溫室氣體二氧化碳與氧化亞氮之釋出與變動;On the variabilities and emissions of the greenhouse gases, CO2 and N2O

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题名:	溫室氣體二氧化碳與氧化亞氮之釋出與變動;On the variabilities and emissions of the greenhouse gases, CO2 and N2O
作者:	薛郁欣;HSUEH, YU-HSIN
贡献者:	國際研究生博士學位學程
关键词:	營養鹽碳氮循環;趨勢與氣候訊號分析;穩定同位素分析;溫室土壤孵育;田間農業系統尺度測量;carbon and nitrogen cycles;trend and climate signal analyses;stable isotope analyses;soil incubation;agriculture field scale measurements
日期:	2022-09-29
上传时间:	2022-10-04 11:47:06 (UTC+8)
出版者:	國立中央大學
摘要:	CO2 和 N2O 是兩種重要的溫室氣體 (GHG)，濃度遠小於CO2的 N2O，其溫室效應潛力卻與 CO2 相當；自工業時代之後，兩者受人為活動直接或間接的影響，在大氣濃度上，都以非線性、且遠高於百萬年以來的速度增加。前人從排放清冊與氣候系統模式結果比對後，發現有出入，而推測自然生態系統可能影響氣體濃度。此兩種氣體參與碳和氮循環，各自與相互的作用機制會受到氣候變化而產生回饋反應。這項回饋機制則具有區域與時間上的變異，且各式生態系統都未被充分的了解，因此全球各地釋出氣體量尚難以完整預估。文起兩個主軸，首先探討長時期的大氣CO2濃度是否帶有生態系統的變動訊號。將東南亞地方尺度的溫室氣體排放量、與太平洋西部區域的遙感探測中所得知的大氣濃度、加以比對，探討其不同頻度的變動來源。大氣CO2濃度隨氣候的年間模式而有季節變動，符合生物生長經光合作用固碳所致。但長期的低頻度訊號則有一段明顯增加幅度，不符合當時台灣或東亞區域人為CO2釋出清冊的穩定趨勢。此低頻的CO2濃度與區域尺度氣候震盪似乎相符，推測受到聖嬰與太平洋十年振盪 (Pacific Decadal Oscillation) 的影響改變CO2濃度。這項在亞洲副熱帶地區觀察結果與現今推估模式有些微落差；證明有如氣候震盪等的未知過程並未被完整了解，顯示長期且全面觀測CO2的重要性。第二個主題則以N2O之釋出機制進行探討。在進行溫室之土壤培養與田間農業施作環境下進行觀察後，研究顯示N2O釋出經由銨氧化與真菌脫硝作用為主。其釋出量對應於 N 投入量，有非線性(溫室)或線性(田間)變化；而添加高量肥料也加強脫硝作用。雙季輪作稻米的田地釋出量N2O較輪作稻米-花生田的釋出的N2O更多，顯示受肥料、淹/排水、土壤擾動、作物殘體效應等影響。以同位素圖譜與定量推測N2O釋出來源包括化學肥料與埋入的作物殘體。因此推測硝化菌在有機氮的存在下，可能從銨-硝酸鹽-直接轉化成N2，因而減少N2O形成。另一方面CO2的釋出量並不完全對應於 N 投入量，但可能與埋入植體類型與時間有關。推測當碳氮比降低，硝化菌與脫硝細菌作用增強，礦質化作用促進有機質降解，N2O釋出減少，CO2釋出卻較高。本研究試圖以大氣氣體濃度與其同位素比值，來辨識造成濃度變化的回饋作用。由於生態系統產出的氣體帶有穩定同位素訊號，在原產物的基質界定之後，能判定產生之機制，由此建立機制與通量的關係。未來若能結合大氣溫室氣體之穩定同位素的自然豐量度與遙感探測方法，連續觀察溫室氣體濃度與同位素比值改變差異，推知大尺度生物-地理-化學特徵資訊，即時分析連續時空尺度的回饋作用，提供同化分析中所需參數，而增進溫室氣體的預測模式。;CO2 and N2O are two important greenhouse gases, presenting significant radiative forcing. The two gases in the atmosphere increase at alarming rates due mainly to anthropogenic activities. Yet, an accurate projection of their concentrations in time and space remains challenging because of a complex interplay between anthropogenic emissions, biospheric responses, and climatic variabilities. The concentrations and surface emissions of CO2 and N2O at various spatial and temporal are thus examined. For CO2, the atmospheric level is found to fluctuate, possessing climatic inter-annual variabilities, such as Pacific Decadal Oscillation (PDO) and El Niño-Southern Oscillation (ENSO). The analysis shows for the first time an intimate connection of the regional CO2 concentration to the climatic oscillation induced by the PDO. The decadal signal, however, is not reproduced by the state-of-the-art data assimilation system, CarbonTacker, suggesting a gap in our knowledge of the modulation of carbon cycling systems and climate. For N2O, the emissions at the laboratory chamber and agriculture field scales are explored. It is found that N2O is produced as the fertilizer rate increases through the co-occurrence of several microbial N2O production pathways, with nitrification and/or fungal denitrification as the dominant processes responsible for N2O emissions. Besides this, dominant signatures of denitrification by bacteria and denitrifier are observed in an N2O emission episode in intermediate urea-N levels in laboratory chamber setting. The signature of N2O consumption by reduction could be traced to declining emissions in treatment with high urea levels. In agriculture field setting, it was also elucidated that the ammonium sulfate and urea combined gave rise to N2O in the agricultural field under a double rice cropping system through aforementioned processes. In a rice-peanut rotation system, however, fewer synthetic fertilizers were transformed into N2O and were likely mediated after amending peanut residue in the soil. In short, the study deepens our knowledge of natural and anthropogenic forcings and responses to the levels of CO2 and N2O in the atmosphere and presents a probable method combining stable isotopic analysis and remote sensing technology to detect gas concentration dynamics. This methodology illustrates how environmental changes incur the emission of CO2 and N2O in space and time, which then enables us to assess the process and scale of the feedback between carbon and nitrogen cycles. Aid with advanced technology, on-site monitoring is possible and can provide real-time information for assimilation between databases in predicting the dynamics of greenhouse gases.
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