Search

In the global context, countries must reduce carbon dioxide emissions to "net zero" by 2050 to limit global warming to 1.5 °C above pre-industrial levels. China's Nationally Determined Contributions (NDCs) are to peak carbon dioxide emissions by 2030 and achieve the carbon neutrality target by 2060. To monitor the achievements of the NDCs, establishing an annual-based accounting mechanism is necessary to record the carbon stocks in China, especially for Blue Carbon. The paper aims to present China's first national-scale systematic Blue Carbon accounting for mangroves, salt marshes, and seagrasses, covering the accounting subjects of physical and monetary assets, as well as relevant indicators for investors. It focuses on the design of the accounting method and system, the selection of data categories applied to this system, and the application of China's Blue Carbon accounting based on this accounting system. Taking Blue Carbon accounting as a starting point, this paper analyses the restoration prospects of these ecosystems and their application potential for NDCs in China compared with the terrestrial ecosystems. The results indicate that mangroves are the most cost-effective type of ecosystem, even compared to terrestrial forests. Thus, the paper provides policymakers with a new perspective on the decision-making of carbon sequestration relevant decisions, aiming to promote the monitoring, restoration, and expansion of China's coastal blue carbon ecosystem through the establishment of a sound Blue Carbon accounting system, and to help achieve the carbon neutrality goal in China's NDCs through regular and systematic monitoring of its national Blue Carbon inventories. • China's coastal blue carbon ecosystems are carbon sources rather than carbon sinks. • Mangroves are the most cost-effective coastal blue carbon ecosystem compared to salt marshes and seagrass beds. • The Blue Carbon of mangroves is more cost-effective than the Green Carbon of terrestrial forests when meeting China's Nationally Determined Contributions target of increasing forest stocks. • Establishing guidelines for Blue Carbon data requirements will lay a scientific foundation for formulating strategies and policies to cope with global climate change. [ABSTRACT FROM AUTHOR]

With the aggravation of global warming and the increasing demand for energy, the development of renewable energy is imminent. Floating photovoltaic (FPV) is a new form of renewable energy generation. However, the impact of FPV on the aquatic environment is still unclear. By long-term empirical monitoring and data analysis, this paper reveals the shading effect of large-scale FPV power station on aquatic environment for the first time. The results show that: (1) Compared with the non-photovoltaic (NP) zone, FPV only significantly reduces the concentration of dissolved oxygen in the photovoltaic (P) zone. (2) The concentration of chlorophyll a , nitrate nitrogen and total phosphorus increase, while pH and ammonia nitrogen decrease. FPV only causes an effect of the same order of magnitude as the initial concentration, and has no significant adverse effects on the nutritional status of the water body at a coverage ratio less than 50%. (3) FPV has a cooling effect on the water body during the daytime and a thermal insulation effect at night, with the most pronounced impact on peak water temperature (T w). The heating and cooling process of T w in P zone usually lags behind the NP zone by 1–3 h. The diurnal fluctuation and vertical difference of T w as well as the stability of water body are reduced under the shading of FPV, alleviating the influence of climate change on T w and water body stratification. (4) If 10% of the water area larger than 1 km2 in China are used to develop FPV, more than 900 million tons of CO 2 emissions can be reduced, and about 5 billion m3 water can be saved, which is significant in the context of climate change. In general, this paper provides a reference for the future aquatic environmental impact assessment of FPV and the formulation of related policies. • The impact of FPV on aquatic environment has been assessed. • The scale effect of FPV and impact of "fish-photovoltaic integration" are revealed. • Spatial-temporal and object specificity of impact on aquatic environment is reviewed. • The responds of FPV to the challenges of global climate change are further discussed. [ABSTRACT FROM AUTHOR]

