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The recommended power quality (PQ) indices in electric power systems are defined based on the discrete Fourier transform (DFT). DFT is mostly evaluated applying fast Fourier transform (FFT) algorithm which requires signals to be periodic in nature. Hence, it evaluates PQ indices accurately for stationary PQ disturbances only. However, in case of nonstationary PQ disturbances signal is aperiodic and FFT results in erroneous assessment due to spectral leakage phenomena. Furthermore, FFT cannot provide time information of the PQ indices as computation is performed in frequency domain only. Which is significant shortcoming of the FFT when dealing with time-varying PQ disturbances to extract dynamic signature of the signal. Thereby, this paper presents a framework of redefining PQ indices for stationary and nonstationary PQ disturbances employing time-frequency distribution (TFD) method. Among all TFDs, reduced interference distribution (RID) represents the most suitable properties for analyzing time-varying PQ disturbances. Hence, in this work, it is employed to reformulate PQ indices typically used in electric power systems. The results of two synthetic examples considering stationary and nonstationary PQ disturbances imply that the RID-based redefined PQ indices are closer to the actual values. Also, they provide more accurate results than the existing transient PQ indices and traditional FFT-based method.

Abstract Plant competitive interactions influence the effect of herbicides, and the effect of competitive interactions on plant responses may be important to include in the ecological risk assessment of herbicides. In the present study the effect of competitive interactions and sublethal doses of 2 herbicides on plant species was investigated in competition experiments and fitted to empirical competition models. Two nontarget species commonly found in agroecosystems (Centaurea cyanus L. and Silene noctiflora L.) and 2 herbicides (glyphosate and metsulfuron methyl) were used in separate experiments. Plants were sprayed at the 6- to 8-leaf stage. Effects of herbicide treatments and plant density were modeled by generalization of a discrete hyperbolic competition model. The 10% effective dose (ED10) was calculated for C. cyanus. All experiments showed that as density increased, plants were negatively affected. Furthermore, in all cases, C. cyanus remained a better competitor than S. noctiflora. Nevertheless, the density of S. noctiflora (competitor) was an influential element in determining the ED10 of C. cyanus measured at the mature stage. With herbicide exposure, the competitive interactions were further altered; C. cyanus was less affected by glyphosate when S. noctiflora increased to high density. In contrast, at the young stage, conspecific density was important in determining the sensitivity of C. cyanus to metsulfuron methyl, whereas the density of the competitor S. noctiflora had a limited influence. Overall, the results demonstrate the importance of integrating the effect of herbicide and species interactions measured at the reproductive stage into the ecological risk assessments of pesticides. Environ Toxicol Chem 2019;38:2053–2064. © 2019 SETAC.

Electric vehicles (EVs) are considered a substitute for fossil-fueled vehicles due to rising fossil fuel prices and accompanying environmental concerns, and their use is predicted to increase dramatically shortly. However, the widespread use of EVs and their large-scale integration into the energy system will present several operational and technological hurdles. In the energy industry, an innovative solution known as the EVs smart parking lot (SPL) is introduced to handle EV charging and discharging electricity and energy supply challenges. This paper investigates social equity access and mobile charging stations (MCSs) for EVs, where the owner of MCSs is the EV parking lot. Accordingly, a new self-scheduling model for SPLs is presented in this paper that incorporates scheduling of the MCSs as temporary charging infrastructures while considering social equity access and optimizes SPL energy generation and storage schedule. The main objectives of this research are to (i) develop MCSs accessibility measures and quantify the equity impacts of MCSs locations by modeling prioritized demand based on several indices; (ii) determine the optimal set-points of SPL components (i.e., combined heat and power (CHP), photovoltaic system, electrical and heat-energy storage, and MCSs) to manage electrical peak demand and to maximize the economic benefits of SPLs. Results indicate that the proposed demand prioritization function model can meet the required EV charging demands for prioritized events, and the self-scheduling model for SPLs satisfies the charging demand of the EVs in the SPL location. Also, the social equity access to the EV charging stations is satisfied by analyzing the operation of MCSs around the prioritized demand of the prioritized events and social equity access indices.

