低碳导向下土地覆被演变模拟——以深圳市为例

全球碳排放水平的不断增加引起的全球变暖越发严重,导致了严重的自然灾害和经济损失,这种失衡发展的态势促使着各个国家开始探索低碳环保的发展模式。为了探究何种土地利用组成可以更好的为低碳城市服务,以深圳市为研究区,结合2020年土地利用现状结构和2020年土地利用规划结构分别估算出碳汇最大化情景和碳排放量最小化情景下2020年各土地利用类型的数量结构,并运用FLUS模型模拟出深圳市土地利用类型在这两种情景下的空间分布特征。最后,从碳密度和碳排放视角对比这两种情景的低碳效益。研究结果如下：①碳汇最大化和碳排放最小化情景下土地利用总碳盈余均比2020年少,且碳汇最大化情景下土地利用总碳盈余最小。碳汇最大化情景下耕地、园地和林地面积增加而水域和建设用地减少,碳排放最小化情景下园地和林地面积增加来源于草地、水域和建设用地的减少,这两种低碳情景的碳汇能力增强而碳排放量减少;②碳汇最大化和碳排放最小化情景下林地明显增加故而土地利用总碳盈余均比实际情景小,而园地和草地的缩减和扩张是引起两种低碳情景碳密度和碳排放量有差异的主要原因。碳汇最大化和碳排放最小化情景下,西部和东南部主要是碳密度增加和碳排放减少的区域,而中部是碳密度减少和碳排放增加的区域。因此对中部区域进行重点调控,有利于深圳市碳中和和碳达峰的实现。研究可以为深圳的低碳发展提供规划建议,同时给其他区域的低碳规划提供参考意见。     

成都平原及其周边区域土地利用碳排放效应及空间格局

土地利用变化的碳排放研究对了解人类活动对生态环境的扰动程度及其机理、制定有效的碳排放政策具有重要意义。采用1990-2010年能源消费数据、遥感与GIS提取的土地利用数据, 通过构建土地利用碳排放模型, 对20 a来成都平原及其周边区域土地利用的碳排放进行了定量分析。结果表明: (1)土地利用变化的碳排放增加3269.37×10⁴ t, 增长率达137%, 呈显著增加趋势。(2)建设用地和林地分别为区域最大的碳源与碳汇。建设用地的碳排放增加3271.55× 10⁴ t, 增长率达139.01%, 林地的碳汇减少1.30×10⁴ t, 减少率达3.12%, 但仍占碳汇的99%以上。(3)土地利用的碳排放存在明显区域差异。中部、北部和南部冲积平原(成都市及其第二圈层、绵阳市辖区、绵竹市、乐山市辖区)碳排放大, 平原周边区域邻近川西高原山地碳排放小。(4)土地利用结构与碳排放存在一定的相互关系, 趋高的碳源、碳汇比导致土地利用的碳源效应远大于碳汇效应。因此, 研究区减排的重点应该在保持或增加现有的林地的同时, 主要以降低建设用地的碳排放、碳足迹为主。     

辽宁中部城镇密集区土地利用变化的碳排放及低碳调控对策

土地利用变化引起的碳排放对全球气候变化有重要影响,调整区域的土地利用方式对适应全球气候变化具有重要的科学意义.本研究利用辽宁省碳排放/吸收参数,估算了辽宁中部城镇密集区土地利用变化的碳排放量.结果表明： 1997—2010年,碳排放量为308.51 Tg C,碳吸收量为11.64 Tg C,碳吸收量可抵消
3.8%的碳排放量.土地利用变化的净碳排放为296.87 Tg C,其中,保持用地类型不变的土地上净碳排放量是182.24 Tg C,对总排放量的贡献为61.4%;发生用地类型转换的土地上净碳排放量是114.63 Tg C,对总碳排放量的贡献为38.6%.通过量化土地利用变化和碳排放之间的映射关系可知,1997—2004年,保持建设用地不变（40.9%）和农田转为建设用地（40.6%）类型对碳源的贡献最大,农田转林地（38.6%）和保持林地不变（37.5%）类型对碳汇的贡献最大;2004—2010年,土地利用类型对碳源和碳汇的贡献类型与前一时段相同,但保持建设用地类型对碳源的贡献提高到80.6%,保持林地类型对碳汇的贡献提高到71.7%.基于不同景观变化类型的碳排放强度,我们从两方面提出低碳土地利用的调控对策：从碳减排方面,严格控制土地利用向建设用地转变,提高建设用地能源利用效率,避免对林地和水域过度开发利用;从碳增汇方面,增加森林覆盖率,实施农田、草地还林,加强对森林、水域的保护,调整农用地内部结构和科学实施农田管理.     

