Blasting is still being considered to be one the most important applicable alternatives for conventional excavations. Ground vibration generated due to blasting is an undesirable phenomenon which is ...harmful for the nearby structures and should be prevented. In this regard, a novel intelligent approach for predicting blast-induced PPV was developed. The distinctive Jaya algorithm and high efficient extreme gradient boosting machine (XGBoost) were applied to obtain the goal, called the Jaya-XGBoost model. Accordingly, 150 sets of data composed of 13 controllable and uncontrollable parameters are chosen as input independent variables and the measured peak particle velocity (PPV) is chosen as an output dependent variable. Also, the Jaya algorithm was used for optimization of hyper-parameters of XGBoost. Additionally, six empirical models and several machine learning models such as XGBoost, random forest, AdaBoost, artificial neural network and Bagging were also considered and applied for comparison of the proposed Jaya-XGBoost model. Accuracy criteria including determination coefficient (R2), root-mean-square error (RMSE), mean absolute error (MAE), and the variance accounted for (VAF) were used for the assessment of models. For this study, 150 blasting operations were analyzed. Also, the Shapley Additive Explanations (SHAP) method is used to interpret the importance of features and their contribution to PPV prediction. Findings reveal that the proposed Jaya-XGBoost emerged as the most reliable model in contrast to other machine learning models and traditional empirical models. This study may be helpful to mining researchers and engineers who use intelligent machine learning algorithms to predict blast-induced ground vibration.
Using the Transportation Mode-Technology-Energy-CO2 (TMOTEC) model which is based on discrete choice mothed and general transport cost simulation, this study made a scenario analysis of energy ...consumption and reductions in CO2 emissions in China’s transport sector. We used scenarios to investigate the relative influences of improving vehicle energy efficiency, promoting EV use, and increasing taxes for fossil fuels and CO2. We found that in the reference scenario, total transport energy consumption would increase to 636 million tons of oil equivalent (Mtoe) in 2050; that would result in 1602 million tons of CO2 emissions. In the comprehensive development scenario, transport energy consumption would peak at 497 Mtoe around 2045; the resulting CO2 emissions peak would be 1129 million tons of CO2 between 2040 and 2045. Both energy consumption and CO2 emissions in the transport sector would decline steadily after reaching their peak. We believe that the Chinese government should make greater efforts with vehicle fuel economy standards, in improving technological progress and market expansion of EVs, and in increasing taxes on traditional transport energy and CO2. This would contribute to reducing energy consumption and achieving a CO2 emissions peak in China’s transport sector as soon as possible.
•A Transportation Mode-Technology-Energy-CO2 model based on discrete choice mothed is set up.•Transportation energy use and CO2 emissions in future in China are simulated.•Transportation energy use could peak at about 500 Million toe around 2045 in China.•Transportation CO2 emissions could peak at about 1130 million tons of CO2 before 2045.
•A provincial model for road transport energy demand and GHG emissions in China.•China’s vehicle stock will keep increasing and reach 540 million in 2050.•EV can have great impact on road transport ...energy demand and GHG emissions.•Future vehicle ownership and GHG emissions vary among Chinese provinces.
Energy consumption and greenhouse gas (GHG) emissions of China’s road transport sector have been increasing rapidly in recent years. Previous studies on the future trends trend to focus on the national picture and cannot offer regional insights. We build a novel bottom-up model to estimate the future energy demand and GHG emissions of China’s road transport at a provincial level, considering local economic development, population and policies. Detailed technical characteristics of the future vehicle fleets are analyzed in several up-to date scenarios. The results indicate that China’s vehicle stock will keep increasing to 543 million by 2050. The total direct petroleum demand and associated GHG emissions will peak at 508 million tonnes of oil equivalent (Mtoe) and 1500 million tonnes CO2 equivalent (Mt CO2,e) around 2030 in the Reference scenario. Natural gas vehicle diffusion has a large impact on petroleum demand reduction in the short term, with decreases of 41–46 Mtoe in 2050. Compared to the Reference case, battery electric and fuel cell vehicles will reduce petroleum demand by 94–157 and 28–54 Mtoe in 2050, respectively. When combined with decarbonization of future power supply, battery electric vehicles can play a significant role in reducing Well-to-Wheels GHG emissions in 2050 with 295–449 Mt CO2,e more reductions. The spatial distributions of future vehicle stock, energy demand and GHG emissions vary among provinces and show a generally downward trend from east to west. Policy recommendations are made in terms of the development of alternative fuels and vehicle technologies considering provincial differences, expansion of natural gas vehicle market and acceleration of electric vehicle market penetration.
