中国农村居民生活氮素流动特征

人类生活消费是陆地生态系统氮素流动的主要驱动力。定量核算和评估农村居民生活消费氮产生(N_RUR)及其活性氮(Nr)排放特征,对农村氮的可持续管理和生态环境改善具有重要的指导意义。以中国为例(2000—2020年),建立了N_RUR的产生及其活性氮排放核算框架。结果表明：20年来N_RUR上升了36.7%,年均5.62 Tg/a,食物消费氮是最大的贡献源(43.2%),工业日用品和家庭生活燃料消费氮分别占31.5%和25.3%;Nr排放量占N_RUR的25.4%(年均1.43 Tg/a),其以年均1.3%速率下降;NH₃挥发是最大的Nr排放源(50.1%),其次为排入地表水的Nr(31.0%)、NO_x(15.8%)和N₂O(2.0%),排入地下水的Nr仅占1.1%。加大人类粪尿排泄物的处置能力,减少秸秆燃料的使用比例、优化农村居民生活能源消费结构对农村居民生活消费Nr减排至关重要。     

福建省行业碳排放驱动因素分解及其与经济增长脱钩关系

主要部门和重点行业的二氧化碳排放是区域碳排放的主要来源。厘清行业碳排放影响因素,分析其与区域经济增长相互关系及程度,从而推动部门和行业碳减排对于落实区域碳排放总量控制具有重要意义。本研究运用对数平均迪式指数分解法(LMDI)和Tapio脱钩模型对福建省1997—2017年13个主要碳排放行业进行碳排放驱动因素分解和脱钩分析。结果表明: 电力、热力的生产和供应业是福建省主要的碳排放行业,1997—2017年,其碳排放总量由18.89 Mt上升到120.63 Mt,增长量为101.74 Mt。有色金属冶炼及压延加工业、纺织业、黑色金属冶炼及压延加工业的碳排放增长速度最快,其年均增长率分别为18.1%、12.1%、12.1%。13个主要行业碳排放变动的驱动因素中,经济增长效应和人口规模效应是主要的正向驱动因素,能源结构效应、能源强度效应和产业结构效应的抑制作用在不断增强。从脱钩关系来看,13个主要碳排放行业的脱钩指数整体呈下降趋势。从“十一五”时期开始,部分行业开始出现不同程度的强脱钩。而在“十三五”时期,农、林、牧、渔、水利业表现为扩张负脱钩,电力、热力的生产和供应业表现为弱负脱钩。能源结构效应和能源强度效应对各行业实现脱钩的影响较大,产业结构效应的脱钩努力较小,人口规模效应未做出脱钩努力。     

Delinking indicators on regional industry development and carbon emissions: Beijing–Tianjin–Hebei economic band case

Based on the two-level Logarithmic Mean Divisia Index (LMDI) method and Tapio index, this paper constructed an expanded decomposition model for decoupling elasticity and effort index of industrial carbon emissions, and further quantitatively analyzed the delinking indicators on industry growth and environmental pressures in Beijing–Tianjin–Hebei (BTH) economic band from 1996 to 2010. The results indicate that: (1) together with the rapid economic growth, industrial energy-related carbon emissions in BTH region rose from 44477.43 × 10⁴ t in 1996 to 105602.33 × 10⁴ t in 2006 and then declined to 64426.71 × 10⁴ t in 2010, with an average annual growth rate of 2.94%. Our results also show that carbon emissions in BTH region were dominated by the secondary industry, which accounted for about 80% of total carbon emissions. (2) “Weak decoupling” was the main characteristic during the 9th Five-Year Plan period (1996–2000) and 11th Five-Year Plan period (2006–2010), particularly “strong decoupling” in 2007; while “weak coupling” was the main characteristic during the 10th Five-Year Plan period (2001–2005). (3) The rapid economic growth was the main factor responsible for industrial decoupling blocking. The energy structure and energy intensity made significant contributions to the industrial decoupling progress. The industrial structure effect had varied considerably over the years without showing a clear trend.     

