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In the realm of high-speed precision broadcasting, the existing seeder opener proves inadequate for the speed of the seeding operation. We focus on the duckbill opener and employ the quadratic regression orthogonal rotation combination test design method to optimize the structural parameters of the opener. Throughout the experiment, the primary performance metrics encompassed the opener's working resistance and the side dumping distance. The selected experimental factors comprised the penetration angle, the angle of soil entry gap, the shovel body width, and the shovel length. The optimal arrangement of structural parameters has been determined: a penetration angle, a soil entry gap angle, a shovel body width of 21 mm, and a shovel length of 142 mm. These parameters contribute to increased velocity, reduced operational resistance, and minimal soil disturbance. Under this combination, the relative deviations between the recorded measurements and the theoretical outcomes for working resistance and the side dumping distance stand at 4.24% and 1.06%, respectively; these confirm the credibility of the optimization results. We performed adaptability testing and conducted a comparative analysis under various operational conditions to assess the innovative opener's ability to reduce force, minimize soil disruption, and maintain depth stability. The findings are as follows: At a depth of 5 cm and velocities ranging from 6 km/h to 8 km/h, an average working resistance reduction of 19.73%, a 5.64% decrease in the side dumping distance, and an average depth stability of 89.5% were observed. When operated at a speed of 7 km/h with a depth ranging from 3 cm to 5 cm, an average reduction of 19.66% in operational resistance, a 2.59% decrease in the side dumping distance, and an average depth stability of 91.1% were recorded. These results illustrate the innovative opener's capacity to significantly reduce working resistance and side dumping distance while satisfying the depth stability requisites. [ABSTRACT FROM AUTHOR]

Excessive phosphorus in water would cause eutrophication and deterioration of the ecological environment. Herein, the La-MOFs/Al2O3 composite was successfully prepared by the in situ hydrothermal synthesis method for granulation, which was conducive to exerting the phosphate adsorption capacity and facilitating practical application. The materials were characterized by SEM, EDX, XRD, BET, FTIR, and Zeta. In addition, the adsorption performance of La-MOFs/Al2O3 was evaluated through adsorption kinetics and isotherms, showing that the Langmuir adsorption capacity was 16.34 mgP·g-1 (25 °C) and increased with the water temperature. Moreover, the batch influence experiments of intimal pH, adsorbent dosage, coexisting ions, and stability tests were performed to analyze the potential for practical applications and verified through the natural micro-polluted water samples from Houxi River and Bailu Lake (China). The results indicated that the La-MOFs/Al2O3 was suited to a wide pH range of 4 to 10 and the phosphate removal efficiency remained above 70% after continuous use for four times, exhibiting excellent stability. It also had excellent selectivity in the presence of SO42-, Cl-, NO3-, and HCO3-, only decreased to 70.24% at high HCO3- ion concentration of 60 mg/L, respectively. And the La-MOFs/Al2O3 had excellent adsorption of total phosphorus, phosphate, and organic phosphorus in the actual river and lake water and completely removed dissolved phosphorus. Finally, a phosphate adsorption mechanism model involved in electrostatic interaction and ligand exchange was proposed. Therefore, La-MOFs/Al2O3 could be considered to be an excellent phosphorus adsorbent for application in the actual water environmental remediation. [ABSTRACT FROM AUTHOR]

The heating methods currently used at oil delivery sites and transfer stations on North China Oilfield include electric bar heating, fuel oil heating, gas heating, etc. The traditional heating methods have adverse effect on energy conservation and environmental protection. They have low energy efficiency of heating and produces great pollution to the environment. The air source heat pump technology uses the heat in the air as the low-temperature heat source and transforms it to the high-temperature hot water, which will later serve as a heat tracing for crude oil gathering and transportation. No combustion effluent is produced in operation and the energy-saving effect is outstanding with high social-benefit.

Highly accurate data on the spatial distribution of ambient fine particulate matter (<2.5 μm: PM 2.5 ) is currently quite limited in China. By introducing NO₂ and Enhanced Vegetation Index (EVI) into the Geographically Weighted Regression (GWR) model, a newly developed GWR model combined with a fused Aerosol Optical Depth (AOD) product and meteorological parameters could explain approximately 87% of the variability in the corresponding PM 2.5 mass concentrations. There existed obvious increase in the estimation accuracy against the original GWR model without NO₂ and EVI, where cross-validation R² increased from 0.77 to 0.87. Both models tended to overestimate when measurement is low and underestimate when high, where the exact boundary value depended greatly on the dependent variable. There was still severe PM 2.5 pollution in many residential areas until 2015; however, policy-driven energy conservation and emission reduction not only reduced the severity of PM 2.5 pollution but also its spatial range, to a certain extent, from 2014 to 2015. The accuracy of satellite-derived PM 2.5 still has limitations for regions with insufficient ground monitoring stations and desert areas. Generally, the use of NO₂ and EVI in GWR models could more effectively estimate PM 2.5 at the national scale than previous GWR models. The results in this study could provide a reasonable reference for assessing health impacts, and could be used to examine the effectiveness of emission control strategies under implementation in China., Competing Interests: The authors declare no conflict of interest.

The real-time estimation of ambient particulate matter with diameter no greater than 2.5 μm (PM 2.5 ) is currently quite limited in China. A semi-physical geographically weighted regression (GWR) model was adopted to estimate PM 2.5 mass concentrations at national scale using the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth product fused by the Dark Target (DT) and Deep Blue (DB) algorithms, combined with meteorological parameters. The fitting results could explain over 80% of the variability in the corresponding PM 2.5 mass concentrations, and the estimation tends to overestimate when measurement is low and tends to underestimate when measurement is high. Based on World Health Organization standards, results indicate that most regions in China suffered severe PM 2.5 pollution during winter. Seasonal average mass concentrations of PM 2.5 predicted by the model indicate that residential regions, namely Jing-Jin-Ji Region and Central China, were faced with challenge from fine particles. Moreover, estimation deviation caused primarily by the spatially uneven distribution of monitoring sites and the changes of elevation in a relatively small region has been discussed. In summary, real-time PM 2.5 was estimated effectively by the satellite-based semi-physical GWR model, and the results could provide reasonable references for assessing health impacts and offer guidance on air quality management in China., Competing Interests: The authors declare no conflict of interest.