Light absorbing particles（LAP, e.g., black carbon, brown carbon, and dust） influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric...Light absorbing particles（LAP, e.g., black carbon, brown carbon, and dust） influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance（a.k.a., surface darkening）, which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice（LAPSI） has been identified as one of major forcings affecting climate change, e.g.in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, and climatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.展开更多
This paper represents the first national effort of its kind to systematically investigate the impact of changes in climate and land use and land cover （LULC） on the carbon cycle with high-resolution dynamic LULC dat...This paper represents the first national effort of its kind to systematically investigate the impact of changes in climate and land use and land cover （LULC） on the carbon cycle with high-resolution dynamic LULC data at the decadal scale （1990s and 2000s）. Based on simulations using well calibrated and validated Carbon Exchanges in the Vegetation-Soil-Atmosphere （CEVSA） model, tem- poral and spatial variations in carbon storage and fluxes in China may be generated empower us to relate these variations to climate variability and LULC with respect to net primary productivity （NPP）, heterotrophic respiration （HR）, net ecosystem productivity （NEP）, storage and soil carbon （SOC）, and vegetation carbon （VEGC） individually or collectively. Overall, the increases in NPP were greater than HR in most cases due to the effect of global warming with more precipitation in China from 1981 to 2000. With this trend, the NEP remained positive during that period, resulting in a net increase of total amount of carbon being stored by about 0.296 PgC within a 20-year time frame. Because the climate effect was much greater than that of changes of LULC, the total carbon storage in China actually increased by about 0.17 PgC within the 20-year time period. Such findings will contribute to the generation of carbon emissions control policies under global climate change impacts.展开更多
Capacity of carbon sequestration in forest ecosystem largely depends on the trend of net primary production (NPP) and the length of ecosystem carbon residence time. Retrieving spatial patterns of ecosystem carbon resi...Capacity of carbon sequestration in forest ecosystem largely depends on the trend of net primary production (NPP) and the length of ecosystem carbon residence time. Retrieving spatial patterns of ecosystem carbon residence time is important and necessary for accurately predicting regional carbon cycles in the future. In this study, a data-model fusion method that combined a process-based regional carbon model (TECO-R) with various ground-based ecosystem observations (NPP, biomass, and soil organic carbon) and auxiliary data sets (NDVI, meteorological data, and maps of vegetation and soil texture) was applied to estimate spatial patterns of ecosystem carbon residence time in Chinese forests at steady state. In the data-model fusion, the genetic algorithm was used to estimate the optimal model parameters related with the ecosystem carbon residence time by minimizing total deviation between modeled and observed values. The results indicated that data-model fusion technology could effectively retrieve model parameters and simulate carbon cycling processes for Chinese forest ecosystems. The estimated carbon residence times were highly heterogenous over China, with most of regions having values between 24 and 70 years. The deciduous needleleaf forest and the evergreen needleleaf forest had the highest averaged carbon residence times (73.8 and 71.3 years, respectively), the mixed forest and the deciduous broadleaf forest had moderate values (38.1 and 37.3 years, respectively), and the evergreen broadleaf forest had the lowest value (31.7 years). The averaged carbon residence time of forest ecosystems in China was 57.8 years.展开更多
The success of catalytic schemes for the large-scale valorization of CO_(2) does not only depend on the development of active,selective and stable catalytic materials but also on the overall process design.Here we pre...The success of catalytic schemes for the large-scale valorization of CO_(2) does not only depend on the development of active,selective and stable catalytic materials but also on the overall process design.Here we present a multidisciplinary study(from catalyst to plant and techno-economic/lifecycle analysis)for the production of green methanol from renewable H2 and CO_(2).We combine an in-depth kinetic analysis of one of the most promising recently reported methanol-synthesis catalysts(InCo)with a thorough process simulation and techno-economic assessment.We then perform a life cycle assessment of the simulated process to gauge the real environmental impact of green methanol production from CO_(2).Our results indicate that up to 1.75 ton of CO_(2) can be abated per ton of produced methanol only if renewable energy is used to run the process,while the sensitivity analysis suggest that either rock-bottom H2 prices(1.5$kg1)or severe CO_(2) taxation(300$per ton)are needed for a profitable methanol plant.Besides,we herein highlight and analyze some critical bottlenecks of the process.Especial attention has been paid to the contribution of H2 to the overall plant costs,CH4 trace formation,and purity and costs of raw gases.In addition to providing important information for policy makers and industrialists,directions for catalyst(and therefore process)improvements are outlined.展开更多
