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学者姓名：郎建垒
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摘要 ：
大气污染领域本体的半自动构建及语义推理
关键词 ：
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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摘要 ：
典型优化目标函数下源参数反演性能对比研究
关键词 ：
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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摘要 ：
基于外场实验数据,从反演高估率、准确性、稳定性角度系统评估了8种典型目标函数在不同未知源参数反演情形下的反演性能差异.研究发现,不同目标函数反演性能差异显著.仅反演单参数源强时(Q),对数变换目标函数高估率最大(79.4%),偏差平方和目标函数准确性最高(P_(ARD<50%)=82.3%,ARD=(35.3±9.1)%),目标函数稳定性无明显差异(CV<0.01).三参数反演(Q,x,y)时,标准化均方根误差目标函数源强高估率最大(98.5%),对数变换目标函数准确性、稳定性最高(P_(ARD<50%)=91.1%,ARD=(48.4±9.8)%;CV=0.01);位置方面,偏差平方和目标函...
关键词 ：
启发式算法 启发式算法 源参数反演 源参数反演 目标函数 目标函数 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]. | 中国环境科学 , 2021 , 41 (05) : 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" . | 中国环境科学 41 . 05 (2021) : 2081-2089 . |
| APA | 胡峰 , 郎建垒 , 毛书帅 , 玄博元 . 典型优化目标函数下源参数反演性能对比研究 . | 中国环境科学 , 2021 , 41 (05) , 2081-2089 . |
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摘要 ：
本发明公开了一种实现秸秆露天焚烧大气污染物排放清单快速更新的方法，利用ArcGIS识别逐月秸秆露天焚烧火点；根据地理位置划分为六个区域；基于识别的月‑省秸秆露天焚烧火点的热辐射功率和区域划分，计算月‑省秸秆露天焚烧火点热辐射能；获取基于实际调研的年‑省秸秆露天焚烧比例数据，针对六个区域分别构建基于卫星遥感热辐射能的秸秆露天焚烧比例估算模型；建立包含全部目标年份与省份的年‑省秸秆露天焚烧比例估算数据库；收集自下而上方法估算秸秆露天焚烧大气污染物排放所需其他活动水平数据以及排放因子；估算年‑省秸秆露天焚烧大气污染物排放清单。本发明可实现年‑省秸秆露天焚烧大气污染物排放清单的快速更新。
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| GB/T 7714 | 周颖 , 张钰蓥 , 郎建垒 . 一种秸秆露天焚烧大气污染物排放清单快速更新的方法 : CN202110092935.7[P]. | 2021-01-25 . |
| MLA | 周颖 et al. "一种秸秆露天焚烧大气污染物排放清单快速更新的方法" : CN202110092935.7. | 2021-01-25 . |
| APA | 周颖 , 张钰蓥 , 郎建垒 . 一种秸秆露天焚烧大气污染物排放清单快速更新的方法 : CN202110092935.7. | 2021-01-25 . |
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摘要 ：
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.
关键词 ：
Air pollutant emissions Air pollutant emissions Atmospheric dispersion coefficients Atmospheric dispersion coefficients Dispersion scheme optimization Dispersion scheme optimization Sensitivity analysis Sensitivity analysis Source inversion Source inversion
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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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摘要 ：
Rural residential coal combustion (RRCC) has detrimental effects on air quality, climate, and human health. There are large uncertainties regarding emissions from RRCC owing to the lack of consideration of several key factors (e.g. combination modes of coal and stoves, combustion modes, and high temporal resolution). In this study, we provided a new estimation framework for RRCC emissions through a case study in the Beijing-Tianjin-Hebei (BTH) region, China. The emission estimations were improved according to four aspects, namely (1) coal-specific and stove-specific coal consumption was calculated based on face-to-face field interviews of 6700 valid volunteers/households covering 288 villages in 50 counties; (2) the influences of combustion modes (flaming and smoldering modes) on emissions were considered; (3) emissions of different fuel-stove combinations were estimated based on coal, stove, and combustion mode-specific RRCC consumption and localised emission factors; and (4) a method for emission estimation with high temporal resolution (1 h) was developed. The results indicated that RRCC emitted 413.6 kt SO2, 55.7 kt NOx, 5717.3 kt CO, 149.4 kt VOCs, 167.1 kt PM2.5, 18.2 kt EC, 32.5 kt OC, and 8.2 kt NH3 in 2016. The combination of bituminous coal and an advanced coal stove was the most significant contributor (20.7-71.8%) to various pollutant emissions. Coal combusted under the flaming mode contributed to most (81.9%) of the total coal consumption, and thus emitted the majority (50.8-99.8%) of pollutants, except for VOCs. Meanwhile, that under the smoldering mode only accounted for 18.1% of the total consumption, but contributed 49.2% and 74.7% of the CO and VOCs emissions, respectively. Two clear emission peaks occurred at approximately 7:00-9:00 and 18:00-20:00. The detailed coal consumption and emissions with high temporal and spatial resolution can provide sound data for further research on rural environmental issues and scientific support to pollution control strategies.
