• ISSN 1008-505X
  • CN 11-3996/S
王琛, 尹兴, 陈盟, 韩建, 张杰, 郭艳杰, 张丽娟. 基于不同监测与估算方法的设施菜田N2O排放量比较[J]. 植物营养与肥料学报, 2020, 26(8): 1375-1383. DOI: 10.11674/zwyf.19489
引用本文: 王琛, 尹兴, 陈盟, 韩建, 张杰, 郭艳杰, 张丽娟. 基于不同监测与估算方法的设施菜田N2O排放量比较[J]. 植物营养与肥料学报, 2020, 26(8): 1375-1383. DOI: 10.11674/zwyf.19489
WANG Chen, YIN Xing, CHEN Meng, HAN Jian, ZHANG Jie, GUO Yan-jie, ZHANG Li-juan. Comparison of different monitoring and estimation methods for N2O emissions from greenhouse vegetables production[J]. Journal of Plant Nutrition and Fertilizers, 2020, 26(8): 1375-1383. DOI: 10.11674/zwyf.19489
Citation: WANG Chen, YIN Xing, CHEN Meng, HAN Jian, ZHANG Jie, GUO Yan-jie, ZHANG Li-juan. Comparison of different monitoring and estimation methods for N2O emissions from greenhouse vegetables production[J]. Journal of Plant Nutrition and Fertilizers, 2020, 26(8): 1375-1383. DOI: 10.11674/zwyf.19489

基于不同监测与估算方法的设施菜田N2O排放量比较

Comparison of different monitoring and estimation methods for N2O emissions from greenhouse vegetables production

  • 摘要:
    目的 为了分析微气象学方法中反演式气体扩散模型在设施菜田N2O排放测定分析中的应用效果及精确度,本研究结合静态箱/气相色谱法同步观测结果,比较了两种观测值之间的差异及其形成的各因素,以验证该方法在测定温室气体排放中的可行性。
    方法 在设施蔬菜大棚中,设置了施肥区和非施肥区,通过箱式法和微气象学方法分别对设施菜田种植区进行72 h的高频监测和全生长季监测,构建N2O浓度特征曲线和排放通量特征曲线。
    结果 田闲期棚区上方3.5 m处N2O浓度明显低于种植期,但田闲期夜间浓度较高,种植期白天浓度较高。棚室内N2O浓度随高度增加呈下降趋势,且差异明显,而且都高于棚室外背景浓度。静态箱/气相色谱法和反演式气体扩散模型测得棚区N2O日排放特征具有较好的一致性,但前者测定结果普遍高于后者,静态箱/气相色谱法测得平均排放通量为252.51 μg/(m2·h),反演式气体扩散模型测得平均排放通量为192.21 μg/(m2·h),前者比后者高26.75%;在设施番茄全生长季观测中,两种方法测定的N2O排放通量特征曲线趋势一致,静态箱/气相色谱法测得土壤净排放通量为1817.49 g/hm2,排放系数为0.45%;反演式气体扩散模型测得土壤净排放通量为1250.95 g/hm2,排放系数为0.32%,较静态箱/气相色谱法测得结果降低了29%。
    结论 反演式气体扩散模型、静态箱/气相色谱法对设施菜田种植区N2O排放通量的测定结果,趋势上一致性较好,但反演式气体扩散模型观测结果明显低于静态箱/气相色谱法,不过反演式气体扩散模型自动化程度高,可以高密监测设施菜田N2O排放全过程,且适用于较大区域的观测,为建立多元化的N2O排放监测体系提供了新的研究方法和思路。

     

    Abstract:
    Objectives In order to introduce an inverse dispersion technique to evaluate N2O emissions from greenhouse with vegetable production, static box gas collection instruments with gas chromatography analysis were used simultaneously to check N2O emission. The results were compared and analyzed to test the feasibility of this new approach.
    Methods In the vegetable greenhouses of the facility, a fertilizing area and a non-fertilizing area were set up. Using box-type method and micro-meteorological method to carry out 72-hour high-frequency monitoring and full-growth monitoring, N2O concentration characteristic curve and emission flux characteristic curve were constructed by measuring results.
    Results The results showed that the N2O concentration at 3.5 m above the shed area of the vacant period was significantly lower than that of the planting period. The nighttime concentration during the vacant period was higher, and the daytime concentration during the planting period was higher. The concentration of N2O in the greenhouse decreased with the increase of height, and the difference of N2O concentration between different heights was significant, which was higher than the external background concentration. The result of the N2O daily emission characteristics by static box/gas chromatogram method and inverse dispersion technique had good consistency, but the former was generally higher than the latter. The average three-day emission flux measured by inverse dispersion technique was 192.2 μg/(m2·h). The average gas emission flux measured by static box/gas chromatogram was 252.5 μg/(m2·h). The difference was 26.8%. In both ways, the flux curve tended to be consistent across the entire growing season of the plant tomato. The cumulative emission flux measured by static box/gas chromatogram was 1817.5 g/hm2, and the emission factor was 0.45%. The cumulative emission flux measured by inverse dispersion technique was 1250.95 g/hm2, and the emission factor was 0.32%, which was 29% lower than that measured by the static box method.
    Conclusions The results of the inversion gas diffusion model and the static box/gas chromatography method on the N2O flux in the vegetable field planting area have good consistency. But the results of the inverse dispersion technique are significantly lower than those of the static box/gas chromatogram method. However, the inversion gas diffusion model has a high degree of automation, which can monitor the whole process of N2O emission in the vegetable field with high density and is suitable for observation in a large area. It provides a reference for the existing measurement methods and provides new ideas for establishing a diversified N2O emission monitoring system.

     

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