• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

利用 OMI 数据的自适应 nudging 方法约束京津冀地区供暖引起的 SO 和 NO 排放的时空变化。

Spatio-temporal variations in SO and NO emissions caused by heating over the Beijing-Tianjin-Hebei Region constrained by an adaptive nudging method with OMI data.

机构信息

Hebei Provincial Environmental Meteorological Center, Shijiazhuang 050021, China.

State Key Lab of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China.

出版信息

Sci Total Environ. 2018 Nov 15;642:543-552. doi: 10.1016/j.scitotenv.2018.06.021. Epub 2018 Jun 14.

DOI:10.1016/j.scitotenv.2018.06.021
PMID:29909321
Abstract

The Beijing-Tianjin-Hebei (BTH) region in China suffers from heavy air pollution, especially in heating period. SO and NO are two of the key primary gaseous pollutants emitted by coal burning. The increase in air pollution caused by heating in the south-central part of the BTH region is higher than that in the northern part. And the distribution of SO and NO increment has significant differences. In this work, SO and NO emissions over the BTH region are determined using an adaptive "nudging" constrained method and a variational processing technique based on Ozone Monitoring Instrument (OMI) satellite data and surface measurement data collected in 2015. The application of the method can provide reliable, up-to-date and high-resolution mapping of sources of SO and NO emissions. These SO and NO emissions reflect the spatial differences in point and area sources in urban agglomerations and rural areas under different meteorological conditions during the non-heating and heating seasons. The intensity and influence of SO and NO emissions, particularly those of SO, are significantly greater during the heating season than those during the non-heating season. Winter increases in SO emissions in the northern areas of the BTH region are larger than those in the southern part. In addition, significant increases in SO emissions occur mainly in suburban and rural areas, while those of NO emissions mainly occur in urban agglomerations. In the major urban areas, where coal has been replaced by natural gas or electric power for heating, winter heating causes much smaller increases in SO emissions than in other areas. The large amounts of bulk coal consumption in the suburban and rural areas could cause significant regional air pollution. Clear increases in SO and NO emissions in winter occur along a belt from southern Beijing to Langfang, Baoding, Shijiazhuang and Xingtai, which is consistent with a special "quasi-steady" air pollutant transport belt in the region. All above results show that the adaptive "nudging" constrained emission method could be an effective tool for air pollution control during certain seasons.

摘要

中国京津冀地区遭受严重的空气污染,特别是在供暖期。二氧化硫(SO)和氮氧化物(NO)是燃煤排放的两种主要气态污染物。京津冀地区中南部地区因供暖导致的空气污染增加量高于北部地区。而且 SO 和 NO 增加量的分布存在显著差异。在这项工作中,采用自适应“推斥”约束方法和基于臭氧监测仪(OMI)卫星数据和 2015 年收集的地面测量数据的变分处理技术,确定了京津冀地区的 SO 和 NO 排放。该方法的应用可以提供可靠、最新和高分辨率的 SO 和 NO 排放源地图。这些 SO 和 NO 排放反映了不同气象条件下非供暖季和供暖季城市群和农村地区点源和面源的空间差异。SO 和 NO 排放的强度和影响,尤其是 SO 的强度和影响,在供暖季明显大于非供暖季。京津冀北部地区冬季 SO 排放量的增加大于南部地区。此外,SO 排放量的显著增加主要发生在郊区和农村地区,而 NO 排放量的增加主要发生在城市群。在主要城市地区,由于冬季采用天然气或电力代替煤炭供暖,SO 排放量的增加幅度远小于其他地区。郊区和农村地区大量散煤的消耗可能导致显著的区域性空气污染。从南部的北京到廊坊、保定、石家庄和邢台,冬季 SO 和 NO 排放量明显增加,这与该地区特殊的“准稳定”污染物输送带一致。所有上述结果表明,自适应“推斥”约束排放方法可能是特定季节空气污染控制的有效工具。