基于LMDI分解的厦门市碳排放强度影响因素分析

研究碳排放强度的变化趋势及其影响因素对于指导低碳城市建设具有重要意义。应用对数平均权重分解法(LMDI),基于厦门市2005—2010年各部门终端消费数据对碳排放强度指标进行因素分解,并将传统分析仅注重产业部门的能源碳排放,拓展到全面考虑产业部门和家庭消费的能源活动和非能源活动影响。研究结果表明:2005—2010年厦门市碳排放强度下降17.29%,其中产业部门能源强度对总碳排放强度变化影响最大(贡献63.07%),家庭消费能源强度是碳排放强度下降的主要抑制因素(-45.46%)。从影响效应角度看,经济效率对碳排放强度下降贡献最大,碳排系数减排贡献最小;从部门减排贡献角度看,第二产业贡献最大,家庭消费贡献最小。总体而言,厦门市未来碳减排重点部门在第二产业,优化产业结构和能源结构有较大减排潜力。     

Decoupling environmental pressure from economic growth on city level: The Case Study of Chongqing in China

As cities represent the microcosms of global environmental change, it is very important for the global sustainable development by decoupling environmental pressure from economic growth on city level. In this paper, the municipality of Chongqing in China is employed as a case to show whether the decoupling of environmental pressures from economic growth has occurred in cities undergoing rapid economic growth; what is the level of decoupling; and what causes the observed degree of decoupling. Results show the following. (1) During the period of 1999–2010, decoupling from economic growth has been absolute for the emissions of SO₂, soot, and waste water, while it has been relative for total energy consumption, emissions of CO₂ and solid waste. (2) Compared with the period 2000–2005, decoupling level improved for all the six environmental pressures in the period 2005–2010. (3) Compared with China and other three municipalities of China, the overall decoupling level of Chongqing is above China’s average while below those of Beijing and Shanghai. (4) During the period 1999–2000, technological change was the dominate factor for decoupling Chongqing’s environmental pressure from economic growth, as it contributed 131.4%, 134.6%, 99.9%, 97.7%, 104.5% and 54.9% to the decoupling of total energy consumption, emissions of CO₂, SO₂, soot, waste water and solid waste, respectively; while economic structural change had very tiny effect to the decoupling of emissions of soot and SO₂, and it even had negative effect to that of total energy consumption, and emissions of CO₂ and waste water. Based on the above observations, we explain the difference in decoupling levels for different environmental pressures and suggest approaches for policy-makers on further promoting decoupling environmental pressure from economic growth.     

基于IPSO-BP神经网络模型的山东省碳排放预测及生态经济分析

在低碳经济发展背景下,针对山东省碳排放数据更新迟缓、以往预测模型难以满足现实需求的问题,统计相关数据,根据政府间气候变化专门委员会(IPCC)推荐方法测算山东省2000—2017年碳排放量和排放强度,并借助脱钩分析、碳承载力和碳赤字探究碳排放的动态变化趋势;基于5项最重要的碳排放影响因素,建立改进的粒子群算法(IPSO...     

Evaluating possible cap and trade legislation on cellulosic feedstock availability

An integrated, socioeconomic–biogeophysical model is used to analyze the interactions of cap‐and‐trade legislation and the Renewable Fuels Standard. Five alternative policy scenarios were considered with the purpose of identifying policies that act in a synergistic manner to reduce carbon emissions, increase economic returns to agriculture, and adequately meet ethanol mandates. We conclude that climate and energy policies can best be implemented together by offering carbon offset payments to conservation tillage, herbaceous grasses for biomass, and by constraining crop residue removal for ethanol feedstocks to carbon neutral level. When comparing this scenario to the Baseline scenario, the agricultural sector realizes an economic benefit of US$156 billion by 2030 and emissions are reduced by 135 Tg C‐equivalent (Eq) yr^?1. Results also indicate that geographic location of cellulosic feedstocks could shift significantly depending on the final policies implemented in cap and trade legislation. Placement of cellulosic ethanol facilities should consider these possible shifts when determining site location.     

