基于DNDC模型的设施菜地N<sub>2</sub>O减排潜力评估

柯华东; 孔陈琛; 雷豪杰; 丁武汉; 李虎

doi:10.12357/cjea.20210735

基于DNDC模型的设施菜地N₂O减排潜力评估

doi: 10.12357/cjea.20210735

中国农业科学院农业资源与农业区划研究所　北京　100081

基金项目: 国家现代农业产业技术体系建设专项(CARS-23-B18)和国家自然科学基金项目(41671303)资助

详细信息

作者简介:
柯华东, 主要研究方向为农业资源利用。E-mail: 82101196128@caas.cn

通讯作者:
李虎, 主要研究方向为农业资源利用与区划。E-mail: lihu0728@sina.com

中图分类号: S19
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出版历程
- 收稿日期: 2021-10-31
- 录用日期: 2022-01-25
- 网络出版日期: 2022-03-01
- 刊出日期: 2022-08-01

Assessment of the N₂O emission reduction potential in greenhouse vegetable fields based on the DNDC model

Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Funds: The study was supported by the Earmarked Fund for China Agriculture Research System (CARS-23-B18) and the National Natural Science Foundation of China (41671303).

More Information

Corresponding author: E-mail: lihu0728@sina.com

摘要

摘要: 设施菜地因水肥投入高而导致大量N₂O排放已成为当前研究热点。N₂O作为主要温室气体之一, 探寻N₂O减排潜力不仅可为设施菜地碳减排方案的制定提供一定参考, 还可为实现我国“双碳”目标提供科学依据。本研究以京郊典型设施黄瓜-番茄系统为研究对象, 通过田间试验与DNDC模型相结合的方法, 基于田间观测数据对模型进行校验, 然后以农民常规种植模式为基线情景, 改变田间管理措施(灌溉方式、施氮量、有机肥替代化肥等)和调控土壤理化性质[土壤有机碳(SOC)、pH等]为替代情景, 运用DNDC模型通过1250次模拟得到单一情景和多组合情景下N₂O排放量, 并评估其减排潜力。结果表明, DNDC模型能够较好地模拟设施菜地土壤温湿度、蔬菜产量和N₂O排放量。基线情景下N₂O排放总量为12.18 kg(N)∙hm⁻²。单因子情景分析表明, 设施菜地N₂O减排潜力变幅为12.23%~17.58%。敏感性指数显示N₂O排放对土壤pH调控和化肥减施的响应比对其余单因子较为敏感, 其中相比于基线情景, 1.2倍土壤pH情景和减施30%化肥情景N₂O排放量分别降低15.60%和14.86%。多组合因子情景表明, 与基线情景相比, 同时采用滴灌、减少30%的化肥施氮量和减施30%有机肥组合情景, 可降低31.69%的N₂O排放。而相同组合在低SOC及高pH的土壤情景中N₂O减排潜力可进一步降低, 达到55.58% [6.77 kg(N)∙hm⁻²]。可见, DNDC模型可较好地模拟田间环境, 克服田间试验中有限的处理设置和较高的监测成本等局限性, 从而为设施菜地N₂O排放定量评估和减排评价提供了一个较好的解决方案。DNDC对设施菜地N₂O排放的单因子情景和组合情景的模拟结果表明, 结合土壤理化性质调控和水肥管理措施优化具有较大的N₂O减排潜力。
- DNDC模型 /
- 设施菜地 /
- 减排潜力 /
- N₂O
Abstract: The large amount of N₂O emission associated with high water and fertilizer inputs in greenhouse vegetable fields has become a salient issue. As N₂O is one of the major greenhouse gases, the research on reducing N₂O emissions can provide not only a reference for the formulation of carbon reduction plans for greenhouse vegetable fields but also a scientific basis to realize China’s “dual carbon” target. In this study, the N₂O emission of a typical greenhouse cucumber-tomato system in the Beijing suburbs was studied by using field monitoring and the DNDC model. The model was calibrated using field observations, and farmers’ conventional practices were set as the baseline scenario. The scenarios with changes in field management practices (e.g., irrigation method, N application rate, and replacement of chemical fertilizer by organic fertilizer) and regulation of soil physicochemical properties (soil organic carbon, pH, etc.) were set. N₂O emissions were obtained from 1250 simulations of the DNDC model for single scenario and multiple combinations of scenarios, and their emission reduction potentials were evaluated. The results showed that the DNDC model can simulate the soil temperature, soil water-filled pore space, vegetable yield, and N₂O emissions in greenhouse vegetable fields. The total N₂O emissions in the baseline scenario were 12.18 kg(N)∙hm⁻². The variation in the N₂O reduction potential of greenhouse vegetable fields ranged from 12.23% to 17.58% under the single-factor scenario. The sensitivity index showed that N₂O emissions were more sensitive to soil pH regulation and fertilizer reduction than to the other scenarios, with N₂O emissions (10.28 kg(N)∙hm⁻²) reduced by 15.60% and 14.86% for the 1.2-unit-change-in-soil-pH scenario and the 30% fertilizer reduction scenario (10.38 kg(N)∙hm⁻²), respectively, compared to the baseline. The multiple combination scenarios showed that a reduction of 31.69% in N₂O emissions from the baseline could be achieved with a combination of drip irrigation, 30% reduction in chemical N application, and 30% reduction in organic fertilizer. The N₂O reduction potential further improved to 55.58% (6.77 kg(N)∙hm⁻²) for the same combination in the low soil organic carbon and high pH soil scenarios. Overall, the DNDC model can simulate the field environment and overcome the drawbacks of limited treatment settings and high monitoring costs in field experiments, providing a useful method to quantitatively assess and reduce N₂O emissions in greenhouse vegetable fields. The combination of regulating soil physicochemical properties and optimizing water and fertilizer management can effectively reduce N₂O emission in greenhouse vegetable fields.
- DNDC model /
- Greenhouse vegetable field /
- Emission reduction potential /
- N₂O