This paper presents a new approach to assess and improve the environmental and economic performance of integrated electricity and heat district energy systems in light of (i) optimal operation of available multi-energy components (e.g., cogeneration and heat pumps) and (ii) energy exchanges within the district through internal electricity and heat networks. The latter is particularly attractive as, instead of constraining energy flows within each building, it enables the production and consumption of energy in the most attractive locations (e.g., in buildings that can accommodate photovoltaic panels). The proposed methodology is formulated as a mixed integer linear programming problem, and demonstrated with a real UK district comprising internal electricity and heat networks and several buildings. The results highlight the attractiveness of optimising multiple energy vectors, particularly in light of energy exchanges between buildings, in economic and environmental terms.

Changes in weather patterns pose a threat to the serviceability and long-term performance of roads, and porous asphalt (PA) roads are particularly sensitive to the freezing-thawing (FT) phenomenon. The main objective of this research is to assess the impact of climate change, particularly freezing and thawing cycles, on PA. Climate models predict changes in air temperature, not pavement temperature. To predict the climate change impact on pavements performance, this requires first establishing a relationship between air and road temperature and a correlation between pavement performance and FT cycles. This project focuses on the Netherlands, where PA pavement use has become mandatory, and recent severe winters have increased the discussion about the cold weather performance of porous asphalt and the potential challenges of changing winter weather patterns. When considering long-term changes in climate, the cost impacts of freeze-thaw on PA pavement are predicted to vary regionally and in most areas reach a point in the middle of the century when a reactive wait-and-see approach is more advantageous than proactive adaptation. Further research is suggested to refine the relationship between observed damage and freeze-thaw impacts on PA pavement.

An experiment in open-top chambers was carried out in summer 2008 in Curno (northern Italy) in order to study the effects of ozone and drought stress on net photosynthesis, growth and stable isotope partitioning on cuttings of an ozone-sensitive poplar clone (Oxford). The biomass (as dry weight) of stems, leaves and roots was assessed five times during the growing season on a set of plants intended for destructive measurements (set 1). Another set of plants (set 2) was used for repeated measurements (net photosynthesis) and then destroyed at the end of the experiment. The dry weight of the stems in set 1 plants was calculated using allometric relations. The results showed that drought stress had a strong effect on all the parameters assessed. Ozone did not have any effect on biomass allocation in woody stems and stable isotope composition but reduced root/shoot ratios and caused loss of leaves during the growing season. The loss of leaves in the lower part of the crown was partly recovered with the emission of new young leaves in the upper part, thus restoring the overall photosynthetic apparatus. We conclude that the metabolic costs suffered to repair damage and support growth, and the reduction in starch reserves in the roots can compromise growth and the capacity to cope with stress factors in subsequent years.

The potential of renewable energy should be fully exploited in the transportation sector to achieve a cleaner production. Therefore, this paper proposes an on-grid hybrid hydrogen refueling and battery swapping station powered by wind energy. This novel concept can promote the development of low-carbon emission vehicles including hydrogen-based vehicle and battery electric vehicle. During the daily operation of the station, the multiple uncertainties may lead to a higher operational cost. To address this problem, a hybrid stochastic/distributionally robust optimization method is proposed to handle different uncertainties for the energy management problem. The first type of uncertainties can be depicted by a certain distribution, i.e. electricity price and wind power, which is processed by a stochastic optimization method. The second type of uncertainties is associated with human behaviors and is difficult to find its probability distribution, i.e. the hydrogen demand of hydrogen-based vehicles, so the second type is processed by a distributionally robust optimization method. The overall objective is to minimize the total operational cost of the station, which also considers the battery swapping station overstock punishment. Because a reasonable battery swapping scheduling can reduce the waiting time of users and operational cost of the station. The results indicate that the proposed method can effectively address the conservatism of solutions as its total operational cost is 4.4% lower than that of the hybrid stochastic/robust optimization method under a high confidence level.

This article combines two neglected elements within the history of online news: public service news sites and weather reporting, and it does so by utilising web archives, which – surprisingly – do not figure very prominently in journalism history. The two elements have – in isolation and in combination – at least in Denmark, become increasingly important as the online news sections of the two public service institutions Denmark’s Radio (DR) and TV2 consistently are among the most visited news sites and since reporting on the weather has gained in prominence and more recently, at least on DR TV, has become increasingly educational in its linking to issues of climate change. This article focusses on online news and conducts a historical analysis of the weather reporting on DR.dk from 2005 to 2022. The analysis seeks to balance the coding of journalistic texts with considerations of the online form of journalism, which here broadly means reading the webpage as a text. A key focus in the analysis is how meteorological data have been woven into cultural and social narratives, some of which are linked to climate change.