关键词 ：
Advanced coal stove Advanced coal stove Coal-stove combination Coal-stove combination Combustion modes Combustion modes Emission factors Emission factors Rural coal emissions Rural coal emissions
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| GB/T 7714 | Zhou Ying , Huang Dawei , Lang Jianlei et al. Improved estimation of rural residential coal emissions considering coal-stove combinations and combustion modes. [J]. | Environmental pollution , 2021 , 272 : 115558 . |
| MLA | Zhou Ying et al. "Improved estimation of rural residential coal emissions considering coal-stove combinations and combustion modes." . | Environmental pollution 272 (2021) : 115558 . |
| APA | Zhou Ying , Huang Dawei , Lang Jianlei , Zi Teng , Chen Dongsheng , Zhang Yuying et al. Improved estimation of rural residential coal emissions considering coal-stove combinations and combustion modes. . | Environmental pollution , 2021 , 272 , 115558 . |
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摘要 ：
Ship-exhausted air pollutants could cause negative impacts on air quality, climate change, and human health. Increasing attention has been paid to investigate the impact of ship emissions on air quality. However, the conclusions are often based on a specific year, the extent to which the inter-annual variation in meteorological conditions affects the contribution is not yet fully addressed. Therefore, in this study, the Weather Research and Forecast model and the Community Multiscale Air Quality model(WRF/CMAQ) were employed to investigate the inter-annual variations in ship-contributed PM2.5 from 2010 to 2019. The Yangtze River Delta (YRD) region in China was selected as the target study area. To highlight the impact of inter-annual meteorological variations, the emission inventory and model configurations were kept the same for the 10-year simulation. We found that: (1) inter-annual meteorological variation had an evident impact on the ship-contributed PM2.5 in most coastal cities around YRD. Taking Shanghai as an example, the contribution varied between 3.05 and 5.74 mu g/m(3), with the fluctuation rate of similar to 65%; (2) the inter-annual changes in ship's contribution showed a trend of almost simultaneous increase and decrease for most cities, which indicates that the impact of inter-annual meteorological variation was more regional than local; (3) the inter-annual changes in the northern part of YRD were significantly higher than those in the south; (4) the most significant inter-annual changes were found in summer, followed by spring, fall and winter.
