy conservation. However, the low recognition accuracy and generalization ability under actual operation conditions limit its commercial application.

OBJECTIVES

To improve the recognition accuracy and generalization ability, a novel image recognition method integrating deep learning and domain knowledge was applied to assist energy saving and emission reduction for industrial energy systems.

METHODS

As a typical industrial scenario, the defrosting control in the refrigeration system was selected as the specific optimization object. By combining deep learning algorithm with domain knowledge, a residual-based convolutional neural network model (RCNN) was proposed specifically for frosty state recognition, which features the residual input and average pooling output. Based on the real-time recognition of frosty levels, a defrosting control optimization method was proposed to initiate and terminate the defrosting operation on demand.

RESULTS

By combining the advanced image recognition technique with specific energy domain knowledge, the proposed RCNN enables both high recognition accuracy and strong generalization ability. The recognition accuracy of RCNN reached 95.06% for the trained objects and 93.67% for non-trained objects while that of only 75.86% for the conventional CNN. By adopting the presented system optimization method assisted by RCNN, the defrosting frequency, accumulated time and energy consumption were 53.8%, 57.02% and 34.5% less than the original control method. Furthermore, the environmental and cost analysis illustrated that the annual reduction in CO₂ emissions is 2145.21 to 3412.84 kg and the payback time was less than 2.5 years which was far below the service life.

CONCLUSION

The technical feasibility and significant energy-saving benefits of deep learning-based image recognition method were demonstrated through the field experiment. Our study shows the great application potential of image recognition technology and promotes carbon neutrality in industrial energy systems.

Quantifying Vegetation Vulnerability to Climate Variability in China

Climate variability has profound effects on vegetation. Spatial distributions of vegetation vulnerability that comprehensively consider vegetation sensitivity and resilience are not well understood in China. Furthermore, the combination of cumulative climate effects and a one-month-lagged autoregressive model represents an advance in the technical approach for calculating vegetation sensitivity. In this study, the spatiotemporal characteristics of vegetation sensitivity to climate variability and vegetation resilience were investigated at seasonal scales. Further analysis explored the spatial distributions of vegetation vulnerability for different regions. The results showed that the spatial distribution pattern of vegetation vulnerability exhibited spatial heterogeneity in China. In spring, vegetation vulnerability values of approximately 0.9 were mainly distributed in northern Xinjiang and northern Inner Mongolia, while low values were scattered in Yunnan Province and the central region of East China. The highest proportion of severe vegetation vulnerability to climate variability was observed in the subhumid zone (28.94%), followed by the arid zone (26.27%). In summer and autumn, the proportions of severe vegetation vulnerability in the arid and humid zones were higher than those in the other climate zones. Regarding different vegetation types, the highest proportions of severe vegetation vulnerability were found in sparse vegetation in different seasons, while the highest proportions of slight vegetation vulnerability were found in croplands in different seasons. In addition, vegetation with high vulnerability is prone to change in Northeast and Southwest China. Although ecological restoration projects have been implemented to increase vegetation cover in northern China, low vegetation resilience and high vulnerability were observed in this region. Most grasslands, which were mainly concentrated on the Qinghai–Tibet Plateau, had high vulnerability. Vegetation areas with low resilience were likely to be degraded in this region. The areas with highly vulnerable vegetation on the Qinghai–Tibet Plateau could function as warning signals of vegetation degradation. Knowledge of spatial patterns of vegetation resilience and vegetation vulnerability will help provide scientific guidance for regional environmental protection.

Significant Increase in Population Exposure to Extreme Precipitation in South China and Indochina in the Future

Extreme precipitation events cause severe economic losses and can seriously impact human health. Therefore, it is essential to project possible future changes in the population’s exposure to precipitation extremes against the background of global warming. On the basis of model outputs from phase 6 of the Coupled Model Intercomparison Project, our study shows that both the frequency and intensity of extreme precipitation are likely to increase in the South China and Indochina region in the coming century, especially under the business-as-usual Shared Socioeconomic Pathway (SSP) scenario, SSP5-8.5. The largest population exposure can be expected under the SSP2-4.5 scenario, both in South China and Indochina. If early adoption of mitigation measures via the SSP1-2.6 scenario can be achieved, it may be possible to limit the average population exposure in South China to a relatively low level, while Indochina’s may even be smaller than it is currently. In terms of spatial distribution, the maximum population exposure is most likely to be centered in southern South China. This study also reveals that the contribution of the population–climate interaction to population exposure is likely to increase in the future, and different contributions from the factors of climate and population correspond to different emission policies. Under SSP2-4.5, the importance of climate change and the population–climate interaction is more likely to increase.

