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学者姓名：郎建垒
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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 ：
Accurate identification of source information (i.e., source strength and location) is crucial for the air pollution control or effective accidental response. Optimization inversion based on bio-inspired algorithms (BIOs) is an effective method for estimating source information. However, the impacts of different BIOs and the shared parameter of population size in BIOs on source inversion performance have not been revealed. Here the source inversion performance (i.e., accuracy and robustness) of six typical BIOs [i.e., bacterial foraging optimization algorithm (BFO), chicken swarm optimization algorithm (CSO), differential evolution algorithm (DE), genetic algorithm (GA), particle swarm optimization (PSO), and seeker optimization algorithm (SOA)], and their population sizes are evaluated based on the Prairie Grass dataset which covering different atmospheric conditions (i.e., Pasquill stability classes A, B, C, D, E, and F). Results indicated the population size has substantial influence on source inversion. The accuracy of all BIOs in source strength fluctuated greatly when the population size was small, whereas, tended to be stable as the population size increased. Overall, the BFO had the best accuracy with lowest deviations (74.5% for source strength and 29.7 m for location parameter x(0)), whereas SOA had the best robustness for all source parameters. Atmospheric conditions indicated an obvious influence on the inversion performance of the BIOs. The BFO and CSO performed the best with the lowest deviations [137.5 and 26.7% for unstable conditions (A, B, and C) and stable condition (E), respectively], all algorithms are comparable (67.4 +/- 2.1%) in neutral condition (D), and BFO and CSO had the comparable performances (23.2 and 24.3%) and performed better under extremely stable condition (F). This study enhances the understanding of the factors influencing source inversion and provides a reference for the selection of appropriate bio-inspired algorithms and the reasonable setting of population size parameter for source inversion in practical environmental management.
Keyword ：
source parameters estimation source parameters estimation atmospheric pollution atmospheric pollution optimization method optimization method inverse modeling inverse modeling performance evaluation performance evaluation
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| GB/T 7714 | Mao, Shushuai , Hu, Feng , Lang, Jianlei et al. Comparative Study of Impacts of Typical Bio-Inspired Optimization Algorithms on Source Inversion Performance [J]. | FRONTIERS IN ENVIRONMENTAL SCIENCE , 2022 , 10 . |
| MLA | Mao, Shushuai et al. "Comparative Study of Impacts of Typical Bio-Inspired Optimization Algorithms on Source Inversion Performance" . | FRONTIERS IN ENVIRONMENTAL SCIENCE 10 (2022) . |
| APA | Mao, Shushuai , Hu, Feng , Lang, Jianlei , Chen, Tian , Cheng, Shuiyuan . Comparative Study of Impacts of Typical Bio-Inspired Optimization Algorithms on Source Inversion Performance . | FRONTIERS IN ENVIRONMENTAL SCIENCE , 2022 , 10 . |
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Abstract ：
Source inversion is an effective approach for estimating air pollutant source parameters (e.g., source emission or source strength [Q(0)], source horizontal location [x(0), y(0)], and release height [z(0)]) in industrial activities or accidents. Air pollution events in the real world generally correspond to complex application scenarios arising from unknown source parameters (i.e., Q(0), [Q(0), z(0)], [Q(0), x(0), y(0)], and [Q(0), x(0), y(0), z(0)]) and atmospheric dispersion conditions. However, the source inversion characteristic law of these complex practical scenarios and the interaction mechanism between source location prior information and source strength inversion have not been revealed. In this study, the source inversion performance (accuracy and robustness) under the aforementioned scenarios was evaluated based on the Prairie Grass field experiments. Results indicated that the estimation accuracy of source strength was worse with an increase in the number of unknown source parameters with absolute relative deviations of 34.4, 46.0, 80.1, and 83.6% for a single parameter and double, triple, and quadruple parameters, respectively. Source strength inversion performance was obviously affected by location parameters; robustness was markedly reduced when source height was unknown, whereas accuracy was obviously reduced when source horizontal locations were unknown. Impacts of atmospheric conditions on different source parameters were distinct. Extreme atmospheric conditions (stability A and F) can obviously reduce the estimation accuracy of source strength for single and double parameter inversion scenarios, whereas unstable conditions (stability A, B, and C) can reduce the estimation accuracy of source strength for triple and quadruple parameter scenarios. Source inversion accuracy and robustness were generally poor under extremely stable conditions. This study can fill the knowledge gap in characteristic laws of source inversion under complex application scenarios and the interaction relationship between different unknown source parameters. The results of the influence law of location prior information on source strength inversion have important guiding significance to further improve the inversion accuracy of source strength in practical environmental managements.
