Showing papers in "Environmental Progress in 2021"

How changes in human activities during the lockdown impacted air quality parameters: A review

Abstract: The health emergency linked to the spread of COVID-19 has led to important reduction in industrial and logistics activities, as well as to a drastic changes in citizens' behaviors and habits. The restrictions on working activities, journeys and relationships imposed by the lockdown have had important consequences, including for environmental quality. This review aims to provide a structured and critical evaluation of the recent scientific bibliography that analyzed and described the impact of lockdown on human activities and on air quality. The results indicate an important effect of the lockdown during the first few months of 2020 on air pollution levels, compared to previous periods. The concentrations of particulate matter, nitrogen dioxide, sulfur dioxide and carbon monoxide have decreased. Tropospheric ozone, on the other hand, has significantly increased. These results are important indicators that can become decision drivers for future policies and strategies in industrial and logistics activities (including the mobility sector) aimed at their environmental sustainability. The scenario imposed by COVID-19 has supported the understanding of the link between the reduction of polluting emissions and the state of air quality and will be able to support strategic choices for the future sustainable growth of the industrial and logistics sector.

Design and implementation of an islanded hybrid microgrid system for a large resort center for Penang Island with the proper application of excess energy

Abstract: The energy demand is growing daily at an accelerated pace due to the internationalization and development of civilization. Yet proper economic utilization of additional energy generated by the Islanded Hybrid Microgrid System (IHMS) that was not consumed by the load is a major global challenge. To resolve the above-stated summons, this research focuses on a multi-optimal combination of IHMS for the Penang Hill Resort located on Penang Island, Malaysia, with effective use of redundant energy. To avail this excess energy efficiently, an electrical heater along with a storage tank has been designed concerning diversion load having proper energy management. Furthermore, the system design has adopted the HOMER Pro software for profitable and practical analysis. Alongside, MATLAB Simulink had stabilized the whole system by representing the values of 2068 and 19,072 kW that have been determined as the approximated peak and average load per day for the resort. Moreover, the optimized IHMS is comprehended of Photovoltaic (PV) cells, Diesel Generator, Wind Turbine, Battery, and Converter. Adjacent to this, the optimized system ensued in having a Net Present Cost (NPC) of $21.66 million, Renewable Fraction (RF) of 27.8%, Cost of Energy (COE) of $0.165/kWh, CO2 of 1,735,836 kg/year, and excess energy of 517.29MWh per annum. Since the diesel generator lead system was included in the scheme, a COE of $0.217/kWh, CO2 of 5,124,879 kg/year, and NPC of $23.25 million were attained. The amount of excess energy is effectively utilized with an electrical heater as a diversion load.

Statistical estimation of hourly diffuse radiation intensity of Budapest City

Abstract: The vulnerability of fossil fuel prices to worldwide events such as the recent coronavirus (COVID‐19) pandemics increases the interest in renewable energy resources that offer more stable energy generation costs Solar energy is one of the most abundant renewable energy resources that have gained significant interest in the last decades with various challenges related to the forecastingof the energy production from these systems Solar radiation intensity varies due to the daily and seasonal changes in the sun's position in addition to the variation in the sky clearness from one location to another which is considered as an important factor that affects the deployment of solar energy systems This study aims to develop statistical models—mainly regression models and parametric model based on ASHRAE model—to estimate the hourly diffuse radiation in Budapest as a case study using the measured hourly global and diffuse radiation between 2011 and 2018 The prediction models relate the clearness index (which is obtained from the extraterrestrial and global radiation) and the global radiation through a generalized equation The parametric model was developed by finding the optimal site‐specific constants of ASHRAE model for Budapest using the measured data that minimize the root mean square error In addition, this study presents a comparison between the results from the developed models and the models reported in the literature The results indicate that all the developed regression models had close correlation coefficients (R2) where the linear, power, and exponential models had the largest R2 ( 69) Finally, the linear model was evaluated on a dataset outside the test data range where the linear model was capable of predicting the diffuse radiation with much better R2 ( 93)