The IPCC SRES narratives were implemented in IMAGE 2.2 to evaluate thefuture condition of the climate system (including the biosphere). A series of scenario experiments was used to assess possible ranges in emissions ...The IPCC SRES narratives were implemented in IMAGE 2.2 to evaluate thefuture condition of the climate system (including the biosphere). A series of scenario experiments was used to assess possible ranges in emissions and concentrations of greenhouse gases, climate change and impacts. These experiments focussed on the role of the terrestrial carbon cycle. The experiments show that the SRES narratives dominate human emissions and not natural processes. In contrary, atmospheric CO2 concentration strongly differs between the experiments. Atmospheric CO2 concentrations range for A1B from 714 to 1009 ppmv CO2 in 2100. The spread of this range is comparable with the full SRES range as implemented in IMAGE 2.2 (515-895 μmol/mol CO2). The most important negative and positive feedback processes in IMAGE 2.2 on the build-up of CO2 concentrations are CO2 fertilisation and soil respiration respectively. Indirect effects of these processes furtherchange land-use patterns, deforestation rates and alter the natural C fluxes. The cumulative effects of these changes have a pronounced influence on the final CO2 concentrations. Our scenario experiments highlight the importance of a proper parameterisation of feedback processes, C-cycle and land use in determining the future states of the climate system.展开更多
A mesoscopic cellular automaton model that takes into account grain deformation during hot deformation has been developed to quantitatively depict the microstructural evolution of the austenite dynamic recrystallizati...A mesoscopic cellular automaton model that takes into account grain deformation during hot deformation has been developed to quantitatively depict the microstructural evolution of the austenite dynamic recrystallization （DRX） in a low-carbon steel. Both the grain deformation and the concept of DRX cycle are introduced, allowing accurate depictions of the grain structures, the overall microstructural properties and the flow stress evolutions that involving in the austenite DRX. The simulation results are compared with the experimental results and the predictions by the macroscopic DRX model and are found to be in good agreement.展开更多
The ionosphere varies over multiple time scales,which are classified into two categories: the climatology and weather variations.In this national report,we give a brief summary of recent progresses in ionospheric clim...The ionosphere varies over multiple time scales,which are classified into two categories: the climatology and weather variations.In this national report,we give a brief summary of recent progresses in ionospheric climatology with focus on(1) the seasonal variations,(2) solar cycle effects, and(3) empirical modeling of the ionosphere.The seasonal variations of the ionosphere have been explored in many works to give a more detailed picture with regional and global features at various altitudes by analyzing the observation data from various sources and models.Moreover,a series of studies reported the response of the ionosphere to solar cycle variations,which revealed some novel and detailed features of solar activity dependence of ionospheric parameters at different altitudes. These investigations have improved our understanding on the states of the ionosphere and underlying fundamental processes,provided clues to future studies on ionospheric weather,and guided ionospheric modeling,forecasting and related applications.展开更多
基金supported by the U.S.Department of Energy, Office of Science, Biological and Environmental Research, as part of the Earth System Modeling ProgramThe NASA Modeling, Analysis, and Prediction (MAP) Program by the Science Mission Directorate at NASA Headquarters supported the work contributed by Teppei J.YASUNARI and William K.M.LAU+2 种基金The NASA GEOS-5 simulation was implemented in the system for NASA Center for Climate Simulation (NCCS).M.G.Flanner was partially supported by NSF 1253154support from the China Scholarship FundThe Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC06-76RLO1830
文摘Light absorbing particles（LAP, e.g., black carbon, brown carbon, and dust） influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance（a.k.a., surface darkening）, which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice（LAPSI） has been identified as one of major forcings affecting climate change, e.g.in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, and climatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.