基于SWAT模型的流溪河流域土地利用与气候变化对径流的影响

选用国内外广泛应用的SWAT分布式水文模型,定量分析流溪河流域土地利用与气候变化对径流的影响,采用情景模拟分析方法设置3类情景进行定量分析.对上中下游的温泉、太平场和南岗3个水文站依次校正与验证得出：除温泉站在验证期的3个系数刚达标之外,其他的相对误差＜15%、相关系数＞0.8、Nash Sutcliffe效率系数＞0.75,说明SWAT模型在流溪河流域的径流量模拟中具有较高的适用性.综合型情景模拟分析得出：以1991-2000年为基准期,2001-2010年土地利用与气候变化综合引起年均径流量增加11.23 m³·s^-1,土地利用变化引起年均径流量减少0.62 m³·s^-1,气候变化引起年均径流量增加11.85 m³·s^-1,气候变化的影响强度强于土地利用变化的影响强度.极端土地利用情景模拟分析得出：与2000年土地利用现状模拟径流量相比,耕地情景和草地情景的径流量分别增加2.7%和0.5%,林地情景的径流量减少0.7%,证明林地有一定的截流能力.气候变化情景模拟分析得出：流域径流量变化与降水变化呈正相关关系（降水每升高10%,径流平均增加11.6%）,与气温变化呈负相关关系（气温每升高1 ℃,径流平均降低0.8%）,降水变化的影响强度强于气温变化的影响强度.在气候变化环境下,需要重视对强降雨的预测和灾害预防,可通过优化土地利用结构与空间布局来减缓气候变化带来的水文负效应,如洪涝灾害.     

基于RS和GIS的科尔沁沙地南缘章古台地区土地利用变化及其驱动力

利用遥感影像,借助于GIS技术以及数理统计方法,对章古台地区近20年间土地利用变化及驱动力进行了分析。结果表明:1988-2009年间,章古台地区土地利用构成以耕地和林地为主;土地利用类型变化以林地、耕地和建设用地面积的增加和草地、水域及未利用土地面积的减少为特征,其中,草地、建设用地和未利用土地的年变化率大于其他土地利用类型;土地利用程度综合指数由1988年的235.34增至2009年的251.65;土地类型间的转化以草地、未利用土地向林地、耕地转化和耕地与林地间转化为主,占总转化面积的95.58%。章古台地区土地利用变化受人口、政策和自然因素的综合影响,虽然自然因素是决定土地利用变化的重要因素,但在20年的时间尺度上,人口增长和政策引导则是加剧这种变化的主导因素。     

基于土地利用变化的四川省碳排放与碳足迹效应及时空格局

土地利用变化的碳排放与碳足迹研究对了解人类活动对生态环境的扰动程度及其机理、制定有效的碳排放政策具有重要意义。采用1990—2010年四川省能源消费数据和土地利用数据,通过构建碳排放模型、碳足迹及其压力指数模型,对研究区20年来土地利用的碳排放及碳足迹进行了定量分析。结果表明:(1)土地利用变化的碳排放和能源消费碳的足迹呈显著增加趋势。碳排放增加5407.839×10~4t,增长率达143%;能源消费的碳足迹增加1566.622×10~4hm~2,四川全省的生态赤字达1563.598×10~4hm~2。(2)建设用地和林地分别为四川省最大的碳源与碳汇。20年间建设用地的碳排放增加5407.072×10~4t,增长率达126.27%,占碳排放总量的88%以上;林地的碳汇减少10.351×10~4t,但仍占四川省碳汇的96%以上。(3)土地利用碳排放、碳足迹和生态赤字存在明显区域差异。成都平原区碳排放、碳足迹压力最大,生态赤字严重,西部高山高原区和盆周山区碳排放、碳足迹最小,未出现生态赤字;成都、德阳、资阳和内江等地的碳排放、碳足迹压力最大,生态赤字最严重,甘孜、阿坝等地的碳排放、碳足迹最小,未出现生态赤字。(4)土地利用结构与碳排放、碳足迹存在一定的相互关系,趋高的碳源、碳汇比导致土地利用的碳源效应远大于碳汇效应。因此,四川省减排的重点应该在保持或增加现有的林地的同时,主要以降低建设用地的碳排放、碳足迹为主。     

