我国已宣布力争2030年前二氧化碳排放达到峰值,为确保河北省能够保质保量完成碳达峰目标,采用联合国政府间气候变化专门委员会(Intergovernmental Panel on Climate Change, IPCC)排放因子法测算河北省2005-2021年化石能源消费碳排放量...我国已宣布力争2030年前二氧化碳排放达到峰值,为确保河北省能够保质保量完成碳达峰目标,采用联合国政府间气候变化专门委员会(Intergovernmental Panel on Climate Change, IPCC)排放因子法测算河北省2005-2021年化石能源消费碳排放量,选取人口、人均GDP、城镇化率、产业结构、能源强度和能源结构6个因素,构建了河北省碳排放人口、财富和技术影响(stochastic impacts by regression on population, affluence, and technology, STIRPAT)预测模型,通过构建河北省碳排放情景,对河北2022-2040年碳排放量进行了预测。结果表明在基准情景和经济发展情景下,河北省碳排放趋势是持续上升的,未出现达峰点;产业转型、绿色发展和目标导向情景下出现了峰值点,其中目标导向情景在2029年达峰,绿色发展情景在2030年达峰,碳达峰量分别为81 626.658万吨二氧化碳和86 018.255万吨二氧化碳,产业转型情景在2035年达峰,碳达峰量为85 214.349万吨二氧化碳。按照目前情景发展下河北省难以在2030年实现碳达峰,为保质保量完成达峰目标,需要以能源绿色低碳发展为关键手段,同时以科技和制度创新为动力,调整优化产业结构和能源结构。展开更多
A multivariate statistical downscaling method is developed to produce regional, high-resolution, coastal surface wind fields based on the IPCC global model predictions for the U.S. east coastal ocean, the Gulf of Mexi...A multivariate statistical downscaling method is developed to produce regional, high-resolution, coastal surface wind fields based on the IPCC global model predictions for the U.S. east coastal ocean, the Gulf of Mexico(GOM), and the Caribbean Sea. The statistical relationship is built upon linear regressions between the empirical orthogonal function(EOF) spaces of a cross- calibrated, multi-platform, multi-instrument ocean surface wind velocity dataset(predictand) and the global NCEP wind reanalysis(predictor) over a 10 year period from 2000 to 2009. The statistical relationship is validated before applications and its effectiveness is confirmed by the good agreement between downscaled wind fields based on the NCEP reanalysis and in-situ surface wind measured at 16 National Data Buoy Center(NDBC) buoys in the U.S. east coastal ocean and the GOM during 1992–1999. The predictand-predictor relationship is applied to IPCC GFDL model output(2.0?×2.5?) of downscaled coastal wind at 0.25?×0.25? resolution. The temporal and spatial variability of future predicted wind speeds and wind energy potential over the study region are further quantified. It is shown that wind speed and power would significantly be reduced in the high CO_2 climate scenario offshore of the mid-Atlantic and northeast U.S., with the speed falling to one quarter of its original value.展开更多
As we know,the projections of future climate change including impacts and strategies in the IPCC Assessment Reports were based on global climate models with scenarios on various human activities.Global climate model s...As we know,the projections of future climate change including impacts and strategies in the IPCC Assessment Reports were based on global climate models with scenarios on various human activities.Global climate model simulations provide key inputs for climate change assessments. In this study,the main objective is to analyze if the projections of fu-ture climate change by global climate models are reli-able.Several workshops have been held on this issue,such as the IPCC expert meeting on assessing and combining multi-model climate projections in January of 2010 (presided by the co-chairs of the IPCC WGI and WGII AR5),and the workshop of the combined global climate model group held by NCAR in June of 2010.展开更多
文摘我国已宣布力争2030年前二氧化碳排放达到峰值,为确保河北省能够保质保量完成碳达峰目标,采用联合国政府间气候变化专门委员会(Intergovernmental Panel on Climate Change, IPCC)排放因子法测算河北省2005-2021年化石能源消费碳排放量,选取人口、人均GDP、城镇化率、产业结构、能源强度和能源结构6个因素,构建了河北省碳排放人口、财富和技术影响(stochastic impacts by regression on population, affluence, and technology, STIRPAT)预测模型,通过构建河北省碳排放情景,对河北2022-2040年碳排放量进行了预测。结果表明在基准情景和经济发展情景下,河北省碳排放趋势是持续上升的,未出现达峰点;产业转型、绿色发展和目标导向情景下出现了峰值点,其中目标导向情景在2029年达峰,绿色发展情景在2030年达峰,碳达峰量分别为81 626.658万吨二氧化碳和86 018.255万吨二氧化碳,产业转型情景在2035年达峰,碳达峰量为85 214.349万吨二氧化碳。按照目前情景发展下河北省难以在2030年实现碳达峰,为保质保量完成达峰目标,需要以能源绿色低碳发展为关键手段,同时以科技和制度创新为动力,调整优化产业结构和能源结构。
基金the Fundamental Research Funds for the Central Universities (3101000-841413030)National Oceanic and Atmospheric Administration through grant NA11NOS0120033+2 种基金National National Science Foundation of China through grants 41506012, 41376001, 41206013, 41476047, 41430963, 41206004the support by National Aeronautics and Space Administration through grant NNX13AD80Gthe public science and technology research funds projects of ocean (201205018)
文摘A multivariate statistical downscaling method is developed to produce regional, high-resolution, coastal surface wind fields based on the IPCC global model predictions for the U.S. east coastal ocean, the Gulf of Mexico(GOM), and the Caribbean Sea. The statistical relationship is built upon linear regressions between the empirical orthogonal function(EOF) spaces of a cross- calibrated, multi-platform, multi-instrument ocean surface wind velocity dataset(predictand) and the global NCEP wind reanalysis(predictor) over a 10 year period from 2000 to 2009. The statistical relationship is validated before applications and its effectiveness is confirmed by the good agreement between downscaled wind fields based on the NCEP reanalysis and in-situ surface wind measured at 16 National Data Buoy Center(NDBC) buoys in the U.S. east coastal ocean and the GOM during 1992–1999. The predictand-predictor relationship is applied to IPCC GFDL model output(2.0?×2.5?) of downscaled coastal wind at 0.25?×0.25? resolution. The temporal and spatial variability of future predicted wind speeds and wind energy potential over the study region are further quantified. It is shown that wind speed and power would significantly be reduced in the high CO_2 climate scenario offshore of the mid-Atlantic and northeast U.S., with the speed falling to one quarter of its original value.
文摘As we know,the projections of future climate change including impacts and strategies in the IPCC Assessment Reports were based on global climate models with scenarios on various human activities.Global climate model simulations provide key inputs for climate change assessments. In this study,the main objective is to analyze if the projections of fu-ture climate change by global climate models are reli-able.Several workshops have been held on this issue,such as the IPCC expert meeting on assessing and combining multi-model climate projections in January of 2010 (presided by the co-chairs of the IPCC WGI and WGII AR5),and the workshop of the combined global climate model group held by NCAR in June of 2010.
