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2022 ◽  
Author(s):  
Anthony Rey-Pommier ◽  
Frédéric Chevallier ◽  
Philippe Ciais ◽  
Grégoire Broquet ◽  
Theodoros Christoudias ◽  
...  

Abstract. Urban areas and industrial facilities, which concentrate most human activity and industrial production, are major sources of air pollutants, with serious implications for human health and global climate. For most of these pollutants, emission inventories are often highly uncertain, especially in developing countries. Spaceborne observations from the TROPOMI instrument, onboard the Sentinel-5 Precursor satellite, are used to measure nitrogen dioxide (NO2) slant column densities with a high spatial resolution. Here, we use two years of TROPOMI retrievals to map nitrogen oxides (NOx = NO + NO2) emissions in Egypt with a top-down model based on the continuity equation in steady state. Emissions are expressed as the sum of a transport term and a sink term representing the three-body reaction comprising NO2 and OH. This sink term requires information on the lifetime of NO2, which is calculated with the use of CAMS near-real-time temperature and hydroxyl radical (OH) concentration fields. The applicability of the OH concentration field is evaluated by comparing the lifetime it provides with the lifetime inferred from the fitting of NO2 line density profiles with an exponentially modified Gaussian function. This comparison, which is conducted for 39 samples of NO2 patterns above the city of Riyadh, provides information on the reliability of the CAMS near-real-time OH concentration fields; It also provides the location of the most appropriate vertical level to represent typical pollution sources in industrial areas and megacities in the Middle East. In Egypt, total derived emissions of NOx are dominated by the sink term. However, they can be locally dominated by wind transport, especially along the Nile where human activities are concentrated. Megacities and industrial regions clearly appear as the largest sources of NOx emissions in the country. Our top-down model produces emissions whose annual variability is consistent with the national electricity consumption. It is also able to detect lower emissions on Fridays, which are inherent to the social norm of the country, and to quantify the drop in emissions due to the COVID-19 pandemic. Overall, our indications of NOx emissions for Egypt are found to be 25.0 % higher than the CAMS-GLOB-ANT_v4.2 inventory, but significantly differ in terms of seasonality.


Author(s):  
Peng He ◽  
Chunyan Wang ◽  
Wanzhong Zhao ◽  
Weiwei Wang ◽  
Gang Wu ◽  
...  

State of energy (SOE) is a critical index of lithium battery. The problem of the inaccurate available energy and recovered energy of lithium battery affects the accuracy of SOE estimation. In order to solve the problem, this paper proposes a method to estimate the available discharge energy of lithium batteries based on response surface model. In this method, the energy efficiency of lithium batteries in different states is obtained by establishing the relationship model of external charge voltage and external discharge voltage, so as to estimate the actual available energy of lithium batteries in different charge states. On this basis, a correction method based on radial basis function (RBF) neural network is proposed to estimate the actual energy released by the recovered energy when the current direction of the battery is changed. The proposed energy correction method is combined with the adaptive particle filter algorithm to estimate SOE. This method is not limited to the assumption of Gaussian function and can accurately predict the noise variance, so as to improve the estimation accuracy of SOE. Simulations under urban dynamometer driving schedule (UDDS) are conducted, and the result shows that the proposed method can effectively estimate the battery energy and improve the accuracy of SOE estimation.


Author(s):  
Jun Zhang ◽  
Wei Xu ◽  
Peiwei Gao ◽  
Xingzhong Weng ◽  
Lihai Su

In order to reveal structural response law of emergency repair pavement under the airplane loading and verify the backfill material and structural applicability, two craters (Crater 1 composed of 2.4 m thick flying objects (FO) + 0.4 m thick graded crushed rocks (GCR) + 0.2 m thick roller compacted concrete + fibre reinforced plastic (FRP) course, and Crater 2 composed of 2.4 m thick FO + 0.6 m thick GCR + FRP course) were backfilled. Static and dynamic loads were applied using two airplanes. Results show that, laying FRP pavement layers reduced the maximum deflection of Crater 2 by 21%. Crater 1 and concrete pavement were both slightly rigid structures with a strong load transfer ability. The dynamic deflection basin curves of Crater 2 could be fit using a Gaussian function; while the curves of Crater 1 and concrete pavement could be fit using a quartic polynomial. Under static loading, the earth pressures of Crater 2 at −0.6 m, −0.4 m, and −0.2 m sites were 4.3, 9, and 9.6 times of those of Crater 1, respectively. At the −0.2 m site, the earth pressure of Crater 1 was 0.11 MPa, while that of Crater 2 reached 1.06 MPa. The research results can guide the rapid quality inspection and optimization design of emergency repair pavement structure and material.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Zhen Yang ◽  
Xuefei Xu ◽  
Keke Wang ◽  
Xin Li ◽  
Chi Ma

