Data-Driven Estimates of High-Resolution Soil HONO Emissions in China from 2000 to 2020

Soil nitrous acid (HONO) emissions influence air quality by affecting atmospheric oxidizing capacity and secondary pollutant formation. However, estimating soil HONO emissions remains uncertain due to complex factors and limited data. Here, we present the first high-resolution soil HONO emissions in China from 2000 to 2020 by establishing a parametrization scheme that links emissions to soil moisture, soil temperature, and fertilization. Particularly, a data-driven model is constructed to capture the dynamic response of soil HONO emissions to soil moisture. The estimated soil HONO emissions in China for 2020 amount to 0.477 Tg N, with approximately 76% from croplands, 19% from forests, and 5% from grasslands. The spatial distribution of soil HONO emissions is notably influenced by soil moisture, with Xinjiang displaying the highest emission intensity among major agricultural regions due to its lower soil moisture. Over the past two decades, soil moisture has played a significant role in variations of soil HONO emissions, exhibiting strong irregular interannual fluctuations. Soil temperature-driven emissions have shown an increasing trend, while fertilizer-driven emissions have displayed a decreasing trend since reaching a peak in 2015. Our research supports improved prediction and mitigation of soil HONO emissions under global climate change and agricultural sustainable development.

Authors

Institutions

Publication Details

Journal
Environmental Science & Technology
Published
2025-06-16
DOI
https://doi.org/10.1021/acs.est.5c03899
Citations
1
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
1.11

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Data-Driven Estimates of High-Resolution Soil HONO Emissions in China from 2000 to 2020

Xiao Fu, Dianming Wu, Chuang Qin, Bokui Chen et al.
1 citations
Environmental Science & Technology
Atmospheric and Environmental Gas Dynamics
1.11
article

Data-Driven Estimates of High-Resolution Soil HONO Emissions in China from 2000 to 2020

Xiao Fu, Dianming Wu, Chuang Qin, Bokui Chen, Jie Li, Jing Chen, Z. Q. Yin, Xianyi Sun
article en
1 citations

Abstract

Soil nitrous acid (HONO) emissions influence air quality by affecting atmospheric oxidizing capacity and secondary pollutant formation. However, estimating soil HONO emissions remains uncertain due to complex factors and limited data. Here, we present the first high-resolution soil HONO emissions in China from 2000 to 2020 by establishing a parametrization scheme that links emissions to soil moisture, soil temperature, and fertilization. Particularly, a data-driven model is constructed to capture the dynamic response of soil HONO emissions to soil moisture. The estimated soil HONO emissions in China for 2020 amount to 0.477 Tg N, with approximately 76% from croplands, 19% from forests, and 5% from grasslands. The spatial distribution of soil HONO emissions is notably influenced by soil moisture, with Xinjiang displaying the highest emission intensity among major agricultural regions due to its lower soil moisture. Over the past two decades, soil moisture has played a significant role in variations of soil HONO emissions, exhibiting strong irregular interannual fluctuations. Soil temperature-driven emissions have shown an increasing trend, while fertilizer-driven emissions have displayed a decreasing trend since reaching a peak in 2015. Our research supports improved prediction and mitigation of soil HONO emissions under global climate change and agricultural sustainable development.

Environmental Science & TechnologyVol. 59(27)
East China Normal University (CN), Tsinghua University (CN)
National Natural Science Foundation of China, Science, Technology and Innovation Commission of Shenzhen Municipality, National Key Research and Development Program of China, Tsinghua Shenzhen International Graduate School
Climate action
Openalex Percentile: Top 23%
Atmospheric and Environmental Gas Dynamics
1.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.