Newer and select maize,wheat, and rice varieties can help mitigate N footprint while producing more grain

Sustainably feeding the growing population amid a changing climate and dwindling resources is a grand challenge facing mankind. Decades‐long advancement in crop breeding has progressively elevated yield potential, markedly enhancing global food production capacity. However, relevant impact on reactive N (Nr) emissions associated with crop variety improvement has not been explicitly described. Here, we report multitiered evidence that newer and select maize, wheat, and rice varieties developed in China have the capacity to substantially lower Nr losses while producing more grain. First, we pooled studies featuring side‐by‐side comparison of different varieties, totaling 269 paired observations, to demonstrate that collectively, relatively newer varieties of maize, wheat, and rice had less Nr emissions (9.6%–23.5%) while yielding more grains (7.3%–11.2%) compared to older varieties under wide‐ranging conditions. Next, we built an extended database (142 field studies with 833 observations) and comprehensively evaluated the Nr‐loss reduction potential of newer varieties (2000 and after) versus older ones (1985–1999). We found that newer varieties had Nr emission factors (N loss as a percentage of N applied after correcting for background emissions) 18.2%–75.7% less for N₂O, 18.3%–75.7% less for , and ?8.5% to 22.8% less for NH₃, while producing more grains (16.0%–24.4%). Individual varieties differed markedly in yield‐emission scores. A nationwide farmer survey (2.47 million responses) indicated tremendous opportunities for a new way of management intervention. Coupling variety selection with sound N and other agronomic management can help lower N footprint while producing more grain.     

东北三省碳源/汇和碳盈亏时空分布与影响因素

碳循环是影响气候变化的关键环节。利用改进的CASA模型对东北三省2000-2020年间自然碳源\汇进行了估算;通过增加真实碳排放量对估算过程的约束,改进了夜间灯光数据和碳排放拟合方法,探究了区域碳源碳汇和碳盈亏的时空分布和影响因素。结果显示：（1）净生态系统生产力在时间上呈现波动上升趋势,空间上黑龙江省自然碳汇总量最高（164.61 Tg C/a）,约占东北三省的60%;（2）能源消费碳排放总量呈现先上升,再下降,近年趋于稳定的时间变化趋势,空间上以辽宁省年均碳排放量增速最快,增速约为6.95 Tg C/a;（3）2005年为东北三省整体从碳盈余转变为碳亏损的转折点,近年来亏损速率有所下降;（4）东北三省碳盈亏与自然因素呈正相关,与人口规模、地区生产总值、碳排放强度、产业结构呈现负相关关系。辽宁省能源消费总量的攀升使能源结构的下降未能扭转其碳亏损的局面,并使其碳盈亏与能源结构呈现正相关关系;黑龙江省和吉林省农业人口流失较快一定程度上导致了城市化水平与碳盈亏呈现正相关关系。（5）东北三省均应降低碳排放强度,黑龙江省和吉林省应调整能源结构,辽宁省应调整产业结构。研究结果可为东北三省"双碳目标"的实现提供理论依据。     

江西县域土地利用变化碳排放时空演变及其影响因素

查明县域尺度下土地利用变化碳排放,对于推进县域低碳发展和土地资源的可持续利用与管理具有重要意义。以江西省为例,基于2000-2020年江西省土地利用数据、社会经济数据等,利用空间自相关模型和对数平均迪氏指数分解法(LMDI) 法,对其县域土地利用碳排放时空演变及影响因素进行分析。结果表明:①2000-2020年间,区县土地利用碳排放均呈上升趋势,碳排放量增速和平均碳排放强度均有下降,但部分区县碳排放增速在2015年后出现提高的变化特征。建设用地是碳排放量增长的首要碳源,林地则具有重要的碳汇作用。②空间上,土地利用变化碳排放呈现出明显的空间差异,表现为北高南低的分布特征和较为稳定的聚类模式,即轻度和重度及以上排放区空间分布上较为集中。经济发达区县成为碳排放量增长"核心",欠发达区县则是碳排放量增长"外围",且这种"核心-外围"格局在不断强化。③总体上,抑制碳排放量增长的主要因素为碳排放强度及土地利用效率;驱动因素则有经济发展水平和建设用地规模。但部分区县碳排放强度可能表现为"前期驱动后期抑制"作用,且抑制作用小于驱动作用,故这类区县土地利用碳排放量仍显著增长。因此,江西省各区县应积极调整产业结构和继续降低碳排放强度及通过优化土地资源配置,提高土地利用效率,如用适度集约模式提高建设用地利用效率以免盲目性扩张浪费。另外,欠发达地区和发达地区需加强在资金、技术等领域的交流与合作,不同区县还应因地制宜,各自明确发展目标,走具有各自县域特色的低碳高质量发展道路。     

