In response to a growing demand for subnational and spatially explicit data on China's future population, this study estimates China's provincial population from 2010 to 2100 by age (0-100+), sex ...(male and female) and educational levels (illiterate, primary school, junior-high school, senior-high school, college, bachelor's, and master's and above) under different shared socioeconomic pathways (SSPs). The provincial projection takes into account fertility promoting policies and population ceiling restrictions of megacities that have been implemented in China in recent years to reduce systematic biases in current studies. The predicted provincial population is allocated to spatially explicit population grids for each year at 30 arc-seconds resolution based on representative concentration pathway (RCP) urban grids and historical population grids. The provincial projection data were validated using population data in 2017 from China's Provincial Statistical Yearbook, and the accuracy of the population grids in 2015 was evaluated. These data have numerous potential uses and can serve as inputs in climate policy research with requirements for precise administrative or spatial population data in China.
•24.7% of China’s final energy consumption in 2012 is caused by household consumption.•Energy linkages between supply side and demand side are shown in a Sankey diagram.•Adopting low-carbon ...consumption and decreasing energy intensity can conserve energy.•Energy conservation potential of several household consumption behaviors is revealed.
The household sector has become the second largest consumer of final energy, ranking only next to the industrial sector in China. Except for the direct energy consumption of the household sector, people’s consumption activities also indirectly affect the energy consumption of multiple production sectors. Previous studies have shed light upon consumer-oriented energy consumption and carbon emission, however, the critical problem of sector-to-sector energy linkages between supply side and demand side has not been fully addressed. Besides, there also lacks sufficient research on the energy conservation potential of residents’ lifestyle change. This paper investigates the direct and indirect impact of household consumption activities on energy consumption in China from the consumers’ lifestyle perspective based on the input-output analysis. The relationship between household energy consumption and industrial energy consumption and the effect of lifestyle change on energy conservation are also considered. It is estimated that China’s energy consumption caused by household consumption activities in 2012 is 29141.97 PJ in total, which accounts for 24.7% of the total final energy consumption. The indirect energy consumption of household consumption activities is 1.35 times more than the direct energy consumption. Housing activities cause the most indirect energy consumption, and the smelting and pressing industry of ferrous metal is the most energy-consuming industrial sector influenced by household consumption. We also find that adopting low-carbon consumption pattern and accelerating the decrease of energy intensity are both effective means to reduce the total energy consumption by scenario analysis. Finally the energy conservation potential by comparing different types of household consumption behaviors is revealed to make policy makers form vivid impressions on the importance of demand side regulation.
Adaptation at farm level is an effective measure to cope with global climate change. The study aims to clarify farmers' intentions and decisions regarding global climate change adaptation. Logistic ...regression models were used to examine the influences of socioeconomic factors and climate adaptation communication processes on farmers' decision to apply adaptation strategies against drought and flood. Specifically, for a thorough understanding of non-adapting farmers, the theory of planned behavior was incorporated, to assess these farmers' intention to adaptation. Results showed that farmers' perceptions were consistent with the weather data over a short period, reporting a rise in temperature and a greater decrease in precipitation. Agricultural experience, farm income, training, social capital, and effective climate adaptation communication were statistically significant in increasing the probability of farmers' adaptation. For farmers who do not perceive climate change but adapted nonetheless, social capital played a major factor, driving their belief in, and behavior to adaptation, of which the most important aspects were neighbors and peer groups. Farmers' intention to adapt was mostly affected by perceived behavioral control factors, followed by attitude and subjective norms. Therefore, successful policies to enhance farmers' perceptions and adaptive capacity can encourage both actual and intended adaptation farmers. Adaptation strategies require the participation of multiple players from all related sectors engaging with local communities and farmers.
•Farmers' perception of climate change can stimulate the initiation of adaptation practice.•Effective climate adaptation communication can encourage farmer's adaptation decision.•Farmer's intention to adapt is a way to exert pressure on policymakers to take action.•Adaptation strategies at farm level need participation from all related sectors.
Gross primary production (GPP) by terrestrial ecosystems is the largest flux in the global carbon cycle, and its continuing increase in response to environmental changes is key to land ecosystems' ...capacity to offset anthropogenic CO2 emissions. However, the CO2- and climate-sensitivities of GPP vary among models. We applied the 'P model'-a parameter-sparse and extensively tested light use efficiency (LUE) model, driven by CO2, climate and remotely sensed greenness data-at 29 sites with multi-year eddy-covariance flux measurements. Observed (both positive and negative) GPP trends at these sites were predicted, albeit with some bias. Increasing LUE (due to rising atmospheric CO2 concentration) and green vegetation cover were the primary controls of modelled GPP trends across sites. Global GPP simulated by the same model increased by 0.46 ± 0.09 Pg C yr-2 during 1982-2016. This increase falls in the mid-range rate of simulated increase by the TRENDY v8 ensemble of state-of-the-art ecosystem models. The modelled LUE increase during 1900-2013 was 15%, similar to a published estimate based on deuterium isotopomers. Rising CO2 was the largest contributor to the modelled GPP increase. Greening, which may in part be caused by rising CO2, ranked second but dominated the modelled GPP change over large areas, including semi-arid vegetation on all continents. Warming caused a small net reduction in modelled global GPP, but dominated the modelled GPP increase in high northern latitudes. These findings strengthen the evidence that rising LUE due to rising CO2 level and increased green vegetation cover (fAPAR) are the main causes of increasing GPP, and thereby, the terrestrial carbon sink.
