Climate Change In China Research Articles

Observation-Constrained Climate Change in China over 1850–2014 by Aerosols in CMIP6 Models

Abstract Aerosols play a very important role in climate change with large uncertainties. Using the multimodel results from CMIP6, we analyzed the aerosol effective radiative forcing (ERF) and aerosol-induced surface air temperature (SAT) change in China in the present day (PD; 11-yr mean of 2004–14) relative to the preindustrial (PI) time (11-yr mean of 1850–60). With the increase in the anthropogenic emissions, the simulated surface PM2.5 concentration and aerosol optical depth (AOD) averaged over eastern China (EC; 18°–44°N, 103°–122°E) increased by 21.43 ± 7.58 μg m−3 and 0.47 ± 0.33, respectively, from PI to PD. The simulated aerosol ERFs in EC were −4.91 ± 2.56 and −5.35 ± 2.40 W m−2 from equilibrium and transient simulations, respectively. The simulated change in SAT caused by the increases in aerosols was −1.37° ± 0.38°C in EC from PI to PD. The simulated values of equilibrium and transient climate sensitivity to aerosols (CSA; aerosol-induced SAT change per unit aerosol ERF) in EC were 0.236° and 0.222°C (W m−2)−1, respectively. By using the observed AOD from MODIS to constrain aerosol ERF, the constrained aerosol equilibrium and transient ERFs over EC were −4.66 and −4.93 W m−2, respectively, which were smaller in magnitude than the simulated values directly from the models. By using the observed SAT from the Climatic Research Unit temperature version 5 to constrain aerosol-induced cooling, the surface cooling caused by aerosols was magnified to −1.47°C. The adjusted CSA after the constraint was calculated by dividing adjusted aerosol-induced SAT change by adjusted aerosol ERF. Adjusted equilibrium and transient CSA values in EC were 0.32° and 0.34°C (W m−2)−1, respectively.

Identification of thresholds and key drivers on water use efficiency in different maize ecoregions in Yellow River Basin of China

Identifying the constrains on water use efficiency (WUE) of crops along a wet-to-dry gradient is important due to irrigation water scarcity, as well as the increasing drought risk under climate change in China. This study coupled five high-resolution climate models from Coupled Model Intercomparison Project Phase 6 (CMIP6) with the Decision Support System for Agrotechnology Transfer (DSSAT)-CERES-Maize model to quantify drought risk and the drivers affecting WUE in five major maize ecoregions of the Yellow River Basin (YRB) under three future scenarios (SSP126, SSP370, and SSP585) for both the historical baseline (1985–2014) and three future periods: 2021–2040 (2030s), 2041–2070 (2050s), and 2071–2100 (2080s). And a bias correction method was implemented for the crop model to analyze optimal WUE thresholds for maize across varying dry-wet gradients. The results indicated that future drought risk will likely persist in the YRB under all scenarios, but with regional differences in drought severity and frequency. The southwestern region (V) experienced the highest frequency of drought (62.50%-SSP126), while the northwestern region (III) exhibited the lowest frequency (33.00%-SSP585) in 2030s, and 83.30% of areas in the southwestern (V) showed significant wetting in the 2080s under SSP126. The bias-corrected CERES-Maize model effectively simulated crop yield and evapotranspiration (ET), resulting in an average reduction of 4.00% and 9.73% in normalized root mean square error (nRMSE) respectively. Distinct WUE thresholds ranging from 1.96 to 8.41 kg ha−1 mm−1 were observed across various scenarios-periods in the maize regions, mostly under slight and moderate dry/wet conditions. Notably, all SSP585 scenarios demonstrated a decrease in WUE thresholds compared to the baseline. Across all scenarios and periods, WUE was mainly driven by yield in the eastern regions (I and II) but by ET in the western regions (III, IV, and V). These findings suggest that regions experiencing varying degrees of drought severity should undergo differentiated management and optimization of agricultural practices to improve WUE under future climate scenarios.

