区域土地利用影响地表CO2浓度异质性特征的动力学机制

本文综合应用高斯方程和拉姆齐模型,针对京津冀地区2000年以来10 km×10 km栅格尺度的地表CO₂浓度开展研究,分析了区域土地利用影响地表CO₂浓度异质性特征的动力学机制。研究发现：① 地表CO₂浓度与土地利用类型密切相关。2000—2018年京津冀地区CO₂浓度的高值区主要集中于经济较发达的快速城镇化地区;② 土地利用强度及土地利用效率上的时空分异为地表CO₂扩散提供了潜在的势能。京津冀地区地表CO₂排放及扩散存在明显的空间异质性,距离CO₂排放高值区越近,其相应的CO₂浓度越高并随时间推移及空间拓展呈逐步减小的态势;③ 京津冀地区在土地利用结构调整、格局优化及效率提升后,CO₂排放强度增幅明显减弱,其区域间的增幅差异也逐渐缩小。产业转型发展、土地利用格局优化、土地利用效率提高有效地抑制了京津冀地区地表CO₂排放强度的提升并促进了该区域的内涵式增长与高质量发展。     

基于交通大数据的广东省高速公路碳排放计量模型与空间格局

以广东省为例,基于高速公路联网收费系统的路段车流数据,建立包含I~IV类客车和I~VI类货车在内的全样本、高精度碳排放计量模型,并采用地理空间分析法探索广东省高速公路碳排放空间差异性。结论主要有：1）广东省高速公路碳排放主要来自于货车,货车碳排放占碳排放总量的57.1%;客车占42.9%。其中,中小型机动车,如I类客车（即小汽车）、I类和III类货车等是高速公路主要碳排放源。2）在高速公路网络中,碳排放高值路段具有集中于国家级高速公路、邻近经济发达和人口密集区、邻近机场和港口等空间特征。客车碳排放高值路段主要集中在珠三角区域,沿广州市向外呈放射状分布;货车碳排放高值路段主要分布在国家级高速公路,且货车载货量越小,碳排放空间分布越集中。3）广东省高速公路碳排放较高的地市多集中在珠三角城市群,广州市城市首位效应突出。县区尺度下,高速公路碳排放的空间非均衡特征显著,碳排放较高的县区多为广州市和佛山市下属县区。     

大气CO2浓度时空变化卫星遥感监测的应用潜力分析

GOSAT卫星观测反演大气CO2浓度精度已经提高到了1—2 ppm,而卫星数据能否准确地揭示全球和区域大气CO2浓度变化特征还缺乏充分的评价与分析。本文针对已经连续运行观测3年的GOSAT卫星,收集了来自美国NASA-OCO团队(ACOS)和日本环境研究所GOSAT团队(NIES)基于各自算法反演的两套大气CO2柱浓度数据,描述并分析了全球大气CO2时空变化特征。分析结果表明,从XCO2反演的绝对值结果来看ACOS总体上比NIES的高出约2 ppm左右,但从时空的相对变化上它们揭示了相近的大气CO2浓度时空变化特征。两套数据显示出全球平均大气CO2浓度在2010年—2012年的3年期间年增量分别为1.8 ppm和2.0 ppm;季节变化幅度,北半球最大4—6 ppm,南半球最大约2 ppm,这与地面观测结果基本一致。进一步将EDGAR 4.2人为排放总量格网化数据与GOSAT卫星观测反演的CO2浓度进行相关统计分析,结果指出两套数据对人为排放量有着微弱的响应。本文结果指出目前GOSAT卫星观测反演的XCO2可以检测出全球和区域大气CO2浓度的年变化、季节变化和区域空间变化的特征;GOSAT卫星10.5 km空间分辨率的观测虽难于检测出点源的浓度变化,但从区域上对人为排放的累积效应的监测显示了一定的应用潜力。     

Exploring land use policy scenarios with the use of a cellular automata-based model: urban sprawl containment and sustainable development in Thessaloniki

This study addresses the issue of urban sprawl through the application of a cellular automata (CA)-based model in the area of Thessaloniki, Greece. The model integrates a multiple regression model at the regional level with a CA model at the local level. New urban land is allocated in a disaggregated field of land units (cells) taking into account a wide range of data. Particular emphasis is placed on the way zoning regulations and land availability data are inserted into the model, so that alternative land use policy scenarios could be examined. Thessaloniki, a typical Mediterranean city, is used as a case study. The model is used to compare two scenarios of urban growth up to year 2030; the first one assuming a continuation of existing trends, whereas the second one assuming the enactment of various land use zoning regulations in order to contain urban sprawl.     