Keyword ：
air pollution air pollution inversion modeling inversion modeling small-scale regions small-scale regions source parameter estimation source parameter estimation atmospheric dispersion conditions atmospheric dispersion conditions multiple pollutant emission scenarios multiple pollutant emission scenarios
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| GB/T 7714 | Mao, Shushuai , Lang, Jianlei , Chen, Tian et al. Comparative Study of Source Inversion Under Multiple Atmospheric Pollutant Emission Scenarios [J]. | FRONTIERS IN ENVIRONMENTAL SCIENCE , 2022 , 10 . |
| MLA | Mao, Shushuai et al. "Comparative Study of Source Inversion Under Multiple Atmospheric Pollutant Emission Scenarios" . | FRONTIERS IN ENVIRONMENTAL SCIENCE 10 (2022) . |
| APA | Mao, Shushuai , Lang, Jianlei , Chen, Tian , Cheng, Shuiyuan , Hu, Feng . Comparative Study of Source Inversion Under Multiple Atmospheric Pollutant Emission Scenarios . | FRONTIERS IN ENVIRONMENTAL SCIENCE , 2022 , 10 . |
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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 ：
Air pollutants from ship exhaust have a negative impact on air quality in coastal areas, which can be greatly exacerbated by sea breeze circulation. However, our understanding of this issue is still limited, especially in coastal areas with a complex topography and winding coastlines, such as the Bohai Rim region in China. In order to fill this knowledge gap, theWeather Research and Forecast model coupled with the chemistry (WRF/Chem) modeling system was employed to investigate the influence of sea breeze circulation on the transport of PM2.5 emitted by ships from April to September in 2014. The major findings are as follows: (1) The concentration of PM2.5 due to ship emissions was 2.94 mu g/m(3) on days with a sea breeze and 2.4 times higher than on days without a sea breeze in coastal cities in the region. (2) The difference in the contribution of ship emissions during days with a sea breeze and days without a sea breeze decreases with increasing distance from the coastline but remains non-negligible up to 50 km inland. (3) The shape of the coastline, the topographic height of the land area, and the latitude have a significant impact on sea breeze circulation and thus on the transport of ship emissions. (4) The differences in the contribution of ship emissions under days with a sea breeze versus days without a sea breeze were more evident than those under onshore versus alongshore and offshore winds, indicating that sea breeze circulation can cause cyclic accumulation of pollutants and thus reinforce the impact of ship emissions on coastal air quality more than by onshore winds. It should be emphasized that during the switching from sea breeze to a non-sea breeze, the pollutants that have been transported to the land area by sea breeze have not yet been carried back to sea, resulting in the ship contribution value still not significantly reduced even if the wind is a non-sea breeze at that moment. In addition, other factors e.g., emissions, precipitation, and chemistry can also play an important role in the observed trends in this study.
