Spatiotemporal distribution and prediction of chlorophyll-a in Ulansuhai lake from an arid area of China

Lake Ulansuhai, a typical shallow lake in an arid area that is economically and ecologically important along the Yellow River, is currently eutrophic. Long-term (2010–2020) data on chlorophyll-a, nutrient, and environmental factors were obtained from three Lake Ulansuhai monitoring stations. The temporal and spatial distribution characteristics of Chl-a were analyzed. Additionally, a hybrid evolutionary algorithm was established to simulate and predict Chl-a, and sensitivity analysis revealed the interaction between environmental factors and eutrophication. The results indicated that (1) the seasonal variation of eutrophication showed an obvious trend of spring > summer > autumn > winter, and the concentration of Chl-a in the inlet was significantly higher than that in the outlet; (2) The inlet, center, and outlet of Ulansuhai Lake are satisfactorily affected by HEA in the best suited method. The fitting coefficients (R2) of the optimal models were 0.58, 0.59, and 0.62 for the three monitoring stations, and the root mean square errors (RMSE) were 3.89, 3.21, and 3.56, respectively; (3) under certain range and threshold conditions, Chl-a increased with the increase of permanganate index, water temperature, dissolved oxygen concentration, and ammonia nitrogen concentration, but decreased with the increase of water depth, Secchi disk depth, pH, and fluoride concentration. The results indicate that the HEA can simulate and predict the dynamics of Chl-a, and identify and quantify the relationships between eutrophication and the threshold data. The research results provide theoretical basis and technical support for the prediction and have great significance for the improvement of water quality and environmental protection in arid and semi-arid inland lakes

Introduction to Special Issue - In-depth study of air pollution sources and processes within Beijing and its surrounding region (APHH-2 Beijing)

Abstract. The Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) programme is an international collaborative project focusing on understanding the sources, processes and health effects of air pollution in the Beijing megacity. APHH-Beijing brings together leading China and UK research groups, state-of-the-art infrastructure and air quality models to work on four research themes: (1) sources and emissions of air pollutants; (2) atmospheric processes affecting urban air pollution; (3) air pollution exposure and health impacts; and (4) interventions and solutions. Themes 1 and 2 are closely integrated and support Theme 3, while Themes 1-3 provide scientific data for Theme 4 to develop cost-effective air pollution mitigation solutions. This paper provides an introduction to (i) the rationale of the APHH-Beijing programme, and (ii) the measurement and modelling activities performed as part of it. In addition, this paper introduces the meteorology and air quality conditions during two joint intensive field campaigns - a core integration activity in APHH-Beijing. The coordinated campaigns provided observations of the atmospheric chemistry and physics at two sites: (i) the Institute of Atmospheric Physics in central Beijing, and (ii) Pinggu in rural Beijing during 10 November – 10 December 2016 (winter) and 21 May- 22 June 2017 (summer). The campaigns were complemented by numerical modelling and automatic air quality and low-cost sensor observations in the Beijing megacity. In summary, the paper provides background information on the APHH-Beijing programme, and sets the scene for more focussed papers addressing specific aspects, processes and effects of air pollution in Beijing

Influence and optimization of mooring angle in multi-point mooring positioning system

[Objectives] In this paper, a method for calculating the static restoring force of a mooring system is proposed in order to optimize the mooring angle and meet the strength requirements of mooring lines. [Methods] Using this method, a study is conducted on the influence of the mooring angle on the static restoring force and heading of the platform, and the tension uniformity of all mooring lines. An improved Genetic Algorithm (GA) is used to optimize the mooring angle, and the accuracy of the algorithm is enhanced in two ways:the first is that it can generate the initial population artificially by analyzing the influence of three factors(value of static restoring force, sensitivity of static restoring force to interference direction, and tension uniformity of all mooring lines);the second is that it strengthens the local search ability by combining an adaptive algorithm. [Results] The results show that the improved genetic algorithm has a higher optimization accuracy. The optimized results are fed back to the tension model of the mooring system, and the breaking strength requirements of the mooring lines are appropriately reduced. [Conclusions] This research can provide valuable references for mooring layout design and the material selection of mooring lines

An Efficient Opportunistic Routing Protocol with Low Latency for Farm Wireless Sensor Networks

Wireless sensor networks (WSN) can accurately and timely obtain the production information of crops, and provide data basis for intelligent agriculture. The dynamic crop state and unstable climate environment make it difficult to predict the connectivity probability of wireless links. Therefore, this paper studies an energy-saving opportunity routing transmission strategy under the influence of dynamic link interaction. The protocol establishes an importance model based on algebraic connectivity to reduce the energy consumption of network key nodes. At the same time, based on the improved Bellman–Ford algorithm, a method of constructing candidate sets is studied. It converts the opportunistic routing transmission cost of farm WSN into anycast link cost and the remaining opportunistic path cost affected by energy consumption. The priority queue is used to determine the nodes participating in the iteration, thereby reducing the computational overhead. The protocol also designs a backoff strategy considering the current residual energy to select the only forwarding node and reduce the unnecessary packet copies in the transmission process. Simulation results show that the studied method is superior to the existing opportunistic routing schemes in terms of packet overhead, network lifetime, energy consumption, and packet delivery rate

An Efficient Opportunistic Routing Protocol with Low Latency for Farm Wireless Sensor Networks

