Application of environmental risk assessment for strategic decision-making in coastal areas: case studies in China

Environmental risk assessment (ERA) is a powerful technical tool for analyzing potential and extreme adverse environmental impacts, and has found wide application in supporting decision-making processes over the last two decades. However, to date there has been no interrelated application of ERA to support the processes of strategic decision-making (SDM), especially in coastal areas.

In this paper, we attempt to verify the feasibility of the proposed integrated ERA–SDM approach and its methodology by applying it to two case studies (in Xiamen Bay and Luoyuan Bay) of the principal coastal functional zoning (PCFZ, a kind of SDM and similar to the coastal and marine spatial planning in western). The results show that the integrated ERA–SDM approach could integrate ERA into the entire SDM process, directly support the PCFZ, and avoid or mitigate dire environmental risk that can be introduced by SDM processes.     

Comparative study on performances of a heat-pipe PV/T system and a heat-pipe solar water heating system

The heat-pipe solar water heating (HP-SWH) system and the heat-pipe photovoltaic/thermal (HP-PV/T) system are two practical solar systems, both of which use heat pipes to transfer heat. By selecting appropriate working fluid of the heat-pipes, these systems can be used in the cold region without being frozen. However, performances of these two solar systems are different because the HP-PV/T system can simultaneously provide electricity and heat, whereas the HP-SWH system provides heat only. In order to understand these two systems, this work presents a mathematical model for each system to study their one-day and annual performances. One-day simulation results showed that the HP-SWH system obtained more thermal energy and total energy than the HP-PV/T system while the HP-PV/T system achieved higher exergy efficiency than the HP-SWH system. Annual simulation results indicated that the HP-SWH system can heat the water to the available temperature (45°C) solely by solar energy for more than 121 days per year in typical climate regions of China, Hong Kong, Lhasa, and Beijing, while the HP-PV/T system can only work for not more than 102 days. The HP-PV/T system, however, can provide an additional electricity output of 73.019 kWh/m², 129.472 kWh/m², and 90.309 kWh/m² per unit collector area in the three regions, respectively.     

The determination and matching analysis of pinch point temperature difference in evaporator and condenser of organic rankine cycle for mixed working fluid

Exergo-economic analysis of the pinch point temperature difference (PPTD) in both evaporator and condenser of sub-critical organic Rankine cycle system (ORCs) are performed based on the first and second laws of thermodynamics. Taking mixture R13I1/R601a as a working fluid and the annual total cost per net output power Z as exergo-economic performance evaluation criterion, the effects of PPTD in evaporator ΔT_e, and the PPTD ratio of condenser to evaporator y, on the exergo-economic performance of ORCs are analyzed. Moreover, how some other parameters influence the optimal PPTD in evaporator ΔT_e,opt and the optimal PPTD ratio of condenser to evaporator y_opt are also discussed. It has been found that the exergo-economic performance of ORCs is remarkably influenced by ΔT_e and y, and there exists ΔT_e,opt and y_opt. In addition, ΔT_e,opt and y_opt are affected by heat transfer coefficient ratio of condenser to evaporator ß, the temperature of working fluid at dew point in condenser T_1a, and composition of R13I1/R601a: larger ß and T_1a lead to lower ΔT_e,opt and y_opt; by contraries, larger mass fraction of R13I1 makes ΔT_e,opt and y_opt increase, and y_opt increases linearly. The effects of the temperature of working fluid at bubble point in evaporator T_3a, mass flow rate of exhaust flue gas m_g, and inlet temperature of exhaust flue gas T_gi on ΔT_e,opt and y_opt are very slight. For comparison, three additional working fluids, namely R601a, R245fa, and 0.32R245fa/0.68R601a, are also taken into account.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.     

The fractionation and geochemical characteristics of rare earth elements measured in ambient size-resolved PM in an integrated iron and steelmaking industry zone

Environmental Science and Pollution Research - Improved understanding of the fractionation and geochemical characteristic of rare earth elements (REEs) from steel plant emissions is important due...     

Combined effects of nitrogen addition and organic matter manipulation on soil respiration in a Chinese pine forest

The response of soil respiration (Rs) to nitrogen (N) addition is one of the uncertainties in modelling ecosystem carbon (C). We reported on a long-term nitrogen (N) addition experiment using urea (CO(NH₂)₂) fertilizer in which Rs was continuously measured after N addition during the growing season in a Chinese pine forest. Four levels of N addition, i.e. no added N (N0: 0 g N m⁻² year⁻¹), low-N (N1: 5 g N m⁻² year⁻¹), medium-N (N2: 10 g N m⁻² year⁻¹), and high-N (N3: 15 g N m⁻² year⁻¹), and three organic matter treatments, i.e. both aboveground litter and belowground root removal (LRE), only aboveground litter removal (LE), and intact soil (CK), were examined. The Rs was measured continuously for 3 days following each N addition application and was measured approximately 3–5 times during the rest of each month from July to October 2012. N addition inhibited microbial heterotrophic respiration by suppressing soil microbial biomass, but stimulated root respiration and CO₂ release from litter decomposition by increasing either root biomass or microbial biomass. When litter and/or root were removed, the “priming” effect of N addition on the Rs disappeared more quickly than intact soil. This is likely to provide a point of view for why Rs varies so much in response to exogenous N and also has implications for future determination of sampling interval of Rs measurement.

     

Decoupling of nonferrous metal consumption from economic growth in China

Nonferrous metal is an important basis material for the development of the national economy, and its consumption directly affects economic development. It has great significance in the effective utilization of nonferrous metals, development of an environment-friendly society, and investigation of the decoupling of nonferrous metal consumption and GDP growth. The decoupling indicators for nonferrous metal consumption and GDP growth (D _r) in China from 1995 to 2010 were calculated in this study, and the results were analyzed. A productive model based on BP neural network was established. Then, the decoupling indicators for nonferrous metal consumption and GDP growth in China for the period of 2011–2020 were predicted. For the period of 1995–2010, the annual average decoupling indicators were <1 for copper, aluminum, zinc, lead, and nickel, except for tin, which was 0.21. The analysis showed that the decoupling of nonferrous metal consumption and GDP growth is in a less optimistic situation to copper, aluminum, zinc, lead, and nickel in China from 1995 to 2010. The annual average decoupling indicator for tin was 0.21, which indicates relative decoupling. For the period of 2011–2020, the predicted decoupling indicators for copper, aluminum, zinc, lead, nickel, and tin were between 0 and 1. This finding indicates the implementation of relative decoupling. However, the total consumption of nonferrous metals did not decouple from GDP growth.