Application of AHP – Entropy–TOPSIS methodology for soil heavy metal classification: Analysis of soil environment status in Jingshan as a case study

Given the complexity of the soil environment, the evaluation of soil pollution should consider the comprehensive weight of multiple evaluation factors to obtain highly objective and scientific conclusions. In this paper, two main ways are proposed to comprehensively analyze the degree of heavy metal pollution in the region: the combination of subjective weight (the analytic hierarchy process method) and objective weight (the entropy method) to determine the combination weight, and the use of the TOPSIS method to quantify the relative relationship between samples and the soil background values in the study area and analyze the spatial and geographical distribution of heavy metal elements in the samples.Analysis results show that the weight ranking of 31 out of 56 samples in the study area is higher than that based on the soil background value of Hubei Province, indicating that 55.36% of the samples had a comprehensive pollution degree lower than the soil background value of Hubei Province. According to the spatial distribution of heavy metal pollution, the soil pollution status in the study area is poor, and some parts are polluted by heavy metals to a certain extent.

Fractional Order Accumulation NGM (1, 1, k) Model with Optimized Background Value and Its Application

Aiming at the problem of unstable prediction accuracy of the classic NGM (1, 1, k) model, the modeling principle and parameter estimation method of this model are deeply analyzed in this study. Taking the minimum mean absolute percentage error as the objective function, the model is improved from the two perspectives of the construction method of the background value and the fractional order accumulation generation. The fractional order accumulation NGM (1, 1, k) model based on the optimal background value (short for the FBNGM (1, 1, k) model) is proposed in the study. The particle swarm optimization algorithm is used to estimate the parameters of the proposed model. Taking two actual cases with economic significance as examples, empirical analysis of the proposed model is conducted. The simulation and prediction results show the practicality and efficiency of the FBNGM (1, 1, k) model proposed in this study, which further broadens the application scope of the grey prediction model.

A New Circulating Accumulation Emission Model for Assessing Dust Emission From Open Pit Mine

In order to reduce the inaccuracy of using the monitoring data outside the pit to evaluate the unorganized emission dust source of open pit mine, the circulating accumulation emission model is established. Based on the model, the monitoring data in the pit can be converted into the dust emission from the pit. Main conclusions include: (1) the circulating accumulation emission model is suitable for the dust diffusion process in open pit mine. The model contains three part, which correspond to dust emission, retention and diffusion in open pit mine. (2) The initial value of the dust in the pit before the team operation has little influence on the final stable value. (3) The dust background value of surrounding environment monitored outside the pit can not be directly used. When the dust enters the pit, it will accumulate under the action of eddy current. To eliminate the effect of background value, the monitoring data should be subtracted by the accumulated value. (4) The dust emission from the pit can be calculated in a certain monitoring period based on the circulating accumulation emission model. Hence the dust emission assessment of open pit can be completed more efficiently based on this model.

Significant Decrease in Heavy Metals in Surface Sediment after Ten-Year Sustainable Development in Huaxi Reservoir Located in Guiyang, Southwestern China

In the Karst area of southwestern China, the heavy metals in the sediment of a reservoir are determined by both human activities and the high background values. Thus, this study explores the change of heavy metals in surface sediment after ten-year sustainable development in the upstream areas of a reservoir, Huaxi Reservoir, located in Guiyang of southwestern China, then evaluates the risk of these heavy metals to water environment systematically and finally identifies the sources in both 2019 and 2009. The results reveal that all of the measured heavy metals decrease dramatically and their spatial distributions change from the increase-decrease pattern to decrease-increase pattern, implying different locations of main source input. The risk indices based on the total or average content and relative or reference values have decreased to the lowest level. However, those indices calculated from the absolute content of each metalloid still show a low or a moderate risk because of the high background value, such as As and Cr. Moreover, although only one main source of heavy metals is identified in both 2019 and 2009, the risk from human activities still cannot be neglected because agricultural production and infrastructure construction would promote the weathering of soil and then these heavy metals from the soil will be brought into the reservoir with the rainfall-runoff process. The high background value of specific heavy metals, e.g., As and Cr would still exert some challenges to the water environment protections because the non-point source input of heavy metal cannot be controlled easily by promulgating a series of bans. These results provide important reference for creating the policies of water environment protection, especially in some Karst area of southwestern China that exhibits high background value of heavy metals.