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图 1 DNDC模型对不同灌溉施肥方式下设施菜地系统作物产量的模拟结果

FP: 农民习惯处理; FPD: 滴灌施肥处理。FP: farmer’s conventional treatment; FPD: drip fertigation treatment

Figure 1. Simulation results of crops yield of greenhouse vegetable system under different irrigation and fertilization treatments by DNDC model

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图 2 DNDC模型对不同灌溉施肥方式下设施菜地土壤5 cm温度的模拟结果

　　FP: 农民习惯处理; FPD: 滴灌施肥处理。

Figure 2. Simulation results of 5 cm soil temperature of greenhouse vegetable system under different irrigation and fertilization treatments by DNDC model

FP: farmer’s conventional treatment; FPD: drip fertigation treatment.

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图 3 DNDC模型对不同灌溉施肥方式下设施菜地土壤0~20 cm孔隙含水率的模拟结果

FP: 农民习惯处理; FPD: 滴灌施肥处理。

Figure 3. Simulation results of 0−20 cm soil water-filled pore space (WFPS) of greenhouse vegetable system under different irrigation and fertilization treatments by DNDC model

FP: farmer’s conventional treatment; FPD: drip fertigation treatment.

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图 4 DNDC模型对不同灌溉施肥方式下设施菜地N₂O排放的模拟结果

FP: 农民习惯处理; FPD: 滴灌施肥处理。

Figure 4. Simulation results of N₂O emission of greenhouse vegetable system under different irrigation and fertilization treatments by DNDC model

FP: farmer’s conventional treatment; FPD: drip fertigation treatment.

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图 5 DNDC模型对不同情景下设施菜地N₂O排放总量模拟结果

*代表基线。横坐标为设置的各组情景。SOC为土壤有机碳。FP: 农民习惯处理; FPD: 滴灌施肥处理。

Figure 5. Simulation results of total N₂O emissions of greenhouse vegetable system under different scenarios by DNDC model

* represents the baseline scenario. The X-axis is scenario settings. SOC is soil organic carbon. FP: farmer’s conventional treatment; FPD: drip fertigation treatment.