Renewable energy is not only an efficient way to ensure energy independence and security but also supports the transition to a low carbon economy and society. The progress of renewable energy technological innovation is an important factor that influences the development of renewable energy. An in-depth analysis of the driving factors that influence this progress is crucial to China's energy transition. Based on Chinese provincial data over 2000–2015 and panel data models, this paper regards the CO 2 emissions as climate change and explores the response of renewable energy technological innovation to intensive CO 2 emissions. We also analyze the effect of the driving factors such as energy price and R&D investment on this innovation process. The main conclusions drawn are: (1) There are significant differences in technological innovation levels across China's provinces. (2) We observe that the intensive CO 2 emissions have promoted renewable energy technological innovation level, meaning that innovation process responds actively to climate changes. (3) R&D investment from government and enterprise both are conducive for promoting the innovation level. (4) Energy price has an insignificant effect on innovation in renewable energy technologies and we attribute this to the unreasonable energy price mechanism. This paper provides clear evidence for understanding the role of innovation on climate change. • The drivers of the renewable energy technological innovation are explored. • There are significant differences in technological innovation across provinces. • Renewable energy technological innovation responds actively to climate changes. • R&D investment is conducive for promoting the technological innovation levels. • The government should give full play to the role of the energy price mechanism. [ABSTRACT FROM AUTHOR]

Global warming has accentuated the effects of extreme heat on health. Health insurance, functioning as a risk management tool, has the potential to alleviate these impacts. Consequently, this paper investigates the correlation between extreme heat events and the demand for health insurance in China. Using data from the China Health and Nutrition Survey, we have observed a substantial increase in the likelihood of residents purchasing health insurance during extreme heat events. To be specific, for every extra day of extreme heat events annually, there is a 0.3% increase in the probability of purchasing health insurance. This effect is not uniform across different demographic groups. It is particularly pronounced among middle-aged and elderly individuals, rural residents, those with lower educational levels, higher income brackets, and individuals residing in underprivileged areas with limited access to green spaces and healthcare facilities. Furthermore, our study indicates that the increased frequency of extreme heat events not only impacts individuals' physical health but also triggers negative emotions, which in turn drive risk-averse behavior related to health insurance purchases. These findings carry substantial policy implications for mitigating the economic consequences of climate change. • Extreme heat increases the likelihood of residents purchasing health insurance. • Each additional day of extreme heat boosts health insurance purchases by 0.3%. • This effect varies among different populations. • Mechanistic analyses indicate extreme heat impacting physical and mental health. [ABSTRACT FROM AUTHOR]

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide. • An integrated framework combining DBN, SD, PLUS and InVEST models was proposed. • Impact of natural and socioeconomic factors on ESs was determined under climate scenarios. • The spatial pattern of ESs was optimized and partitioned using DBNs. • ESs in arid oasis urban agglomerations are mainly affected by natural factors. [ABSTRACT FROM AUTHOR]

In recent years, China has achieved numerous economic miracles but it has also been plagued by severe air pollution. The frequent hazy weather has severely restricted China's sustainable development. To investigate the nonlinear threshold effect of socio-economic factors on urban haze in China, this study constructs a spatial econometric Smooth Transition Autoregressive Regression (STAR) model based on the STIRPAT theory by using the remote sensing inversion PM 2.5 data of 223 prefecture-level and above cities in China mainland during 2004–2016. In this study, the ARAR-STAR model is estimated by quasi-maximum likelihood estimation, and the accuracy of parameter estimation is verified by Monte Carlo simulation, which proves that the ARAR-STAR model constructed in this study is robust. It is concluded that: there is a complex spatial nonlinear relationship between socio-economic factors such as economic development level, population density, advanced industrial structure, energy consumption, opening-up, and haze pollution. The effect of socio-economic factors on haze emission reduction under the spatial influence has complex heterogeneity with the smooth transition between high and low regimes with economic development. The ARAR-STAR model constructed in this paper, which has both individual fixed effects and time fixed effects, expands the form of existing spatial panel nonlinear models and enriches and implements the application of spatial panel smooth transfer threshold models in the environmental field. Not only can it provide policy recommendations for China to achieve "coordinated efficiency in pollution reduction and carbon reduction" as soon as possible, but it also contributes to China's plan to address global climate change and promote global sustainable development. • Using spatial panel smooth transition autoregressive regression model for 2004–2016, we revisit the nonlinear effects of socio-economic factors on urban haze in China. • The ARAR-STAR model is estimated by quasi-maximum likelihood estimation. • We employ Monte Carlo simulation to obtain robust results. • The effect of population density, industrial structure, energy consumption, opening-up on haze emission has heterogeneity with the smooth transition between high and low regimes with economic development. [ABSTRACT FROM AUTHOR]

