Research and application of a novel selective stacking ensemble model based on error compensation and parameter optimization for AQI prediction.

With the ongoing process of industrialization, the issue of declining air quality is increasingly becoming a critical concern. Accurate prediction of the Air Quality Index (AQI), considered as an all-inclusive measure representing the extent of pollutants present in the atmosphere, is of paramount importance. This study introduces a novel methodology that combines stacking ensemble and error correction to improve AQI prediction. Additionally, the reptile search algorithm (RSA) is employed for optimizing model parameters. In this study, four distinct regional AQI data containing a collection of 34864 data samples are collected. Initially, we perform cross-validation on ten commonly used single models to obtain prediction results. Then, based on evaluation indices, five models are selected for ensemble. The results of the study show that the model proposed in this paper achieves an improvement of around 10% in terms of accuracy when compared to the conventional model. Thus, the model introduced in this study offers a more scientifically grounded approach in tackling air pollution.

A multi-scale evolutionary deep learning model based on CEEMDAN, improved whale optimization algorithm, regularized extreme learning machine and LSTM for AQI prediction.

With the rapid development of economy, air pollution occurs frequently, which has a huge negative impact on human health and urban ecosystem. Air quality index (AQI) can directly reflect the degree of air pollution. Accurate AQI trend prediction can provide reliable information for the prevention and control of air pollution, but traditional forecasting methods have limited performance. To this end, a dual-scale ensemble learning framework is proposed for the complex AQI time series prediction. First, complete ensemble empirical mode decomposition adaptive noise (CEEMDAN) and sample entropy (SE) are used to decompose and reconstruct AQI series to reduce the difficulty of direct modeling. Then, according to the characteristics of high and low frequencies, the high-frequency components are predicted by the long short-term memory neural network (LSTM), and the low-frequency items are predicted by the regularized extreme learning machine (RELM). At the same time, the improved whale optimization algorithm (WOA) is used to optimize the hyper-parameters of RELM and LSTM models. Finally, the hybrid prediction model proposed in this paper predicts the AQI of four cities in China. This work effectively improves the prediction accuracy of AQI, which is of great significance to the sustainable development of the cities.

An evolutionary deep learning soft sensor model based on random forest feature selection technique for penicillin fermentation process.

Accurate and reliable measurement of key biological parameters during penicillin fermentation is of great significance for improving penicillin production. In this research context, a new hybrid soft sensor model method based on RF-IHHO-LSTM (random forest-improved​ Harris hawks optimization-long short-term memory) is proposed for penicillin fermentation processes. Firstly, random forest (RF) is used for feature selection of the auxiliary variables for penicillin. Next, improvements are made for the Harris hawks optimization (HHO) algorithm, including using elite opposition-based learning strategy (EOBL) in initialization to enhance the population diversity, and using golden sine algorithm (Gold-SA) in the search strategy to make the algorithm accelerate convergence. Then the long short-term memory (LSTM) network is constructed to build a soft sensor model of penicillin fermentation processes. Finally, the hybrid soft sensor model is used to the Pensim platform in simulation experimental research. The simulation test results show that the established soft sensor model, with high accuracy of measurement and good effect, can meet the actual requirements of engineering.

A review on proliferation of artificial intelligence in wind energy forecasting and instrumentation management.

Energy is the source of economic growth, and energy consumption indicates the country's state of development. Energy engineering is a relatively new technical discipline. It is increasingly considered as a significant step in meeting carbon reduction targets, which can produce a variety of appealing outcomes that are useful to humanity's evolution. Many countries have adopted national policies to decrease pollution by reducing fossil fuel use and increasing renewable energy usage by alleviating climate change (wind and solar, etc.). The ever-growing need for renewable sources has led to economic and technological problems, such as wind energy, essential for effective grid control, and the design of a wind project. Precise estimates offer network operators and power system designers vital information for the generation of an appropriate wind turbine and controlling demand and supply power. This work provides an in-depth study of the proliferation of artificial intelligence (AI) in the prediction of wind energy generation. The devices employed to calculate wind speed are examined and discussed, with a focus on studies recently published. This review's findings show that AI is being employed in power wind energy measurement and forecasts. When compared to individual systems, the hybrid AI system gives more accurate findings. The discussion also found that correct handling and calibration of the anemometer can increase predicting accuracy. This conclusion suggests that increasing the accuracy of wind forecasting can be accomplished by lowering equipment errors that measure the meteorological parameter and mitigate carbon emission.