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图 6 DNDC 模型对不同管理措施组合情景下设施菜地N₂O排放模拟

F和D分别代表漫灌和滴灌。*代表基线。

Figure 6. N₂O emission simulation of greenhouse vegetable system under different management measures combination scenarios by DNDC model

F and D represent flood irrigation and drip irrigation. * represents the baseline scenario.

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图 7 DNDC 模型对漫灌条件下不同组合情景的设施菜地N₂O排放模拟结果

SOC为土壤有机碳; *代表基线, pH基线值为7.23, SOC baseline值为14.3 g(C)∙kg⁻¹。

Figure 7. N₂O emission simulation results of greenhouse vegetable system by DNDC model under different combination scenarios under flooding irrigation

SOC is soil organic carbon. * represents the baseline scenario. The baseline vales of pH and SOC are 7.23 and 14.3 g(C)∙kg⁻¹, respectively.

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图 8 DNDC 模型对滴灌条件下不同组合情景的设施菜地N₂O排放模拟结果

SOC为土壤有机碳; *代表基线, pH基线值为7.23, SOC baseline值为14.3 g(C)∙kg⁻¹。

Figure 8. N₂O emission simulation results of greenhouse vegetable system by DNDC model under different combination scenarios under drip irrigation

SOC is soil organic carbon. * represents the baseline scenario. The baseline vales of pH and SOC are 7.23 and 14.3 g(C)∙kg⁻¹, respectively.

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表 1 设施黄瓜-番茄轮作周期的灌溉施肥管理表

Table 1. Detailed irrigation and fertilization management for cucumber-tomato rotation in greenhouse

种植季 Planting season	项目 Project	日期(月-日) Date (month-day)	施肥量 Fertilization rate [kg(N)∙hm⁻²]	灌水量 Irrigation amount (mm)
黄瓜季 Cucumber	施有机肥 Organic fertilizer application	09-13	700	—
	施基肥 Basal dressing	09-13	710	41.7
	第1次追肥 First dressing	10-12	140	32.1
	第2次追肥 Second dressing	11-01	140	29.2
	第3次追肥 Third dressing	11-20	140	29.2
	第4次追肥 Fourth dressing	12-04	70	32.1
番茄季 Tomato	施有机肥 Organic fertilizer application	03-12	800	—
	基肥 Basal dressing	03-16	950	29.2
	第1次追肥 First dressing	04-15	150	29.2
	第2次追肥 Second dressing	05-12	150	41.7
	第3次追肥 Third dressing	05-27	150	41.7
	第4次追肥 Fourth dressing	06-12	150	41.7

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表 2 温室黄瓜-番茄种植系统的DNDC模型输入参数汇总表

Table 2. Summary table of input parameters of DNDC model of cucumber-tomato planting system in greenhouse

参数 Parameter		黄瓜 Cucumber	番茄 Tomato
土壤表层有机碳 Surface soil organic carbon content [g(C)∙kg⁻¹]		14.3
田间持水量 Field capacity (soil water-filled pore space, WFPS)		0.6
土壤质地 Soil texture		粉壤土 Silt loam
黏粒含量 Clay fraction		0.14
容重 Soil bulk density (g∙cm⁻³)		1.29
萎蔫点 Soil WFPS at wilting point		0.16
孔隙度 Porosity		0.65
目标产量 Max. biomass production [kg(C)∙hm⁻²]		560.00	1660.68
成熟时生物量分配比例 Biomass fraction at harvest	果 Grain	0.65	0.36
	叶 Leaf	0.15	0.22
	茎 Stem	0.15	0.22
	根 Root	0.05	0.20
成熟时C/N比值 C/N ratio at harvest	果 Grain	12.00	26.00
	叶 Leaf	11.97	26.00
	茎 Stem	11.33	26.00
	根 Root	25.00	45.00
生长积温 Thermal degree days for maturity (℃)		1000	1400
需水量 Water demand [g(water)∙g⁻¹(DM)]		500	300

