ABSTRACT
The Changzhi Basin in Shanxi is renowned for its extensive mining activities. It's crucial to comprehend the spatial distribution and geochemical factors influencing its water quality to uphold water security and safeguard the ecosystem. However, the complexity inherent in hydrogeochemical data presents challenges for linear data analysis methods. This study utilizes a combined approach of self-organizing maps (SOM) and K-means clustering to investigate the hydrogeochemical sources of shallow groundwater in the Changzhi Basin and the associated human health risks. The results showed that the groundwater chemical characteristics were categorized into 48 neurons grouped into six clusters (C1-C6) representing different groundwater types with different contamination characteristics. C1, C3, and C5 represent uncontaminated or minimally contaminated groundwater (Ca-HCO3 type), while C2 signifies mixed-contaminated groundwater (HCO3-Ca type, Mixed Cl-Mg-Ca type, and CaSO4 type). C4 samples exhibit impacts from agricultural activities (Mixed Cl-Mg-Ca), and C6 reflects high Ca and NO3- groundwater. Anthropogenic activities, especially agriculture, have resulted in elevated NO3- levels in shallow groundwater. Notably, heightened non-carcinogenic risks linked to NO3-, Pb, F-, and Mn exposure through drinking water, particularly impacting children, warrant significant attention. This research contributes valuable insights into sustainable groundwater resource development, pollution mitigation strategies, and effective ecosystem protection within intensive mining regions like the Changzhi Basin. It serves as a vital reference for similar areas worldwide, offering guidance for groundwater management, pollution prevention, and control.
Subject(s)
Environmental Monitoring , Groundwater , Mining , Water Pollutants, Chemical , Groundwater/chemistry , Groundwater/analysis , China , Water Pollutants, Chemical/analysis , Humans , Environmental Monitoring/methods , Risk AssessmentABSTRACT
To eliminate the time shift of code edges on a single-sideband (SSB) modulation signal transmission in a radio-over-fiber (RoF) system, a new, to the best of our knowledge, SSB modulation scheme based on an optimal transmission point for a double-parallel Mach-Zehnder modulator (DP-MZM) is proposed. The scheme is based on DP-MZM to realize the separation of the carrier and the +1st-order sideband at the optimal transmission point, and the baseband signal modulates the 2.5 Gb/s data signal to the +1st-order sideband of the SSB signal; then, the carrier and the +1st-order sideband are transmitted with a carrier-to-sideband ratio of 0 dB. Theoretical analysis shows that compared to the traditional SSB-modulated optical millimeter-wave signal generation scheme this scheme completely solves the problem of the time shift of code edges caused by dispersion. The simulation results show that the improved SSB modulation scheme has a Q factor of 23.362, the minimum bit error rate is 4.207×10-127 at 73.453 km, and the eye diagram is still very clear. Under the premise of meeting the basic requirements of communications, the maximum communications distance can reach 135 km, which is 270% of the transmission distance of a traditional SSB modulation model. Thus, the system performance has been greatly improved.
ABSTRACT
The decoherence effect of a laser caused by a speckle field seriously restricts the development of heterodyne lidar. To address this problem, we proposed a spatial decoherence compensation algorithm, whose feasibility was proved by experiments with a system featuring simple structure and convenient operation. The results demonstrated that the speed of the proposed algorithm was several orders higher than that of other algorithms and the system SNR was increased by a maximum of 1464 times after the algorithm processing. The proposed algorithm can process the signal in real time and effectively, having great application potential in long-distance weak target detection.