气候与土地利用变化下宁夏清水河流域径流模拟

气候和土地利用变化是影响水资源变化最直接的因素。应用SWAT模型对干旱半干旱区小流域宁夏清水河流域径流进行多情景模拟预测,以历史气候要素变化趋势和CA-Markov模型分别设置未来气候和土地利用变化情景,以决定系数R2和Nash-Sutcliffe模型效率系数Ens(Nash-Sutcliffe efficiency coefficient)来衡量模拟值与实测值之间的拟合度,并评价模型在清水河流域的适用性。结果表明,韩府湾站在校准期和验证期的R~2分别为0.80和0.71,Ens分别为0.77和0.69,泉眼山站在校准期和验证期的R2分别为0.66和0.63,Ens分别为0.62和0.56,表明构建的SWAT模型可以用于清水河流域的径流模拟。对未来气候和土地利用变化情景下径流的模拟结果显示,径流变化主要由降水变化主导,降水减少和气温升高的综合作用对流域径流变化影响最为显著;由于耕地和建设用地的增加,未来3种土地利用情景下流域径流量将均会呈现明显增加变化。与2010年相比,到2020年,自然增长情景流域径流将增加17.04%,林地保护情景径流将增加14.44%,规划情景径流将增加13.98%;综合降水、气温和土地利用的结合变化情景显示,未来流域径流将会有不同程度的下降,规划情景和气候变化的结合情景的径流下降最为明显,而有意增大林地和加强生态保护的林地保护情景对减缓流域径流下降具有一定作用。在气候变化的大背景下,根据水资源利用管理目标,可通过调整流域管理措施,特别是土地利用变化和改善区域小气候来减缓气候变化对流域水资源的负面效果,以此来改善流域径流和生态环境状况。     

1990—2015年武汉市土地利用碳排放格局研究

土地利用变化引起的碳排放增加,是全球碳排放量增加的重要原因,土地利用不合理会影响区域碳平衡。利用1990—2015年遥感影像数据和能耗数据,通过碳排放模型构建、碳排放效应测算、土地利用碳排放动态度和碳排放贡献率等方法,剖析了武汉市土地利用碳排放时空变化。结果表明:(1)武汉市碳排放量逐年增加,研究期内增加了91.02%,年均增长率为3.64%。建设用地是最大碳源,水域和林地是主要碳汇,建设用地的碳排放量是决定土地利用净碳排放量的主导因素。(2)单位国内生产总值的碳排放强度波动下降,人均碳排放强度稳定上升。(3)碳排放强度较大的地区主要集中在城市中心的建城区,远郊区林地集中的地区碳排放强度较小。武汉市“碳源”增强区以市中心呈现典型的圆形分布,而“碳汇”增强区零星分布在公园建设、退耕还林和退建还林区。(4)建设用地对区域碳排放量变化的碳排放贡献率高达99.75%,是区域碳排放的主要贡献因子。     