Intentional versus unintentional nitrogen use in the United States: trends, efficiency and implications

Human actions have both intentionally and unintentionally altered the global economy of nitrogen (N), with both positive and negative consequences for human health and welfare, the environment and climate change. Here we examine long-term trends in reactive N (Nr) creation and efficiencies of Nr use within the continental US. We estimate that human actions in the US have increased Nr inputs by at least ~5 times compared to pre-industrial conditions. Whereas N₂ fixation as a by-product of fossil fuel combustion accounted for ~1/4 of Nr inputs from the 1970s to 2000 (or ~7 Tg N year^?1), this value has dropped substantially since then (to <5 Tg N year^?1), owing to Clean Air Act amendments. As of 2007, national N use efficiency (NUE) of all combined N inputs was equal to ~40 %. This value increases to 55 % when considering intentional N inputs alone, with food, industrial goods, fuel and fiber production accounting for the largest Nr sinks, respectively. We estimate that 66 % of the N lost during the production of goods and services enters the air (as NO _x , NH₃, N₂O and N₂), with the remaining 34 % lost to various waterways. These Nr losses contribute to smog formation, acid rain, eutrophication, biodiversity declines and climate change. Hence we argue that an improved national NUE would: (i) benefit the US economy on the production side; (ii) reduce social damage costs; and (iii) help avoid some major climate change risks in the future.     

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。     

湖南市域化石能源消费碳排放时空格局及驱动因素

研究碳排放时空格局演变及其影响因素对指导碳减排具有重要意义。利用2008—2013年湖南省14地市规模以上工业企业终端能源消费数据,运用IPCC提供的参考方法和对数平均迪氏指标分解模型(Logarithmic Mean Divisia Index,LMDI)对湖南市域碳排放量、人均碳排放量、碳排放强度的时空格局及碳排放量变化的影响因素进行了研究。结果表明:1)2008—2013年湖南市域碳排放量随时间变化趋势不一,大致呈3种类型变化;累积碳排放量居前3位的市域依次是娄底、岳阳和湘潭,三者累积碳排放量占全省同期的48.92%,而吉首、张家界和怀化3市的累积碳排放量合计仅占全省的2.59%。2)湖南市域能源消费碳排放量、人均碳排放量存在相似的空间差异,二者均表现为东高西低的格局,且具有较强的相关性,碳排放量高的市域,人均碳排放量也较高;2008—2013年湖南市域碳排放强度呈下降趋势,属于低强度区的市域由2008年的4个增加到2013年的7个,碳排放强度的空间分布与市域产业类型有关。3)能源结构、能源强度对碳排放的增长主要起抑制作用,但能源结构的贡献很小,碳排放量的降低主要是由能源强度引起的;经济发展是碳排放增长的最主要因素,在2008—2010年和2011—2013年两个时段其累积贡献值分别为74.285和27.579;人口规模对碳排放的驱动较小,在2011—2013年对碳排放增加产生的累积贡献值仅为2.252。湖南当前及未来碳减排的重点是加快发展清洁能源与提高能效并重,优化能源结构和促进产业结构升级,从战略层面促进湖南"四大区域"协调发展。     

Does directed technological change get greener: Empirical evidence from Shanghai's industrial green development transformation

The degree of technological change biased to the environmental factor is crucial to industrial sustainable development. Using the stochastic frontier analysis method based on the translog production function and the panel data of 32 industrial sub-sectors in Shanghai over 1994–2011, this paper combines the evolution dynamic of the frontier technological structure with the evolution dynamic of technological change direction to estimate the output elasticities of production factors and the growth rate of green total factor productivity. Also, we investigate and compare the degrees of technological change biased to four production factors, i.e., capital, labor, energy, and carbon emissions. The results show that the industrial green total factor productivity in Shanghai presents an overall upward trend and mainly depends on the technical efficiency change. The improvements of labor productivity, R&D intensity, and energy efficiency can effectively enhance the green technical efficiency, while capital deepening has a mitigation effect on the green technical efficiency. The technological change of Shanghai's industrial production biases to energy use and capital saving, causing a high energy demand of industrial development. Under the dual impacts of economic development and energy-saving and emission-reduction policies, the degree of technological change biased to the environmental factor (carbon emissions) displays strong and weak alternations, indicating that the green bias of industrial technological change in Shanghai is not stable and that the green transformation of industrial development model needs to be further advanced.     