Binder-Free Porous 3D-ZnO Hexagonal-Cubes for Electrochemical Energy Storage Applications.

Considerable efforts are underway to rationally design and synthesize novel electrode materials for high-performance supercapacitors (SCs). However, the creation of suitable materials with high capacitance remains a big challenge for energy storage devices. Herein, unique three-dimensional (3D) ZnO hexagonal cubes on carbon cloth (ZnO@CC) were synthesized by invoking a facile and economical hydrothermal method. The mesoporous ZnO@CC electrode, by virtue of its high surface area, offers rich electroactive sites for the fast diffusion of electrolyte ions, resulting in the enhancement of the SC's performance. The ZnO@CC electrode demonstrated a high specific capacitance of 352.5 and 250 F g-1 at 2 and 20 A g-1, respectively. The ZnO@CC electrode revealed a decent stability of 84% over 5000 cycles at 20 A g-1 and an outstanding rate-capability of 71% at a 10-fold high current density with respect to 2 A g-1. Thus, the ZnO@CC electrode demonstrated improved electrochemical performance, signifying that ZnO as is promising candidate for SCs applications.

Persistence, transmission, and infectivity of SARS-CoV-2 in inanimate environments.

Currently, the emergence of a novel coronavirus, referred to as SARS-CoV-2, has become a global health concern which cause severe respiratory tract infections in humans. Person-to-person transmission of SARS-CoV-2 has occurred across the globe, within a short period of SARS-CoV-2 emergence. The goal of this analysis is to summarize in various inanimate surfaces and environments information about the frequency, persistence, potential dissemination, and infectivity of SARS-CoV-2. Most respiratory viruses, including coronaviruses, SARS-CoVs, or influenza may persist for a few days on the surfaces or objects. The length of tenacity on various inanimate surfaces depends on the environmental and growth conditions and overall survival rate could range from minutes to month time. The SARS-CoV-2 may survive and maintain infectivity in the air in unventilated buses for 30 â€‹min. As no specific vaccines or therapeutic drugs are available for this contagious virus, timely prevention measures would be crucial to control the future outbreak of this infectious disease. Precautionary strategies such as wearing masks and frequent washing hands are effective to mitigate COVID-19. Following careful consideration of the above-mentioned scenarios, the short review spotlights the pressing environmental issues regarding the persistence, transmission, and infectivity of SARS-CoV-2 in different environmental matrices. Aiming to address this issue with further and deeper insight into the SARS-CoV-2 emergence, a list of most concerned questions is given that should be carefully considered and answered in future studies.

Water matrices as potential source of SARS-CoV-2 transmission - An overview from environmental perspective.

Evidently, the emergence of novel coronavirus disease (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has rapidly blowout across the world. Since, the presence of coronaviruses, including SARS-CoV-2 in the fecal specimens and anal swabs of some infected patients, has raised emerging concern with the likelihood of fecal-based spread must be inspected and clarified. Therefore, herein, an effort has been made to spotlight the current scenarios and possible solutions to better understand the risks associated with the wastewater matrices as a potential source of SARS-CoV-2 transmission in the environment. The information reviewed here constitutes a paramount intellectual basis to sustenance ongoing research to tackle the SARS-CoV-2 issue. Thus, this overview indicates the most accessible frontiers related to the detection, quantification, and possible transmission of SARS-CoV-2 in the environment through water routes. The regulatory authorities and policymakers must assure the society via dissemination of evidence-based guidelines that the water matrices, including groundwater and drinking water resources are safe. Finally, we have identified and enlisted a number of pressing questions concerning the ongoing SARS-CoV-2 transmission or COVID-19 emergence issue that must be carefully answered to put further and deeper insight into SARS-CoV-2/COVID-19 in future studies.

Thermochemical and electrochemical aspects of carbon dioxide methanation: A sustainable approach to generate fuel via waste to energy theme.