China has adopted targets for developing renewable electricity that would require expansion on an unprecedented scale. During the period from 2010 to 2020, we find that current renewable electricity ...targets result in significant additional renewable energy installation and a reduction in cumulative CO2 emissions of 1.8% relative to a No Policy baseline. After 2020, the role of renewables is sensitive to both economic growth and technology cost assumptions. Importantly, we find that the CO2 emissions reductions due to increased renewables are offset in each year by emissions increases in non-covered sectors through 2050. We consider sensitivity to renewable electricity cost after 2020 and find that if cost falls due to policy or other reasons, renewable electricity share increases and results in slightly higher economic growth through 2050. However, regardless of the cost assumption, projected CO2 emissions reductions are very modest under a policy that only targets the supply side in the electricity sector. A policy approach that covers all sectors and allows flexibility to reduce CO2 at lowest cost – such as an emissions trading system – will prevent this emissions leakage and ensure targeted reductions in CO2 emissions are achieved over the long term.
•The 2020 targets and subsidies make renewable electricity economically viable in the short term.•Cumulative CO2 emissions (2010-2020) are reduced by 1.8% in the Current Policy scenario.•Displacing fossil fuels from electricity leads to increases in other sectors, offsetting emissions reductions.•The expansion of renewables after 2020 depends on cost reductions achieved.
To control rising energy use and CO2 emissions, China׳s leadership has enacted energy and CO2 intensity targets as part of the Twelfth Five-Year Plan (the Twelfth FYP, 2011–2015). Both to support ...achievement of these targets and to lay the foundation for a future national market-based climate policy, at the end of 2011, China׳s government selected seven areas to establish pilot emissions trading systems (ETS). In this paper, we provide a comprehensive overview of current status of China׳s seven ETS pilots. Pilots differ in the extent of sectoral coverage, the size threshold for qualifying installations, and other design features that reflect diverse settings and priorities. By comparing the development of the ETS pilots, we identify issues that have emerged in the design process, and outline important next steps for the development of a national ETS.
•We summarize the history of China׳s climate policy and milestones in China׳s ETS development.•We provide a comprehensive overview of the current status of China׳s seven ETS pilots.•We discuss some key issues and challenges related to the implementation of the ETS pilots.•We identify next steps to support development of a national ETS in China.
The main purpose of blasting operation is to produce desired and optimum mean size rock fragments. Smaller or fine fragments cause the loss of ore during loading and transportation, whereas large or ...coarser fragments need to be further processed, which enhances production cost. Therefore, accurate prediction of rock fragmentation is crucial in blasting operations. Mean fragment size (MFS) is a crucial index that measures the goodness of blasting designs. Over the past decades, various models have been proposed to evaluate and predict blasting fragmentation. Among these models, artificial intelligence (AI)-based models are becoming more popular due to their outstanding prediction results for multi-influential factors. In this study, support vector regression (SVR) techniques are adopted as the basic prediction tools, and five types of optimization algorithms, i.e. grid search (GS), grey wolf optimization (GWO), particle swarm optimization (PSO), genetic algorithm (GA) and salp swarm algorithm (SSA), are implemented to improve the prediction performance and optimize the hyper-parameters. The prediction model involves 19 influential factors that constitute a comprehensive blasting MFS evaluation system based on AI techniques. Among all the models, the GWO-v-SVR-based model shows the best comprehensive performance in predicting MFS in blasting operation. Three types of mathematical indices, i.e. mean square error (MSE), coefficient of determination (R2) and variance accounted for (VAF), are utilized for evaluating the performance of different prediction models. The R2, MSE and VAF values for the training set are 0.8355, 0.00138 and 80.98, respectively, whereas 0.8353, 0.00348 and 82.41, respectively for the testing set. Finally, sensitivity analysis is performed to understand the influence of input parameters on MFS. It shows that the most sensitive factor in blasting MFS is the uniaxial compressive strength.
