Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77004, USA.
Environ Pollut. 2022 Aug 1;306:119419. doi: 10.1016/j.envpol.2022.119419. Epub 2022 May 5.
Vegetation plays an important role as both a sink of air pollutants via dry deposition and a source of biogenic VOC (BVOC) emissions which often provide the precursors of air pollutants. To identify the vegetation-driven offset between the deposition and formation of air pollutants, this study examines the responses of ozone and PM concentrations to changes in the leaf area index (LAI) over East Asia and its neighboring seas, using up-to-date satellite-derived LAI and green vegetation fraction (GVF) products. Two LAI scenarios that examine (1) table-prescribed LAI and GVF from 1992 to 1993 AVHRR and 2001 MODIS products and (2) reprocessed 2019 MODIS LAI and 2019 VIIRS GVF products were used in WRF-CMAQ modeling to simulate ozone and PM concentrations for June 2019. The use of up-to-date LAI and GVF products resulted in monthly mean LAI differences ranging from -56.20% to 96.81% over the study domain. The increase in LAI resulted in the differences in hourly mean ozone and PM concentrations over inland areas ranging from 0.27 ppbV to -7.17 ppbV and 0.89 μg/m to -2.65 μg/m, and the differences of those over the adjacent sea surface ranging from 0.69 ppbV to -2.86 ppbV and 3.41 μg/m to -7.47 μg/m. The decreases in inland ozone and PM concentrations were mainly the results of dry deposition accelerated by increases in LAI, which outweighed the ozone and PM formations via BVOC-driven chemistry. Some inland regions showed further decreases in PM concentrations due to reduced reactions of PM precursors with hydroxyl radicals depleted by BVOCs. The reductions in sea surface ozone and PM concentrations were accompanied by the reductions in those in upwind inland regions, which led to less ozone and PM inflows. The results suggest the importance of the selective use of vegetation parameters for air quality modeling.
植被通过干沉降吸收空气污染物,并排放生物挥发性有机化合物(BVOC),这些化合物通常是空气污染物的前体,因此在空气污染物的形成和沉积过程中起着重要作用。为了确定植被对空气污染物沉降和形成的抵消作用,本研究利用最新的卫星衍生叶面积指数(LAI)和绿色植被分数(GVF)产品,考察了东亚及其邻近海域臭氧和 PM 浓度对叶面积指数变化的响应。研究中使用了两种 LAI 情景,分别是:(1)1992 年至 1993 年 AVHRR 和 2001 年 MODIS 产品中的表定 LAI 和 GVF;(2)重新处理的 2019 年 MODIS LAI 和 2019 年 VIIRS GVF 产品。WRF-CMAQ 模式使用这些数据来模拟 2019 年 6 月的臭氧和 PM 浓度。使用最新的 LAI 和 GVF 产品导致研究区域内的月平均 LAI 差异范围为-56.20%至 96.81%。LAI 的增加导致内陆地区每小时平均臭氧和 PM 浓度的差异范围分别为 0.27 ppbV 至-7.17 ppbV 和 0.89μg/m 至-2.65μg/m,以及邻近海面的差异范围分别为 0.69 ppbV 至-2.86 ppbV 和 3.41μg/m 至-7.47μg/m。内陆臭氧和 PM 浓度的降低主要是由于 LAI 的增加导致的干沉降加速,这超过了 BVOC 驱动化学导致的臭氧和 PM 形成。一些内陆地区由于 BVOC 消耗了羟基自由基,导致 PM 前体的反应减少,因此 PM 浓度进一步降低。海面臭氧和 PM 浓度的降低伴随着上风内陆地区臭氧和 PM 浓度的降低,从而减少了臭氧和 PM 的流入。研究结果表明,在空气质量模型中选择性使用植被参数的重要性。