中国湿地温室气体清单编制研究进展

湿地是重要的土地利用类型之一,在陆地生态系统碳循环中起重要作用。在缔约国向《联合国气候变化框架公约》提交的温室气体国家清单报告中,湿地作为“农业、林业及其他土地利用(AFOLU)”的一部分,因其不确定性较高而备受关注。自2006年以来,IPCC先后发布了《2006 IPCC国家温室气体清单指南》、《2013 IPCC 2006国家温室气体清单指南的增补：湿地》和《IPCC 2006年国家温室气体清单指南2019精细化》,为缔约国提供了清单编制的参考方法学。然而,IPCC指南中对湿地的定义和分类与中国现行的土地利用类型和并不统一,其提供的缺省参数对中国的研究亦未充分整合。因此,亟需在IPCC框架下开发适合中国的湿地温室气体清单方法学及参数库,以降低清单编制的不确定性。综述了IPCC湿地清单编制的方法学与中国湿地清单的研究进展,主要包括(1)比较了IPCC三部指南中的湿地清单的方法学,梳理了后两部对《2006 IPCC国家温室气体清单指南》在湿地类型、评估方法和缺省参数的更新内容;(2)比较了中国湿地清单编制与其他湿地温室气体研究结果的差异并探讨原因;(3)梳理了IPCC三部清单指南中湿地...     

Terrestrial ecosystems and the carbon cycle

The terrestrial biosphere plays an important role in the global carbon cycle. In the 1994 Intergovernmental Panel Assessment on Climate Change (IPCC), an effort was made to improve the quantification of terrestrial exchanges and potential feedbacks from climate, changing CO₂, and other factors; this paper presents the key results from that assessment, together with expanded discussion. The carbon cycle is the fluxes of carbon among four main reservoirs: fossil carbon, the atmosphere, the oceans, and the terrestrial biosphere. Emissions of fossil carbon during the 1980s averaged 5.5 Gt y^?1. During the same period, the atmosphere gained 3.2 Gt C y^?1 and the oceans are believed to have absorbed 2.0 Gt C y^?1. The regrowing forests of the Northern Hemisphere may have absorbed 0.5 Gt C y^?1 during this period. Meanwhile, tropical deforestation is thought to have released an average 1.6 Gt C y^?1 over the 1980s. While the fluxes among the four pools should balance, the average 198Ds values lead to a ‘missing sink’ of 1.4 Gt C y^?1 Several processes, including forest regrowth, CO₂ fertilization of plant growth (c. 1.0 Gt C y^?1), N deposition (c. 0.6 Gt C y^?1), and their interactions, may account for the budget imbalance. However, it remains difficult to quantify the influences of these separate but interactive processes. Uncertainties in the individual numbers are large, and are themselves poorly quantified. This paper presents detail beyond the IPCC assessment on procedures used to approximate the flux uncertainties. Lack of knowledge about positive and negative feedbacks from the biosphere is a major limiting factor to credible simulations of future atmospheric CO₂ concentrations. Analyses of the atmospheric gradients of CO₂ and ¹³ CO₂ concentrations provide increasingly strong evidence for terrestrial sinks, potentially distributed between Northern Hemisphere and tropical regions, but conclusive detection in direct biomass and soil measurements remains elusive. Current regional-to-global terrestrial ecosystem models with coupled carbon and nitrogen cycles represent the effects of CO₂ fertilization differently, but all suggest longterm responses to CO₂ that are substantially smaller than potential leaf- or laboratory whole plant-level responses. Analyses of emissions and biogeochemical fluxes consistent with eventual stabilization of atmospheric CO₂ concentrations are sensitive to the way in which biospheric feedbacks are modeled by c. 15%. Decisions about land use can have effects of 100s of Gt C over the next few centuries, with similarly significant effects on the atmosphere. Critical areas for future research are continued measurements and analyses of atmospheric data (CO₂ and ¹³CO₂) to serve as large-scale constraints, process studies of the scaling from the photosynthetic response to CO₂ to whole-ecosystem carbon storage, and rigorous quantification of the effects of changing land use on carbon storage.     

Dynamics of nitrous oxide in groundwater at the aquatic–terrestrial interface

Few data are available to validate the Intergovernmental Panel on Climate Change's (IPCC) emission factors for indirect emissions of nitrous oxide (N₂O). In particular the N₂O emissions resulting from nitrogen leaching and the associated groundwater and surface drainage (EF5-g) are particularly poorly characterized. In situ push–pull methods have been used to identify the fate of NO₃⁻ in the groundwater. In this study, we adapted a previously published in situ denitrification push–pull method to examine the fate of ¹⁵N₂O introduced into the subsoil–groundwater matrix. Enriched ¹⁵N₂O was manufactured, added to groundwater via a closed system in the laboratory, and then introduced into the groundwater–subsoil matrix in an upland-marsh transition zone of a salt marsh and a forested alluvial riparian zone. Conservative tracers (SF₆ and Br⁻) and ¹⁵N₂O were injected into the groundwater and left for 1–4 h after which the groundwater was sampled. Added ¹⁵N₂O behaved in a conservative manner at one site while the other site showed variability with some injections showing significant consumption (3–8 μg N₂O-¹⁵N kg⁻¹ soil day⁻¹) of ¹⁵N₂O. Our results show that the fate and dynamics of N₂O in groundwater are complex and variable and that these dynamics should be considered in the development of improved IPCC inventory calculations.     