Along with high-speed economic development and increasing energy consumption, the Chinese Government faces a growing pressure to maintain the balance between energy supply and demand. In 2009, China ...has become both the largest energy consumer and CO
2 emitting country in the world. In this case, the inappropriate energy consumption structure should be changed. As an alternative, a suitable infrastructure for the implementation of renewable energy may serve as a long-term sustainable solution. The perspective of a 100% renewable energy system has been analyzed and discussed in some countries previously. In this process, assessment of domestic renewable energy sources is the first step. Then appropriate methodologies are needed to perform energy system analyses involving the integration of more sustainable strategies. Denmark may serve as an example of how sustainable strategies can be implemented. The Danish system has demonstrated the possibility of converting into a 100% renewable energy system. This paper discusses the perspective of renewable energy in China firstly, and then analyses whether it is suitable to adopt similar methodologies applied in other countries as China approaches a renewable energy system. The conclusion is that China’s domestic renewable energy sources are abundant and show the possibility to cover future energy demand; the methodologies used to analyse a 100% renewable energy system are applicable in China. Therefore, proposing an analysis of a 100% renewable energy system in China is not unreasonable.
•The Emission Trading System will bring about considerable air quality co-benefits.•The PM2.5 concentration is reduced under the Emission Trading System.•The reduction of the exposure to PM2.5 causes ...the nationwide health improvement.•The morbidity and mortality are reduced under the Emission Trading System.•GDP loss can be partially offset considering the health benefits.
Quantification of the air quality and health co-benefits of climate policies can provide explicit near-term localized assessment of the benefits of efforts to mitigate climate change. In the study, the air quality and PM2.5 associated health co-benefits of China's national Emission Trading System to achieve the Nationally Determined Contribution is analyzed. The interdisciplinary integrated assessment model framework, named the Regional Emissions Air quality Climate Health Model, is applied. The results showed that substantial air quality improvement and health benefit will be achieved under the national Emission Trading System. But the cost and benefits varies according to the CO2 emission cap set. To peak CO2 emissions by 2025 will bring about more obvious improvement in air quality (ranging from 3% to 12% PM2.5 concentration reduction at provincial level compared with that to peak CO2 emission by 2030), more morbidities avoided from acute exposure and more mortalities avoided from acute exposure and chronic exposure. While the net health benefit to achieve peaking by 2025 is US$ 100 billion less than that to achieve peaking by 2030 due to greater GDP loss in 2030. The net benefit is subjected to the valuation of the health benefits. If a higher Value of a Statistical Life, US$ 1.92 million, is chosen, the net benefits to achieve peak CO2 emissions by 2025 can be equal to that to achieve peak CO2 emissions by 2030.
This review article presents a description of contemporary developments and findings related to the different elements needed in future 4th generation district heating systems (4GDH). Unlike the ...first three generations of district heating, the development of 4GDH involves meeting the challenge of more energy efficient buildings as well as the integration of district heating into a future smart energy system based on renewable energy sources. Following a review of recent 4GDH research, the article quantifies the costs and benefits of 4GDH in future sustainable energy systems. Costs involve an upgrade of heating systems and of the operation of the distribution grids, while benefits are lower grid losses, a better utilization of low-temperature heat sources and improved efficiency in the production compared to previous district heating systems. It is quantified how benefits exceed costs by a safe margin with the benefits of systems integration being the most important.
•Provides a review of 4th Generation District Heating (4GDH) in scientific papers.•Shows how 4GDH is an important integrated part of future sustainable energy systems.•Quantifies costs and benefits of 4GDH in a future sustainable energy system.•Shows how benefits exceed costs by a safe margin.•Shows the significant benefits of systems integration.
The Well-to-Meter (WTM) analysis module in the Tsinghua-CA3EM model has been used to examine the primary fossil energy consumption (PFEC) and greenhouse gas (GHG) emissions for electricity generation ...and supply in China. The results show that (1) the WTM PFEC and GHG emission intensities for the 2007 Chinese electricity mix are 3.247
MJ/MJ and 297.688
g carbon dioxide of equivalent (gCO
2,
e
)/MJ, respectively; (2) power generation is the main contributing sub-stage; (3) the coal-power pathway is the only major contributor of PFEC (96.23%) and GHG emissions (97.08%) in the 2007 mix; and (4) GHG emissions intensity in 2020 will be reduced to 220.470
gCO
2,
e
/MJ with the development of nuclear and renewable energy and to 169.014
gCO
2,
e
/MJ if carbon dioxide capture and storage (CCS) technology is employed. It is concluded that (1) the current high levels of PFEC and GHG emission for electricity in China are largely due to the dominant role of coal in the power-generation sector and the relatively low efficiencies during all the sub-stages from resource extraction to final energy consumption and (2) the development of nuclear and renewable energy as well as low carbon technologies such as CCS can significantly reduce GHG emissions from electricity.
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