Identifying ecological vulnerable regions is a significant aspect in ecological conservation and environmental management. This paper presents a first attempt to provide a prototype framework that can assess ecological vulnerability and evaluate potential impacts of natural, social, economic, environmental pollution, and human health elements on ecological vulnerability with integrating spatial analysis of Geographic Information System (GIS) method and multi-criteria decision analysis (MCDA). A general ecological vulnerability index was constructed to describe the vulnerability status in an ecological hotspot of China. The assessment results of this study confirm the poor ecological vulnerability in China that only 1.32% of the China's population lives in not vulnerable ecosystem. A very high percentage (98.68%) of Chinese with 1.34 billion people lives in vulnerable and highly vulnerable area. This situation is mainly caused by increasing population pressure, exhausted nature resources, extensive economic growth, severe environmental pollution, insufficient environmental protection investment, and accelerating population aging. The spatial comparison indicates that spatial disparity existed in China with the central and northwestern provinces showing higher ecological vulnerability than the northeastern and southern provinces. The results of ecological vulnerability assessment can support effective guidance for mid- or long-term ecologic management. The developed framework can be replicated at different spatial and temporal scales using context-specific datasets to support ecological managers and government with decision-making. With available robust climate change models, future research might incorporate climate change into the ecological vulnerability framework. [ABSTRACT FROM AUTHOR]

Understanding the changes in hydrological process is a key subject for water resource management of a high-diversity watershed. In this paper, through an establishment of a SWAT-based model, the effects of climate change and its induced vegetation change on hydrological process were analyzed in the East River Basin. The model could well simulate the hydrological processes of the basin including surface runoff (SURQ), groundwater (GWQ), lateral flow (LATQ), total water yield (WYLD), actual evapotranspiration (ET), and groundwater recharge (PERC). Under the vegetation change induced by temperature increase, the effects of the vegetation change on hydrological process were larger than that of the temperature change. Under the vegetation change caused by the increase of temperature and precipitation, the vegetation change enhanced the effects of climate change on annual SURQ, LATQ, GWQ, WYLD, and PERC of the basin. Under spatial scale, when the temperature and precipitation changed simultaneously, the increase of precipitation could promote the increase of annual ET in sub-watersheds. Also, the annual SURQ, WYLD, GWQ and ET in western sub-watersheds were more sensitive to the cumulative changes of vegetation and climate. This work can provide useful information to decision makers in water resource management of watersheds. • A SWAT-based model was established for a multi-level simulation. • Response of hydrological process to a climate-driven vegetation change was explored. • Effect of climate and vegetation changes on hydrological process was quantified. [ABSTRACT FROM AUTHOR]

As a major carbon dioxide-emitting country, China set carbon trading market to reduce enterprise carbon emissions through the rational allocation of carbon quotas among different enterprises and regions. The market has also conducted a preliminary exploration for the country to achieve carbon dioxide emissions peak in 2030 and carbon neutrality in 2060 while actively addressing the challenges of global climate change. This study analysed the emission reduction effect of China's carbon trading pilot policy, especially the role of carbon quota and carbon trading price. The analysis used county-level panel data from 1997 to 2017, regarded the implementation of the carbon trading pilot policy as a quasi-natural experiment, and used the difference-in-differences method. The results showed that, first, the policy implementation not only reduced regional carbon emissions but also inhibited carbon dioxide emissions per capita, with long-term effects. Second, the carbon emission reduction effect brought by the carbon pilot policy showed significant heterogeneous results with the different degrees of regional carbon emissions and environmental supervision. The effect was greater in areas with higher carbon emission density and stronger legal supervision. Third, the difference in carbon quota allocations resulted in different emission reduction effects, among which the historical method had the strongest effect. The carbon quota price and number of enterprises participating carbon trading market were the key factors affecting carbon emission reduction. • This paper investigates the impact of carbon emission trading market on the carbon reduction. • China provides an excellent "Quasi-natural Experiment" for assessing the role of carbon emission trading market in environmental management. • It is found that policy implementation has significantly reduced various types of carbon emissions, and this reduction effect is long-term. • Stimulating the vitality of the carbon market and expanding the supply and demand of carbon quotas are the main ways to achieve carbon emission reduction. [ABSTRACT FROM AUTHOR]

