In view of the great contribution of coal-fired units to CO2 emissions, the coupled coal and power system with consideration of CO2 mitigation is a typical sub-system of the highly emitting Chinese energy system for low-carbon studies. In this study, an inexact mix-integer two-stage programming (IMITSP) model for the management of low-carbon energy systems was developed based on the integration of multiple inexact programming techniques. Uncertainties and complexities related to the carbon mitigation issues in the coupled coal and power system can be effectively reflected and dealt with in this model. An optimal CO2 mitigation strategy associated with stochastic power-generation demand under specific CO2 mitigation targets could be obtained. Dynamic analysis of capacity expansion, facility improvement, coal selection, as well as coal blending within a multi-period and multi-option context could be facilitated. The developed IMITSP model was applied to a semi-hypothetical case of long-term coupled management of coal and power within a low-carbon energy system in north China. The generated decision alternatives could help decision makers identify desired strategies related to coal production and allocation, CO2 emission mitigation, as well as facility capacity upgrade and expansion under various social-economic, ecological, environmental and system-reliability constraints. It could also provide interval solutions with a minimized system cost, a maximized system reliability and a maximized power-generation demand security. Moreover, the developed model could provide an in-depth insight into various CO2 mitigation technologies and the associated environmental and economic implications under a given reduction target. Tradeoffs among system costs, energy security and CO2 emission reduction could be analyzed.
An inexact two-stage fuzzy chance-constrained programming (ITSFCCP) model was developed in this study for dealing with multiple uncertainties associated with solid waste management systems. The model was formulated by incorporating fuzzy chance-constrained programming and interval linear programming within a two-stage stochastic programming framework. The model could be used to facilitate analysis of the policy scenarios; meanwhile, the uncertainties associated with solid waste management systems could be expressed as probability distributions, possibility distribution and discrete intervals. A long-term waste planning problem was used to demonstrate the applicability of the ITSFCCP model. The study results indicated that ITSFCCP could provide a linkage to pre-defined policies and allowed violation of system constraints at predefined confidence levels. Moreover, it allowed uncertain information presented as discrete intervals to be communicated into the optimisation process. ITSFCCP could help waste manag...
Abstract Human-induced climate change has affected weather and extreme climate events, the Three Gorges Hydropower Project is the largest hydropower project in the world, which must inevitably have some impacts on the regional climate and extreme climate. Based on the data of precipitation, temperature, sunshine hours, relative humidity, minimum temperature and maximum temperature of 14 meteorological stations in the study area for 59 years from 1961 to 2019, this paper adopts the climate tendency rate, Mann-Kendall test, ordered clustering method, Kriging difference method to analyze the climate change trend and spatial differentiation characteristics before and after the impoundment of the Three Gorges Reservoir. The results indicated that the impact on precipitation is weak, there is no significant trends; sunshine hours and relative humidity all showed a significant decreasing trend at 11 stations. However, Except Gaoping, Badong, Enshi and Laifeng, the temperature of the other 10 stations has changed significantly rise trend from a cooling trend to a warming trend. The Three Gorges Reservoir has a slowing effect on the rise of minimum temperature at Wanyuan, Badong, Wufeng, Yichang, Jingzhou, Wanzhou, Shapingba, Laifeng and Yibing, the impact on the ecosystem is beneficial. The increase of maximum temperature at 13 stations except Yichang will inevitably change the regional ecosystem. The abrupt changes of temperature, relative humidity and maximum temperature all occurred after impoundment of the Three Gorges Reservoir. After the impoundment of the Three Gorges Dam, the precipitation variability increased in the west and decreased in the east; North-central temperatures rise more; The decrease range in the east is greater than that in the west; Relative humidity in the west decreased more than that in the east. The temporal and spatial changes of lacal climate will inevitably have a certain impact on the local ecosystem.
Inter-provincial trade is accompanied by the transfer of embodied pollution emissions, leading to emissions leakage, thereby hindering the sustainable development of society. Therefore, it is imperative to analyze the characteristics of embodied pollutant emission and spatial transfer driven by inter-provincial trade. In this study, the quantitative and spatial characteristics of the six main embodied pollutants (i.e., SO2, NOX, CO, VOC, PM2.5, and PM10) were analyzed by a hypothetical extraction method (HEM) and complex network analysis (CNA) under an input–output analysis (IOA) framework. Then, the row arrange series (RAS) method was employed to simulate the impacts of varying levels of trade intensity, economic growth rate, and technological progress on embodied pollutants and spatial-transfer characteristics. The major findings are as follows: (i) the increase in inter-provincial trade led to a corresponding rise in embodied pollutant emissions due to the relocation of production activities towards provinces with higher emission intensity. Excessive responsibility was assumed by provinces such as Shanxi and Hebei, engaging in production outsourcing for reducing pollutants. (ii) The macro direction of pollutant transfer paths was from the resource-rich northern and central provinces towards the trade-developed southern provinces. Sectors in the transfer path, such as the industry sectors of Shanxi, Guangdong, Henan, and the transport sector of Henan, exhibited high centrality and dominated pollutant transfer activities in the network. (iii) The industry sector, characterized by substantial energy consumption, was the predominant emitter of all pollutant production-based emissions, accounting for more than 40% of total emissions. This study is conducive to analyzing the impacts of inter-provincial trade on embodied pollutant emissions and developing emissions reduction policies considering equitable allocation of emissions responsibilities from both production and consumption perspectives.
Abstract China’s coastal lands and seas are highly susceptible to the changing environment due to their dense population and frequent economic activities. These areas experience more significant impacts from climate change-induced extreme events than elsewhere. The most noticeable effects of climate change are extreme high temperatures and extreme precipitation. We employ an ensemble of RCMs (Regional Climate Models) to investigate and project changes in temperature, precipitation, and Compound Heat-Precipitation Extreme events (CHPEs) over selected China’s coastal lands and seas for both historical (1985–2004) and future periods (2080–2099). The multi-model ensemble projects that daily temperature extremes will increase by 2.9 °C to 5.4 °C across China’s coastal lands and seas, with land areas showing a higher temperature increase than marine areas. Extreme precipitation shows a high geographical heterogeneity with a 2.8–3.9 mm d −1 reduction over the 15–25°N marine areas while a 2.2–5.4 mm d −1 increment over the 25°N-35°N land areas. We use the Clausius–Clapeyron relationship to reveal that the peak of daily extreme precipitation will increase by 2–7 mm d −1 and the temperature at which extreme precipitation peaks will increase by 2 °C to 6 °C by warming. The land area of 25–30°N has the highest peak precipitation increase of 9.87 mm d −1 and a peak temperature increase of 6 °C. As precipitation extremes intensify with daily temperature extremes increase, CHPEs are projected to occur more frequently over both land and marine areas. Compared with the historical period, the frequency of CHPEs will increase by 40.9%-161.2% over marine areas, and by 36.2%-163.6% over land areas in the future. The 15–20°N area has the highest frequency increase of CHPE events, and the 25–30°N area has the largest difference in frequency increase under two different scenarios. It indicated that the 25–30°N area will be more easily affected by climate change.
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