Sustainable generation of green energy and fine chemicals from carbon dioxide (CO2) is the most desirable and promising route for justifying the atmospheric CO2 build-up and carbon sequestration. This additionally serves to mitigate or defer global warming and avoid serious climate change. Renewable carbon is a possible source to reduce CO2 emission and avoid the combustion of coal and petroleum products. In this context, there is a dire need to introduce modern industrial procedures to develop new carbon recycling strategies for CO2, like spent carbon from CO2. The role of diverse industrial processes for the proper utilization of renewable carbon would fruitfully simulate the natural procedure. For the past few decades, both heterogeneous and homogeneous catalysis approaches have been useful for the conversion of CO2. Still, unfortunately, none of them addressed the current safety needs, cost-effectiveness, efficiency, reaction conditions, and selectivity. This review signifies the thermochemical and electrochemical approaches for the useful conversion of CO2, in the presence of catalyst material, to some high-value products of industrial interests, such as fuels (methane). Furthermore, several suitable examples are discussed to represent the potential and perspective of these technologies. In summary, a highly efficient conversion of CO2 to fuels and related high-value chemicals would fulfill the rising demands of diverse sectors of the modern world.

Environmental impacts and risk factors of renewable energy paradigm-a review.

The transition to a low carbon society is dependent on renewable energy-based electrification. Nevertheless, energy programs have resulted in growing societal polarization in several regions. Therefore, around the globe, government and legislative authorities at the local, regional, national, and international levels are highly concerned about the environmental impacts and risk factors that influence the energy paradigm. Thus, to minimize and/or limit the environmental insecurity issues, the world needs swift and effective actions to secure the climate for a better tomorrow. Moreover, there is a dire need to look for new energy alternatives, along with reducing the complete dependence on petro-based energy sources. Keeping this burning issue in mind, herein, an effort has been made to present the potential of several renewable energy sources, including wind-based renewable energy, solar-based renewable energy, hydro-based renewable energy, and biomass-based renewable energy. Following a brief introduction of energy-related problems and opportunities, a comparative overview is given to renewable vs. non-renewable energy sources. Then, several renewable energy sources, including wind, solar, hydro, and biomass, along with the worldwide energy capacity of each energy source are given with suitable examples and statistics. Finally, risk factors, concluding remarks, and future guidelines are discussed towards the end.

Environmental perspectives of interfacially active and magnetically recoverable composite materials - A review.

Aquatic ecosystem contaminated with toxic pollutants and heavy metals due to the rapid growth of industrialization has become a top-priority global concern exhibiting highly adverse effects on human health and the environment. Many treatment techniques have been envisioned for the removal of these toxic contaminants from the aqueous environment. Among these techniques, magnetic separation has attracted burgeoning research attention owing to its simplicity, eco-friendly nature, large surface area, electron mobility, and excellent performance for removing water contaminants. In particular, interfacial active nanoparticles and nanocomposites with unique structures and magnetic properties are considered as ideal provides candidates in material science for next-generation water treatment. This review gives an insight into current research activities associated with the synthesis strategies and applications of interfacially active and magnetically responsive nanomaterials and nanocomposites for sustainable purification processes. In the first half, various synthesis routes for magnetic iron oxide nanoparticles development and the corresponding formation mechanism are summarized. In the second half, we reviewed the magnetic and wettability properties of interfacially active and magnetically responsive nanocomposites and their environmental applications including oil-water separation, removal of hazardous dye-based pollutants and potentially toxic heavy metals. Finally, the review is wrapped up with major concluding remarks and future perspectives of these magnetic nanoscale composite materials for sustainable wastewater remediation.

Environmental impact and pollution-related challenges of renewable wind energy paradigm - A review.

With ever increasing environmental and socio-economic awareness, government and legislative authorities, around the globe, are concerned and considering the pollution-related challenges and parameters that influence the energy paradigm. Therefore, renewable energy resources, for instance, wind, solar, and hydro- are used to generate electricity to reduce fossil-fuel-related environmental concerns. The world needs swift, equitable, significant, and effective climate action on this stage. The scientific evidence has been mounting for decades to employ renewable energy resources. One of these shared resources is wind energy, which currently appears as an emerging source of energy around the world. Electricity production using wind power schemes could be an essential replacement for conventional fossil-based fuel resources by using different modalities. Although the initial cost of installing a photovoltaic system is relatively high, however, the running cost is very low. Herein, we reviewed the environmental impact and considerable challenges of the technological paradigm for the development of wind energy technology with particular reference to Pakistan's future perspective. It is anticipated that the discussion provided can stimulate a negotiation between decision makers and raise attentiveness of environmental characteristics and a set of challenges related to the wind power industry development of Pakistan.