土地利用变化对区域碳源汇的影响研究进展

土地利用变化对陆地生态系统碳循环有着重要的影响,既可能成为碳源,也可能是碳汇。在国内外相关研究的基础上,综述了土地利用变化对全球及区域尺度上森林、草地和农业生态系统碳循环的影响。全球范围内,森林砍伐后向草地和农田的转化发挥碳源的作用,在毁林碳排放中占主导地位,其中热带地区森林转变为农田和草场的碳排放均高于温带和北方森林。另一方面,土地利用变化可促进森林的碳贮存,如退耕还林、改善森林管理等。各区域森林生态系统通过土地利用变化贮存碳的潜力存在显著差别,热带湿润和半湿润地区具有较大的碳汇潜力,而干旱地区减少碳排放的空间相对较少。开垦活动是影响草地生态系统碳储存最主要的人类活动,草地转变为农田伴随着土壤碳的流失。森林或草场转变为农田的过程伴随着植被和土壤碳储量的减少,生态系统碳储量降低,因此它是一个碳排放的过程。伴随着城市的扩张,农田向建设用地的转化也是一个碳排放的过程。当前评估土地利用变化影响的研究方法主要有遥感观测和遥感模型、统计估算、生态系统模型以及土地利用与生态系统模型的耦合。研究方法得到不断地完善和改进的同时,还存在着一些不确定性,因此需要建立统一的观测统计方法,降低数据中的不确定性;完善土地利用与生态系统模型的耦合研究;建立多尺度土地利用变化及生态系统综合技术方法体系;开展碳减排目标下土地利用最优化布局研究。     

LUCC及气候变化对澜沧江流域径流的影响

运用SWAT模型,通过设置不同情景,定量分析了澜沧江流域土地利用与土地覆被变化(Land Use and Land Cover Change,LUCC)和气候变化对径流的影响,并结合RCP4.5、RCP8.5两种排放情景对流域未来径流的变化进行预估。结果表明:SWAT模型在澜沧江流域径流模拟中具有很好的适用性,率定期和验证期的模型参数R~2分别达到0.80、0.74,Ens分别达到0.80、0.73;从土地利用变化方面考虑,流域内的农业用地转化为林地或草地,均会导致径流量的减少,而林地转化为草地则会引起径流量的增加,农业用地、林地、草地三者对径流增加贡献顺序为农业用地草地林地,从气候变化方面考虑,流域内的径流量与降雨量成正比,与气温成反比;2006—2015年间澜沧江流域气候变化引起的月均径流减少幅度强于LUCC引起的月均径流增加幅度,径流变化由气候变化主导;在RCP4.5和RCP8.5两种排放情景下,2021—2050年间澜沧江流域的径流均呈增加趋势,这与1971—2015年间流域实测径流的变化趋势相反。     

Large uncertainty in carbon uptake potential of land‐based climate‐change mitigation efforts

Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land‐based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land‐based mitigation scenarios from two land‐use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ‐GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land‐use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land‐use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land‐use change. Differences between land‐use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land‐based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy.     

Meeting Europe's climate change commitments: quantitative estimates of the potential for carbon mitigation by agriculture

Under the Kyoto Protocol, the European Union is committed to a reduction in CO₂ emissions to 92% of baseline (1990) levels during the first commitment period (2008–2012). The Kyoto Protocol allows carbon emissions to be offset by demonstrable removal of carbon from the atmosphere. Thus, land‐use/land‐management change and forestry activities that are shown to reduce atmospheric CO₂ levels can be included in the Kyoto targets. These activities include afforestation, reforestation and deforestation (article 3.3 of the Kyoto Protocol) and the improved management of agricultural soils (article 3.4). In this paper, we estimate the carbon mitigation potential of various agricultural land‐management strategies and examine the consequences of European policy options on carbon mitigation potential, by examining combinations of changes in agricultural land‐use/land‐management. We show that no single land‐management change in isolation can mitigate all of the carbon needed to meet Europe's climate change commitments, but integrated combinations of land‐management strategies show considerable potential for carbon mitigation. Three of the combined scenarios, one of which is an optimal realistic scenario, are by themselves able to meet Europe's emission limitation or reduction commitments. Through combined land‐management scenarios, we show that the most important resource for carbon mitigation in agriculture is the surplus arable land. We conclude that in order to fully exploit the potential of arable land for carbon mitigation, policies will need to be implemented to allow surplus arable land to be put into alternative long‐term land‐use. Of all options examined, bioenergy crops show the greatest potential for carbon mitigation. Bioenergy crop production also shows an indefinite mitigation potential compared to other options where the mitigation potential is finite. We suggest that in order to exploit fully the bioenergy option, the infrastructure for bioenergy production needs to be significantly enhanced before the beginning of the first Kyoto commitment period in 2008. It is not expected that Europe will attempt to meet its climate change commitments solely through changes in agricultural land‐use. A reduction in CO₂‐carbon emissions will be key to meeting Europe's Kyoto targets, and forestry activities (Kyoto Article 3.3) will play a major role. In this study, however, we demonstrate the considerable potential of changes in agricultural land‐use and ‐management (Kyoto Article 3.4) for carbon mitigation and highlight the policies needed to promote these agricultural activities. As all sources of carbon mitigation will be important in meeting Europe's climate change commitments, agricultural carbon mitigation options should be taken very seriously.     