Surface water provides a basic resource for life and is vital for maintaining climate stability, hydrological cycles, and natural ecosystems. Lakes, which are an important part of surface water, play a crucial role in sustaining the hydrological balance and maintaining a healthy environment. The onset of climate change and anthropogenic disturbance on lakes and the environment, however, have drastically changed the morphological characteristics of lakes, leading to undesirable negative effects on the ecological environment. In recent years, many lakes around the world are undergoing phenomenal changes due to climate change and human activities. These changes have greatly affected the availability of freshwater resources, leading to a series of regional ecological and environmental problems, which constrain the regional sustainable development. Changes in lake parameters often indicate environmental change. Therefore, it is of great practical significance to extract lake water information to reflect the water quantity changes in the lake, understand its implications, and come up with timely solutions. This paper summarizes the existing research methods of lake water estimation in China and abroad and draws the following conclusions: (1) In the study of lake water volume estimation, it can be roughly divided into with topographic data and without topographic data. The most representative methods are the estimation methods based on topographic parameters and the Triangle Irregular Network (TIN) model method. In the actual research process, most of the scarce data that are difficult to obtain are lake topographic data, prompting researchers to constantly put forward new methods; (2) From the perspective of research methods, estimation of lake water volume can be divided into remote sensing-based and non-remote sensing-based research. With the continuous improvement of scientific and technological levels, current geographical researchers tend to use remote sensing to monitor lake water volume; (3) Although researchers have proposed a series of models for lake water volume estimation for the long-time process. However, many models are based on the ideal static estimation process, which poses challenges for researchers to make a long-term dynamic estimation of lake storage capacity in the future. At the same time, the accuracy of the model can be a problem that researchers need to work out solutions in the future. Finally, combined with the current development of remote sensing technology, the application potential and the future prospect of remote sensing in lake monitoring are briefly discussed. • Lake water volume estimation, it can roughly be divided into with topographic data and without topographic data. • Estimation of lake water volume can be divided into remote sensing-based and non-remote sensing research. • The application potential and the future prospect of remote sensing in lake monitoring are briefly discussed. [ABSTRACT FROM AUTHOR]

Widespread concern about ecological degradation has prompted development of concepts and exploration of methods to quantify ecological quality with the aim of measuring ecosystem changes to contribute to future policy-making. This paper proposes a conceptual framework for ecological quality measurement based on current ecosystem functions and biodiverse habitat, compared with pixel-scale historical baselines. The framework was applied to evaluate the changes and driving factors of ecological quality for Chinese terrestrial ecosystems through remote sensing-based and ecosystem process modeled data at 1 km spatial resolution from 2000 to 2018. The results demonstrated the ecological quality index (EQI) had a very different spatial pattern based upon vegetation distribution. An upward trend in EQI was found over most areas, and variability of 46.95% in EQI can be explained well by change in climate, with an additional 10.64% explained by changing human activities, quantified by population density. This study demonstrated a practical and objective approach for quantifying and assessing ecological quality, which has application potential in ecosystem assessments on scales from local to region and nation, yet would provide a new scientific concept and paradigm for macro ecosystems management and decision-making by governments. • Proposes an ecosystem functions based ecological quality. • Comparing with historical baselines on the pixel scale. • Appling to measure ecological quality of Chinese ecosystems in recent 20 years. • The 46.95% variability due to climate change, while 10.64% by human activity. [ABSTRACT FROM AUTHOR]