基于智慧交通的可达性与交通出行碳排放——理论与实证

信息与通信技术的发展推动了智慧交通建设,并将进一步提高城市交通可达性和影响居民出行。在全球应对气候变化、减少碳排放的共识背景下,由于"智慧交通—可达性—出行行为(碳排放)"间复杂的影响作用机制,已有的研究难以判断智慧化背景下的城市交通可达性提高将增加抑或减少出行碳排放。如何通过提高城市交通可达性来缓解交通拥堵,保障城市交通运输系统的有效运行,并提高居民出行效率,减少出行碳排放是当前中国智慧交通发展面临的关键问题之一。针对以上科学问题,本文尝试提出基于智慧交通的可达性与交通出行碳排放的理论框架,并以广州为研究案例地,研究了社区居民通勤碳排放特征及其影响机理,社区出行低碳指数格局及其影响因素的空间异质性,以及基于碳排放—位置分配模型的公共中心规划支持系统设计与应用,可为今后的相关研究提供借鉴。     

Country-specific dietary shifts to mitigate climate and water crises

Undernutrition, obesity, climate change, and freshwater depletion share food and agricultural systems as an underlying driver. Efforts to more closely align dietary patterns with sustainability and health goals could be better informed with data covering the spectrum of countries characterized by over- and undernutrition. Here, we model the greenhouse gas (GHG) and water footprints of nine increasingly plant-forward diets, aligned with criteria for a healthy diet, specific to 140 countries. Results varied widely by country due to differences in: nutritional adjustments, baseline consumption patterns from which modeled diets were derived, import patterns, and the GHG- and water-intensities of foods by country of origin. Relative to exclusively plant-based (vegan) diets, diets comprised of plant foods with modest amounts of low-food chain animals (i.e., forage fish, bivalve mollusks, insects) had comparably small GHG and water footprints. In 95 percent of countries, diets that only included animal products for one meal per day were less GHG-intensive than lacto-ovo vegetarian diets (in which terrestrial and aquatic meats were eliminated entirely) in part due to the GHG-intensity of dairy foods. The relatively optimal choices among modeled diets otherwise varied across countries, in part due to contributions from deforestation (e.g., for feed production and grazing lands) and highly freshwater-intensive forms of aquaculture. Globally, modest plant-forward shifts (e.g., to low red meat diets) were offset by modeled increases in protein and caloric intake among undernourished populations, resulting in net increases in GHG and water footprints. These and other findings highlight the importance of trade, culture, and nutrition in diet footprint analyses. The country-specific results presented here could provide nutritionally-viable pathways for high-meat consuming countries as well as transitioning countries that might otherwise adopt the Western dietary pattern.     

全球气候变化中的人类活动视角:社会经济情景的演变

社会经济情景的设定是全球气候变化研究的基础,也是气候变化影响评估的关键环节.本文回顾了社会经济情景的发展过程,阐述了共享社会经济路径的主要特点和最新发展趋势,介绍了区域社会经济情景的构建及在灾害风险领域中的应用,最后对共享社会经济路径的发展进行了展望.     

城镇化模式与低碳发展的关联分析——以石家庄市为例

不同城镇化发展模式对城市碳排放有显著影响。以石家庄市为案例,基于历年统计数据及实地调研数据,采用情景分析方法,定量核算石家庄市不同城镇化模式下的碳排放,结果表明在不同的城镇化模式下,石家庄市能源消费和碳排放将存在显著差异。与延续目前相对高碳的城镇化模式相比,在低碳城镇化模式下,2015—2030年,在城镇化率同样提升18.7%的情景下,碳排放的年均增速将由4.3%下降至0.4%,碳减排效果非常显著。     

未来甲烷排放增加对平流层水汽和全球臭氧的影响

利用一个耦合的大气化学-气候模式(WACCM3)研究了地表甲烷排放增加对平流层水汽和全球臭氧变化的影响.结果表明,如果地表甲烷的排放量在2000年的基础上增加50%(达到政府间气候变化专门委员会A1B排放情景中2050年的值),平流层水汽体积分数将平均增加约0.8×10^-6.南半球平流层甲烷转化为水汽的效率比北半球高.在北半球平流层中,1mol甲烷分子可以转化为约1.63mol的水汽分子,而在南半球1mol甲烷分子大概可以转化为约1.82mol的水汽分子.甲烷排放增加50%将使全球中低纬度地区以及北半球高纬度地区的臭氧柱总量增加1%-3%,使南半球高纬度地区臭氧柱总量增加近8%,而秋季(南半球春季)南极地区臭氧柱总量增加幅度可高达20%,南极臭氧的这种显着增加主要是由于甲烷增加造成的化学反馈所致.在北半球中高纬度地区,甲烷增加引起的臭氧变化主要与甲烷氧化导致的水汽增加有关.研究还表明,未来甲烷排放增加对臭氧的恢复作用其实与溴化物排放的减少一样重要.     

Statistical downscaling of summer temperature extremes in northern China

Two approaches of statistical downscaling were applied to indices of temperature extremes based on percentiles of daily maximum and minimum temperature observations at Beijing station in summer during 1960-2008. One was to downscale daily maximum and minimum temperatures by using EOF analysis and stepwise linear regression at first, then to calculate the indices of extremes; the other was to directly downscale the percentile-based indices by using seasonal large-scale temperature and geo-potential height records. The cross-validation results showed that the latter approach has a better performance than the former. Then, the latter approach was applied to 48 meteorological stations in northern China. The cross-validation results for all 48 stations showed close correlation between the percentile-based indices and the seasonal large-scale variables. Finally, future scenarios of indices of temperature extremes in northern China were projected by applying the statistical downscaling to Hadley Centre Coupled Model Version 3 (HadCM3) simulations under the Representative Concentration Pathways 4.5 (RCP 4.5) scenario of the Fifth Coupled Model Inter-comparison Project (CMIP5). The results showed that the 90th percentile of daily maximum temperatures will increase by about 1.5℃, and the 10th of daily minimum temperatures will increase by about 2℃ during the period 2011-35 relative to 1980-99.