文摘This paper represents the first national effort of its kind to systematically investigate the impact of changes in climate and land use and land cover （LULC） on the carbon cycle with high-resolution dynamic LULC data at the decadal scale （1990s and 2000s）. Based on simulations using well calibrated and validated Carbon Exchanges in the Vegetation-Soil-Atmosphere （CEVSA） model, tem- poral and spatial variations in carbon storage and fluxes in China may be generated empower us to relate these variations to climate variability and LULC with respect to net primary productivity （NPP）, heterotrophic respiration （HR）, net ecosystem productivity （NEP）, storage and soil carbon （SOC）, and vegetation carbon （VEGC） individually or collectively. Overall, the increases in NPP were greater than HR in most cases due to the effect of global warming with more precipitation in China from 1981 to 2000. With this trend, the NEP remained positive during that period, resulting in a net increase of total amount of carbon being stored by about 0.296 PgC within a 20-year time frame. Because the climate effect was much greater than that of changes of LULC, the total carbon storage in China actually increased by about 0.17 PgC within the 20-year time period. Such findings will contribute to the generation of carbon emissions control policies under global climate change impacts.
基金supported by the National Natural Science Foundation of China (Grant Nos.30970514,30590384,40671173,40425008)the Open Funding from the Key Laboratory of Regional Climate-Environment Research for Temperate East Asia
文摘Capacity of carbon sequestration in forest ecosystem largely depends on the trend of net primary production (NPP) and the length of ecosystem carbon residence time. Retrieving spatial patterns of ecosystem carbon residence time is important and necessary for accurately predicting regional carbon cycles in the future. In this study, a data-model fusion method that combined a process-based regional carbon model (TECO-R) with various ground-based ecosystem observations (NPP, biomass, and soil organic carbon) and auxiliary data sets (NDVI, meteorological data, and maps of vegetation and soil texture) was applied to estimate spatial patterns of ecosystem carbon residence time in Chinese forests at steady state. In the data-model fusion, the genetic algorithm was used to estimate the optimal model parameters related with the ecosystem carbon residence time by minimizing total deviation between modeled and observed values. The results indicated that data-model fusion technology could effectively retrieve model parameters and simulate carbon cycling processes for Chinese forest ecosystems. The estimated carbon residence times were highly heterogenous over China, with most of regions having values between 24 and 70 years. The deciduous needleleaf forest and the evergreen needleleaf forest had the highest averaged carbon residence times (73.8 and 71.3 years, respectively), the mixed forest and the deciduous broadleaf forest had moderate values (38.1 and 37.3 years, respectively), and the evergreen broadleaf forest had the lowest value (31.7 years). The averaged carbon residence time of forest ecosystems in China was 57.8 years.
基金support from the King Abdullah University of Science and Technology(KAUST).T.Cordero-Lanzac and A.T.Aguayo acknowledge the financial support received from the Spanish Ministry of Science and Innovation with some ERDF funds(CTQ2016-77812-R)the Basque Government(IT1218-19)+2 种基金T.Cordero-Lanzac also acknowledges the Spanish Ministry of Education,Culture and Sport for the award of his FPU grant(FPU15-01666)A.Navajas and L.M.Gandía gratefully acknowledge the financial support from Spanish Ministerio de Ciencia,Innovación y Universidades,and the European Regional Development Fund(ERDF/FEDER)(grant RTI2018-096294-B-C31)L.M.Gandía also thanks Banco de Santander and Universidad Pública de Navarra for their financial support under“Programa de Intensificación de la Investigación 2018”initiative.
