scholarly journals A hybrid methodology to quantitatively identify inorganic aerosol of PM2.5 source contribution

2022 ◽  
pp. 128173
Author(s):  
Yu-Cheng Chen ◽  
Ruei-Hao Shie ◽  
Jun-Jie Zhu ◽  
Chin-Yu Hsu
Author(s):  
Pushpendra Singh ◽  
P.N. Hrisheekesha ◽  
Vinai Kumar Singh

Content based image retrieval (CBIR) is one of the field for information retrieval where similar images are retrieved from database based on the various image descriptive parameters. The image descriptor vector is used by machine learning based systems to store, learn and template matching. These feature descriptor vectors locally or globally demonstrate the visual content present in an image using texture, color, shape, and other information. In past, several algorithms were proposed to fetch the variety of contents from an image based on which the image is retrieved from database. But, the literature suggests that the precision and recall for the gained results using single content descriptor is not significant. The main vision of this paper is to categorize and evaluate those algorithms, which were proposed in the interval of last 10 years. In addition, experiment is performed using a hybrid content descriptors methodology that helps to gain the significant results as compared with state-of-art algorithms. The hybrid methodology decreases the error rate and improves the precision and recall for large natural scene images dataset having more than 20 classes.


Measurement ◽  
2021 ◽  
Vol 174 ◽  
pp. 109058
Author(s):  
Muxiao Li ◽  
Shuoqiao Zhong ◽  
Tiesong Deng ◽  
Ziwei Zhu ◽  
Xiaozhen Sheng

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 189
Author(s):  
Min He ◽  
Junhui Chen ◽  
Yuming He ◽  
Yuan Li ◽  
Qichao Long ◽  
...  

As one of the most populated regions in China, Sichuan province had been suffering from deteriorated air quality due to the dramatic growth of economy and vehicles in recent years. To deal with the increasingly serious air quality problem, Sichuan government agencies had made great efforts to formulate various control measures and policies during the past decade. In order to better understand the emission control progress in recent years and to guide further control policy formulation, the emission trends and source contribution characteristics of SO2, NOX, PM10 and PM2.5 from 2013 to 2017 were characterized by using emission factor approach in this study. The results indicated that SO2 emission decreased rapidly during 2013–2017 with total emission decreased by 52%. NOX emission decreased during 2013–2015 but started to increase slightly afterward. PM10 and PM2.5 emissions went down consistently during the study period, decreased by 26% and 25%, respectively. In summary, the contribution of power plants kept decreasing, while contribution of industrial combustion remained steady in the past 5 years. The contribution of industrial processes increased for SO2 emission, and decreased slightly for NOX, PM10 and PM2.5 emissions. The on-road mobile sources were the largest emission contributor for NOX, accounting for about 32–40%, and its contribution increased during 2013–2015 and then decreased. It was worth mentioning that nonroad mobile sources and natural gas fired boilers were becoming important NOX contributors in Sichuan. Fugitive dust were the key emission sources for PM10 and PM2.5, and the contribution kept increasing in the study period. Comparison results with other inventories, satellite data and ground observations indicated that emission trends developed in this research were relatively credible.


2021 ◽  
Vol 279 ◽  
pp. 111803
Author(s):  
Jeffrey B. Kast ◽  
Anna M. Apostel ◽  
Margaret M. Kalcic ◽  
Rebecca L. Muenich ◽  
Awoke Dagnew ◽  
...  

2021 ◽  
Vol 32 ◽  
pp. 382-395
Author(s):  
W. Haanstra ◽  
A.J.J. Braaksma ◽  
L.A.M. van Dongen

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rui Feng ◽  
Rong Zhou ◽  
Weiwei Shi ◽  
Nanjing Shi ◽  
Xuekun Fang

AbstractWe focus on the causes of fluctuations in wintertime PM10 in nine regional core cities of China using two machine learning models, Random Forest (RF) and Recurrent Neural Network (RNN). RF and RNN both show high performance in predicting hourly PM10 using only gaseous air pollutants (SO2, NO2 and CO) as inputs, showing the predominance of the secondary inorganic aerosol and implying the existence of thermodynamic equilibrium between gaseous air pollutants and PM10. Also, we find the following results. The correlation of gaseous air pollutants and PM10 were more relevant than that of meteorological conditions and PM10. CO was the predominant factor for PM10 in the Beijing-Tianjin-Hebei Plain and the Yangtze River Delta while SO2 and NO2 were also important features for PM10 in the Pearl River Delta and Sichuan Basin. The spatial heterogeneity and temporal homogeneity of PM10 in China are revealed. The long-range transported PM10 was substantiated to be insignificant, except in the sandstorms. The severity of PM10 was attributable to the lopsided shift of thermodynamic equilibrium and the phenology of indigenous flora.


2014 ◽  
Vol 105 (1) ◽  
pp. 22-47 ◽  
Author(s):  
Timothy L. Hawthorne ◽  
Patricia Solís ◽  
Brittney Terry ◽  
Marie Price ◽  
Christopher L. Atchison

Sign in / Sign up

Export Citation Format

Share Document