Invited review: Intergovernmental Panel on Climate Change,agriculture, and food—A case of shifting cultivation and history

Since 1990, the Intergovernmental Panel on Climate Change (IPCC) has produced five Assessment Reports (ARs), in which agriculture as the production of food for humans via crops and livestock have featured in one form or another. A constructed database of the ca. 2,100 cited experiments and simulations in the five ARs was analyzed with respect to impacts on yields via crop type, region, and whether adaptation was included. Quantitative data on impacts and adaptation in livestock farming have been extremely scarce in the ARs. The main conclusions from impact and adaptation are that crop yields will decline, but that responses have large statistical variation. Mitigation assessments in the ARs have used both bottom‐up and top‐down methods but need better to link emissions and their mitigation with food production and security. Relevant policy options have become broader in later ARs and included more of the social and nonproduction aspects of food security. Our overall conclusion is that agriculture and food security, which are two of the most central, critical, and imminent issues in climate change, have been dealt with an unfocussed and inconsistent manner between the IPCC five ARs. This is partly a result of not only agriculture spanning two IPCC working groups but also the very strong focus on projections from computer crop simulation modeling. For the future, we suggest a need to examine interactions between themes such as crop resource use efficiencies and to include all production and nonproduction aspects of food security in future roles for integrated assessment models.     

基于IPCC Tier 1层级的中国反刍家畜胃肠道甲烷排放格局变化分析

依据政府间气候变化委员会(IPCC)2006年公布的反刍家畜胃肠道CH4排放系数(奶牛61 kg CH4头-1a-1,肉役牛47 kg CH4头-1a-1,绵羊和山羊均为5 kg CH4头-1a-1)和IPCC Tier 1计算方法,结合《中国统计年鉴》和《中国畜牧业统计年鉴》,估算了中国以及各个省份1990—2010年CH4的排放总量,绘制出中国反刍家畜胃肠道CH4排放格局及历史变化图。研究结果表明:11990—2010年期间,中国反刍家畜胃肠道CH4排放量(5.90—7.65 Tg)总体呈现先上升(1995年最高)后下降的趋势,其中肉役牛(主要是黄牛和水牛)胃肠道CH4排放量(4.33 Tg)及其所占比例(65%)最大。奶牛胃肠道CH4排放量及其比例呈现逐年增加的趋势,2006年(0.83 Tg,12.7%)超过山羊和绵羊胃肠道CH4排放量及其比例,成为中国反刍家畜胃肠道CH4排放第二大源。但是,奶牛单位产奶量所排放的CH4量逐年降低,表明中国奶牛饲养技术与生产性能不断提高。2中国反刍家畜胃肠道CH4排放格局呈现区域集中特点,主要集中在中西部和北部的各个省份,其中四川、内蒙古、新疆、河南、西藏、山东、河北、黑龙江、云南和甘肃等10个省份的排放量占中国排放总量的50%以上。总之,1990—2010年间,中国反刍家畜胃肠道CH4排放总量为(6.77±0.46)Tg(肉役牛为主要排放源),随时间推移呈现先上升后下降的趋势;中国反刍家畜胃肠道CH4排放的格局呈区域集中分布,中西部和北部的各个省份占60%以上。     

The importance of considering animal body mass in IPCC greenhouse inventories and the underappreciated role of wild herbivores

Methane is an important greenhouse gas, but characterizing production by source sector has proven difficult. Current estimates suggest herbivores produce ~20% (~76–189 Tg yr^?1) of methane globally, with wildlife contributions uncertain. We develop a simple and accurate method to estimate methane emissions and reevaluate production by wildlife. We find a strikingly robust relationship between body mass and methane output exceeding the scaling expected by differences in metabolic rate. Our allometric model gives a significantly better fit to empirical data than IPCC Tier 1 and 2 calculations. Our analysis suggests that (i) the allometric model provides an easier and more robust estimate of methane production than IPCC models currently in use; (ii) output from wildlife is much higher than previously considered; and (iii) because of the allometric scaling of methane output with body mass, national emissions could be reduced if countries favored more, smaller livestock, over fewer, larger ones.     