Understanding the impact of climate change on terrestrial wet and dry changes and the relationship between the two is of great significance to the sustainable development of terrestrial ecosystems. The farming-pastoral ecotone of northern China (FPENC) is an area that is sensitive to climate change, suffering from perennial drought and a clear aridification trend. Unlike previous single-factor, single-timescale studies, we identified aridification in the region based on a dataset established by remote sensing and ground-based monitoring stations from a combination of two perspectives: climate and soil. The results show that, in terms of climate, the period from 2000 to 2019 was the driest in the region during the last 120 years , and the summer drought was the most severe and shifted from a summer to spring drought; in terms of soil, the soil aridification trend in the region was severe, with 16.1% of the areas becoming significantly drier (P < 0.1) among the years and 41.6% in spring, respectively. Similar to climate change, soils exhibited recessive aridification due to the counterbalancing effect of the dry and wet seasons within the year. Then the coupling relationship between climate change and soil aridification was established in time and space. Moreover, the spatiotemporal response patterns of both were obtained. The results showed that the frequency of soil drought under meteorological drought conditions showed an increasing trend and that the sensitivity of soil drought occurrence increased. Among them, the effect of precipitation on relative soil moisture (RSM) was immediate, and the effect of prolonged warming on RSM is greater. The area of soil aridification that was caused by climatic aridification in spring accounted for 13.7% of the entire area. The regional aridification research mode proposed in this paper can provide ideas for subsequent studies. [Display omitted] • A comprehensive judgment mode of the regional aridification combining climate elements, soil moisture was established. • Over the last 20 years, the central part of the FPENC showed overall warming and wetting of the climate. • Over the last 20 years, the trend of the soil aridification in the central part of the FPENC remained severe. • The counterbalancing effect of the dry and wet seasons leads to recessive aridification. • The sensitivity of the occurrences of soil drought to the climate drought anomalies continuously became stronger. [ABSTRACT FROM AUTHOR]

Understanding the impact of climate change on terrestrial wet and dry changes and the relationship between the two is of great significance to the sustainable development of terrestrial ecosystems. The farming-pastoral ecotone of northern China (FPENC) is an area that is sensitive to climate change, suffering from perennial drought and a clear aridification trend. Unlike previous single-factor, single-timescale studies, we identified aridification in the region based on a dataset established by remote sensing and ground-based monitoring stations from a combination of two perspectives: climate and soil. The results show that, in terms of climate, the period from 2000 to 2019 was the driest in the region during the last 120 years , and the summer drought was the most severe and shifted from a summer to spring drought; in terms of soil, the soil aridification trend in the region was severe, with 16.1% of the areas becoming significantly drier (P < 0.1) among the years and 41.6% in spring, respectively. Similar to climate change, soils exhibited recessive aridification due to the counterbalancing effect of the dry and wet seasons within the year. Then the coupling relationship between climate change and soil aridification was established in time and space. Moreover, the spatiotemporal response patterns of both were obtained. The results showed that the frequency of soil drought under meteorological drought conditions showed an increasing trend and that the sensitivity of soil drought occurrence increased. Among them, the effect of precipitation on relative soil moisture (RSM) was immediate, and the effect of prolonged warming on RSM is greater. The area of soil aridification that was caused by climatic aridification in spring accounted for 13.7% of the entire area. The regional aridification research mode proposed in this paper can provide ideas for subsequent studies. [Display omitted] • A comprehensive judgment mode of the regional aridification combining climate elements, soil moisture was established. • Over the last 20 years, the central part of the FPENC showed overall warming and wetting of the climate. • Over the last 20 years, the trend of the soil aridification in the central part of the FPENC remained severe. • The counterbalancing effect of the dry and wet seasons leads to recessive aridification. • The sensitivity of the occurrences of soil drought to the climate drought anomalies continuously became stronger. [ABSTRACT FROM AUTHOR]

