Preprints
https://doi.org/10.5194/acp-2022-739
https://doi.org/10.5194/acp-2022-739
 
10 Nov 2022
10 Nov 2022
Status: this preprint is currently under review for the journal ACP.

Impacts of land cover changes on biogenic emission and its contribution to ozone and secondary organic aerosol in China

Jinlong Ma1, Shengqiang Zhu1, Siyu Wang1, Peng Wang2,3,4, Jianmin Chen1, and Hongliang Zhang1,4,5 Jinlong Ma et al.
  • 1Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Fudan University, Shanghai, China
  • 2Department of Atmospheric and Oceanic Science, Fudan University, Shanghai 200438, China
  • 3Shanghai Frontiers Science Center of Atmosphere—Ocean Interaction, Fudan University, Shanghai 200438, China
  • 4IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
  • 5Institute of Eco-Chongming (IEC), Shanghai 200062, China

Abstract. The greening impacts in China led to an increase in natural emissions, which may further aggravate the local burden of secondary organic aerosol and ozone. Thus, a robust natural emissions inventory is crucial for assessing the contribution of biogenic volatile organic compounds (BVOCs) to air quality. However, using different satellites will introduce uncertainties in BVOC estimations. Quantitative analysis is needed for evaluating the accuracy of BVOC estimations and their impacts on air quality. In this study, Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1 was used to investigate the impact of different LAI and LC datasets on BVOC emissions in China in 2016 and impacts on O3 and SOA were evaluated based on the Community Multiscale Air Quality Modelling System (CMAQ). Three LAI satellite datasets of the Global LAnd Surface Satellite (GLASS), the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD15A2H version 6 (MOD15), and the Copernicus Global Land Service (CGLS), as well as three LC satellite datasets of the MODIS MCD12Q1 LC products, the Copernicus Climate Change Service (C3S) LC products, and the CGLS LC products were used in five parallel experiments (cases: C1-C5). Results show that BVOC emissions in China range from 25.42 to 37.39 Tg in 2016 and are mainly concentrated in central and south-eastern China, with the highest in C5 (using GLASS and CGLS LC) and the least in C4 (using GLASS and C3S LC). According to model validations, C4 is the better choice for estimating BVOC emissions in China compared to other scenarios. In addition, the use of different LAI and LC inputs has a further impact on the concentrations of O3 and SOA, especially in central and eastern China, where the differences are up to 4.8–6.9 ppb and 5.3–8.4 μg m-3 in O3 and biogenic SOA (BSOA), respectively. Due to the summer monsoon, a large amount of O3 is also transported from southern China to the Yangtze River Delta (YRD) and North China Plain (NCP), resulting in a large difference in O3 concentrations between different cases. For example, the O3 in C1 (using GLASS and MCD12Q1) is 3.6 ppb higher than in C4 in the YRD. Furthermore, isoprene contributes most to BSOA concentrations in China, which is 1-fold higher than monoterpenes and 1.5-fold higher than sesquiterpenes. The BSOA formed by isoprene is the main reason resulting in the difference between C1 and C5.

Jinlong Ma et al.

Status: open (until 22 Dec 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-739', Anonymous Referee #1, 05 Dec 2022 reply

Jinlong Ma et al.

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Short summary
An updated version of the CMAQ model with BVOC emissions from MEGAN was applied to study the impacts of different land cover inputs on O3 and SOA in China. The estimated BVOCs emissions ranged from 25.42 to 37.39 Tg using different LAI and LC inputs. Those differences further induced differences of 4.8–6.9 ppb in O3 concentrations and differences of 5.3–8.4 μg m-3 in SOA concentrations in central China.
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