Keyword ：
sea breeze sea breeze WRF/Chem WRF/Chem ship emissions ship emissions Bohai Rim region Bohai Rim region PM2.5 PM2.5
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| GB/T 7714 | Ma, Yizhe , Chen, Dongsheng , Fu, Xinyi et al. Impact of Sea Breeze on the Transport of Ship Emissions: A Comprehensive Study in the Bohai Rim Region, China [J]. | ATMOSPHERE , 2022 , 13 (7) . |
| MLA | Ma, Yizhe et al. "Impact of Sea Breeze on the Transport of Ship Emissions: A Comprehensive Study in the Bohai Rim Region, China" . | ATMOSPHERE 13 . 7 (2022) . |
| APA | Ma, Yizhe , Chen, Dongsheng , Fu, Xinyi , Shang, Fang , Guo, Xiurui , Lang, Jianlei et al. Impact of Sea Breeze on the Transport of Ship Emissions: A Comprehensive Study in the Bohai Rim Region, China . | ATMOSPHERE , 2022 , 13 (7) . |
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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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Abstract ：
典型优化目标函数下源参数反演性能对比研究
Keyword ：
目标函数 目标函数 启发式算法 启发式算法 源参数反演 源参数反演 突发大气污染事故 突发大气污染事故 高斯烟羽模型 高斯烟羽模型
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| GB/T 7714 | 胡峰 , 郎建垒 , 毛书帅 et al. 典型优化目标函数下源参数反演性能对比研究 [J]. | 胡峰 , 2021 , 41 (5) : 2081-2089 . |
| MLA | 胡峰 et al. "典型优化目标函数下源参数反演性能对比研究" . | 胡峰 41 . 5 (2021) : 2081-2089 . |
| APA | 胡峰 , 郎建垒 , 毛书帅 , 玄博元 , 中国环境科学 . 典型优化目标函数下源参数反演性能对比研究 . | 胡峰 , 2021 , 41 (5) , 2081-2089 . |
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Abstract ：
大气污染领域本体的半自动构建及语义推理
Keyword ：
语义推理 语义推理 注意力机制 注意力机制 大气污染 大气污染 自然语言处理 自然语言处理 实体关系抽取 实体关系抽取 本体 本体
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| GB/T 7714 | 刘博 , 张佳慧 , 李建强 et al. 大气污染领域本体的半自动构建及语义推理 [J]. | 刘博 , 2021 , 47 (3) : 246-259 . |
| MLA | 刘博 et al. "大气污染领域本体的半自动构建及语义推理" . | 刘博 47 . 3 (2021) : 246-259 . |
| APA | 刘博 , 张佳慧 , 李建强 , 李永 , 郎建垒 , 北京工业大学学报 . 大气污染领域本体的半自动构建及语义推理 . | 刘博 , 2021 , 47 (3) , 246-259 . |
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Abstract ：
Although weather conditions significantly affect air pollutant concentrations, few quantitative studies have been conducted on the effects of long-term and seasonal changes in meteorology on air quality. Hence, in this study, the trends in Shandong Province, China, for six criteria pollutants (viz., sulfur dioxide [SO2], carbon monoxide [CO], particulate matter [PM] with an aerodynamic diameter of < 10 mu m [PM10], PM with an aerodynamic diameter of < 2.5 mu m [PM2.5], nitrogen dioxide [NO2], and ozone [O-3]) were analyzed for the period of 2013-2019, when overall emissions of air pollutants decreased, and the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem) was applied to evaluate the role of inter-annual and seasonal meteorological changes. Five of the six criteria pollutants exhibited a sharp drop in concentration until 2017 and a gradual decline afterward, with the maximum and minimum annual values occurring during winter and summer, respectively. In contrast, the level of O-3 rose between 2013 and 2019 and displayed the opposite seasonal trend. Also, the diurnal concentrations of the first five criteria pollutants showed a typical bimodal distribution, whereas those of the O-3 showed a typical unimodal distribution. Furthermore, a trimodal distribution was observed for the ratios between the diurnal PM2.5 and PM10 concentrations. Using 2013 as the baseline, the inter-annual meteorological changes accounted for only 3.4-18.6% of the decrease in the five criteria pollutants-with little effect on the O-3-between 2015 and 2019, indicating that emission control measures drove the long-term improvement in air quality during these years. However, seasonal meteorological factors, which favored diffusion during summer and winter but accumulation during spring and autumn, played a larger role in the short term for all six species, especially during winter, when they reduced concentrations (excluding those of SO2 in 2019 and O-3 altogether) by 6.5-31.0%.
