In the context of energy transformation and environmental governance, the development of the photovoltaic (PV) industry not only alleviates the conflict between energy using and environmental protection, but also provides wind and sand fixation services for the region. This paper firstly summarized the model of calculation on wind prevention and sand fixation service at home and abroad. Then we analyzed the modification and improvement of the Revised Wind Erosion Equation (RWEQ) model. In terms of the benefit accounting of wind prevention and sand fixation service in photovoltaic industry, this paper analyzed the research of experts in the field of ecosystem services evaluation, and summarized the research status and limitations of the benefit accounting related to wind prevention and sand fixation service in the photovoltaic industry. This paper provided recommendations on benefit accounting to improve the accuracy of ecosystem services assessments.
This study investigates the impact of urbanization on water efficiency using panel data from 31 provinces and cities in China from 2011 to 2021. By employing the spatial Dubin model, we examine the spatial heterogeneity and spatial agglomeration effects in water usage per 10,000 yuan of GDP. The findings reveal that urbanization in China significantly supports the improvement of water efficiency and exhibits spatial spillover effects. Moreover, the decomposition of spatial effects indicates that the indirect effects play a dominant role. These findings contribute to our understanding of the relationship between urbanization and water efficiency, providing valuable insights for water resource management and sustainable urban development.
Considering the potential risks of using reclaimed water, the uncertain relationship between the use of reclaimed water and the stability of the network of reclaimed water systems needs to be investigated. This study takes Beijing as the study area and uses relevant data affecting the demand, supply and use of reclaimed water from 2012 to 2020. A model of reclaimed water supply and demand was constructed using a system dynamics approach to characterize the changes in reclaimed water supply and demand from 2021 to 2050, and to identify changes in water use between the domestic, industrial and environmental sectors in economic, social and environmental scenarios. Based on the ecological network analysis method, the system metabolic efficiency, redundancy and sectoral relationship characteristics of the reclaimed water network were analyzed. This reveals the robustness of the reclaimed water system and the metabolic relationships between the sectors of the system, and assesses the role of different policy scenarios on the stability of the reclaimed water system. The results show that the error between the simulated and realistic values of the reclaimed water system is less than 10%. The established reclaimed water system dynamics model can provide accurate feedback on the causal relationship between reclaimed water variables and clarify the characteristics of the changes in reclaimed water supply and demand. The simulation showed that Beijing’s reclaimed water supply will increase slightly from 2013 to 2050 at a rate of 2.65%, which is much lower than the multi-year average growth rate of reclaimed water demand of 3.96%. The future increase in reclaimed water use will need to be achieved by upgrading the reclaimed water supply. This study analyses the reclaimed water consumption capacity under different policy contexts and provides a reference for water conservation in the industrial sector in Beijing.
Achieving a synergistic effect of carbon emission and pollution reduction is important to China. However, whether the low-carbon transformation measures can simultaneously achieve the reduction of industrial pollution remains unclear. This paper takes the low-carbon city pilots as a quasi-natural experiment, combining the time-varying difference in difference (DID) model and the spatial Durbin model to explore whether the low-carbon city policy can reduce industrial SO2 emissions. The results show that the low-carbon city policy significantly reduces local industrial SO2 emissions, but raises the emissions of neighboring cities. For the mechanism, the low-carbon city policy promotes green technology innovation to reduce industrial SO2 emissions. In addition, low-carbon city policy shows a spatial spillover effect by influencing local industrial enterprises and foreign direct investment to transfer to non-pilot cities.
Bus Rapid Transit (BRT) is a popular transit priority measure that is widely implemented. However, when BRT lanes are not frequently used, it can negatively impact the efficiency of signalized intersections, leading to increased vehicle fuel consumption and environmental pollution. This study proposes the innovative strategy of implementing shared BRT lanes at intersections to address these challenges, and evaluates its effectiveness using various metrics. The findings demonstrate that shared BRT lanes significantly improve traffic efficiency, reduce vehicle fuel consumption. Furthermore, this approach offers a sustainable solution by conserving energy resources and mitigating environmental pollution, thereby highlighting its practical applications in urban transportation planning.