“双碳”目标下闽三角碳排放脱钩状态及驱动机制分析

快速城市化背景下,建设低碳城市群是实现"双碳"目标的最佳方式。在碳排放核算的基础上,使用Tapio脱钩模型和LMDI方法对闽三角以及厦门、漳州和泉州的脱钩状态和碳排放的驱动机制进行了研究。主要结论如下：（1）2005-2017年闽三角碳排放和人均碳排放均持续增加,二者有相同的变化趋势。闽三角的工业中心泉州有最高的碳排放和人均碳排放。发展型城市漳州碳排放最低,但碳排放和人均碳排放增长率均最高。服务型城市厦门碳排放增长率最低。（2）闽三角的脱钩状态逐渐改善,平均脱钩系数为1.03,脱钩状态为扩张性连接。厦门、漳州和泉州的平均脱钩系数分别为0.45、2.70和1.10,3个城市分别以弱脱钩、扩张负脱钩和扩张性连接状态为主。（3）人均GDP和人口规模是闽三角碳排放的正向因素,能源结构和能源强度是负向因素。正向因素的贡献在下降,负向因素的贡献在升高。人均GDP和能源结构分别对漳州和厦门碳排放有最强的促进和抑制效应。能源强度对3个城市碳排放变化的效应不同。（4）人口扩张促进碳排放增加,使碳排放与经济发展无法脱钩。人口规模对闽三角碳减排无脱钩努力。能源结构优化和能源强度下降有助于碳排放与经济发展脱钩,是闽三角碳减排的强脱钩努力和弱脱钩努力。能源强度对泉州碳减排无脱钩努力。优化能源结构是闽三角实现碳减排和"双碳"目标的关键。已经脱钩的厦门宜尽早制定碳达峰行动计划,引领闽三角的碳达峰行动。漳州可通过升级产业结构实现减排。泉州必须提升能源效率才能降低碳排放。     

基于长期能源替代规划模型的江苏省能源CO2排放达峰时间及峰值水平

为了应对全球气候变暖,中国政府提出到2030年CO₂排放达到峰值(或峰值平台)的减排目标.为了探究中国能否实现该减排目标,本研究以江苏省为例,基于长期能源规划替代模型(LEAP),耦合对数平均迪氏分解模型,运用情景分析法科学设定快速、中速、慢速达峰3种发展情景,预测CO₂排放达峰时间及峰值水平.结果表明: 2000—2015年间,经济规模效应是CO₂排放总量增长的主要驱动因素,其贡献度高达147.4%;技术进步效应是最重要的缓解因素,贡献度为-60.4%,一次能源结构效应、产业结构效应、人均收入效应、人口规模效应的贡献度分别为-5.3%、9.7%、11.0%、0.6%.在快速、中速达峰情景下,江苏省分别在2025和2029年达到CO₂排放峰值,峰值分别为7.01、7.95亿t,慢速达峰情景下未能实现2030年的CO₂排放达峰目标.综合研究分析,江苏省有着较大的减排潜力,经过相应的努力能够实现CO₂减排目标.为实现2030年的CO₂减排目标可采取以下措施:主动适应经济新常态,稳定发展增速;积极发展第三产业,平衡经济结构;持续推进节能减排技术,降低能源消费强度;大力发展天然气及核电等清洁能源,优化一次能源消费结构.     

长三角城市群碳排放与城市用地增长及形态的关系

城市是一种重要的碳源,城市扩张过程中的用地面积增长和空间特征变化均会影响城市碳排放。分析1995—2015年长三角城市群碳排放重心转移,查明碳排放和城市用地增长的脱钩状态时空变化,并通过构建面板数据模型探究城市形态对碳排放的影响,得出以下结论:(1) 1995—2015年长三角城市群碳排放重心经历了西南向-西北向-东南向-西北向的转移过程,这种转移过程与其相应时期内部分城市的工业发展与产业结构调整有关;(2) 1995—2015年,长三角城市群碳排放与城市用地增长的脱钩状态存在着显著的时空异质性。研究区由以扩张负脱钩为主变化为以弱脱钩为主,2005年以后,区域之间的脱钩差异开始缩小,总体来看研究区脱钩状态趋向于同质。至2015年,近70%的城市已达到了脱钩,其中上海等城市实现了强脱钩;(3)连续完整的地块在区域内的主导程度会对城市碳排放产生负向的影响,而城市用地斑块的破碎化程度和聚集程度对碳排放有着正向的影响,且相对而言,聚集程度的正向影响更为显著。     