The corresponding countermeasures of landslide risk control under influence of climate change in China

As one of the most landslide-prone countries, China is significantly affected by climate change worldwide. Understanding the influences of climate change on landslides and optimizing the corresponding countermeasures cannot be overstated. In this article, an overview of climate change’s influences on landslides in China is presented, and the developing trends of landslides in various natural topographical regions were analyzed based on two decades of historical recordings. The regions and major categories of landslides that are potentially influenced by climate change are summarized. The results indicate a growing trend of climate change is affecting the geo-environment, leading to the corresponding increase in severity, complexity, and spatial-temporal uncertainties of landslides in China. Accordingly, a proactive response is warranted to establish a more dynamic, efficient, and integrated framework of landslide risk control. This framework should encompass the entire risk control process from landslide identification, risk assessment, monitoring, early warning and mitigation, to address the issues of ‘What-Where-When-Why’ landslides would occur, ‘Who’ are the vulnerable elements, and ‘How’ the mitigation should be performed scientifically. This article is expected to help better understand the influences of climate changes on landslides in China and highlight the countermeasures responding to the challenges.

Industry return volatility and spillover effects in stock market under climate risk perception

ABSTRACT Utilizing alternative dimension reduction methods, this study constructs three Climate Risk Perception Indices (CRPIs) to quantify the impact of investor climate change sentiment on industry return volatility in the Chinese stock market. There are several findings in this study including (1) the CRPIs effectively capture the trend of climate change in China over the past decade. (2) The investor’s attention to climate change positively influences short-term stock market returns, exhibiting seasonal characteristics and industry heterogeneity. (3) The attention serves as an information sender for stocks in Telecommunication, Oil & Petrochemicals, and Environmental Protection. (4) The total spillover effect among climate-sensitive industries is significantly higher during extreme climate events. These conclusions provide empirical evidence for the stock market to respond effectively to climate risks.

Socio-demographic factors shape mortality risk linked to compound drought-heatwave events under climate change in China

Socio-demographic factors shape mortality risk linked to compound drought-heatwave events under climate change in China

Energy-water-carbon system management in response to climate change in China under uncertainties (2026–2050)

Climate change has seriously affected the resource utilization of the energy-water-carbon system, while the system carbon emissions continuously act on climate change. Given the interaction between the two, there is an urgent need to facilitate the rational allocation of system resources to realize the positive feedback between climate change and energy-water-carbon system development. In this study, an interval stochastic fuzzy integer programming (ISFIP) model is developed to support resource planning and management of the energy-water-carbon system in response to climate change in China. The developed model has advantages in characterizing the complexity and uncertainty of the energy-water-carbon system and providing optimal system decision-making options under multiple climate change scenarios. The results show that the SSP126-NZE scenario power system would reduce carbon emissions by 16.23 %, air pollutant emissions by 19.31 %, water consumption by 30.96 %, and increase economic benefits by 10.97 %, respectively, compared to the SSP585-STEPS baseline scenario.

Can combined wind and solar power meet the increased electricity load on heatwave days in China after the carbon emission peak? A case study in southern Hebei

Wind and photovoltaic (PV) power are the fastest-growing renewable energy sources; however, they are vulnerable to weather extremes. In the context of global warming, the frequency of extreme weather events, particularly heatwaves (HW), is anticipated to increase. Compared to normal summer days, HW days not only cause a rise in electricity demand but also exhibit a complementary growth in wind/PV generation. Therefore, determining whether the increase in wind/PV generation on HW days can meet the corresponding surge in electricity load is pivotal for replacing fossil fuel-based electricity. To address this question, this study conducts a case study for southern Hebei Province, which has the highest combined wind/PV installations in China, for the period 2031–2040 under the scenario that China will achieve its carbon peak (2030) and carbon neutrality goals as planned. We use recently developed load and wind power models and calibrate a boosting ensemble learning model to simulate PV generation. The results reveal that the total increase in wind/PV generation on HW days can fully meet the total increase in electricity consumption starting in 2039. However, due to the uneven distribution of wind/PV generation and load changes throughout the HW days, 9 GWh of energy storage capacity is required to ensure electricity supply in the early morning hours. Under China's climate change adaptation strategy, Hebei Province can harness wind/PV energy to address peak load demands during HW conditions and initiate climate-resilient urban development pilot projects.