Keyword ：
Seasonal variation Seasonal variation WRF/Chem WRF/Chem Diurnal variation Diurnal variation Meteorological condition Meteorological condition Air pollution Air pollution
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| GB/T 7714 | Zhao, Na , Wang, Gang , Li, Guohao et al. Trends in Air Pollutant Concentrations and the Impact of Meteorology in Shandong Province, Coastal China, during 2013-2019 [J]. | AEROSOL AND AIR QUALITY RESEARCH , 2021 , 21 (6) . |
| MLA | Zhao, Na et al. "Trends in Air Pollutant Concentrations and the Impact of Meteorology in Shandong Province, Coastal China, during 2013-2019" . | AEROSOL AND AIR QUALITY RESEARCH 21 . 6 (2021) . |
| APA | Zhao, Na , Wang, Gang , Li, Guohao , Lang, Jianlei . Trends in Air Pollutant Concentrations and the Impact of Meteorology in Shandong Province, Coastal China, during 2013-2019 . | AEROSOL AND AIR QUALITY RESEARCH , 2021 , 21 (6) . |
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Abstract ：
Estimating accurately airborne pollutant emissions source information (source strength and location) is important for achieving effective air pollution management or adequate emergency responses to accidents. Inversion method is one of the useful tools to identify the source parameters. The atmospheric dispersion scheme has been proven to be the key to determining the source inversion performance by influencing the accuracy of the dispersion models. Modifying the atmospheric dispersion scheme is an important potential method to improve the inversion performance, but this has not been studied previously. To fill this gap, a novel approach for parameter sensitivity analysis combined with an optimization method was proposed to improve the source inversion performance by optimizing empirical scheme. The dispersion coefficients σy and σz of the typical BRIGGS scheme under different atmospheric dispersion conditions were optimized and used for air pollutant dispersion and source inversion. The results showed that the prediction performance of the air pollutant concentrations was greatly improved with statistical indices |FB| and NMSE decreased by 0.22 and 2.07, respectively; FAC2 and R increased by 0.10, and 0.08, respectively. For source inversion, the results of the significance analysis suggested that the accuracy in the source strength and location parameter (x0) were both significantly improved by ∼271% (relative deviation reduced from 60.0% to 16.2%) and ∼121% (absolute deviation reduced from 27.6 to 12.5 m). The improvement of source strength inversion accuracy was more significant under unstable atmospheric conditions (stability class A, B, and C); the mean absolute relative deviation was reduced by 97.5%. These results can help to obtain more accurate source information and to provide reliable reference for air pollution managements or emergency response to accidents. This study provides a novel and versatile approach to improve estimation performance of pollutant emission sources and enhances our understanding of source inversion.
Keyword ：
Atmospheric dispersion coefficients Atmospheric dispersion coefficients Air pollutant emissions Air pollutant emissions Sensitivity analysis Sensitivity analysis Source inversion Source inversion Dispersion scheme optimization Dispersion scheme optimization
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| GB/T 7714 | Mao Shushuai , Lang Jianlei , Chen Tian et al. Improving source inversion performance of airborne pollutant emissions by modifying atmospheric dispersion scheme through sensitivity analysis combined with optimization model. [J]. | Environmental pollution , 2021 , 284 : 117186 . |
| MLA | Mao Shushuai et al. "Improving source inversion performance of airborne pollutant emissions by modifying atmospheric dispersion scheme through sensitivity analysis combined with optimization model." . | Environmental pollution 284 (2021) : 117186 . |
| APA | Mao Shushuai , Lang Jianlei , Chen Tian , Cheng Shuiyuan . Improving source inversion performance of airborne pollutant emissions by modifying atmospheric dispersion scheme through sensitivity analysis combined with optimization model. . | Environmental pollution , 2021 , 284 , 117186 . |
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