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Abstract ：
Abrupt air pollution accidents can endanger people's health and destroy the local ecological environment. The appropriate emergency response can minimize the harmful effects of accidents and protect people's lives and property. This paper provides an overview of the key emergency response technologies for abrupt air pollution accidents around the globe with emphasis on the major achievements that China has obtained in recent years. With decades of effort, China has made significant progress in emergency monitoring technologies and equipment, source estimation technologies, pollutant dispersion simulation technologies and others. Many effective domestic emergency monitoring instruments (e.g., portable DOAS/FT-IR systems, portable FID/PID systems, portable GC-MS systems, scanning imaging remote sensing systems, and emergency monitoring vehicles) had been developed which can meet the demands for routine emergency response activities. A monitoring layout technique combining air dispersion simulation, fuzzy comprehensive evaluation, and a post-optimality analysis was proposed to identify the optimal monitoring layout scheme under the constraints of limited monitoring resources. Multiple source estimation technologies, including the forward method and the inversion method, have been established and evaluated under various scenarios. Multi-scale dynamic pollution dispersion simulation systems with high temporal and spatial resolution were further developed. A comprehensive emergency response platform integrating database support, source estimation, monitoring schemes, fast monitoring of pollutants, pollution predictions and risk assessment was developed based on the technical idea of "source identification - model simulation - environmental monitoring" dynamic interactive feedback. It is expected that the emergency response capability for abrupt air pollution accidents will gradually improve in China. (c) 2022 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.
Keyword ：
Pollutant dispersion simulation Pollutant dispersion simulation Emergency monitoring Emergency monitoring Air pollution accidents Air pollution accidents Emergency response Emergency response Source estimation Source estimation
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| GB/T 7714 | Duan, Jun , Mao, Shushuai , Xie, Pinhua et al. Key emergency response technologies for abrupt air pollution accidents in China [J]. | JOURNAL OF ENVIRONMENTAL SCIENCES , 2023 , 123 : 235-254 . |
| MLA | Duan, Jun et al. "Key emergency response technologies for abrupt air pollution accidents in China" . | JOURNAL OF ENVIRONMENTAL SCIENCES 123 (2023) : 235-254 . |
| APA | Duan, Jun , Mao, Shushuai , Xie, Pinhua , Lang, Jianlei , Li, Ang , Tong, Jingjing et al. Key emergency response technologies for abrupt air pollution accidents in China . | JOURNAL OF ENVIRONMENTAL SCIENCES , 2023 , 123 , 235-254 . |
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Abstract ：
本发明公开了一种监测站点大气污染物本地排放贡献的量化识别方法，属于大气污染防治领域；包括：基于空气质量模型模拟得到各站点区域贡献浓度，逐时刻计算各站点区域贡献与全部站点区域贡献平均浓度的比值，即为区域贡献不均匀系数；引入区域平均和本地贡献优化变量，将区域贡献平均优化浓度与区域贡献不均匀系数相乘，得到区域贡献优化浓度表达式；以本地和区域贡献优化浓度之和与监测浓度误差最小化为目标，构建目标方程；确定本地贡献优化浓度的限制范围，联合目标方程构建优化模型；根据监测浓度与区域贡献不均匀系数，通过求解优化模型，得到站点的本地贡献优化浓度。本发明实现了站点本地贡献浓度的量化识别，为精细化污染管控提供支撑。