关键词 ：
inter-annual meteorological variation inter-annual meteorological variation PM2.5 PM2.5 ship emission ship emission WRF/CMAQ WRF/CMAQ Yangtze River Delta Yangtze River Delta
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| GB/T 7714 | Chen, Dongsheng , Liang, Dingyue , Li, Lei et al. The Temporal and Spatial Changes of Ship-Contributed PM2.5 Due to the Inter-Annual Meteorological Variation in Yangtze River Delta, China [J]. | ATMOSPHERE , 2021 , 12 (6) . |
| MLA | Chen, Dongsheng et al. "The Temporal and Spatial Changes of Ship-Contributed PM2.5 Due to the Inter-Annual Meteorological Variation in Yangtze River Delta, China" . | ATMOSPHERE 12 . 6 (2021) . |
| APA | Chen, Dongsheng , Liang, Dingyue , Li, Lei , Guo, Xiurui , Lang, Jianlei , Zhou, Ying . The Temporal and Spatial Changes of Ship-Contributed PM2.5 Due to the Inter-Annual Meteorological Variation in Yangtze River Delta, China . | ATMOSPHERE , 2021 , 12 (6) . |
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摘要 ：
Atmospheric visibility is an indicator of atmospheric transparency and its range directly reflects the quality of the atmospheric environment. With the acceleration of industrialization and urbanization, the natural environment has suffered some damages. In recent decades, the level of atmospheric visibility shows an overall downward trend. A decrease in atmospheric visibility will lead to a higher frequency of haze, which will seriously affect people's normal life, and also have a significant negative economic impact. The causal relationship mining of atmospheric visibility can reveal the potential relation between visibility and other influencing factors, which is very important in environmental management, air pollution control and haze control. However, causality mining based on statistical methods and traditional machine learning techniques usually achieve qualitative results that are hard to measure the degree of causality accurately. This article proposed the seq2seq-LSTM Granger causality analysis method for mining the causality relationship between atmospheric visibility and its influencing factors. In the experimental part, by comparing with methods such as linear regression, random forest, gradient boosting decision tree, light gradient boosting machine, and extreme gradient boosting, it turns out that the visibility prediction accuracy based on the seq2seq-LSTM model is about 10% higher than traditional machine learning methods. Therefore, the causal relationship mining based on this method can deeply reveal the implicit relationship between them and provide theoretical support for air pollution control.
关键词 ：
Atmospheric visibility Atmospheric visibility deep learning deep learning granger causality granger causality multidimensional time series multidimensional time series
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| GB/T 7714 | Liu, Bo , He, Xi , Song, Mingdong et al. A Method for Mining Granger Causality Relationship on Atmospheric Visibility [J]. | ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA , 2021 , 15 (5) . |
| MLA | Liu, Bo et al. "A Method for Mining Granger Causality Relationship on Atmospheric Visibility" . | ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA 15 . 5 (2021) . |
| APA | Liu, Bo , He, Xi , Song, Mingdong , Li, Jiangqiang , Qu, Guangzhi , Lang, Jianlei et al. A Method for Mining Granger Causality Relationship on Atmospheric Visibility . | ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA , 2021 , 15 (5) . |
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摘要 ：
Crop residue open burning has substantial negative effects on air quality, human health, and climate change, and accurate and timely estimates of its air pollutant emissions are essential. Open burning proportion (OBP) is the key parameter in estimating the emission from the crop residue open burning by bottom-up method. However, the OBP is mainly obtained by field investigation, which consumes much time, manpower and financial resources, leading to the OBP data deficient seriously. In this study, the significant logarithmic relations were found between OBP and fire radiative energy (FRE), and then the FRE-based OBP estimation models were developed for different regions of China. The comparison between the FRE-based OBP and the field-investigated OBP illustrated the reliability of the developed models (r = 0.71, NMB = -8% and NME = 25%). The OBPs of different municipalities/provinces in mainland China from 2003 to 2018 were further calculated. The results showed that the estimated OBP variation exhibited fluctuating upward trend with annual mean growth rate of 3.7% from 2003 to 2014, while dramatically decreased with annual mean reduction rate of 5.9% from 2014 to 2018. The estimation accuracy of emission from open biomass burning can also be can be significantly improved by basing on the yearspecific OBP, compared with the calculation based on fixed OBP. The annual PM2.5 emissions would decrease 4.5%-25.9% and increase 6.6%-30.7% in the scenarios of a fixed OBP during 2003-2014 and 2014-2018, respectively. The developed models complemented the severely missing OBP data of mainland China for the first time. By combining the advantages of bottom-up approach and FRE method, the proposed FRE-based models can avoid their disadvantages, and can help to get more accurately and timely emissions from crop residue open burning.
