scholarly journals Impact of modified turbulent diffusion of PM<sub>2.5</sub> aerosol in WRF-Chem simulations in Eastern China

2021 ◽  
Author(s):  
Wenxing Jia ◽  
Xiaoye Zhang
Keyword(s):  
Diffusion Process ◽  
Turbulent Diffusion ◽  
Turbulent Transport ◽  
Eastern China ◽  
Mixing Process ◽  
Heavy Pollution ◽  
Mixing Length Theory ◽  
Relationship Of ◽  
Pm2.5 Concentration

Abstract. Correct description of the boundary layer mixing process of particle is an important prerequisite to understanding the mechanism of heavy pollution episodes. Turbulent mixing process of particles is usually denoted by the turbulent diffusion relationship of heat, meaning that the turbulent transport of particles and heat are similar. This similarity has, however, never been verified. Here we investigate the dissimilarity between particles and heat, indicating that the unified treatment of all scalars in the model is questionable. Using mixing-length theory, the turbulent diffusion relationship of particle is established, embedded in the model and verified on a long-term scale. Simulated results of PM2.5 concentration were improved by 8.3 % (2013), 17 % (2014), 11 % (2015) and 11.7 % (2017) in Eastern China, respectively. However, under the influence of complex topography, the turbulent diffusion process is insensitive to the simulation of the pollutant concentration. In addition to the PM2.5 concentration, the simulation of the CO concentration has also been improved, which shows that the turbulent diffusion process is extremely critical to the change in the concentration of pollutants.

scholarly journals Impact of modified turbulent diffusion of PM<sub>2.5</sub> aerosol in WRF-Chem simulations in eastern China

2021 ◽  
Vol 21 (22) ◽  
pp. 16827-16841
Author(s):  
Wenxing Jia ◽  
Xiaoye Zhang
Keyword(s):  
Boundary Layer ◽  
Diffusion Process ◽  
Turbulent Mixing ◽  
Turbulent Diffusion ◽  
Eastern China ◽  
Pollutant Concentration ◽  
Mixing Process ◽  
Mountainous Areas ◽  
Turbulent Diffusion Coefficient ◽  
Pm2.5 Concentration

Abstract. Correct description of the boundary layer mixing process of particle is an important prerequisite for understanding the formation mechanism of pollutants, especially during heavy pollution episodes. Turbulent vertical mixing determines the distribution of momentum, heat, water vapor and pollutants within the planetary boundary layer (PBL). However, what is questionable is that the turbulent mixing process of particles is usually denoted by turbulent diffusion of heat in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). With mixing-length theory, the turbulent diffusion relationship of particle is established, embedded into the WRF-Chem and verified based on long-term simulations from 2013 to 2017. The new turbulent diffusion coefficient is used to represent the turbulent mixing process of pollutants separately, without deteriorating the simulation results of meteorological parameters. The new turbulent diffusion improves the simulation of pollutant concentration to varying degrees, and the simulated results of PM2.5 concentration are improved by 8.3 % (2013), 17 % (2014), 11 % (2015) and 11.7 % (2017) in eastern China, respectively. Furthermore, the pollutant concentration is expected to increase due to the reduction of turbulent diffusion in mountainous areas, but the pollutant concentration did not change as expected. Therefore, under the influence of complex topography, the turbulent diffusion process is insensitive to the simulation of the pollutant concentration. For mountainous areas, the evolution of pollutants is more susceptible to advection transport because of the simulation of obvious wind speed gradient and pollutant concentration gradient. In addition to the PM2.5 concentration, the concentration of CO as a primary pollutant has also been improved, which shows that the turbulent diffusion process is extremely critical for variation of the various aerosol pollutants. Additional joint research on other processes (e.g., dry deposition, chemical and emission processes) may be necessary to promote the development of the model in the future.

scholarly journals Domain randomization-enhanced deep learning models for bird detection

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin Mao ◽  
Jun Kang Chow ◽  
Pin Siang Tan ◽  
Kuan-fu Liu ◽  
Jimmy Wu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Continuous Monitoring ◽  
Bird Species ◽  
Training Data ◽  
Learning Models ◽  
Fine Grained ◽  
Bird Detection ◽  
Relationship Of ◽  
The Relationship