Analysis of Synergistic Drivers of CO2 and NOX Emissions from Thermal Power Generating Units in Beijing–Tianjin–Hebei Region, 2010–2020

Synergistic control of the emissions of air pollutants and CO2 is critical to the dual challenges of air quality improvement and climate change in China. Based on the emission inventories of thermal power units in Beijing, Tianjin, and Hebei, this study analyzes the CO2 and NOX emission characteristics of these units, and identifies and quantifies the synergistic drivers affecting these emission trends. The inventory data show that, between 2010 and 2020, NOX emissions were reduced by 86.1%, while CO2 emissions were reduced by only 29.8%. Although significant progress has been made in reducing NOX emissions through measures such as end-of-pipe treatment, controlling CO2 emissions remains a difficult task. The index decomposition analysis reveals that economic growth is the main driver of CO2 and NOX emission growth, energy intensity reduction is the main driver of CO2 emission reduction, and end-of-pipe treatment is the main driver of NOX emission reduction. Currently, coal occupies about 87% of the energy consumption of thermal power units in the Beijing–Tianjin–Hebei region, and remains the main type of energy for synergistic emissions, and the potential for emission reduction in the energy structure remains huge. For NOX emissions, it is expected that 90% of the reduction potential can be achieved through energy restructuring and end-of-pipe treatment. In conclusion, this high-precision unit-by-unit emission study confirms the effectiveness of the control policy for thermal power units in the region and provides some scientific reference for future policy formulation.

Long-Term Variation Patterns of Precipitations Driven by Climate Change in China from 1901 to 2022

Studying long-term precipitation trends is crucial for sustainable development, as the proper utilization of water resources is essential for maintaining a sustainable water supply. The objective and novelty of this paper was to reveal the gradual mutation process of precipitation in China over a century. This study utilized monthly precipitation data from 1901 to 2022 (at a century scale) to analyze and explore the spatiotemporal variability in precipitation across different time scales and regions with a trend analysis, an abrupt change analysis, and gravity center models. The findings indicate that (1) from 1901 to 2022, the precipitation in China generally decreased from the southeast coastal areas toward the northwest inland regions. (2) There were significant differences in the migration of precipitation gravity centers among the different study regions, with the least dispersion being observed in the Liao River basin, while the Hai River basin, various river basins in the northwest, and the Pearl River basin exhibited certain regularities in gravity center movement, and other regions showed periodic variations. (3) Over the period from 1901 to 2022, there was a trend of transitioning from lower to higher precipitation levels. (4) According to continuous long-term abrupt change tests, the timing of precipitation shifts varied across different basins. Precipitation, as a crucial component of natural resources, directly impacts various aspects of socio-economic life. Research findings provide decision support for regional flood control and disaster reduction and offer scientific decisions for ecological security.

Ensemble Predictions of Rainfall-Induced Landslide Risk under Climate Change in China Integrating Antecedent Soil-Wetness Factors

Ensemble Predictions of Rainfall-Induced Landslide Risk under Climate Change in China Integrating Antecedent Soil-Wetness Factors

Long‐term changes of wind resources and its impact on wind power development under climate change in China

AbstractThe development of wind energy is indispensable in the pursuit of global carbon neutrality. This article's analysis of observational data across China reveals the annual average wind speed declined at a rate of −0.167 m · s−1 decade−1 between 1981 and 2014. This rate is 33 times faster than projections from the Coupled Model Intercomparison Project (CMIP) of the World Climate Research Programme. We propose a novel wind power scale estimation method based on annual average wind speed, suitable for assessing climate change impacts. Considering China's planned wind power generation in 2030, climate change may increase the required wind installed capacity by over 25% under the observed trend scenario. In contrast, historical average and CMIP scenarios could substantially overestimate wind potential while underestimating the necessary future wind power development scale. Climate change poses potential adverse impacts on China's carbon peak goals, necessitating targeted measures to mitigate these effects.

Measuring climate change perception in China using mental images: A nationwide open-ended survey.

