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Black Plastic Film Mulching Increases Soil Nitrous Oxide Emissions in Arid Potato Fields

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  • Chaobiao Meng

    (Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
    Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China)

  • Jianyu Zhao

    (Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China)

  • Ning Wang

    (Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China)

  • Kaijing Yang

    (China Institute of Water Resources and Hydropower Research, Beijing 100048, China)

  • Fengxin Wang

    (Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China)

Abstract

Black plastic film mulching is a common practice for potato production in the arid area of Northwest China. Many studies have reported the significant positive effect of black plastic film mulch on potato harvest, while the effect of black plastic film mulch treatment on soil nitrous oxide (N 2 O) emissions is still unclear. As a consequence, this study aimed to examine the effect of black plastic film mulch treatment on N 2 O emission from arid upland potato fields. With the static chamber-gas chromatography method, soil N 2 O emissions were measured. The results showed that black plastic film mulching treatment significantly increased cumulative soil N 2 O emissions by 21–26% compared with non-mulched treatment. Cumulative N 2 O emission positively correlated with soil temperature, soil moisture, soil CO 2 concentration, and amoA - AOB abundance. This study indicated that black plastic film mulching, mainly through increasing soil temperature and soil moisture, increasing soil carbon dioxide (CO 2 ) concentration, and promoting the abundance of nitrification-related functional gene of amoA - AOB , regulated N 2 O emissions. This study also highlighted that the specific soil environment under black plastic film mulch is conducive to N 2 O emissions and lay the foundation for settling the contradiction between food production and greenhouse gas mitigation in upland soils. The negative effects of black plastic film mulching on the environment should be considered in future applications in food production.

Suggested Citation

  • Chaobiao Meng & Jianyu Zhao & Ning Wang & Kaijing Yang & Fengxin Wang, 2022. "Black Plastic Film Mulching Increases Soil Nitrous Oxide Emissions in Arid Potato Fields," IJERPH, MDPI, vol. 19(23), pages 1-12, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:16030-:d:989421
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    References listed on IDEAS

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    1. Ma, Dedi & Chen, Lei & Qu, Hongchao & Wang, Yilin & Misselbrook, Tom & Jiang, Rui, 2018. "Impacts of plastic film mulching on crop yields, soil water, nitrate, and organic carbon in Northwestern China: A meta-analysis," Agricultural Water Management, Elsevier, vol. 202(C), pages 166-173.
    2. Dave S. Reay & Eric A. Davidson & Keith A. Smith & Pete Smith & Jerry M. Melillo & Frank Dentener & Paul J. Crutzen, 2012. "Global agriculture and nitrous oxide emissions," Nature Climate Change, Nature, vol. 2(6), pages 410-416, June.
    3. Ding, Dianyuan & Zhao, Ying & Feng, Hao & Hill, Robert Lee & Chu, Xiaosheng & Zhang, Tibin & He, Jianqiang, 2018. "Soil water utilization with plastic mulching for a winter wheat-summer maize rotation system on the Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 201(C), pages 246-257.
    4. Zhao, Ying & Zhai, Xiafei & Wang, Zhaohui & Li, Huijie & Jiang, Rui & Lee Hill, Robert & Si, Bing & Hao, Feng, 2018. "Simulation of soil water and heat flow in ridge cultivation with plastic film mulching system on the Chinese Loess Plateau," Agricultural Water Management, Elsevier, vol. 202(C), pages 99-112.
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    Cited by:

    1. Chenglin Wang & Qiyu Han & Chunjiang Li & Jianian Li & Dandan Kong & Faan Wang & Xiangjun Zou, 2024. "Assisting the Planning of Harvesting Plans for Large Strawberry Fields through Image-Processing Method Based on Deep Learning," Agriculture, MDPI, vol. 14(4), pages 1-22, April.

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