Refine your search
Collections
Co-Authors
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Lei, Yang
- Factor Analysis of Mass Concentration Characterization of PM2.5 and its Impact Factors in a Suburban Roadside: Taking a National Road of Zhengzhou, China as an Example
Abstract Views :115 |
PDF Views:0
Authors
Affiliations
1 School of Energy and Environment Engineering, Zhongyuan University of Technology, Zhengzhou 450007, CN
2 School of Economics & Management, Zhongyuan University of Technology, Zhengzhou 450007, CN
3 National Institute for Health and Welfare, Helsinki 00271, FI
4 School of Environmental Science and Engineering, Donghua University, Shanghai 201620, CN
1 School of Energy and Environment Engineering, Zhongyuan University of Technology, Zhengzhou 450007, CN
2 School of Economics & Management, Zhongyuan University of Technology, Zhengzhou 450007, CN
3 National Institute for Health and Welfare, Helsinki 00271, FI
4 School of Environmental Science and Engineering, Donghua University, Shanghai 201620, CN
Source
Nature Environment and Pollution Technology, Vol 14, No 2 (2015), Pagination: 409-414Abstract
During the winter season from November 4, 2014 to November 16, 2014, one-hour average fine samples (PM2.5) of airborne particulate matter were collected at a busy roadside of the No. 107 national road located in a suburb of Zhengzhou City, China. For a convenient comparative analysis, two sets of data were tested in two different locations (No. 1 and No. 2) at a distance of 200m beside the road. Following previous research results, we considered traffic flow, ambient air temperature, relative humidity, wind speed, wind direction, atmospheric pressure and haze condition as factors to analyse their potential influence on the mass concentration of PM2.5. Same day data from the China National Environmental Monitoring Centre were also compared with the data of the study. Results showed that the average ambient PM2.5 concentrations were significantly higher at the tested suburban roadside than in the city region. However, the t-test result disclosed that the two sets of data had no significant difference (p = 0.001). The difference between the roadside data and the background concentration could be attributed to certain factors that were only sampled at the suburban roadside. Pearson correlation analysis was performed to identify the source contribution of the ambient PM2.5 concentration at the study locations. The correlation values indicated that the major factors with relatively significant influence on the PM2.5 data during the events under study were temperature (0.310 at the No. 1 site and 0.268 at the No. 2 site), relative humidity (0.532 at the No. 1 site and 0.303 at the No. 2 site), traffic flow (0.393 at the No. 1 site and 0.379 at the No. 2 site), wind speed ("0.264 at the No. 1 site and "0.187 at the No. 2 site), and wind direction (0.262 at the No. 2 site). Among all the impact parameters considered in the study, traffic flow contributed most to the PM2.5 mass concentration (correlation values were 0.393 and 0.379 for the No. 1 and No. 2 sites, respectively). Relative humidity (correlation value = 0.532 for the No. 1 site and correlation value = 0.303 for the No. 2 site) and wind speed contributed to the reduction of the PM2.5 mass concentration.Keywords
PM2.5, Mass Concentration, Factor Analysis, Suburban Roadside.- Impact on Population Exposure to PM2.5 by its Source Factors in China:Provincial Panel Data Analysis
Abstract Views :228 |
PDF Views:0
Authors
Affiliations
1 School of Energy and Environment, Zhongyuan University of Technology, Zhengzhou, 450007, P.R., CN
2 School of Economics and Management, Zhongyuan University of Technology, Zhengzhou, 450007, P.R., CN
3 National Institute for Health and Welfare, Helsinki 00271, FI
4 School of Environmental Science and Engineering, Donghua University, Shanghai 201620, CN
1 School of Energy and Environment, Zhongyuan University of Technology, Zhengzhou, 450007, P.R., CN
2 School of Economics and Management, Zhongyuan University of Technology, Zhengzhou, 450007, P.R., CN
3 National Institute for Health and Welfare, Helsinki 00271, FI
4 School of Environmental Science and Engineering, Donghua University, Shanghai 201620, CN
Source
Nature Environment and Pollution Technology, Vol 16, No 1 (2017), Pagination: 37-43Abstract