黄河流域国土空间碳中和度研究——以内蒙古段为例

基于全球气候治理背景以及黄河流域在我国生态文明建设中的重要地位,以黄河流域内蒙古段为例,通过情景分析法,建立改进的IPAT模型和集成生态圈模拟器IBIS,预测不同情景下2018-2060年研究区碳排放变化趋势和达峰情况,并结合对碳汇水平的模拟分析2060年碳中和实现进程。结果显示①在基准情景、节能情景、低碳情景和粗放情景下,黄河流域内蒙古段将分别于2040年、2035年、2030年和2050年实现碳达峰,峰值碳排放量分别为12209万t、11213万t、9784万t和17635万t;②在IPCC RCP2.6和RCP6.0气候变化情景下,黄河流域内蒙古段的陆地生态系统整体分别呈现出碳汇和碳源的不同效应,净初级生产力分别为1533万t和-506万t;③综合能源消费碳排放和碳汇水平,在RCP2.6气候情景下,若碳排放选取基准、节能、低碳和粗放情景,则2060年黄河流域内蒙古段分别可实现碳中和进程的18.42%、22.37%、34.46%和9.90%;在RCP6.0气候情景下,由于研究区陆地生态系统呈现出碳源效应,因此难以对碳中和进程的推进做出贡献。可见,对于黄河流域内蒙古段而言,需要科学制订碳达峰、碳中和目标实现时间,未来要更进一步保护重要碳汇生态系统,提升固碳增汇能力;调整能源消费结构,增加可再生能源发展规划指标;构建碳排放权交易市场,促进碳指标流动;制定土地利用碳排放标准,优化国土空间格局。     

从湿地到农田:围垦对生态系统碳排放的影响

湿地围垦转化为农田直接影响碳循环过程,但之前的众多研究忽略了相关人为活动如农资生产、农用器械使用等所产生的碳排放.为了更全面认识湿地围垦为农田所导致的这种变化,以崇明岛为研究地区,基于通量观测和生命周期评价,本文分别探讨当考虑和不考虑人为活动伴随的碳排放时,生态系统总碳排放的变化.结果表明: 如果只考虑生态系统与大气间的碳通量,农田仍表现为碳汇,但与自然湿地相比,其碳排放增加了10.47 t (CO₂-eq)·hm^-2;当将农业生产中人为活动碳排放纳入计算后,崇明岛自然湿地和围垦农田的碳排放总量分别为-15.38和6.54 t (CO₂-eq)·hm^-2,碳排放增加了21.92 t (CO₂-eq)·hm^-2,其中,人为活动碳排放为11.45 t (CO₂-eq)·hm^-2;田间种植和农资生产的碳排放共占农田生命周期碳排放总量的84.6%,化肥的生产施用是农田生命周期碳排放的主要来源之一.围垦使生态系统乃至区域尺度的碳源汇属性发生变化,需重新评估其影响;同时,为了达到低碳农业的目的,需减少化肥施用、提高化肥使用效率.     