•This study investigates the importance of sectoral coverage in designing an ETS in China.•The study uses a dynamic CGE model with disaggregated electricity technologies.•The cost of INDC targets ...through the proposed eight-sector ETS is 10.5% GDP in 2030.•GDP losses can be reduced to 3.3% by covering another 24.8% of emissions in ETS by 2030.•Air pollution co-benefits of China’s INDC can be as large as 136.7billion USD in 2030.
This study contributes to the existing literature on optimal carbon mitigation policy by quantifying the impacts of various sectoral coverage options for the emissions trading systems (ETS) used to achieve China’s Intended Nationally Determined Contribution (INDC) targets for the Paris Agreement on climate change. The CHEER model, a computable general equilibrium (CGE) model of China with detailed representation of electricity and other energy intensive sectors, as well asa complete CO2 emissions accounting module and carbon market, is used in this study. Results show several important findings. First, China’s INDC targets can be achieved through an economy-wide ETS at an economic cost of 2.1% of real GDP by 2030. Second, including only the eight sectors proposed for initial implementation of the ETS in China is likely to result in a much larger mitigation cost than the economy-wide approach, estimated to be as high as 10.5% of 2030 real GDP. Thirdly, this study further indicates that the mitigation costs can be reduced to 3.3% of real GDP in 2030 if other energy-intensive sectors, accounting for additional 24.8% of total emissions, are included in the ETS. Asa result, not all sectors are required to get close to the first-best mitigation option so long as critical sectors are not excluded. In addition, the temporal dimension of mitigation costs and air pollution co-benefits under different sectoral schemes of China’s ETS gives policy-makers a degree of short-run flexibility in terms of phasing in additional industries over time.
Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and ...identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.
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•AI system that can diagnose COVID-19 pneumonia using CT scans•Prediction of progression to critical illness•Potential to improve performance of junior radiologists to the senior level•Can assist evaluation of drug treatment effects with CT quantification
Zhang et al. present an AI-based system, based on hundreds of thousands of human lung CT scan images, that can aid in distinguishing patients NCP versus other common pneumonia and can help to predict the prognosis of COVID-19 patients.
This paper has changed the vague understanding that “the short-lived buildings have huge environmental footprints (EF)” into a concrete one. By estimating the annual floor space of buildings ...demolished and calibrating the average building lifetime in China, this paper compared the EF under various assumptive extended buildings’ lifetime scenarios based on time-series environmental-extended input-output model. Results show that if the average buildings’ lifetime in China can be extended from the current 23.2 years to their designed life expectancy, 50 years, in 2011, China can reduce 5.8 Gt of water withdrawal, 127.1 Mtce of energy consumption, and 426.0 Mt of carbon emissions, each of which is equivalent to the corresponding annual EF of Belgium, Mexico, and Italy. These findings will urge China to extend the lifetime of existing and new buildings, in order to reduce the EF from further urbanization. This paper also verifies that the lifetime of a product or the replacement rate of a sector is a very important factor that influences the cumulative EF. When making policies to reduce the EF, adjusting people’s behaviors to extend the lifetime of products or reduce the replacement rate of sectors may be a very simple and cost-effective option.
Heat stress caused by climate change and heat-related labor productivity losses have become global concerns. Estimating the economic impacts of heat stress is of great significance for employers, as ...well as sectoral and national policy makers who are searching for solutions to reduce productivity losses. As the value of economic impacts are sensitive to the research methodologies, we conducted a systematic review of published literature on the methodologies and results of economic impacts of heat on labor productivity. Four methods were summarized: the human capital (HC) method, the econometric method (EM), the input–output (IO) method, and the computable general equilibrium (CGE) model. Considering adaptation measures, global economic losses due to heat-related labor productivity losses are projected to range from 0.31% (0.14–0.5%, RCP2.6) to 2.6% (1.4–4%, RCP8.5) of global GDP in 2100. The published studies found that large economic losses occurred mainly in South and Southeast Asia, Sub-Saharan Africa, and Central America. Owing to different methodologies and considerations of adaptation measures, the disparities of results within the same area at a given time can be as high as 7.4-fold. We summarized the knowledge gaps in existing studies and proposed new directions to provide more targeted and reliable results for policy makers.
The configuration of user-side energy storage can effectively alleviate the timing mismatch between distributed photovoltaic output and load power demand, and use the industrial user electricity ...price mechanism to earn revenue from peak shaving and valley filling. The configuration of photovoltaic & energy storage capacity and the charging and discharging strategy of energy storage can affect the economic benefits of users. This paper considers the annual comprehensive cost of the user to install the photovoltaic energy storage system and the user’s daily electricity bill to establish a bi-level optimization model. The outer model optimizes the photovoltaic & energy storage capacity, and the inner model optimizes the operation strategy of the energy storage. And calculate the actual life of the energy storage through the rain flow counting method. Use the fmincon function in the optimization toolbox to solve the problem on the matlab platform. The result of the calculation example verifies the improvement effect of the bi-level optimization model proposed in this paper on user economy.
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