In order to accurately identify targets such as insulators, shock hammers, bird nests, and spacers on high-voltage transmission lines, this paper proposes a multitarget detection model for transmission lines based on DANet and YOLOv4. First, the DANet and YOLOv4 are fused to solve the difficulty in understanding the scene and the discrimination of pixels caused by the complex and diverse scenes of UAV’ (unmanned aerial vehicle) aerial images (lighting, viewing angle, scale, occlusion, and so on) so as to improve the significance of the detection target. Gaussian function and KL (Kullback–Leibler) divergence are used to improve the nonmaximum suppression in YOLOv4 so as to improve the recognition rate of occluded targets; the focal loss function and the balanced cross entropy function are used to improve the loss function of YOLOv4 in order to reduce the impact of not only the imbalance between the background and the detection target but also the imbalance among the samples, which is aimed at improving the accuracy of the detection. Then, a data set is made for the experiment by using the UAV inspection image provided by a power grid company in Eastern Inner Mongolia. Finally, the algorithm proposed in this paper is compared with other target detection algorithms. Experimental results show that the average detection accuracy of the proposed algorithm can reach 94.7%, and the detection time of each image is 0.05 seconds. The method has good accuracy, real-time, and robustness.


PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261418
Author(s):  
Hisatomo Waga ◽  
Hajo Eicken ◽  
Toru Hirawake ◽  
Yasushi Fukamachi

The Arctic is experiencing rapid changes in sea-ice seasonality and extent, with significant consequences for primary production. With the importance of accurate monitoring of spring phytoplankton dynamics in a changing Arctic, this study further examines the previously established critical relationship between spring phytoplankton bloom types and timing of the sea-ice retreat for broader temporal and spatial coverages, with a particular focus on the Pacific Arctic for 2003–2019. To this end, time-series of satellite-retrieved phytoplankton biomass were modeled using a parametric Gaussian function, as an effective approach to capture the development and decay of phytoplankton blooms. Our sensitivity analysis demonstrated accurate estimates of timing and presence/absence of peaks in phytoplankton biomass even with some missing values, suggesting the parametric Gaussian function is a powerful tool for capturing the development and decay of phytoplankton blooms. Based on the timing and presence/absence of a peak in phytoplankton biomass and following the classification developed by the previous exploratory work, spring bloom types are classified into three groups (under-ice blooms, probable under-ice blooms, and marginal ice zone blooms). Our results showed that the proportion of under-ice blooms was higher in the Chukchi Sea than in the Bering Sea. The probable under-ice blooms registered as the dominant bloom types in a wide area of the Pacific Arctic, whereas the marginal ice zone bloom was a relatively minor bloom type across the Pacific Arctic. Associated with a shift of sea-ice retreat timing toward earlier dates, we confirmed previous findings from the Chukchi Sea of recent shifts in phytoplankton bloom types from under-ice blooms to marginal ice zone blooms and demonstrated that this pattern holds for the broader Pacific Arctic sector for the time period 2003–2019. Overall, the present study provided additional evidence of the changing sea-ice retreat timing that can drive variations in phytoplankton bloom dynamics, which contributes to addressing the detection and consistent monitoring of the biophysical responses to the changing environments in the Pacific Arctic.