Studying the impacts of PM2.5 concentrations is critical due to health risks associated with PM2.5. This study analyses 2001-2010 provincial panel data of population-weighted PM2.5 exposure and its main sources in China to identify any correlations that may exist. The results show that energy consumption, highway length, and construction positively affect population-weighted PM2.5 exposure, but vehicle possession has a negative effect. Increasing energy consumption, highway length, and construction areas by 1% resulted in 0.11%, 0.12%, and 0.06% increases to PM2.5 population exposure, respectively. However, when vehicle possession increased by 1%, population exposure to PM2.5 decreased by 0.20%. Highway length may be a very important factor for the increased PM2.5 concentrations in China. Therefore, China should consider national and provincial factors when developing policies to control PM2.5 emissions.Keywords
Population-Weighted, PM2.5 Exposure, Energy Consumption, Highway Length, Construction Area, Panel Data Analysis.- Determining Method of Backfill Strength Based on Damage Constitutive Model
Abstract Views :79 |
PDF Views:0
Authors
Affiliations
1 College of Resources & Civil Engineering, Northeastern University, Shenyang 110 819., CN
1 College of Resources & Civil Engineering, Northeastern University, Shenyang 110 819., CN
Source
Journal of Mines, Metals and Fuels, Vol 66, No 3 (2018), Pagination: 199-202Abstract
Backfill strength and ratio determining is one of the key for the stage of open stoping with subsequent filling mining method. Since some problems occur when adopting traditional method to determine filling strength, it is necessary to explore a more scientific approach to study reasonable match between backfill strength and rock mass. ZhongGuan iron mine’s backfill were subjected to laboratory mechanics test, and their stress-strain curves were obtained, backfill's damage constitutive models before peak stress were established by using damage mechanics. According to the principle that the peak deformation energy of backfill should be corresponded to releasing energy from excavated rock mass, the optimum backfill strength and ratio of ZhongGuan iron mine were determined, which plays a significant role in fill mining production on site.Keywords
No KeywordsReferences
- Jones, H. and Boger, D. V. (2012): “Sustainability and waste management in the resource industries [J].” Ind. Eng. Chem. Res., 2012, 51 (30): 10057-10065.
- Kermani, M., Hassani, F. P. and Aflaki, E. et al. (2015): “Evaluation of the effect of sodium silicate addition to mine backfill, Gelfill - Part 1 [J].” Journal of Rock Mechanics and Geotechnical Engineering, 2015, 7(3): 266-272.
- Li, Li. (2013): “A new concept of backfill designApplication of wick drains in backfilled stopes.” International Journal of Mining Science and Technology, 2013, 23(5): 763-770.
- Cai, Si-jing, Huang, Gang and Wu, Di, et al. (2015): “Experimental and Modeling Study on the Rheological Properties of Tailings Backfill [J].” Journal of Northeastern University:Natural Science, 2015, 36(6): 882-886.
- Belem, Tikov and Benzaazoua, Mostafa (2008): “Design and Application of Underground Mine Paste Backfill Technology [J].” Geotechnical and Geological Engineering, 2008, 26(2): 147-174.
- Zhang, Fa-wen, Liu, Wen-xia and Shen, Lian-feng (2012): Damage constitutive model for cemented paste backfill after mixing waste rock [C]//2012 World Automation Congress (WAC). Puerto Vallarta: IEEE, 2012: 1-4.
- Yu, Gen-bo, Yang, Peng and Chen, Yin-zhou (2013): “Study on Damage Constitutive Model of Cemented Tailings Backfill under Uniaxial Compression [J].” Applied Mechanics and Materials, 2013, 353-356: 379-383.
- Zhang, Qian-gui, Yin, Guang-zhi and Fan, Xiang-yu, et al. (2012): “A damage constitutive model of tailings based on the analysis of elastic-plastic and sliding of skeleton grains [J].” Disaster Advances, 2012, 5(4): 730-735.
- Liu, Zhi-xiang, Li, Xi-bing and Dai, Ta-gen, et al. (2006): “On damage model of cemented tailings backfill and its match with rock mass [J].” Rock and Soil Mechanics, 2006, 27(9):1442-1446.
- Xue, Zhi-cheng, Yang, Lu and Yang, Zeng-jie (2010): A damage model with subsection curve of concrete and its numerical verification based on ABAQUS[C]// 2010 International Conference on Computer Design and Applications (ICCDA), Qinhuangdao: IEEE, 2010, 5:34-37.
- Lemaitre, J. (1984): “How to use damage mechanics [J].” Nuclear Eang. & Design, 1984, 80(1):233-245.
- Liu, Zhi-xiang, Lan, Ming and Xiao, Shi-You, et al. (2015): “Damage failure of cemented backfill and its reasonable match with rock mass [J].” Transactions of Nonferrous Metals Society of China, 2015, 25(3): 954-959.
- Liu, Yu-long, Ding, De-xing and Li, Guang-yue, et al. (2013): “Match between the solidification of the cemented backfill and the vertical stress in the excavated ore body [J].” Journal of Mining and Safety Engineering, 2013, 30(4):526-530.