Current knowledge about public climate change perception mainly covers belief, concern, and attitudes. However, how this discourse is interpreted using individuals' own frame of reference remains largely unknown, particularly in many large emitters from non-Annex I countries such as China. This study, for the first time, performs a nationwide open-ended survey covering 4,037 respondents and collected 12,100 textual answers. Using a semiautomated coding method, we find seven mental images that exclusively represent the Chinese interpretation of the climate change issue, including global warming, distant icons, natural disasters, environmental degradation, cause, solution, and weather. Analysis of influencing factors shows that females, those with lower education levels, lower income, and older individuals tend to connect climate change with natural weather phenomena. Younger and well-educated residents in developed cities are more aware of various consequences and anthropogenic causes of climate change. People with stronger climate change beliefs, policy support, and personal experience of extreme weather are more likely to mention disastrous impacts, carbon emission as causes, and potential solutions. Employing the multilevel regression and post-stratification technique, we map the prevalence of mental images in China at the prefecture-city level. The results reveal significant geographical heterogeneity, with estimated national means ranging from a high of 55% (weather) to a low of 11% (solution). Our findings reveal diverse perspectives and a widespread misconception of climate change in China, suggesting the need for tailored clarification strategies to gain public consent.

Response of Reduced Grassland Degradation Index to Climate Change in China

Grasslands have been increasingly impacted by human activities, gradually becoming one of the most threatened ecosystems globally. Advanced geographic information technology and remote sensing techniques allow for a fresh perspective on studying the response of the grassland degradation index (GDI) to climate change. This study utilized remote sensing image data of grasslands to calculate the vegetation coverage and derive the GDI for five grassland regions of China from 2001 to 2019. The results indicate that the national degradation status of grasslands remained at a level of mild degradation. The increasing trend of the GDI in some regions was effectively inhibited by regional climate change, especially in the Northeastern and Northern Plain–Mountain–Hill Grassland regions, where the GDI showed a continuous decreasing trend. GDI was strongly correlated with atmospheric pressure, precipitation, temperature, and wind speed. In the arid northern region, the increasing precipitation and decreasing temperatures predominantly contributed to the depressed GDI. In the Qinghai–Tibetan Plateau Grassland region, the instability of the GDI is attributed to fluctuating atmospheric pressure, with a correlation coefficient ranging from 0.5 to 0.8. Our findings underscore the importance of meteorological factors to evaluate and forecast grassland ecosystem stability. This understanding is vital for developing informed conservation and management strategies to address current and future climate challenges.

Genetic diversity and geographic distribution patterns of Malus landraces from 5 cultivated species under climate change in China

China is the largest center of genetic diversity of apple (Malus Mill.), with rich germplasm resources. In the process of evolution and domestication, a large number of apple landraces appeared, and they played a very important role before the introduction of modern cultivated apple varieties to China. However, the habitat of Malus landraces is under serious threat. In this study, 19 pairs of polymorphic simple sequence repeat primers were used to analyze the genetic structure and genetic relationships of Malus landraces and the potential distribution was predicted according to eight environmental variables using MaxEnt modeling. The results showed that the genetic variation of Malus landraces was high (Ho = 0.728 and He = 0.884), and the genetic differentiation was mainly distributed within respective populations and with almost no differentiation among populations. The five population groups were ranked, from highest genetic diversity level to lowest, as follows: Malus domestica subsp. chinensis > Malus prunifolia > Malus robusta > Malus asiatica > Malus micromalus. The 216 germplasms were divided into five groups based on Nei's genetic distance, whereas the Bayesian structure analysis categorized them into two groups. Population structure and principal coordinate analyses showed that Malus domestica subsp. chinensis, Malus asiatica and Malus prunifolia may be derived from similar genetic sources. In the modeling analysis, the cumulative contribution of temperature to the distribution of Malus landraces in suitable growth areas reached 66.1 %, and BIO4 (temperature seasonality) was identified as the major factor influencing the distribution of Malus landraces. Under four future emission scenarios, the potential distribution range of Malus landraces basically unchanged, but the total potential distribution area is projected to grow greatly over time and will tend to shift to higher latitudes.