Author(s):  
William Menke ◽  
Roger Creel

ABSTRACT This article explains the features of differential data that make them attractive, their shortcomings, and the situations for which they are best suited. The use of differential data is ubiquitous in the seismological community, in which they are used to determine earthquake locations via the double-difference method and the Earth’s velocity structure via geotomography; furthermore, they have important applications in other areas of geophysics, as well. A common assumption is that differential data are uncorrelated and have uniform variance. We show that this assumption is well justified when the original, undifferenced data covary with each other according to a two-sided exponential function. It is not well justified when they covary according to a Gaussian function. Differences of exponentially correlated data are approximately uncorrelated with uniform variance when they are regularly spaced in distance. However, when they are irregularly spaced, they are uncorrelated with a nonuniform variance that scales with the spacing of the data. When differential data are computed by taking differences of the original, undifferenced data, model parameters estimated using ordinary least squares applied to the differential data are almost exactly equal to those estimated using weighed least squares applied to the original, undifferenced data (with the weights given by the inverse covariance matrix). A better solution only results when the differential data are directly estimated and their variance is smaller than is implied by differencing the original data. Differential data may be appropriate for global seismic travel-time data because the covariance of errors in predicted travel times may have a covariance close to a two-sided exponential, on account of the upper mantle being close to a Von Karman medium with exponent κ≪12.


2021 ◽  
Vol 13 (24) ◽  
pp. 5018
Author(s):  
Xueying Li ◽  
Wenquan Zhu ◽  
Zhiying Xie ◽  
Pei Zhan ◽  
Xin Huang ◽  
...  

The accurate evaluation of shifts in vegetation phenology is essential for understanding of vegetation responses to climate change. Remote-sensing vegetation index (VI) products with multi-day scales have been widely used for phenology trend estimation. VI composites should be interpolated into a daily scale for extracting phenological metrics, which may not fully capture daily vegetation growth, and how this process affects phenology trend estimation remains unclear. In this study, we chose 120 sites over four vegetation types in the mid-high latitudes of the northern hemisphere, and then a Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A4 daily surface reflectance data was used to generate a daily normalized difference vegetation index (NDVI) dataset in addition to an 8-day and a 16-day NDVI composite datasets from 2001 to 2019. Five different time interpolation methods (piecewise logistic function, asymmetric Gaussian function, polynomial curve function, linear interpolation, and spline interpolation) and three phenology extraction methods were applied to extract data from the start of the growing season and the end of the growing season. We compared the trends estimated from daily NDVI data with those from NDVI composites among (1) different interpolation methods; (2) different vegetation types; and (3) different combinations of time interpolation methods and phenology extraction methods. We also analyzed the differences between the trends estimated from the 8-day and 16-day composite datasets. Our results indicated that none of the interpolation methods had significant effects on trend estimation over all sites, but the discrepancies caused by time interpolation could not be ignored. Among vegetation types with apparent seasonal changes such as deciduous broadleaf forest, time interpolation had significant effects on phenology trend estimation but almost had no significant effects among vegetation types with weak seasonal changes such as evergreen needleleaf forests. In addition, trends that were estimated based on the same interpolation method but different extraction methods were not consistent in showing significant (insignificant) differences, implying that the selection of extraction methods also affected trend estimation. Compared with other vegetation types, there were generally fewer discrepancies between trends estimated from the 8-day and 16-day dataset in evergreen needleleaf forest and open shrubland, which indicated that the dataset with a lower temporal resolution (16-day) can be applied. These findings could be conducive for analyzing the uncertainties of monitoring vegetation phenology changes.


2021 ◽  
Vol 11 (23) ◽  
pp. 11575
Author(s):  
Fengqin Zhu ◽  
Oleg E. Gulin ◽  
Igor O. Yaroshchuk

In this study, the problem of the influence of a horizontally inhomogeneous liquid bottom impedance, given by random Gaussian function of the speed of sound and by density, on the propagation of low-frequency sound in a shallow-water waveguide is considered. The model parameters are referenced to the conditions of sound propagation in the regions of the seas of the Russian Arctic shelf. By the example of statistical modeling of the sound field intensity, we show that sound speed fluctuations in the bottom lead to similar effects that were previously established for volumetric fluctuations of the speed of sound in the water layer. With the distance from the source, the decrease in the average intensity slows down in comparison with a deterministic medium in which there are no fluctuations. This deceleration of the decay of the intensity in a random waveguide can be significant already at short distances. Changes in the law of decay of intensity at a fixed frequency are mainly determined by the correlation radius of inhomogeneities and the average penetrability of the bottom, which leads to attenuation of sound propagating in the waveguide.


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