Wireless sensor networks (WSN) can accurately and timely obtain the production information of crops, and provide data basis for intelligent agriculture. The dynamic crop state and unstable climate environment make it difficult to predict the connectivity probability of wireless links. Therefore, this paper studies an energy-saving opportunity routing transmission strategy under the influence of dynamic link interaction. The protocol establishes an importance model based on algebraic connectivity to reduce the energy consumption of network key nodes. At the same time, based on the improved Bellman–Ford algorithm, a method of constructing candidate sets is studied. It converts the opportunistic routing transmission cost of farm WSN into anycast link cost and the remaining opportunistic path cost affected by energy consumption. The priority queue is used to determine the nodes participating in the iteration, thereby reducing the computational overhead. The protocol also designs a backoff strategy considering the current residual energy to select the only forwarding node and reduce the unnecessary packet copies in the transmission process. Simulation results show that the studied method is superior to the existing opportunistic routing schemes in terms of packet overhead, network lifetime, energy consumption, and packet delivery rate

Fault-Tolerant Topology of Agricultural Wireless Sensor Networks Based on a Double Price Function

Wireless sensor networks (WSN) enable the acquisition of multisource environmental data and crop states in precision agriculture. However, the complex agricultural environment causes the WSN topology to change frequently and link connection probability is difficult to predict. In order to improve the utilization of network resources and balance the network energy consumption, this paper studies an agricultural fault-tolerant topology construction method based on the potential game and cut vertex detection. Considering the connectivity redundancy, node lifetime, and residual energy, a fault-tolerant topology algorithm for agricultural WSN based on a double price function is designed. The network is clustered according to the node location and residual energy to form a single-hop effective cluster. Based on the network cluster, the price function is constructed in order to reduce energy consumption and balance network energy efficiency. The initial transmit power set supporting inter-cluster communication is obtained by potential game theory. While preserving the game characteristics of topology, the redundant links are eliminated and the transmit power is adjusted by a cut vertex detection algorithm to realize the construction of a 2-connected cluster head network. Simulation results show that the network topology constructed by the studied algorithm can balance the energy consumption and prolong the network lifetime effectively

Fault-Tolerant Topology of Agricultural Wireless Sensor Networks Based on a Double Price Function

Wireless sensor networks (WSN) enable the acquisition of multisource environmental data and crop states in precision agriculture. However, the complex agricultural environment causes the WSN topology to change frequently and link connection probability is difficult to predict. In order to improve the utilization of network resources and balance the network energy consumption, this paper studies an agricultural fault-tolerant topology construction method based on the potential game and cut vertex detection. Considering the connectivity redundancy, node lifetime, and residual energy, a fault-tolerant topology algorithm for agricultural WSN based on a double price function is designed. The network is clustered according to the node location and residual energy to form a single-hop effective cluster. Based on the network cluster, the price function is constructed in order to reduce energy consumption and balance network energy efficiency. The initial transmit power set supporting inter-cluster communication is obtained by potential game theory. While preserving the game characteristics of topology, the redundant links are eliminated and the transmit power is adjusted by a cut vertex detection algorithm to realize the construction of a 2-connected cluster head network. Simulation results show that the network topology constructed by the studied algorithm can balance the energy consumption and prolong the network lifetime effectively

Testing Study of Different Flow Direction and Structure for Air-Cooled Proton Exchange Membrane Fuel Cell

The air-cooled proton exchange membrane fuel cell is widely used in unmanned aerial vehicle since its small size and high efficiency. The bipolar plate structure is an important factor affecting the performance of fuel cells. This article conducts experimental research on the impact of different channel structures on performance based on the annular bipolar plate designed by the team. A single air-cooled fuel cell with 50cm2 is used in the experiment to investigate the dynamic response under different current loading rates of 0–40 A. The test results show that the hydrogen and oxygen in different flow directions have a significant impact on the performance of the fuel cell, with a performance improvement of 8.1% by the hydrogen and oxygen in vertical and staggered flow directions for the enhancement of heat and mass transfer ability, and a decrease of about 3.5° compared with the hot spot temperature. In addition, this study further demonstrated the applicability of the annular bipolar plate structure, and verified the impact of different channels on cathode side and ridge shaped structure on performance, wind speed, temperature distribution, stability and mass power density, of which the performance of the fan channel/linear ridge is the best, which is about 8.5% higher than the output power of the worst fan channel/fan back. These test results provide basic data and technical support for the system design and application of air-cooled fuel cell of open cathode

Classification, identification, and reservoir characteristics of intermediate mafic lava flows: a case study in Dongling area, Songliao Basin

Intermediate mafic lava is a special oil and gas reservoir. While its internal structure is an important factor affecting the reservoir properties, the identification of facies and understanding of the relationship between facies architecture and reservoir are limited. This study evaluated the intermediate mafic lava flows of the Yingcheng Formation in the Dongling area of Songliao Basin by analyzing drilling cores, corresponding thin sections, and scanning electron microscope (SEM) images, as well as well-logging and seismic attributes. We also performed helium gas experiments and high-pressure mercury intrusion (HPMI) analysis to assess the physical properties and pore structure of the reservoir, respectively. The results showed that intermediate mafic lava flows develop tabular lava flow, compound lava flow, and hyaloclastite. Three facies showed present diverse well-logging and seismic responses. The intermediate mafic lava facies architecture was divided into crater-proximal facies (CF-PF), medial facies (MF), and distal facies (DF), which were characterized by their vesicles and joints and could be identified through their seismic attributes. The reservoir spaces including vesicles, amygdale inner pores, joint fissures, and dissolution pores predominantly showed oil and gas accumulation. The results of the tests of the reservoir’s physical properties showed that the reservoir quality was best in the CF-PF, which is the main target of oil and gas exploration