Traditional building automation controllers are having low performance in dealing with non-linear phenomena. In recent years, model predictive control (MPC) has become a notable control algorithm for building automation system capable of handling non-linear processes. Performance of model-based controllers, such as MPC, is depending on reasonably accurate process models. For a building using baseboard radiator heater, a non-linear model is a more reliable representation of heat distribution system. Therefore, this study aims to present a non-linear gray-box model for a residential building connected to the local district heating network that is equipped with radiator heat emitters. The model is supposed to forecast the indoor air temperature as well as the radiator secondary return temperature. The model is validated using measurements collected from a building in Västerås, Sweden. In addition to a better accuracy, another motivation behind using a non-linear heating circuit model is to enhance its generalization performance. With the added benefits of accuracy and generalization, this model is expected to extend practical MPC implementation for such buildings.
Due to the current booming growth of electric vehicles (EVs), the insufficiency of charging infrastructure (CI) distributions has become one of the key obstacles to the potential expansion of the EV market. To further upgrade the Electric vehicles Charging infrastructure (EVCI) in the UK, governments have launched multiple incentives to encourage EVCI deployment and investment from the industry. In order to measure the effectiveness and feasibility of the current policies and seek other potential measurements, this paper applies an evolutionary game analysis integrated with complex network topologies, which aims to probe into the interactions and competitiveness between stakeholders. It contributes to practitioners and academia in the following aspects: (1) thorough insights into EVCI markets by modelling the evolution of EVCI distribution under heterogeneous incentives. (2) an equilibrium of EVCI deployment in the evolution process and elucidates the different impacts of incentives. (3) a whole network involving the main stakeholders, governments, EVCI investors, and end-users, facilitating an effective policy framework.
Accurate lithium-ion battery health estimation is crucial to ensure the safe and stable operation of energy storage battery systems. To address the problem of inaccurate battery state of health (SOH) estimation due to low sampling frequency and few stored data in the energy storage battery system, this paper proposes a battery capacity degradation trajectory reconstruction method based on convolutional neural network (CNN). Firstly, the battery capacity increment curves are analyzed to select the voltage segments with obvious differentiation for various degradation states of batteries. Secondly, the selected voltage-capacity segments in the first 30 cycles of batteries are input to a 3-layer CNN. Finally, the life-span capacity degradation curves are directly reconstructed without artificially feature selection and any voltage-capacity data after 30 cycles. The results show that the method has a high accuracy of capacity reconstruction with a mean absolute percentage error (MAPE) within 0.7%.
This paper proposes a state of charge (SOC) estimation model that combines data-driven method with model-based filtering method. Firstly, an improved arithmetic optimization algorithm (AOA) is employed to optimize the initial values of the long short-term memory (LSTM) network, and the optimized LSTM network is utilized for the preliminary estimation of SOC. Then, an adaptive unscented Kalman filter (AUKF) is employed to correct the SOC estimation results. Experimental results demonstrate that the proposed model achieves accurate and smooth SOC estimation while being able to quickly respond to initial SOC errors.
Urbanization is increasing the proportion of surface imperviousness, resulting in frequent urban waterlogging and in turn, triggers water pollution and ecological degradation. The establishment of low impact development (LID) facilities can effectively mitigate the impacts while generating multiple ecosystem service benefits, which is important in the context of climate change and dual carbon. This study proposes a many-objective optimization framework to optimize the layout of LID facilities. Firstly, the costs and ecosystem service benefits of different LID facilities are monetized to obtain the net cost. Secondly, runoff and water quality pollution are simulated to obtain the corresponding reduction and removal rates via the SWMM model. The total runoff control rate is combined with the net cost to form a dual-objective function. The optimal paving ratio layout of LID is acquired using the elite non-dominated sorted genetic algorithm (NSGA-II). Deterministic scenario simulation and optimization are carried out in Beijing Zijing Yayuan neighborhood as an example. The results show that the excess carbon released during construction of the permeable paving scenario increases net cost pressure, but its runoff reduction rates and water quality pollution removal rates perform well. The final optimization scenario can realize conflicting trade-offs between objectives, which can reduce direct cost inputs by up to 3.2*105 RMB and ecological compensation inputs by 1.5*105 RMB when the minimum total runoff control rate and pollutant removal rate are achieved. This study contributes to supporting decision-making stormwater management scenarios and highlights the effectiveness of permeability for flooding mitigation.