文摘The success of catalytic schemes for the large-scale valorization of CO_(2) does not only depend on the development of active,selective and stable catalytic materials but also on the overall process design.Here we present a multidisciplinary study(from catalyst to plant and techno-economic/lifecycle analysis)for the production of green methanol from renewable H2 and CO_(2).We combine an in-depth kinetic analysis of one of the most promising recently reported methanol-synthesis catalysts(InCo)with a thorough process simulation and techno-economic assessment.We then perform a life cycle assessment of the simulated process to gauge the real environmental impact of green methanol production from CO_(2).Our results indicate that up to 1.75 ton of CO_(2) can be abated per ton of produced methanol only if renewable energy is used to run the process,while the sensitivity analysis suggest that either rock-bottom H2 prices(1.5$kg1)or severe CO_(2) taxation(300$per ton)are needed for a profitable methanol plant.Besides,we herein highlight and analyze some critical bottlenecks of the process.Especial attention has been paid to the contribution of H2 to the overall plant costs,CH4 trace formation,and purity and costs of raw gases.In addition to providing important information for policy makers and industrialists,directions for catalyst(and therefore process)improvements are outlined.
文摘The IPCC SRES narratives were implemented in IMAGE 2.2 to evaluate thefuture condition of the climate system (including the biosphere). A series of scenario experiments was used to assess possible ranges in emissions and concentrations of greenhouse gases, climate change and impacts. These experiments focussed on the role of the terrestrial carbon cycle. The experiments show that the SRES narratives dominate human emissions and not natural processes. In contrary, atmospheric CO2 concentration strongly differs between the experiments. Atmospheric CO2 concentrations range for A1B from 714 to 1009 ppmv CO2 in 2100. The spread of this range is comparable with the full SRES range as implemented in IMAGE 2.2 (515-895 μmol/mol CO2). The most important negative and positive feedback processes in IMAGE 2.2 on the build-up of CO2 concentrations are CO2 fertilisation and soil respiration respectively. Indirect effects of these processes furtherchange land-use patterns, deforestation rates and alter the natural C fluxes. The cumulative effects of these changes have a pronounced influence on the final CO2 concentrations. Our scenario experiments highlight the importance of a proper parameterisation of feedback processes, C-cycle and land use in determining the future states of the climate system.
基金the financial supports from the National Natural Science Foundation of China (NSFC) under Grant Nos. 51401214 and 51371169
文摘A mesoscopic cellular automaton model that takes into account grain deformation during hot deformation has been developed to quantitatively depict the microstructural evolution of the austenite dynamic recrystallization （DRX） in a low-carbon steel. Both the grain deformation and the concept of DRX cycle are introduced, allowing accurate depictions of the grain structures, the overall microstructural properties and the flow stress evolutions that involving in the austenite DRX. The simulation results are compared with the experimental results and the predictions by the macroscopic DRX model and are found to be in good agreement.
基金supported by the Chinese Academy of Sciences(KZZD-EW-01-3)National Key Basic Research Program of China(2012- CB825604)National Natural Science Foundation of China(41074112,41174137)
文摘The ionosphere varies over multiple time scales,which are classified into two categories: the climatology and weather variations.In this national report,we give a brief summary of recent progresses in ionospheric climatology with focus on(1) the seasonal variations,(2) solar cycle effects, and(3) empirical modeling of the ionosphere.The seasonal variations of the ionosphere have been explored in many works to give a more detailed picture with regional and global features at various altitudes by analyzing the observation data from various sources and models.Moreover,a series of studies reported the response of the ionosphere to solar cycle variations,which revealed some novel and detailed features of solar activity dependence of ionospheric parameters at different altitudes. These investigations have improved our understanding on the states of the ionosphere and underlying fundamental processes,provided clues to future studies on ionospheric weather,and guided ionospheric modeling,forecasting and related applications.