Robustness and cost effectiveness are major concerns for sustainable stormwater management under deep uncertainty of climate change. Given that many traditional static planning strategies are not working with unpredictable future conditions, the possibility of system failure, and the lock-in effects, the Adaptation Pathway (AP) approach was adopted for dynamically robust and cost-effective planning in this paper. In order to increase optimization accuracy of multi-staged planning, a continuous definition of the AP optimization problem was raised by improving the simplified versions in existing studies. A case study in Suzhou, a provincial pilot Sponge City in China undergoing increasing annual rainfall and severe water environment deterioration, was included by integrating Long-Term Hydrologic Impact Assessment-Low Impact Development model with optimization methods, aiming to persistently control the non-point source total phosphorus loading below an acceptable amount in the following unforeseen 20 years via multi-staged low-impact development (LID) construction. A novel optimization method developed by the authors in a companion paper, namely marginal-cost-based greedy strategy (MCGS), was successfully applied to efficiently solve the continuous version of the AP optimization problem. The popular genetic algorithm (GA) was used as a contrast. A weather generator was elaborated based on four Representative Concentration Pathway scenarios and 17 spatial downscaled general circulation models to simulate the unforeseen future annual rainfalls that helped with evaluating cost effectiveness of each prospective LID plan. Results showed that the adaptation pathways optimized by MCGS could save the whole life net present cost of an LID plan by 1%–60% compared with those optimized by GA, and the computational efficiency of MCGS was over 13 times faster than GA. • Deep uncertainty of climate change requires dynamically robust LID planning. • The Adaptation Pathway (AP) approach guarantees robustness and cost effectiveness. • The AP optimization problem was redefined in a continuous manner. • A greedy strategy was designed to optimize the adaptation pathway of LID placement. • The greedy strategy prevailed over the popular genetic algorithm significantly. [ABSTRACT FROM AUTHOR]

The diffusion of renewable energy sources (RES) is a fundamental objective of the worldwide policy actions for sustainable development, at the UN level with the sustainable development goals (SDG) recommendations, to ensure access to affordable, reliable, sustainable and modern energy for all (SDG 7). Also, primary attention to RES has been given at the EU level with the new Green Deal and the new objectives of the Next Generation EU after the Covid pandemic, and at the level of national Governments worldwide. So far, there has not been an analysis of the RES convergence process across countries worldwide, given that the issue of climate change is a global externality. Previous analyses have focused on specific regions, such as EU, OECD, provinces of China. This paper fills this gap, providing new evidence on the convergence process of RES for the 176 countries that account for more than 98% of the world population, from 1990 to 2018. A common panel data set has been used to take into account countries' specific effects. Several socio-economics and political variables are introduced to test conditional convergence such as openness to trade, developments in financial markets, income distribution, level of education. The results of this new contribution reveal that there is evidence of sigma-absolute and conditional beta-convergence process for several groups of countries. Moreover, the conditional convergence analysis shows that spatial spillover effects exert rich and complex impact on convergence speed. Finally, we provide policy recommendations, highlighting that the decarbonization target in 2050 needs additional mobilization of public and private resources to pursue a common, convergence path worldwide. • We analyze the renewable energy convergence process across countries worldwide. • We analyses the catching-up measuring the gap between benchmark and non-benchmark. • We use variables RES as percentage of electricity production and energy consumption. • We find that heterogeneity exists in the worldwide RES convergence process. • A possible line for future research could be to disaggregate renewable sources. [ABSTRACT FROM AUTHOR]

This paper summarises the methodology and results of work involved in the investigation of energy demand in six Chinese villages included in the SUCCESS Project. The procedures used to collect data associated with local energy demand are explained and the approach to data analysis is explained. Results are provided in terms for delivered energy consumption, as an indicator of energy demand; primary energy consumption, as an indicator of energy resource depletion; and carbon dioxide emissions, as an indicator of global climate change. Similarities and differences between results for this sample of villages are considered. The important causes of differences in results are investigated. [Copyright &y& Elsevier]

Faced with severe and growing social inequality among elderly individuals, a more complete understanding of the interconnection between the seasonal migration of the elderly and climate change is clearly needed. This paper tries to clarify the relation between the seasonal migration of the elderly and climate change from a multidimensional perspective. Our study adds to the research on population aging against the background of climate change. This study shows that climate change has a significant impact on regional population aging and that there are significant internal differences between the distribution and scale of the migratory elderly stemming from unequal environmental conditions. Advanced economic conditions and relatively comfortable environments have put some pressure on social endowment services in the three provinces of Northeast China, especially Liaoning Province. With their complex migration mechanism, the fate of the elderly in mainland China is closely intertwined with climatic factors, individual and socioeconomic conditions, traditional cultural backgrounds, etc. A comparatively advanced economy, well-developed endowment resources, and a comfortable environment will help in the development of regional aging resources. Regional inequality and the pursuit of a meaningful life have created different categories of migratory elderly. • Climate change makes the seasonal migration characteristics of the middle-class elderly more distinct. • The migratory elderly in mainland China is closely intertwined with climatic, individual and socioeconomic conditions. • Regional inequality and the pursuit towards value and spirit in life have formed different kinds of migratory elderly. [ABSTRACT FROM AUTHOR]