Contrasting range changes and drivers of four forest foundation species under future climate change in China

Forest foundation species, vital for shaping community structure and dynamics through non-trophic level interactions, are key to forest succession and sustainability. Despite their ecological importance, the habitat ranges of these species in China and their responses to future climate change remain unclear. Our study employed the optimal MaxEnt model to assess the range shifts and their essential drivers of four typical forest foundation species from three climatic zones in China under climate scenarios, including Acer tegmentosum, Acer pseudo-sieboldianum (temperate zone), Quercus glandulifera (subtropical zone), and Ficus hispida (tropical zone). The optimal MaxEnt model exhibited high evaluation indices (AUC values > 0.90) for the four foundation species, indicating excellent predictive performance. Currently, we observed that A. tegmentosum and A. pseudo-sieboldianum are predominantly inhabited temperate forest areas in northeastern China, Q. glandulifera is primarily concentrated in subtropical forests in southeastern China, and F. hispida is mainly distributed across the tropical forests in southern China. Climate factors, particularly temperature, emerged as the primary environmental factors influencing the potential range of forest foundation species. Moreover, precipitation strongly influenced the potential range of A. tegmentosum and A. pseudo-sieboldianum, while elevation exhibited a greater impact on the range of Q. glandulifera and F. hispida. Under future climate scenarios, suitable areas for A. tegmentosum and A. pseudo-sieboldianum tend to expand southward, F. hispida tends to expand northward, while Q. glandulifera exhibited a tendency to contract towards the center. This study advances our understanding of the spatial and temporal dynamics of forest foundation species in China under climate change, providing critical insights for conservation efforts and sustainable forest management practices.

A Corpus-Based Critical Discourse Analysis of Chinese and American News Coverage on Climate Change

As the 27th Conference of the Parties to the United Nations Framework Convention on Climate Change (COP27) convened, the climate issue remained a focal point of coverage in both Chinese and American mainstream media. This paper seeks to explore the linguistic features of news discourse of climate change in China and the United States and the discursive strategy applied to strengthen national ideologies. Taking the reports on climate change in China Daily and Los Angeles Times within 2 months after COP27 as the research corpus, this paper examines the language features, the discursive processes of the text and possible social factors through a combination of corpus linguistics(CL) and critical discourse analysis(CDA) under the framework of Fairclough’s Three-Dimensional Model of Discourse. The finding suggests that both countries enhance national ideologies by constructing a responsible national image through objective climate reporting. Chinese media tends to focus on national efforts to improve ecological environment and global cooperation, while US newspaper attaches importance to climate security and pursues a leading position in global ecological governance.

Forecast of Current and Future Distributions of Corythucha marmorata (Uhler) under Climate Change in China

Corythucha marmorata (Uhler) emerged as an invasive pest in China around 2010, posing a significant threat to plants within the Asteraceae family. Employing the MaxEnt model, this study endeavors to anticipate the potential geographic distribution of Corythucha marmorata amid present and forthcoming climatic conditions, utilizing a dataset of 60 distributional occurrences alongside environmental parameters. The results revealed that presently, suitable regions span from 18–47° N to 103–128° E, with pronounced suitability concentrated notably in Jiangsu, Shanghai, Anhui, Hubei, Jiangxi, Hunan, Guangdong, Guangxi, Chongqing, and Sichuan. Projections suggested a general expansion of suitable habitats, albeit with exceptions noted in SSP1–2.6 and SSP2–4.5 scenarios in the 2050s and SSP5–8.5 in the 2070s. The potential suitability of areas for Corythucha marmorata was influenced by major factors such as precipitation in the warmest quarter (bio18), mean temperature in the warmest quarter (bio10), mean temperature in the wettest quarter (bio8), and annual precipitation (bio12). Notably, temperature and precipitation emerge as primary determinants affecting both current and future ranges. In comparison with the current distributional area, there was a trend towards increasing the potentially suitable areas in the future. Moreover, there was a greater risk of spreading to the north of China in the future. This study serves as a pivotal resource for guiding future endeavors in monitoring, early detection, and preventative management strategies targeting Corythucha marmorata.