相似文献

1
Spatio-temporal variations in SO and NO emissions caused by heating over the Beijing-Tianjin-Hebei Region constrained by an adaptive nudging method with OMI data.利用 OMI 数据的自适应 nudging 方法约束京津冀地区供暖引起的 SO 和 NO 排放的时空变化。
Sci Total Environ. 2018 Nov 15;642:543-552. doi: 10.1016/j.scitotenv.2018.06.021. Epub 2018 Jun 14.
2
Long-term (2006-2015) variations and relations of multiple atmospheric pollutants based on multi-remote sensing data over the North China Plain.基于多遥感数据的华北平原多种大气污染物的长期(2006-2015 年)变化及其关系。
Environ Pollut. 2019 Dec;255(Pt 3):113323. doi: 10.1016/j.envpol.2019.113323. Epub 2019 Oct 4.
3
Spatial and temporal variation characteristics of atmospheric NO and SO in the Beijing-Tianjin-Hebei region before and after the COVID-19 outbreak.新冠疫情爆发前后京津冀地区大气中一氧化氮和二氧化硫的时空变化特征
Air Qual Atmos Health. 2021;14(8):1175-1188. doi: 10.1007/s11869-021-01016-8. Epub 2021 Apr 2.
4
Effects of short-term exposure to air pollution on hospital admissions of young children for acute lower respiratory infections in Ho Chi Minh City, Vietnam.越南胡志明市短期暴露于空气污染对幼儿急性下呼吸道感染住院率的影响。
Res Rep Health Eff Inst. 2012 Jun(169):5-72; discussion 73-83.
5
Village energy survey reveals missing rural raw coal in northern China: Significance in science and policy.村庄能源调查揭示中国北方农村原煤缺失:科学与政策意义。
Environ Pollut. 2017 Apr;223:705-712. doi: 10.1016/j.envpol.2017.02.009. Epub 2017 Feb 10.
6
Air pollution episodes during the COVID-19 outbreak in the Beijing-Tianjin-Hebei region of China: An insight into the transport pathways and source distribution.中国京津冀地区新冠疫情期间的空气污染事件:对传输路径和源分布的洞察
Environ Pollut. 2020 Dec;267:115617. doi: 10.1016/j.envpol.2020.115617. Epub 2020 Sep 8.
7
[Characteristics of Two Pollution Episodes Before and After City Heating in Beijing from February to March of 2019].[2019年2月至3月北京城市供暖前后两次污染过程的特征]
Huan Jing Ke Xue. 2021 May 8;42(5):2110-2120. doi: 10.13227/j.hjkx.202008181.
8
Spatio-temporal evolution of ozone pollution and its influencing factors in the Beijing-Tianjin-Hebei Urban Agglomeration.京津冀城市群臭氧污染的时空演变及其影响因素。
Environ Pollut. 2020 Jan;256:113419. doi: 10.1016/j.envpol.2019.113419. Epub 2019 Oct 23.
9
Study on clean heating based on air pollution and energy consumption.基于空气污染和能耗的清洁供暖研究。
Environ Sci Pollut Res Int. 2020 Feb;27(6):6549-6559. doi: 10.1007/s11356-019-07093-8. Epub 2019 Dec 24.
10
Air pollutant emissions from Chinese households: A major and underappreciated ambient pollution source.中国家庭的空气污染物排放:一个主要且未得到充分认识的环境污染源。
Proc Natl Acad Sci U S A. 2016 Jul 12;113(28):7756-61. doi: 10.1073/pnas.1604537113. Epub 2016 Jun 27.

引用本文的文献

1
A data-driven supervised machine learning approach to estimating global ambient air pollution concentrations with associated prediction intervals.一种基于数据驱动的监督式机器学习方法,用于估计全球环境空气污染浓度及相关预测区间。
R Soc Open Sci. 2025 Jul 23;12(7):241288. doi: 10.1098/rsos.241288. eCollection 2025 Jul.
2
Evaluation of NOx emissions before, during, and after the COVID-19 lockdowns in China: A comparison of meteorological normalization methods.中国新冠疫情封锁期间及前后氮氧化物排放评估:气象归一化方法比较
Atmos Environ (1994). 2022 Jun 1;278:119083. doi: 10.1016/j.atmosenv.2022.119083. Epub 2022 Mar 25.
3
Study on clean heating based on air pollution and energy consumption.
基于空气污染和能耗的清洁供暖研究。
Environ Sci Pollut Res Int. 2020 Feb;27(6):6549-6559. doi: 10.1007/s11356-019-07093-8. Epub 2019 Dec 24.
4
Valuing urban air quality: a hedonic price analysis in Beijing, China.重视城市空气质量:中国北京的基于效用的价格分析。
Environ Sci Pollut Res Int. 2020 Jan;27(2):1373-1385. doi: 10.1007/s11356-019-06874-5. Epub 2019 Nov 20.
5
Comparison of air pollutant-related hospitalization burden from AECOPD in Shijiazhuang, China, between heating and non-heating season.比较中国石家庄在供暖季和非供暖季因 AECOPD 导致的与空气污染物相关的住院负担。
Environ Sci Pollut Res Int. 2019 Oct;26(30):31225-31233. doi: 10.1007/s11356-019-06242-3. Epub 2019 Aug 28.
6
The effect and burden modification of heating on adult asthma hospitalizations in Shijiazhuang: a time-series analysis.石家庄市成人哮喘住院的加热效应和负担改变:时间序列分析。
Respir Res. 2019 Jun 14;20(1):122. doi: 10.1186/s12931-019-1092-0.