This paper explores the historical relationship between weather fluctuations and mortality evolution in China. Using panel data on the annual provincial mortality rate and daily weather variables for the 1964–2008 period, we applied a dynamic model structure with sufficient controls to estimate the short-term effects of temperature shocks on China's mortality rate. Our main results show that an additional 1 °C rise in average temperature in a given year increases the annual mortality rate by an average of 3.2%. In addition, days with daily average temperatures exceeding 27 °C (30 °C) are associated with an increase in the annual mortality rate of nearly 0.1% (0.2%) or approximately 9,520 (19,040) additional deaths. In contrast, extremely cold days do not have these effects. By applying a hybrid model structure (the long difference approach) to examine the medium-term effects of temperature changes, we find that there is little evidence of overall adaptation to high temperatures when moving from the short term to the medium term. In addition, by introducing interactions between temperatures and potential modifiers such as access to doctors, hospital beds, air conditioning and refrigerators, we determined that only residential air conditioning played an important role in mitigating the temperature-mortality relationship. However, the penetration of air conditioning in China is still relatively low. These findings indicate that climate change could partially explain the historical phenomenon of China's rising mortality rate during the unprecedented economic boom experienced since the 1980s. • Increases in the number of extreme hot days increase annual mortality rate. • Little evidence of adaptation when moving from short run to medium run. • Residential air conditioning has played an important role in mitigating the temperature-mortality relationship. [ABSTRACT FROM AUTHOR]

To tackle climate change, Chinese government has applied an array of mitigating measures to reduce CO2 emissions. During the 11th Five-year Plan, Chinese government set the emission reduction target policy to reduce energy consumption per unit of gross domestic product (GDP) by 20%. This paper attempts to estimate the effect of this emission reduction target policy on industrial performance from complexity perspective. The result shows more complex industrial structure is related to less coal consumption. In general, emission reduction target policy has a negative effect on the probability of branching into new industries and lower the productivity and profitability of a given industry. However, this negative effect is weaker for more complex industries. Only for industries with very high complexity, emission reduction target policy can improve the performance of an industry rather than exerting a negative effect. Our finding not only helps to design a more effective policy to achieve industrial development strategy, but also provides a potential way to achieve economic growth while reduce the emission of greenhouse gases at the same time. • We investigate the impact of Emission reduction target policy(ERT) on industrial performance from complexity perspective. • We apply the method of reflection to calculate the Economic Complexity of provinces and Industry Complexity of industries. • More complex industrial structure contributes to the coal consumption reduction. • ERT has negative effects on the probability of branching into new industries, lowers the productivity and profitability of a given industry. • ERT has weaker negative effects for more complex industries. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems have received considerable attention as a significant sink for organic carbon at regional to global scales. Previous studies were focused on assessment and quantification of carbon sinks for one ecotype, and few have worked on the interconnection of terrestrial sinks. In this paper, we synthesized the data from China's second national soil survey and direct measurements from 54 lakes. Meanwhile, we investigated the controlling factors of carbon accumulation dynamics in soils and lakes. Results showed varied spatial distribution of soil and lake organic carbon in different regions, and three storage modes were found. The storage mode of watershed collection was observed in the region of the Qinghai-Tibetan Plateau, while the northeast China and Yunnan-Guizhou Plateau revealed another storage mode of autochthonous deposition, and the mode of human activities affection was represented by the East Plain and Mongolia-Xinjiang Plateau. The spatial difference throughout China was regulated by various climate patterns, geological conditions and anthropogenic interference. Our results provide insights into carbon storage modes in various regions, and also inform strategies for enhancing global carbon sequestration and future mitigation policies towards global climate change. • Climate, topography and human activity regulate regional soil and lake carbon storage. • Three carbon storage modes based on relationship between soil and lake carbon. • Suggestions to enhance carbon sequestration through soil and lake management. [ABSTRACT FROM AUTHOR]