AbstractAutomatic bird detection in ornithological analyses is limited by the accuracy of existing models, due to the lack of training data and the difficulties in extracting the fine-grained features required to distinguish bird species. Here we apply the domain randomization strategy to enhance the accuracy of the deep learning models in bird detection. Trained with virtual birds of sufficient variations in different environments, the model tends to focus on the fine-grained features of birds and achieves higher accuracies. Based on the 100 terabytes of 2-month continuous monitoring data of egrets, our results cover the findings using conventional manual observations, e.g., vertical stratification of egrets according to body size, and also open up opportunities of long-term bird surveys requiring intensive monitoring that is impractical using conventional methods, e.g., the weather influences on egrets, and the relationship of the migration schedules between the great egrets and little egrets.

scholarly journals Evaluations of Surface PM10 Concentration and Chemical Compositions in MERRA-2 Aerosol Reanalysis over Central and Eastern China

2021 ◽  
Vol 13 (7) ◽  
pp. 1317
Author(s):  
Xiaodan Ma ◽  
Peng Yan ◽  
Tianliang Zhao ◽  
Xiaofang Jia ◽  
Jian Jiao ◽  
...  
Keyword(s):  
Eastern China ◽  
Mainland China ◽  
Chemical Components ◽  
Chemical Compositions ◽  
Observation Data ◽  
Causative Factors ◽  
Routine Sampling ◽  
Aerosol Compositions ◽  
Modern Era

The chemical composition dataset of Aerosol Reanalysis of NASA’s Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRAero) has not been thoroughly evaluated with observation data in mainland China due to the lack of long-term chemical components data. Using the 5-year data of PM10 mass concentrations and chemical compositions obtained from the routine sampling measurements at the World Meteorological Organization the Global Atmosphere Watch Programme regional background stations, Jing Sha (JS) and Lin’An (LA), in central and eastern China, we comprehensively evaluate the surface PM10 concentrations and chemical compositions such as sulfate (SO42−), organic carbon (OC) and black carbon (BC) derived from MERRAero. Overall, the concentrations of PM10, SO42−, OC and BC from the MERRAero agreed well with the measurements, despite a slight and consistent overestimation of BC concentrations and a moderate and persistent underestimation of PM10 concentrations throughout the study period. The MERRAero reanalysis of aerosol compositions performs better during the summertime than wintertime. By considering the nitrate particles in PM10 reconstruction, MERRAero performance can be significantly improved. The unreasonable seasonal variations of PM10 chemical compositions at station LA by MERRAero could be causative factors for the larger MERRAero discrepancies during 2016–2017 than the period of 2011–2013.

scholarly journals Non-Local and Multi-Scale Mechanisms for Image Inpainting

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3281
Author(s):  
Xu He ◽  
Yong Yin
Keyword(s):  
Markov Random Fields ◽  
Receptive Fields ◽  
Image Inpainting ◽  
Long Distance ◽  
Visual Appearance ◽  
Fine Grained ◽  
Multi Scale ◽  
Non Local ◽  
Relationship Of

Recently, deep learning-based techniques have shown great power in image inpainting especially dealing with squared holes. However, they fail to generate plausible results inside the missing regions for irregular and large holes as there is a lack of understanding between missing regions and existing counterparts. To overcome this limitation, we combine two non-local mechanisms including a contextual attention module (CAM) and an implicit diversified Markov random fields (ID-MRF) loss with a multi-scale architecture which uses several dense fusion blocks (DFB) based on the dense combination of dilated convolution to guide the generative network to restore discontinuous and continuous large masked areas. To prevent color discrepancies and grid-like artifacts, we apply the ID-MRF loss to improve the visual appearance by comparing similarities of long-distance feature patches. To further capture the long-term relationship of different regions in large missing regions, we introduce the CAM. Although CAM has the ability to create plausible results via reconstructing refined features, it depends on initial predicted results. Hence, we employ the DFB to obtain larger and more effective receptive fields, which benefits to predict more precise and fine-grained information for CAM. Extensive experiments on two widely-used datasets demonstrate that our proposed framework significantly outperforms the state-of-the-art approaches both in quantity and quality.

scholarly journals Trends in PM2.5 Concentration in Nagoya, Japan, from 2003 to 2018 and Impacts of PM2.5 Countermeasures

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 590
Author(s):  
Makiko Yamagami ◽  
Fumikazu Ikemori ◽  
Hironori Nakashima ◽  
Kunihiro Hisatsune ◽  
Kayo Ueda ◽  
...  
Keyword(s):  
Fine Particulate Matter ◽  
Control Measures ◽  
Source Control ◽  
Atmospheric Concentration ◽  
Construction Machinery ◽  
Emission Regulations ◽  
Volatile Organic ◽  
Stationary Sources ◽  
Pm2.5 Concentration