A Novel Extrapolation-Based Grey Prediction Model for Forecasting China’s Total Electricity Consumption

Accurately forecasting China’s total electricity consumption is of great significance for the government in formulating sustainable economic development policies, especially, China as the largest total electricity consumption country in the world. The calculation method of the background value of the GM(1, 1) model is an important factor of unstable model performance. In this paper, an extrapolation method with variable weights was used for calculating the background value to eliminate the influence of the extreme values on the performance of the GM(1, 1) model, and the novel extrapolation-based grey prediction model called NEGM(1, 1) was proposed and optimized. The NEGM(1, 1) model was then used to simulate the total electricity consumption in China and found to outperform other grey models. Finally, the total electricity consumption of China from 2018 to 2025 was forecasted. The results show that China’s total electricity consumption will be expected to increase slightly, but the total is still very large. For this, some corresponding recommendations to ensure the effective supply of electricity in China are suggested.

Application of the Foreshock Traffic Light System to the 2019 Ridgecrest sequence

<p>The relative earthquake size distribution, or b-value of the Gutenberg and Richter relationship, can act as an indirect stress meter in the earth crust, a finding confirmed in numerous laboratory studies but also in diverse natural systems.  In 2018, we analysed the average size-distribution of about 60 well-monitored earthquakes sequences showing that, after a mainshock with M>=6, the b-value increases by about 20% respect to the background reference value.</p><p>In 2019, based on such result, we hypothesized and demonstrated that it may be possible, under specific circumstances, to discriminate if an ongoing sequence is representing a typically decaying aftershock sequence or rather foreshocks to an upcoming larger event.  We proposed a simple traffic light classification to assess in near real-time the level of concern for subsequent larger event, and tested it against 58 sequences, reaching a classification accuracy of 95%.</p><p>The Foreshock Traffic Light System (FTLS) has been implemented in a pseudo-prospective test to the 2019 Ridgecrest sequence. Results are fully in line with the hypothesis: in this Ridgecrest case study, after analyzing carefully the magnitude of completeness of the sequences, we find that in the hours after the first Mw6.4 Ridgecrest event, the b-value drops by 23% on average, when compared to the background value, resulting in a red foreshock traffic light. Spatially mapping the changes in b, we identify an area to the north of the rupture plane as the most likely location of a subsequent event. After the second, magnitude-7.1 mainshock, which did occur in the low b-value region, the b-value subsequently increased by 26% over the background value, triggering a green traffic light setting. Here we will report on these findings, discuss additional case studies, criticisms raised and discuss physics-based mechanics that may allow us to understand and model the observations.</p>

Characterization of gravity wave activity over the tropical band, using high resolution balloon measurements

<p>Tropical gravity wave activity is investigated using measurements of momentum flux obtained by superpressure balloons. The dataset contains 8 balloons that flew in the equatorial band from November 2019 to February 2020, for 2 to 3 months each, collecting data every 30s. The relation between gravity waves and deep convection was investigated using geostationary satellite data from the NOAA/NCEP GPM\_MERGEIR satellite data product, at 1 hour resolution. The amplitude of gravity wave momentum fluxes shows a clear dependence on the distance to the nearest convection site, with a strong decay as distance to convection increases. The largest values of momentum flux (more than 5 mPa) are only found in the vicinity of deep convection (< 200 km). The sensitivity to distance from convection is stronger for high frequency gravity waves (periods shorter than 30 minutes). Lower frequency waves tend to a non-zero, background value away from convection, supporting some background value in gravity-wave drag parameterizations. On the other hand, the wide range of momentum flux values close to the convection sites emphasizes the intermittent nature of gravity waves. This intermittency was also studied on a larger scale, using a 20° longitudinal grid of the recorded momentum flux in the deep tropics. The results highlight spatial variations of gravity wave activity, with the highest momentum flux recorded over the continent, and associated to higher intermittency.</p>