The levels of carbonyl compounds in Shanghai ambient air were measured in five periods from January 2007 to October 2007 (covering
winter, high-air-pollution days, spring, summer and autumn). A total of 114 samples were collected and eighteen carbonyls
were identified. Formaldehyde, acetaldehyde and acetone were the most abundant carbonyls and their mean concentrations of
19.40 ± 12.00, 15.92 ± 12.07 and 11.86 ± 7.04 μg m−3 respectively, in the daytime for five sampling periods. Formaldehyde and acetaldehyde showed similar diurnal profiles with
peak mixing ratios in the morning and early afternoon during the daytime. Their mean concentrations were highest in summer
and lowest in winter. Acetone showed reversed seasonal variation. The high molecular weight (HMW, ≥C5) carbonyls also showed
obvious diurnal variations with higher concentrations in the daytime in summer and autumn, while they were all not detected
in winter. Formaldehyde and acetaldehyde played an important role in removing OH radicals in the atmosphere, but the contribution
of acetone was below 1%. The carbonyls levels in high-air-pollution days were reported. More carbonyl species with higher
concentrations were found in high-air-pollution days than in spring. These carbonyls were transported with other pollutants
from north and northwest in March 27 to April 2, 2007 and then mixed with local sources. Comparing with Beijing and Guangzhou,
the concentrations of formaldehyde and acetaldehyde in Shanghai were the highest, which indicated that the air pollution in
Shanghai was even worse than expected. 相似文献
Results from PAMELA and ATIC indicate that the Kaluza-Klein type dark matter particles could be the annihilation source of the observed excess of electrons and positrons.Assuming the existence of a nearby black hole with 10000–100000 solar masses and a point source boost algorithm,we apply the standard propagation model and find that the results fit the data well. 相似文献
A reliable and accurate prediction of the tunnel boring machine(TBM) performance can assist in minimizing the relevant risks of high capital costs and in scheduling tunneling projects.This research aims to develop six hybrid models of extreme gradient boosting(XGB) which are optimized by gray wolf optimization(GWO), particle swarm optimization(PSO), social spider optimization(SSO), sine cosine algorithm(SCA), multi verse optimization(MVO) and moth flame optimization(MFO), for estimation of the TBM penetration rate(PR).To do this, a comprehensive database with 1286 data samples was established where seven parameters including the rock quality designation, the rock mass rating, Brazilian tensile strength(BTS), rock mass weathering, the uniaxial compressive strength(UCS), revolution per minute and trust force per cutter(TFC), were set as inputs and TBM PR was selected as model output.Together with the mentioned six hybrid models, four single models i.e., artificial neural network, random forest regression, XGB and support vector regression were also built to estimate TBM PR for comparison purposes.These models were designed conducting several parametric studies on their most important parameters and then, their performance capacities were assessed through the use of root mean square error, coefficient of determination, mean absolute percentage error, and a10-index.Results of this study confirmed that the best predictive model of PR goes to the PSO-XGB technique with system error of(0.1453, and 0.1325), R~2 of(0.951, and 0.951), mean absolute percentage error(4.0689, and 3.8115), and a10-index of(0.9348, and 0.9496) in training and testing phases, respectively.The developed hybrid PSO-XGB can be introduced as an accurate, powerful and applicable technique in the field of TBM performance prediction.By conducting sensitivity analysis, it was found that UCS, BTS and TFC have the deepest impacts on the TBM PR. 相似文献