Impact of Interaction between Metropolitan Area and Shallow Lake on Daily Extreme Precipitation over Eastern China

Both cities and lakes have significant impacts on regional precipitation. With global warming, extreme precipitation events in Eastern China have increased significantly, and the single/joint influences of metropolises and lakes on extreme precipitation still need to be quantitatively evaluated. To reveal the impact of the single/joint influences of metropolises and lakes on the shear line torrential rain process, the Suzhou-Wuxi-Changzhou Metropolitan Area (SXCMA) and Lake Taihu in Eastern China were selected as the study area. Utilizing a WRF model, comparative studies of sensitivity simulations were conducted for the two typical extreme precipitation events caused by the low-level shear line (LLSL) on 27 June 2015 (EP627) and 25 September 2017 (EP925). Both results show that the existence of Lake Taihu and SXCMA will increase precipitation in the study area. SXCMA has a more obvious effect on enhancing precipitation, which is about twice the effect of Lake Taihu. SXCMA mainly strengthens the intensity and movement of the surface convergence line (SCL) in the study area and indirectly affects the shift of the LLSL, which finally affects the intensity and location of precipitation. Lake Taihu affects the intensity and movement of SCL, triggering ground vertical convections due to lower surface roughness, and acts as a land-lake breeze and water vapor source, which will affect the distribution and intensity of precipitation.

Increasing trend of lightning activity in the South Asia region

Lightning is an important natural source of wildfires and oxynitride, and hence significantly influences ecological systems and atmospheric chemistry. Here, we choose South Asia, an important region for global water reallocation and global climate changes, to examine lightning variations based on the longest existing lightning dataset from the OTD/LIS observations. We identify a clear increase in lightning density in the research region, increasing at a rate of 0.096 fl km^-2 a^-1 over the last two decades. Multiple linear regression analysis is adopted to identify the main influencing factors among ten potential thermodynamic or microphysical factors and the crucial areas contributing to the increases in lightning. The surface latent heat flux along the west coast of the Indian subcontinent is the largest contributor, explaining 52% of the lightning variance and contributing to a 0.025 fl km^-2 a^-1 increase. The sea surface temperature in the Arabian Sea, the convective available potential energy (CAPE) over the northwestern Indian subcontinent, and the wind shear along the northwestern coast also make important contributions to the lightning increase, indicating that the thermodynamic effects overwhelm the microphysical effects on lightning activity over the South Asia region.

Evaluation of Six Satellite and Reanalysis Precipitation Products Using Gauge Observations over the Yellow River Basin, China

Satellite-based and reanalysis products are precipitation data sources with high potential, which may exhibit high uncertainties over areas with a complex climate and terrain. This study aimed to evaluate the accuracy of the latest versions of six precipitation products (i.e., Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) V2.0, gauge-satellite blended (BLD) Climate Prediction Center Morphing technique (CMORPH) V1.0, European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA) 5-Land, Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) V6 Final, Global Satellite Mapping of Precipitation (GSMaP) near-real-time product (NRT) V6, and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN)-CDR) over the Yellow River Basin, China. The daily precipitation amounts determined by these products were evaluated against gauge observations using continuous and categorical indices to reflect their quantitative accuracy and capability to detect rainfall events, respectively. The evaluation was first performed at different time scales (i.e., daily, monthly, and seasonal scales), and indices were then calculated at different precipitation grades and elevation levels. The results show that CMORPH outperforms the other products in terms of the quantitative accuracy and rainfall detection capability, while CHIRPS performs the worst. The mean absolute error (MAE), root mean square error (RMSE), probability of detection (POD), and equitable threat score (ETS) increase from northwest to southeast, which is similar to the spatial pattern of precipitation amount. The correlation coefficient (CC) exhibits a decreasing trend with increasing precipitation, and the mean error (ME), MAE, RMSE, POD and BIAS reveal an increasing trend. CHIRPS demonstrates the highest capability to detect no-rain events and the lowest capability to detect rain events, while ERA5 has the opposite performance. This study suggests that CMORPH is the most reliable among the six precipitation products over the Yellow River Basin considering both the quantitative accuracy and rainfall detection capability. ME, MAE, RMSE, POD (except for ERA5) and BIAS (except for ERA5) increase with the daily precipitation grade, and CC, RMSE, POD, false alarm ratio (FAR), BIAS, and ETS exhibit a negative correlation with elevation. The results of this study could be beneficial for both developers and users of satellite and reanalysis precipitation products in regions with a complex climate and terrain.

Smallholders' Agricultural Production Efficiency of Conservation Tillage in Jianghan Plain, China-Based on a Three-Stage DEA Model

Based on interviews with 695 smallholders in Jianghan Plain, this paper introduced the three-stage data envelopment analysis (DEA) model to analyze the agricultural production efficiency of conservation tillage adopters and explored the impact of environmental factors on agricultural production efficiency. The empirical results showed the following (1) Planting area, seed consumption, labor input, pesticide usage, chemical fertilizer usage, agricultural film usage were selected as input indicators, agricultural output was chosen as an output indicator, and the traditional DEA model was used to calculate the production efficiency of smallholders, and the agricultural production efficiency of smallholders was found to be at a low level. In addition, environmental and random factors both have significant impacts on efficiency, so they should be stripped. (2) After excluding environmental factors and random factors, the drop in pure technical efficiency of smallholders in the third stage was higher than the drop in scale efficiency when compared with the first stage. Moreover, the true technical efficiency was the main restricting factor for the agricultural production efficiency. (3) Educational level of smallholders, policy support, and information acquisition were the factors that affect the technical efficiency significantly. Improving the efficiency of agricultural production technology for smallholders requires strengthening rural basic education, improving subsidy policies for conservation agricultural technology, and establishing and improving rural information technology services.