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| GB/T 7714 | 郎建垒 , 李孟珍 , 周颖 . 一种监测站点大气污染物本地排放贡献的量化识别方法 : CN202310935719.3[P]. | 2023-07-28 . |
| MLA | 郎建垒 et al. "一种监测站点大气污染物本地排放贡献的量化识别方法" : CN202310935719.3. | 2023-07-28 . |
| APA | 郎建垒 , 李孟珍 , 周颖 . 一种监测站点大气污染物本地排放贡献的量化识别方法 : CN202310935719.3. | 2023-07-28 . |
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Abstract ：
本发明公开了一种大气污染物排放清单的联合优化反演方法及系统，属于大气环境技术领域，方法包括：获取气象场数据，结合气象模型和空气质量模型得到气象场数值模型，并代入先验排放清单数据，模拟得到模拟贡献浓度和浓度贡献系数；根据空气质量监测数据和浓度贡献系数，以计算浓度与监测浓度误差最小为优化目标、构建优化方程；根据气象变化对污染物浓度变化的影响量化值及不同时段的波动，构建气象约束条件；构建污染物排放清单联合反演模型，求解得到污染物排放优化反演清单。通过本发明的技术方案，在用浓度进行排放量优化时，减少了气象条件对污染物浓度的影响，降低了反演优化清单的不确定性，更准确快速地实现排放清单反演。
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| GB/T 7714 | 周颖 , 李佳 , 郎建垒 et al. 一种大气污染物排放清单的联合优化反演方法及系统 : CN202310746146.X[P]. | 2023-06-25 . |
| MLA | 周颖 et al. "一种大气污染物排放清单的联合优化反演方法及系统" : CN202310746146.X. | 2023-06-25 . |
| APA | 周颖 , 李佳 , 郎建垒 , 张晔华 . 一种大气污染物排放清单的联合优化反演方法及系统 : CN202310746146.X. | 2023-06-25 . |
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Abstract ：
本发明公开一种复杂下垫面下局地尺度大气污染源强快速反算方法，属于大气污染防治与源强反算技术领域；该方法包括：对待研究区域构建CFD模型；在CFD模型的计算域范围内选取若干采样点；基于CFD模型进行仿真计算，采集不同源强情景下各个采样点的污染物浓度数据；构建源强反算模型并获取传递系数；构建传递系数响应面模型；获取监测点的污染物浓度监测数据；将监测点的污染物浓度监测数据输入到源强反算模型和传递系数响应面模型中进行源强反算。本发明充分考虑局地尺度复杂下垫面物理意义的同时对复杂的仿真模型进行统计学简化，能够更快速、有效的为污染事件的响应以及局地尺度精细化管控提供科学支撑。
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| GB/T 7714 | 郎建垒 , 王奕璇 , 周颖 . 复杂下垫面下局地尺度大气污染源强快速反算方法及系统 : CN202310903823.4[P]. | 2023-07-24 . |
| MLA | 郎建垒 et al. "复杂下垫面下局地尺度大气污染源强快速反算方法及系统" : CN202310903823.4. | 2023-07-24 . |
| APA | 郎建垒 , 王奕璇 , 周颖 . 复杂下垫面下局地尺度大气污染源强快速反算方法及系统 : CN202310903823.4. | 2023-07-24 . |
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Abstract ：
本发明公开了一种基于站点浓度差异的本外地排放贡献估算方法，属于大气污染防治技术领域；包括：基于城市监测站点各污染物浓度数据，逐时刻分别计算不同污染物的站点间浓度差异(变异系数CVc)和站点浓度平均值；将逐时刻浓度平均值进行区间划分；基于气象和空气质量模型，模拟得到逐时刻的外地排放贡献率；计算不同浓度区间对应的CVc和外地排放贡献率平均值；对外地排放贡献率和CVc均值进行数学拟合，得到外地排放贡献估算模型；基于该模型，快速估算本/外地排放对大气污染物的浓度贡献。本发明基于站点间浓度差异建立外地排放贡献估算模型，可基于环境监测浓度数据快速估算城市本/外地排放贡献，为城市污染管控提供支撑。
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| GB/T 7714 | 郎建垒 , 杨欣欣 , 周颖 . 一种基于站点浓度差异的本外地排放贡献估算方法 : CN202310658278.7[P]. | 2023-06-06 . |
| MLA | 郎建垒 et al. "一种基于站点浓度差异的本外地排放贡献估算方法" : CN202310658278.7. | 2023-06-06 . |
| APA | 郎建垒 , 杨欣欣 , 周颖 . 一种基于站点浓度差异的本外地排放贡献估算方法 : CN202310658278.7. | 2023-06-06 . |
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Abstract ：
本发明提供一种大气污染协同控制区域、时间识别方法，涉及大气污染防控技术领域，包括：模拟研究区域的气象条件、获取大气污染物多尺度排放数据，构建研究区域各污染源间的高时间分辨率大气污染物传输矩阵；计算各污染源对目标区域重污染过程每个时刻的贡献度；应用模糊C均值聚类得到每个时刻需要协同控制的污染源；计算各污染源对目标区域重污染过程的总贡献度和控制频率；应用系统聚类识别出重污染过程需协同控制的污染源；分别计算需协同控制的污染源每个时刻的大气污染物排放对重污染过程的总贡献浓度；应用K均值聚类得到重污染过程中各污染源启动和解除大气污染协同控制的时间。本发明将污染物排放控制的时间尺度精细化到小时。
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| GB/T 7714 | 郎建垒 , 李凯 , 周颖 et al. 一种大气污染协同控制区域、时间识别方法 : CN202310186701.8[P]. | 2023-03-02 . |
| MLA | 郎建垒 et al. "一种大气污染协同控制区域、时间识别方法" : CN202310186701.8. | 2023-03-02 . |
| APA | 郎建垒 , 李凯 , 周颖 , 梁晓玉 , 玄博元 . 一种大气污染协同控制区域、时间识别方法 : CN202310186701.8. | 2023-03-02 . |
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Abstract ：
本发明公开了一种基于大气污染浓度变化率的突出值站点识别方法，属于大气污染防治技术领域；包括：基于各站点长时间序列历史浓度数据，计算逐时刻的站点浓度平均值；基于逐时刻平均值，依据各污染物浓度标准，划分逐时刻污染等级；逐站点计算研究时刻相较上一时刻的浓度变化率；将逐时刻的浓度变化率与划分的逐时刻污染等级相匹配，得到不同污染等级的时刻变化率数组，分别绘制概率分布图；依据概率分布图，分别确定变化率上限值，作为不同污染等级的突出值识别标准，即：标准变化率限值；基于标准限值，实时动态识别突出值站点与时刻。本发明基于浓度变化率实时动态识别需要重点管控的站点和管控时刻，可为面向监测站点的污染精细化管控提供技术支撑。