Projected changes in mineral soil carbon of European croplands and grasslands, 1990–2080

We present the most comprehensive pan‐European assessment of future changes in cropland and grassland soil organic carbon (SOC) stocks to date, using a dedicated process‐based SOC model and state‐of‐the‐art databases of soil, climate change, land‐use change and technology change. Soil carbon change was calculated using the Rothamsted carbon model on a European 10 × 10′ grid using climate data from four global climate models implementing four Intergovernmental Panel on Climate Change (IPCC) emissions scenarios (SRES). Changes in net primary production (NPP) were calculated by the Lund–Potsdam–Jena model. Land‐use change scenarios, interpreted from the narratives of the IPCC SRES story lines, were used to project changes in cropland and grassland areas. Projections for 1990–2080 are presented for mineral soil only. Climate effects (soil temperature and moisture) will tend to speed decomposition and cause soil carbon stocks to decrease, whereas increases in carbon input because of increasing NPP will slow the loss. Technological improvement may further increase carbon inputs to the soil. Changes in cropland and grassland areas will further affect the total soil carbon stock of European croplands and grasslands. While climate change will be a key driver of change in soil carbon over the 21st Century, changes in technology and land‐use change are estimated to have very significant effects. When incorporating all factors, cropland and grassland soils show a small increase in soil carbon on a per area basis under future climate (1–7 t C ha^?1 for cropland and 3–6 t C ha^?1 for grassland), but when the greatly decreasing area of cropland and grassland are accounted for, total European cropland stocks decline in all scenarios, and grassland stocks decline in all but one scenario. Different trends are seen in different regions. For Europe (the EU25 plus Norway and Switzerland), the cropland SOC stock decreases from 11 Pg in 1990 by 4–6 Pg (39–54%) by 2080, and the grassland SOC stock increases from 6 Pg in 1990 to 1.5 Pg (25%) under the B1 scenario, but decreases to 1–3 Pg (20–44%) under the other scenarios. Uncertainty associated with the land‐use and technology scenarios remains unquantified, but worst‐case quantified uncertainties are 22.5% for croplands and 16% for grasslands, equivalent to potential errors of 2.5 and 1 Pg SOC, respectively. This is equivalent to 42–63% of the predicted SOC stock change for croplands and 33–100% of the predicted SOC stock change for grasslands. Implications for accounting for SOC changes under the Kyoto Protocol are discussed.     

Intensification of dairy production can increase the GHG mitigation potential of the land use sector in East Africa

Sub‐Saharan Africa (SSA) could face food shortages in the future because of its growing population. Agricultural expansion causes forest degradation in SSA through livestock grazing, reducing forest carbon (C) sinks and increasing greenhouse gas (GHG) emissions. Therefore, intensification should produce more food while reducing pressure on forests. This study assessed the potential for the dairy sector in Kenya to contribute to low‐emissions development by exploring three feeding scenarios. The analyses used empirical spatially explicit data, and a simulation model to quantify milk production, agricultural emissions and forest C loss due to grazing. The scenarios explored improvements in forage quality (Fo), feed conservation (Fe) and concentrate supplementation (Co): FoCo fed high‐quality Napier grass (Pennisetum purpureum), FeCo supplemented maize silage and FoFeCo a combination of Napier, silage and concentrates. Land shortages and forest C loss due to grazing were quantified with land requirements and feed availability around forests. All scenarios increased milk yields by 44%–51%, FoCo reduced GHG emission intensity from 2.4 ± 0.1 to 1.6 ± 0.1 kg CO₂eq per kg milk, FeCo reduced it to 2.2 ± 0.1, whereas FoFeCo increased it to 2.7 ± 0.2 kg CO₂eq per kg milk because of land use change emissions. Closing the yield gap of maize by increasing N fertilizer use reduced emission intensities by 17% due to reduced emissions from conversion of grazing land. FoCo was the only scenario that mitigated agricultural and forest emissions by reducing emission intensity by 33% and overall emissions by 2.5% showing that intensification of dairy in a low‐income country can increase milk yields without increasing emissions. There are, however, risks of C leakage if agricultural and forest policies are not aligned leading to loss of forest to produce concentrates. This approach will aid the assessment of the climate‐smartness of livestock production practices at the national level in East Africa.     