基于氮排放估算的区域生态风险评价——以中国台湾地区为例

随着全球人口不断成长,农业生产、工业发展、能源消耗及生活消费等人类活动不断增加,对城市区域乃至于区域生态系统均带来显著负面影响。为量化评估人类活动对区域生态系统的影响,以人类活动产生的氮排放为切入点,选择中国台湾地区为研究区,针对其高投入的农业生产、密集的交通工业设施及人口分布等背景,构建了基于氮排放的区域生态风险评价研究框架。分析了2001年至2010年中国台湾地区农业及城市系统所产生的氮排放变化情况,并在空间上比较了各县市的氮排放差异;其次,依据各用地类型特点,定义了其对氮排放压力的脆弱程度,藉以评估中国台湾地区生态风险变化及其潜在风险强度。研究结果表明中国台湾地区2005至2010年期间氮排放带来的生态风险值先降后升,主要原因源于期间农业活动产生的氮排放减少,但交通运输带来能源消耗却明显增加了氮排放;通过分区比较,确定低风险县市主要包括金门县、连江县、澎湖县、新竹市、嘉义市及基隆市,而台中市、屏东县、台南市、高雄市及新北市,由于农业生产活动密集且人口分布密度高,为中国台湾地区高生态风险区。     

黄河流域农业生产活性氮排放及减排对策

人口增长和城市化进程促使粮食和肉禽奶类食品需求不断增加,由此带来的农业生产活性氮(Nr)大量排放对生态环境及人类健康的影响日益加剧。黄河流域作为中国的粮食主产区,农业生产活动强度高,为研究其Nr排放规律,采用排放因子法估算2000、2005及2010年黄河流域内9省(区)农业生产不同形态Nr的排放源。结果表明：(1)黄河流域9省(区)中,农业生产Nr排放量最大的为河南省,最小的为四川省,河南省Nr排放量是四川的8倍。(2)4种形态Nr排放量从大到小依次为Nr-wp(排放到水体的Nr)、NH₃、N₂O和NO_x。化学氮肥施用和畜禽散养是NH₃排放的最主要贡献源,其次是规模化养殖和放牧饲养,四者贡献率达85%以上。农田作物系统径流、淋洗以及畜禽养殖流失淋洗对Nr-wp排放的贡献率各占1/3左右。四季非蔬菜旱地和畜禽养殖是N₂O排放的主要来源,其贡献率之和大于66%。(3)黄河流域内9省(区)单位农业GDP、单位耕地面积、单位农村人口Nr排放强度最大的均为青海省,单位农业GDP和单位农...     

Decoupling Analysis of Four Selected Countries

We examine decoupling conditions of domestic extraction of materials, energy use, and sulfur dioxide (SO₂) emissions from gross domestic product (GDP) for two BRIC (Brazil, Russia, India and China) countries (i.e., China and Russia) and two Organisation for Economic Co‐operation and Development (OECD) countries (Japan and the United States) during 2000–2007, using a pair of decoupling indicators for resource use (D_r) and waste emissions (D_e) and the decoupling chart, which can distinguish between absolute decoupling, relative decoupling, and non‐decoupling. We find that (1) during 2000–2007, decoupling between environmental indicators and GDP was higher in the two OECD countries as compared with the two BRIC countries. The key reason is that these countries were in different development stages with different economic growth rates. (2) Changes in environmental policies can significantly influence the degree of decoupling in a country. (3) China, Japan, and the United States were more successful in decoupling SO₂ emissions from GDP than in decoupling material and energy use from GDP. The main reason is that, unlike resource use, waste emissions (e.g., SO₂ emissions) can be reduced by effective end‐of‐pipe treatment. (4) The decoupling indicator is different from the changing rate of resource use and waste emissions. If two countries have different GDP growth rates, even though they may have similar values using the decoupling indicator, they may show different rates of change for resource use and waste emissions.