In Japan, various countermeasures have been undertaken to reduce the atmospheric concentration of fine particulate matter (PM2.5). We evaluated the extent to which these countermeasures were effective in reducing PM2.5 concentrations by analyzing the long-term concentration trends of the major components of PM2.5 and their emissions in Nagoya City. PM2.5 concentrations decreased by 53% over the 16-year period from fiscal years 2003 to 2018 in Nagoya City. Elemental carbon (EC) was the component of PM2.5 with the greatest decrease in concentration over the 16 years, decreasing by 4.3 μg/m3, followed by SO42− (3.0 μg/m3), organic carbon (OC) (2.0 μg/m3), NH4+ (1.6 μg/m3), and NO3− (1.3 μg/m3). The decrease in EC concentration was found to be caused largely by the effect of diesel emission control. OC concentrations decreased because of the effects of volatile organic compound (VOC) emission regulations for stationary sources and reductions in VOCs emitted by vehicles and construction machinery. NO3− concentrations decreased alongside decreased contributions from vehicles, construction machinery, and stationary sources, in descending order of the magnitude of decrease. Although these findings identify some source control measures that have been effective in reducing PM2.5, they also reveal the ineffectiveness of some recent countermeasures for various components, such as those targeting OC concentrations.

Technology and Employment in Developing Countries

1978 ◽  
Vol 16 (4) ◽  
pp. 549-564 ◽  
Author(s):  
J. W. Garmany
Keyword(s):  
Developing Countries ◽  
Optimum Combination ◽  
Current Consumption ◽  
The Creation ◽  
Relationship Of ◽  
The Relationship ◽  
Choice Of Technology

This article discusses some of the issues involved in the choice of technology in developing countries, especially those in Africa, and the relationship of this to employment and output. The problem is to find an optimum combination of productive resources that comes nearest to satisfying two objectives: the full and economically efficient utilisation of such resources, and the creation of as much surplus as possible over current consumption, thereby making possible new investment and long-term growth.

scholarly journals The Relationship between Reputation, Customer Satisfaction, Trust, and Loyalty

2014 ◽  
Vol 4 (3) ◽  
pp. 368 ◽  
Author(s):  
Roshana Gul
Keyword(s):  
Customer Satisfaction ◽  
Customer Loyalty ◽  
Significant Relationship ◽  
Positive Sign ◽  
Medical College ◽  
Independent Variable ◽  
Relationship Of ◽  
The Relationship ◽  
Self Administered Questionnaire

Though a lot of studies have been done to conclude customer loyalty as dependent variable but still there is a vast margin of researches to be conducted in future in different spheres of this construct. On the other hand the truth of the importance of customer loyalty as an enduring asset cannot be falsified. It is fundamental for organizations to build up long term and mutual beneficial associations with the customers. The purpose of this research paper is to show the inter relationship of reputation, customer satisfaction and trust on customer loyalty. According to the observations reputation is the major independent variable that has significant relationship with customer satisfaction, customer loyalty, and trust. Data for this research study was taken from the Islamia University, Quaid-e-Azam Medical College, and different banks located at various geographic locations of Bahawalpur region of Pakistan. Data was collected through self administered questionnaire and analyzed by using regression through SPSS. The results have been drawn from 150 users of NISHAT LINEN and it was found that there is positive and significant relationship among reputation, customer satisfaction, trust and customer loyalty. Hence the studies give the positive sign that with the increment of reputation, customer satisfaction and trust the customer loyalty enhances.  

The Research on the Strategies for Sustainable Development and Environmental Protection

2013 ◽  
Vol 869-870 ◽  
pp. 786-790
Author(s):  
Chen Chen Zhang
Keyword(s):  
Sustainable Development ◽  
Environmental Protection ◽  
Development Strategy ◽  
Protection Measures ◽  
The Sustainable Development ◽  
National Economic ◽  
History Of ◽  
Dialectical Relationship ◽  
Relationship Of

The strategies for sustainable development have been included in the medium and long term plan of 2010 for national economic and social development. Protecting the environment is the most important prerequisite and safeguards for the sustainable development strategy. In the study, we described the history of the environmental problems in the world, the proposal and implications of sustainable development, and outlined the dialectical relationship of development with the environment. The environmental protection measures for sustainable development were proposed here, according to the environmental situation severely affecting its biophysical environment.

scholarly journals Mixing process in turbulent diffusion flames.

1989 ◽  
Vol 55 (510) ◽  
pp. 517-522 ◽  
Author(s):  
Kohoichi SUZUKI ◽  
Kinichi TORIKAI ◽  
Kiyoshi SAKUMA
Keyword(s):  
Turbulent Diffusion ◽  
Diffusion Flames ◽  
Mixing Process ◽  
Turbulent Diffusion Flames
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