德州市低碳农业发展潜力分析及对策

进入21世纪,农业节能减排逐渐引起人们的关注。运用能源碳排放计算模型,对德州市2003-2008年农业碳源、碳汇进行计算分析,结果表明:(1)目前德州市农业碳源现状为7.29TgCO2eq.a-1,其中由农业能源消费、土壤呼吸、化肥施用和牲畜饲养造成碳排放分别为2.81、2.12、0.93和1.43TgCO2eq.a-1;(2)农业碳汇现状能力为9.24TgCO2eq.a-1,包括由于土地利用变化造成的碳排放4.73TgCO2eq.a-1和通过施用有机肥和实施秸秆还田的固碳能力4.51TgCO2eq.a-1;(3)碳汇能力较碳源释碳量有所盈余,具有发展低碳农业的潜力。从减源、增汇两个方面提出德州市未来发展低碳农业的相关措施,如调整农业产业结构,改进土地利用方式、实行保护性耕作、提倡农村可再生能源利用、推广立体种养模式,发展种养结合的循环农业等。     

Effects of 21st‐century climate,land use,and disturbances on ecosystem carbon balance in California

Terrestrial ecosystems are an important sink for atmospheric carbon dioxide (CO₂), sequestering ~30% of annual anthropogenic emissions and slowing the rise of atmospheric CO₂. However, the future direction and magnitude of the land sink is highly uncertain. We examined how historical and projected changes in climate, land use, and ecosystem disturbances affect the carbon balance of terrestrial ecosystems in California over the period 2001–2100. We modeled 32 unique scenarios, spanning 4 land use and 2 radiative forcing scenarios as simulated by four global climate models. Between 2001 and 2015, carbon storage in California's terrestrial ecosystems declined by ?188.4 Tg C, with a mean annual flux ranging from a source of ?89.8 Tg C/year to a sink of 60.1 Tg C/year. The large variability in the magnitude of the state's carbon source/sink was primarily attributable to interannual variability in weather and climate, which affected the rate of carbon uptake in vegetation and the rate of ecosystem respiration. Under nearly all future scenarios, carbon storage in terrestrial ecosystems was projected to decline, with an average loss of ?9.4% (?432.3 Tg C) by the year 2100 from current stocks. However, uncertainty in the magnitude of carbon loss was high, with individual scenario projections ranging from ?916.2 to 121.2 Tg C and was largely driven by differences in future climate conditions projected by climate models. Moving from a high to a low radiative forcing scenario reduced net ecosystem carbon loss by 21% and when combined with reductions in land‐use change (i.e., moving from a high to a low land‐use scenario), net carbon losses were reduced by 55% on average. However, reconciling large uncertainties associated with the effect of increasing atmospheric CO₂ is needed to better constrain models used to establish baseline conditions from which ecosystem‐based climate mitigation strategies can be evaluated.     

福建省土地利用碳排放空间关联性与碳平衡分区

全球变暖与二氧化碳浓度升高密不可分，在工业化及城镇化发展过程中，人类对土地的利用和改造是造成全球大气中含碳量迅速增加的重要原因，且土地在利用过程中碳减排的潜力较大。因此，从不同土地利用方式视角研究福建省碳排放量，采用基尼系数来衡量福建省各设区市碳收支的空间差异，探索区域内土地利用碳收支规模和空间分异；运用社会网络分析方法对福建省土地利用碳排放空间网络结构的整体特征和设区市在网络结构中的角色进行考察，有助于从基础层面对人类活动所造成的环境影响进行评估，及时调整土地利用方式从而促进低碳经济发展。结果表明：2006-2018年福建省土地利用净碳排放量逐年递增，呈现东高西低的空间分布特征，建设用地是主要碳源，而林地起到主要碳汇的作用；区域内碳补偿率逐年递减且存在明显的空间差异，经济较发达的区域碳补偿率低于经济欠发达的区域，生态承载系数东西差距不断加强，东部地区碳排放的比例明显超过了碳吸收的比例；福建省土地利用碳排放在空间上具有明显的关联性和溢出效应，碳排放空间关联网络越来越复杂、稳定，各设区市在网络中所处地位和作用存在明显的不均衡性，厦门市在整个碳排放网络中占据领导地位，其他城市的碳影响力在网络中的地位及作用随着经济联系逐渐加强正在逐步提高；对网络空间聚类发现，第一模块和第三模块对模块内外均有溢出效应且密度值较大，属于"双向溢出模块"，其余第二、四模块均属于"净收益模块"。在研究的基础上将福建省各设区市分为3类区域：低碳优化区、碳总量控制区和碳汇功能区，并提出协同减排的差异性对策建议。