Estimating aboveground net biomass change for tropical and subtropical forests: Refinement of IPCC default rates using forest plot data

As countries advance in greenhouse gas (GHG) accounting for climate change mitigation, consistent estimates of aboveground net biomass change (?AGB) are needed. Countries with limited forest monitoring capabilities in the tropics and subtropics rely on IPCC 2006 default ?AGB rates, which are values per ecological zone, per continent. Similarly, research into forest biomass change at a large scale also makes use of these rates. IPCC 2006 default rates come from a handful of studies, provide no uncertainty indications and do not distinguish between older secondary forests and old‐growth forests. As part of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, we incorporate ?AGB data available from 2006 onwards, comprising 176 chronosequences in secondary forests and 536 permanent plots in old‐growth and managed/logged forests located in 42 countries in Africa, North and South America and Asia. We generated ?AGB rate estimates for younger secondary forests (≤20 years), older secondary forests (>20 years and up to 100 years) and old‐growth forests, and accounted for uncertainties in our estimates. In tropical rainforests, for which data availability was the highest, our ?AGB rate estimates ranged from 3.4 (Asia) to 7.6 (Africa) Mg ha^?1 year^?1 in younger secondary forests, from 2.3 (North and South America) to 3.5 (Africa) Mg ha^?1 year^?1 in older secondary forests, and 0.7 (Asia) to 1.3 (Africa) Mg ha^?1 year^?1 in old‐growth forests. We provide a rigorous and traceable refinement of the IPCC 2006 default rates in tropical and subtropical ecological zones, and identify which areas require more research on ?AGB. In this respect, this study should be considered as an important step towards quantifying the role of tropical and subtropical forests as carbon sinks with higher accuracy; our new rates can be used for large‐scale GHG accounting by governmental bodies, nongovernmental organizations and in scientific research.     

Methane emission from global livestock sector during 1890–2014: Magnitude,trends and spatiotemporal patterns

Human demand for livestock products has increased rapidly during the past few decades largely due to dietary transition and population growth, with significant impact on climate and the environment. The contribution of ruminant livestock to greenhouse gas (GHG) emissions has been investigated extensively at various scales from regional to global, but the long‐term trend, regional variation and drivers of methane (CH₄) emission remain unclear. In this study, we use Intergovernmental Panel on Climate Change (IPCC) Tier II guidelines to quantify the evolution of CH₄ emissions from ruminant livestock during 1890–2014. We estimate that total CH₄ emissions in 2014 was 97.1 million tonnes (MT) CH₄ or 2.72 Gigatonnes (Gt) CO₂‐eq (1 MT = 10¹² g, 1 Gt = 10¹⁵ g) from ruminant livestock, which accounted for 47%–54% of all non‐CO₂ GHG emissions from the agricultural sector. Our estimate shows that CH₄ emissions from the ruminant livestock had increased by 332% (73.6 MT CH₄ or 2.06 Gt CO₂‐eq) since the 1890s. Our results further indicate that livestock sector in drylands had 36% higher emission intensity (CH₄ emissions/km²) compared to that in nondrylands in 2014, due to the combined effect of higher rate of increase in livestock population and low feed quality. We also find that the contribution of developing regions (Africa, Asia and Latin America) to the total CH₄ emissions had increased from 51.7% in the 1890s to 72.5% in the 2010s. These changes were driven by increases in livestock numbers (LU units) by up to 121% in developing regions, but decreases in livestock numbers and emission intensity (emission/km²) by up to 47% and 32%, respectively, in developed regions. Our results indicate that future increases in livestock production would likely contribute to higher CH₄ emissions, unless effective strategies to mitigate GHG emissions in livestock system are implemented.     

Bias and variance in model results associated with spatial scaling of measurements for parameterization in regional assessments

Models are central to global change analyses, but they are often parameterized using data that represent only a portion of heterogeneity in a region. This creates uncertainty in the results and constrains the reliability of model inferences. Our objective was to evaluate the uncertainty associated with differential scaling of parameterization data to model soil organic carbon stock changes as a function of US agricultural land use and management. Specifically, we compared analyses in which model parameters were derived from field experimental data that were scaled to the entire US vs. the same data scaled to climate regions within the country. We evaluated the effect of differential scaling on both bias and variance in model results. Model results had less variance by scaling data to the entire country because of a larger sample size for deriving individual parameter values, although there was a relatively large bias associated with this parameterization, estimated at 2.7 Tg C yr^?1. Even with the large bias, resulting confidence intervals from the two parameterizations had considerable overlap for the estimated national rate of SOC change (i.e. 77% overlap in those intervals). Consequently, the results were relatively similar when focusing on the uncertainty rather than solely on the mean estimate. In contrast, large biases created less overlap in confidence intervals for the change rates within individual climate regions, compared with the national estimates. For example, the overlap in resulting intervals from the two parameterizations was only 32% for the warm temperate moist region, with a corresponding bias of 3.1 Tg C yr^?1. These findings demonstrate that there is a greater risk of making erroneous inferences because of large biases if models are parameterized with broader scale information, such as an entire country, and then used to address impacts at a finer spatial scale, such as sub‐regions within a country. In addition, the study demonstrates a trade‐off between variance and bias in model results that depends on the scaling of data for model parameterization.