文獻(xiàn)信息：

Tian Hanqin*, Xu Rongting, Canadell Josep, Thompson Rona, Winiwarter Wilfried, Suntharalingam Parvadha, Davidson Eric, Ciais Philippe, Jackson Robert, Janssens-Maenhout Greet, Prather Michael, Régnier Pierre, Pan Naiqing, Pan Shufen, Peters Glen, Shi Hao, Tubiello Francesco, Zaehle S?nke, Zhou Feng, Arneth Almut, Battaglia Gianna, Berthet Sarah, Bopp Laurent, Bouwman Alexander, Buitenhuis Erik, Chang Jinfeng, Chipperfield Martyn, Dangal Shree, Dlugokencky Edward, Elkins James, Eyre Bradley, Fu Bojie, Hall Bradley, Ito Akihiko, Joos Fortunat, Krummel Paul, Landolfi Angela, Laruelle Goulven, Lauerwald Ronny, Li Wei, Lienert Sebastian, Maavara Taylor, MacLeod Michael, Millet Dylan, Olin Stefan, Patra Prabir, Prinn Ronald, Raymond Peter, Ruiz Daniel, Van Der Werf Guido, Vuichard Nicolas, Wang Junjie, Weiss Ray, Wells Kelley, Wilson Chris, Yang Jia, Yao Yuanzhi. A comprehensive quantification of global nitrous oxide sources and sinks. Nature, 2020, 586(7828): 248-256. DOI: 10.1038/s41586-020-2780-0

摘  要：氧化亞氮(N₂O)和二氧化碳一樣，是一種在大氣中長(zhǎng)期存在的溫室氣體。在過(guò)去150年里，大氣中N₂O濃度的增加導(dǎo)致平流層臭氧消耗和氣候變化，目前以每十年2%的速率增長(zhǎng)?，F(xiàn)有的國(guó)家清單沒(méi)有提供N₂O排放的全面情況，因?yàn)樗鼈?/span>忽略了自然來(lái)源，并且在確定人為來(lái)源的方法上存在一定的局限性。在此，本研究提出了一個(gè)全球N₂O清單，其中包括自然和人為來(lái)源，并說(shuō)明了氮添加與控制N₂O排放生物化學(xué)過(guò)程之間的相互作用。本研究使用自下而上(清單；測(cè)定通量的統(tǒng)計(jì)外推；基于過(guò)程的陸地和海洋建模)和自上而下(大氣反演)的方法，對(duì)1980年至2016年間21個(gè)自然和人類(lèi)部門(mén)之間產(chǎn)生的全球N₂O源和匯進(jìn)行了綜合量化。2007年至2016年間，全球N₂O排放量為每年17(最小-最大估算值:12.2~23.5)Tg N(自下而上方法)和每年16.9(15.9~17.7)Tg N(自上而下方法)。在過(guò)去的四十年里，以向農(nóng)田施氮為主的全球人為排放增加了30%，達(dá)到每年增長(zhǎng)7.3(4.2~11.4)Tg N，這種增加是大氣氮負(fù)荷增加的主要原因。本研究發(fā)現(xiàn)表明，新興經(jīng)濟(jì)體（尤其是巴西、中國(guó)和印度）的N₂O排放量正在增加?；谶^(guò)程的模型估算結(jié)果揭示了一種新出現(xiàn)的N₂O-氣候反饋，而這種反饋是由氮添加和氣候變化之間的相互作用產(chǎn)生的。最近N₂O排放量的增長(zhǎng)超過(guò)了一些最高的預(yù)測(cè)排放情景，這凸顯了減少N₂O排放的緊迫性。

Abstract: Nitrous oxide (N₂O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N₂O concentrations have contributed to stratospheric ozone depletion and climate change, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N₂O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N₂O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N₂O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N₂O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N₂O emissions were 17.0 (minimum–maximum estimates: 12.2–23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9–17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2–11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N₂O emissions in emerging economies—particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N₂O–climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N₂O emissions exceeds some of the highest projected emission scenarios, underscoring the urgency to mitigate N₂O emissions.