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| GB/T 7714 | 郎建垒 , 杨欣欣 , 周颖 . 一种基于大气污染浓度变化率的突出值站点识别方法 : CN202310506028.1[P]. | 2023-05-08 . |
| MLA | 郎建垒 et al. "一种基于大气污染浓度变化率的突出值站点识别方法" : CN202310506028.1. | 2023-05-08 . |
| APA | 郎建垒 , 杨欣欣 , 周颖 . 一种基于大气污染浓度变化率的突出值站点识别方法 : CN202310506028.1. | 2023-05-08 . |
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Abstract ：
本发明公开一种监测站点风速和风向协同时序预测方法，属于大气污染气象要素预测技术领域；该方法包括：获取目标站点的气象数据，对风速数据和风向数据进行分解；通过风向数据将气压梯度力分解；利用压强正弦分量Pu、压强余弦分量Pv和气象数据与经向风分量u和纬向风分量v的关联程度筛选关键影响因子；分别构建u、v分量与关键影响因子之间的关系模型；根据关系模型进行预测；对u、v分量的预测结果进行合成。本发明还提供一种监测站点风速和风向协同时序预测系统。本发明通过分别构建基于关键影响因子的u、v分量时序预测模型，实现了对风速、风向准确预测，可为面向监测站点的大气污染气象条件分析与精细化防控奠定基础。
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| GB/T 7714 | 郎建垒 , 严允序 , 玄博元 et al. 一种监测站点风速和风向协同时序预测方法及系统 : CN202310935610.X[P]. | 2023-07-28 . |
| MLA | 郎建垒 et al. "一种监测站点风速和风向协同时序预测方法及系统" : CN202310935610.X. | 2023-07-28 . |
| APA | 郎建垒 , 严允序 , 玄博元 , 周颖 . 一种监测站点风速和风向协同时序预测方法及系统 : CN202310935610.X. | 2023-07-28 . |
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Abstract ：
Air pollution has become a great challenge to achieving sustainable development. Among the pollutants, aerosols significantly affect human health and play an important role in global climate change. The concentration of aerosols in the ambient air is influenced strongly by the regional transport of pollutants and their precursors and may vary considerably under different meteorological conditions in different years. This inter-annual variation in meteorology may yield conflicting results in the quantification of the contribution from regional transport of air pollutants. It creates uncertainty for local governments to develop pollution control measures to reduce the challenges to sustainable development. Previous studies on this issue are often year-specific or cover short time spans, and the inter-city transport of air pollutants in the long term is still not fully understood. Therefore, in this study, the Weather Research and Forecasting (WRF) model and Community Multiscale Air Quality (CMAQ) model was used to assess inter-annual variations in the contribution of inter-city transport to the PM2.5 concentration in the Beijing-Tianjin-Hebei region from 2010 to 2019. To highlight the impact of inter-annual variations in meteorology, the authors used the same emission inventory and the same model configurations for the 10-year simulation. The major findings can be summarized as follows: (1) Both PM2.5 concentration and inter-city transport in the Beijing-Tianjin-Hebei (BTH) region were influenced by the inter-annual variation in meteorological conditions. (2) The simulated annual average concentrations in 13 cities in BTH are highly variable, with fluctuations ranging from 30.8% to 54.1%, and more evident variations were found in seasonal results. (3) Seven out of thirteen cities have a contribution from regional transport exceeding 50%, which are located in the eastern half of the Beijing-Tianjin-Hebei region. (4) The magnitude of the regional transport contribution varies significantly among the cities of BTH, on an annual basis, from a minimum inter-annual fluctuation of 8.9% to a maximum of 37.2%, and seasonal fluctuation is even more strongly evident. These results indicate that, when formulating pollution control strategies, inter-annual changes in meteorological conditions should not be ignored.