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表 3 设施菜地N₂O减排措施

Table 3. N₂O emission reduction measures of greenhouse vegetable fields

研究方法 Research method	种植时间(年-月) Period (year-month)	减排措施 Emission reduction measure	减排效果 Emission reduction effect (%)	参考文献 Reference
黄瓜-芹菜(Apium graveolens L.)田间试验 Cucumber-celery field experiment	2016-03—2016-07	滴灌、减施50%化肥 Drip irrigation, 50% chemical fertilizer reduction	35.2~57.5	[13]
黄瓜-番茄田间试验 Cucumber-tomato field experiment	2017-09—2017-12	滴灌、减施50%化肥 Drip irrigation, 50% chemical fertilizer reduction	23.5~47.2	[11]
芹菜-番茄田间试验 Celery-tomato field experiment	2009-10—2021-02	有机肥替代0%、25%、50%、75%、100%化肥 Organic fertilizer replacing 0%, 25%, 50%, 75%, 100% chemical fertilizer	66.3~85.1	[29]
番茄田间试验 Tomato field experiment	2016-09—2016-12	有机肥替代0%、50%、100%化肥 Organic fertilizer replacing 0%, 50%, 100% chemical fertilizer	45.1~33.2	[30]
室内培养 Indoor culture	—	调整pH至5.5~7.5 Adjusting pH to 5.5−7.5	42.6~70.1	[31]
室内培养 Indoor culture	—	调整pH至5.1~8.15 Adjusting pH to 5.1−8.15	18.8~42.3	[32]
Meta分析 Meta-analysis	—	土壤有机碳变化范围为6.27~24.1 g∙kg⁻¹ The variation range of soil organic carbon was 6.27− 24.1 g∙kg⁻¹	48.6%	[33]

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表 4 DNDC模型土壤基础性质及管理措施情景设置

Table 4. Soil basic properties and management measures scenarios setting in DNDC model

项目 Item	情景设置 Scenario	单位 Unit	值 Value
灌溉方式 Irrigation method	滴灌、漫灌^* Flood irrigation, drip irrigation	—	—
有机肥替代化肥比例 Proportion of organic fertilizer replacing chemical fertilizer	在基准线上有机肥替代一定比例的化肥 Organic fertilizer replacing a certain proportion of chemical fertilizer based on the baseline	—	0%^*, 25%, 50%, 75%, 100%
化肥施氮量 Chemical-N application rate	在基准线上减少10%、20%、30%施氮量或提高10% Reduce nitrogen application by 10%, 20%, 30% or increase it by 10% based on the baseline	kg(N)∙hm⁻²	1015, 1160, 1305, 1450^*, 1595
有机肥施氮量 Organic-N application rate	在基准线上减少10%、20%、30%施氮量或提高10% Reduce nitrogen application by 10%, 20%, 30% or increase it by 10% based on the baseline	kg(N)∙hm⁻²	910, 1040, 1170, 1300, 1430
酸碱度 pH	在基准线上提高或减少10%、20%土壤酸碱度 Increasing or decreasing 10%, 20% soil pH based on baseline	—	5.78, 6.46, 7.23^*, 7.90, 8.68
土壤有机碳含量 Soil organic carbon content	在基准线上提高或减少20%、40%土壤有机质含量 Increasing or decreasing 20%, 40% soil organic matter content based on baseline	g(C)∙kg⁻¹	8.6, 11.4, 14.3^*, 17.2, 20.0
代表基线情景。 represents the baseline scenario.

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表 5 基于DNDC模型的设施菜地系统N₂O排放总量敏感性指数

Table 5. Sensitive indexes of total N₂O emissions of greenhouse vegetable system based on DNDC model

输入参数 Parameter	情景设置 Scenario setting	敏感性指数 Sensitive index
灌溉方式 Irrigation method	滴灌、漫灌 Flood irrigation, drip irrigation	—
有机肥替代化肥比例 Proportion of organic fertilizer replacing chemical fertilizer	0~100%	0.466
化肥施氮量 Nitrogen application rate	1015~1595 kg(N)∙hm⁻²	0.580
pH	5.74~8.62	0.867
土壤有机碳含量 Soil organic carbon content	8.6~20.0 g(C)∙kg⁻¹	0.428

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