关键词 ：
Agriculture fire Agriculture fire China China Emission calculation Emission calculation MODIS MODIS OBP estimation Model OBP estimation Model
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| GB/T 7714 | Zhou, Ying , Zhang, Yuying , Zhao, Beibei et al. Estimating air pollutant emissions from crop residue open burning through a calculation of open burning proportion based on satellite-derived fire radiative energy [J]. | ENVIRONMENTAL POLLUTION , 2021 , 286 . |
| MLA | Zhou, Ying et al. "Estimating air pollutant emissions from crop residue open burning through a calculation of open burning proportion based on satellite-derived fire radiative energy" . | ENVIRONMENTAL POLLUTION 286 (2021) . |
| APA | Zhou, Ying , Zhang, Yuying , Zhao, Beibei , Lang, Jianlei , Xia, Xiangchen , Chen, Dongsheng et al. Estimating air pollutant emissions from crop residue open burning through a calculation of open burning proportion based on satellite-derived fire radiative energy . | ENVIRONMENTAL POLLUTION , 2021 , 286 . |
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摘要 ：
Particles with an aerodynamic diameter of 2.5 mu m or less (PM2.5) in the ambient air are affected not only by local emissions but also by regional transport of the pollutant and its precursors, which may vary considerably under different meteorological conditions. This issue has been extensively investigated in terms of the contribution of regional transport to PM2.5 at different seasons in a specific year. However, the literature yields conflicting results, and the extent to which inter-annual meteorological variation affects the contribution of regional transport is not fully understood, especially in the long-term. Therefore, in this study, the WRF/CMAQ model was employed to investigate inter-annual variations in the contribution of regional transport to PM2.5 concentration in Beijing from 2001 to 2015. The emission inventory and model configurations were kept the same for the 15year simulation to highlight the impact of inter-annual meteorological variations. The major findings can be summarized as follows: (1) inter-annual meteorological variation has an impact on both the PM2.5 concentration in Beijing and the contribution of regional transport; (2) the annual average PM2.5 concentrations in Beijing varied during the study period, from 75.3 mu g/m(3) in 2002 to 108.1 mu g/m(3) in 2003; (3) the years with high annual anomalies of PM2.5 was found during periods of low wind speed, high relative humidity, and low planetary boundary layer (PBL) height; (4) the annual variability was relatively small compared to the changes in seasonal because some seasons in a year are higher than their historical average values, and some are lower, which often negate each other, making the annual average close to the historical average; (5) the contribution of regional transport averaged 44.5% and ranged from 40.7% in 2007 to 48.5% in 2001. On a seasonal basis, the interannual fluctuation was more significant, with fluctuation rates of 43.0%, 25.5%, 25.0%, and 20.6% in winter, fall, spring, and summer, respectively; and (6) in general, there is a good positive correlation between the regional contribution and PM2.5 concentration in Beijing. Specifically, when the regional transport contribution is large, the PM2.5 concentration tends to be higher. This is especially true during years when both the concentration and contribution deviate significantly from the historical average.
关键词 ：
Contribution of regional transport Contribution of regional transport Inter-annual meteorological variation Inter-annual meteorological variation PM2.5 PM2.5 WRF/CMAQ WRF/CMAQ
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| GB/T 7714 | Chen, Dongsheng , Xia, Lin , Guo, Xiurui et al. Impact of inter-annual meteorological variation from 2001 to 2015 on the contribution of regional transport to PM2.5 in Beijing, China [J]. | ATMOSPHERIC ENVIRONMENT , 2021 , 260 . |
| MLA | Chen, Dongsheng et al. "Impact of inter-annual meteorological variation from 2001 to 2015 on the contribution of regional transport to PM2.5 in Beijing, China" . | ATMOSPHERIC ENVIRONMENT 260 (2021) . |
| APA | Chen, Dongsheng , Xia, Lin , Guo, Xiurui , Lang, Jianlei , Zhou, Ying , Wei, Lin et al. Impact of inter-annual meteorological variation from 2001 to 2015 on the contribution of regional transport to PM2.5 in Beijing, China . | ATMOSPHERIC ENVIRONMENT , 2021 , 260 . |
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