圖1 2007-2016 年全球N₂O收支

Fig. 1 Global N₂O budget for 2007–2016. The coloured arrows represent N₂O fluxes (in Tg N yr^?1 for 2007–2016) as follows: red, direct emissions from nitrogen additions in the agricultural sector (agriculture); orange, emissions from other direct anthropogenic sources; maroon, indirect emissions from anthropogenic nitrogen additions; brown, perturbed fluxes from changes in climate, CO₂ or land cover; green, emissions from natural sources. The anthropogenic and natural N₂O sources are derived from bottom-up estimates. The blue arrows represent the surface sink and the observed atmospheric chemical sink, of which about 1% occurs in the troposphere. The total budget (sources + sinks) does not exactly match the observed atmospheric accumulation, because each of the terms has been derived independently and we do not force top-down agreement by rescaling the terms. This imbalance readily falls within the overall uncertainty in closing the N₂O budget, as reflected in each of the terms. The N₂O sources and sinks are given in Tg N yr^?1. Copyright the Global Carbon Project.

表 1 1980 年代、1990 年代、2000 年代和 2007-2016 年的全球N₂O收支

Table 1 The global N₂O budget in the 1980s, 1990s, 2000s and 2007–2016.

Bottom-up estimates include four categories of anthropogenic source and one category for natural sources and sinks. The sources and sinks of N₂O are given in Tg N yr^?1. The atmospheric burden is given in Tg N.

a Calculated from satellite observations with a photolysis model (about 1% of this sink occurs in the troposphere).

b Calculated from the combined NOAA and AGAGE record of surface N₂O, and adopting the uncertainty of the IPCC Assessment Report 5 (Chapter 6). Detailed information on calculating each sub-category is shown in Supplementary Tables 1–13.

圖2 2007-2016十年間的區(qū)域 N₂O 來(lái)源

Fig. 2 Regional N₂O sources in the decade 2007–2016. The Earth’s ice-free land is partitioned into ten regions: North America, South America, Europe, Middle East, Africa, Russia, East Asia, South Asia, Southeast Asia and Oceania. Each subplot shows the emissions from five sub-sectors using bottom-up approaches, followed by the sum of these five categories using bottom-up approaches (blue) and the estimates from top-down approaches (yellow). Bottom-up and top-down estimates of ocean emissions are shown at the bottom left (from bottom to top, lighter to darker, the contributions from the 30°–90° N, 30° S–30° N and 90°–30° S regions). Error bars indicate the spread between the minimum and the maximum values. The centre map shows the spatial distribution of 10-year average N₂O emissions from land and ocean based on the land and ocean models. Per capita N₂O emission (kg N per capita per year) during 2007–2016 is shown in Supplementary Fig. 2. The map was created using ESRI ArcMap 10.4.1.

圖 3 1980-2016 年期間區(qū)域人為 N₂O 排放

Fig. 3 Ensembles of regional anthropogenic N₂O emissions over the period 1980–2016. The bar chart in the centre shows the accumulated changes in regional and global N₂O emissions during the study period of 1980–2016. Error bars indicate the 95% confidence interval for the average of accumulated changes. The Mann–Kendall test was performed to examine a monotonic increasing or decreasing trend in the estimated ensemble N₂O emissions globally and for each region over the period 1980–2016. The accumulated changes were calculated from the linear regressed annual change rate (Tg N yr^?2) multiplied by 37 years. All regions except Southeast Asia show a significant increasing or decreasing trend in the estimated ensemble N₂O emissions during the study period . *P < 0.05.

圖 4 歷史和預(yù)測(cè)的全球人為 N₂O 排放和濃度

Fig. 4 Historical and projected global anthropogenic N₂O emissions and concentrations. a–d, Global anthropogenic N₂O emissions (a, b) and concentrations (c, d) compared to the four RCPs in the IPCC assessment report 5 (a, c; ref. 2) and the new marker scenarios based on the SSPs used in CMIP6 (b, d; ref. 48). The historical emissions data are represented as the mean of the bottom-up and top-down estimates of anthropogenic N₂O emissions, whereas the historical atmospheric concentration data are from the three available observation networks: AGAGE, NOAA, and CSIRO. Top-down anthropogenic emissions were calculated by subtracting natural fluxes derived from bottom-up approaches. To aid the comparison, the four RCPs were shifted down so that the 2005 value is equal to the 2000–2009 average of the mean of top-down and bottom-up estimates. The SSPs are harmonized3 to match the historical emissions used in CMIP649; Extended Data Fig. 10 shows the unharmonized data.