Keyword ：
WRF WRF regional air pollution regional air pollution CMAQ CMAQ inter-annual meteorological variation inter-annual meteorological variation inter-city transport inter-city transport
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| GB/T 7714 | Chen, Dongsheng , Jin, Xin , Fu, Xinyi et al. Impact of Inter-Annual Variation in Meteorology from 2010 to 2019 on the Inter-City Transport of PM2.5 in the Beijing-Tianjin-Hebei Region [J]. | SUSTAINABILITY , 2022 , 14 (10) . |
| MLA | Chen, Dongsheng et al. "Impact of Inter-Annual Variation in Meteorology from 2010 to 2019 on the Inter-City Transport of PM2.5 in the Beijing-Tianjin-Hebei Region" . | SUSTAINABILITY 14 . 10 (2022) . |
| APA | Chen, Dongsheng , Jin, Xin , Fu, Xinyi , Xia, Lin , Guo, Xiurui , Lang, Jianlei et al. Impact of Inter-Annual Variation in Meteorology from 2010 to 2019 on the Inter-City Transport of PM2.5 in the Beijing-Tianjin-Hebei Region . | SUSTAINABILITY , 2022 , 14 (10) . |
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Abstract ：
Accurate simulation of pollution diffusion under uneven terrain with complicated obstacles is a difficult but important scientific and technological issue. The inlet-boundary was important and single boundary meteorological factors (e.g., wind direction and speed) input were generally employed for the Computational Fluid Dynamics (CFD) simulation. However, for uneven terrain with complicated obstacles, the boundary meteorological condition may be quite different, single boundary input may bring large simulation uncertainty. Consequently, the impact of different inlet boundary number and locations on CFD simulation was investigated based on a scarce tracer-gas field experiment carried out in a chemical industrial park located in a mountainous area. The experimental results implied gas diffusion was influenced by a combination of meteorological conditions from multi-inlet boundaries. The simulation results confirmed that and indicated commonly-used single-inlet boundary input can bring great inaccuracies. The case of inlet boundaries closed to emission sources and intersected the crosswind plane agreed best with measurements. It was also found that the inlet boundary number and locations significantly influence velocity and turbulence. Finally, a guideline for determining the inlet boundaries was proposed. This study can enhance the understanding on CFD simulation, and is beneficial for the selection of inlet meteorological sites to precise prediction.
Keyword ：
Gas diffusion and flow Gas diffusion and flow Small scale Small scale Field experiment Field experiment Inlet boundary conditions Inlet boundary conditions Complex environment Complex environment
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| GB/T 7714 | Shen, Zeya , Lang, Jianlei , Li, Mengzhen et al. Impact of inlet boundary number and locations on gas diffusion and flow in a typical chemical industrial park near uneven terrain [J]. | PROCESS SAFETY AND ENVIRONMENTAL PROTECTION , 2022 , 159 : 281-293 . |
| MLA | Shen, Zeya et al. "Impact of inlet boundary number and locations on gas diffusion and flow in a typical chemical industrial park near uneven terrain" . | PROCESS SAFETY AND ENVIRONMENTAL PROTECTION 159 (2022) : 281-293 . |
| APA | Shen, Zeya , Lang, Jianlei , Li, Mengzhen , Mao, Shushuai , Hu, Feng , Xuan, Boyuan . Impact of inlet boundary number and locations on gas diffusion and flow in a typical chemical industrial park near uneven terrain . | PROCESS SAFETY AND ENVIRONMENTAL PROTECTION , 2022 , 159 , 281-293 . |
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