Role of Dust and Iron Solubility in Sulfate Formation during the Long-Range Transport in East Asia Evidenced by 17O-Excess Signatures

硫酸盐 CMAQ 环境化学 化学 东亚 溶解度 环境科学 空气质量指数 二氧化硫 硫黄 污染 大气科学 臭氧 气象学 中国 地质学 无机化学 物理 有机化学 法学 生物 生态学 政治学
作者
Syuichi Itahashi,Shohei Hattori,Akinori Ito,Yasuhiro Sadanaga,Naohiro Yoshida,Atsushi Matsuki
出处
期刊:Environmental Science & Technology [American Chemical Society]
卷期号:56 (19): 13634-13643 被引量:15
标识
DOI:10.1021/acs.est.2c03574
摘要

Numerical models have been developed to elucidate air pollution caused by sulfate aerosols (SO42-). However, typical models generally underestimate SO42-, and oxidation processes have not been validated. This study improves the modeling of SO42- formation processes using the mass-independent oxygen isotopic composition [17O-excess; Δ17O(SO42-)], which reflects pathways from sulfur dioxide (SO2) to SO42-, at the background site in Japan throughout 2015. The standard setting in the Community Multiscale Air Quality (CMAQ) model captured SO42- concentration, whereas Δ17O(SO42-) was underestimated, suggesting that oxidation processes were not correctly represented. The dust inline calculation improved Δ17O(SO42-) because dust-derived increases in cloud-water pH promoted acidity-driven SO42- production, but Δ17O(SO42-) was still overestimated during winter as a result. Increasing solubilities of the transition-metal ions, such as iron, which are a highly uncertain modeling parameter, decreased the overestimated Δ17O(SO42-) in winter. Thus, dust and high metal solubility are essential factors for SO42- formation in the region downstream of China. It was estimated that the remaining mismatch of Δ17O(SO42-) between the observation and model can be explained by the proposed SO42- formation mechanisms in Chinese pollution. These accurately modeled SO42- formation mechanisms validated by Δ17O(SO42-) will contribute to emission regulation strategies required for better air quality and precise climate change predictions over East Asia.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研通AI6.3应助新野采纳,获得10
2秒前
直率的熊猫完成签到 ,获得积分10
2秒前
香蕉静芙发布了新的文献求助20
2秒前
Glufo发布了新的文献求助10
2秒前
谦让夜香完成签到,获得积分10
2秒前
藿藿发布了新的文献求助10
2秒前
邵竺发布了新的文献求助10
3秒前
3秒前
huihui发布了新的文献求助10
3秒前
小小牛马发布了新的文献求助10
3秒前
4秒前
JamesPei应助木雨超采纳,获得10
5秒前
5秒前
一般通过飞鸽完成签到,获得积分20
5秒前
飞燕完成签到,获得积分10
6秒前
6秒前
green发布了新的文献求助30
7秒前
传奇3应助cp采纳,获得10
8秒前
8秒前
9秒前
落寞向珊完成签到,获得积分10
9秒前
油菜籽发布了新的文献求助10
10秒前
隐形曼青应助organicboy采纳,获得10
10秒前
许123发布了新的文献求助10
10秒前
英俊的铭应助Scorpia112采纳,获得10
11秒前
左右发布了新的文献求助10
11秒前
蓝天发布了新的文献求助10
11秒前
11秒前
勤劳发布了新的文献求助10
13秒前
丘比特应助星姽采纳,获得10
13秒前
CodeCraft应助00采纳,获得10
13秒前
14秒前
green完成签到,获得积分10
15秒前
177发布了新的文献求助10
15秒前
夏鱼完成签到,获得积分10
16秒前
16秒前
17秒前
17秒前
17秒前
himat完成签到,获得积分10
17秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Arthritis and Related Conditions, An Issue of Orthopedic Clinics 1000
Development of a Bridge Weigh-In-Motion System: A technology to convert the bridge response to the passage of traffic into data on vehicle configurations, speeds, times of travel and weights 1000
ズームレンズの光学設計に関する研究 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7293004
求助须知:如何正确求助?哪些是违规求助? 8911808
关于积分的说明 18866192
捐赠科研通 6959826
什么是DOI,文献DOI怎么找? 3209680
关于科研通互助平台的介绍 2379200
邀请新用户注册赠送积分活动 2185713