Motivating factors of farmers’ adaptation behaviors to climate change in China: A meta-analysis

Adapting to climate change is critical to building sustainable and resilient agricultural systems. Understanding farmers' perceptions of climate change has become the key to the effective implementation of climate change adaptation policies. This research draws multidisciplinary attention to how farmers participate in decision-making on adaptation behaviors and provides useful insights for realizing synergies between environmental change and agricultural production. In this work, we conducted a meta-analysis of 63 quantitative studies on Chinese farmers' adaptation to climate change to assess the relationship between motivational factors and adaptation behavior. Our analysis highlights that farmers' perceptions of precipitation changes are often inaccurate; however, other psychological factors, such as perception, experience, and risk attitude, significantly positively impact their adaptation behavior. In addition, different climate regions are the main source of high heterogeneity in inter-study comparisons of climate change perception, and the effect of climate regions may therefore constitute a moderating factor that weakens the positive relationship between climate change perception and adaptive behavior. Furthermore, this study highlights the need to intervene at the household level to enhance farmers' adaptability to climate change, which includes providing support through income diversification, early warning information services, training, assistance, credit, subsidies, and other resources. In the future, research on how perception, experience, and risk interact to affect adaptive behavior should be strengthened.

Predicting the potential distribution of Perina nuda under climate change in China

AbstractPerina nuda (Fabricius) (Lepidoptera: Lymantriidae) is an important leaf‐feeding pest of Ficus species. It significantly affects the growth and reproduction of Ficus species, the economic prospects of growers, and the beauty of urban gardens. This study employed the MaxEnt model to predict and analyze the potential distribution of P. nuda in China, utilizing global distribution data and the correlation between the distribution of P. nuda and environmental variables. The results showed that the dominant environmental variables influencing the distribution of P. nuda included the warmest quarterly precipitation, coldest monthly minimum temperature, annual precipitation, and wettest monthly precipitation. The potential distribution area of P. nuda in China under current climatic conditions is 158 × 104 km2, accounting for 16.4% of the total area of the country. According to the SSP5‐8.5 scenario in 2050, the potential distribution area of P. nuda is projected to reach 200 × 104 km2, an increase of 26.5% compared to the current. P. nuda is widespread in China and has a tendency to spread, threatening the growth of Ficus species. This study is important for monitoring and control of P. nuda in areas where it is present, and where it may be present in the future.

Projecting heat-related cardiovascular mortality burden attributable to human-induced climate change in China

Cardiovascular disease (CVD) has been found to be particularly vulnerable to climate change and temperature variability. This study aimed to assess the extent to which human-induced climate change contributes to future heat-related CVD burdens. Daily data on CVD mortality and temperature were collected in 161 Chinese communities from 2007 to 2013. The association between heat and CVD mortality was established using a two-stage time-series design. Under the natural forcing, human-induced, and combined scenarios, we then separately projected excess cause-/age-/region-/education-specific mortality from future high temperature in 2010-2100, assuming no adaptation and population changes. Under shared socioeconomic pathway with natural forcing scenario (SSP2-4.5-nat), heat-related attributable fraction of CVD deaths decreased slightly from 3.3% [95% empirical confidence interval (eCI): 0.3, 5.8] in the 2010s to 2.8% (95% eCI: 0.1, 5.2) in the 2090s, with relative change of-0.4% (95% eCI:-0.8, 0.0). However, for combined natural and human-induced forcings, this estimate would surge to 8.9% (95% eCI: 1.5, 15.7), 14.4% (95% eCI: 1.5, 25.3), 21.3% (95% eCI:-0.6, 39.4), and 28.7% (95% eCI:-3.3, 48.0) in the 2090s under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. When excluding the natural forcing, the number of human-induced heat-related CVD deaths would increase from approximately eight thousand (accounting for 31% of total heat-related CVD deaths) in the 2010s to 33,052 (68%), 63,283 (80%), 101,091 (87%), and 141,948 (90%) in the 2090s under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. Individuals with stroke, females, the elderly, people living in rural areas, and those with lower education level would exhibit heightened susceptibility to future high temperature. In addition, Southern and Eastern regions of China were expected to experience a faster increase in heat-related attributable fraction of CVD deaths. Human activities would significantly amplify the future burden of heat-related CVD. Our study findings suggested that active adaptation and mitigation measures towards future warming could yield substantial health benefits for the patients with CVD. National Natural Science Foundation of China.