Key Issues for Realizing Open Ecoacoustic Monitoring in Australia

Many organizations are attempting to scale ecoacoustic monitoring for conservation but are hampered at the stages of data management and analysis. We reviewed current ecoacoustic hardware, software, and standards, and conducted workshops with 23 participants across 10 organizations in Australia to learn about their current practices, and to identify key trends and challenges in their use of ecoacoustics data. We found no existing metadata schemas that contain enough ecoacoustics terms for current practice, and no standard approaches to annotation. There was a strong need for free acoustics data storage, discoverable learning resources, and interoperability with other ecological modeling tools. In parallel, there were tensions regarding intellectual property management, and siloed approaches to studying species within organizations across different regions and between organizations doing similar work. This research contributes directly to the development of an open ecoacoustics platform to enable the sharing of data, analyses, and tools for environmental conservation.

The Drivers and Barriers of Corporate Social Responsibility: A Comparison of the MENA Region and Western Countries

(1) Although numerous articles have been published to address the drivers or barriers of corporate social responsibility (CSR), some parts of the world have received less attention. In this study, I reviewed the literature from 2010 to 2021 to identify drivers and barriers of CSR in the Middle East and North Africa (MENA) region and compare them with the findings in Western countries. (2) Methods: For this study, I used a structured literature review method. By setting the inclusion and exclusion criteria, only 28 articles remained from the selected database. (3) Results: The findings revealed that some CSR drivers, such as leadership styles, profitability, reputation, moral commitment, and environmental conservation, are common in both regions. There are also some differences between CSR drivers, for example, religious beliefs, low concentration of ownership, and company characteristics are some of the drivers in the MENA region. Maintaining social license to operate, and avoiding the risks of community opposition, pressure from the government, and consumer demand tend to be more important in Western countries. Common barriers in both regions are lack of financial resources, cost, lack of CSR knowledge and awareness, and ownership concentration. This review also highlighted that lack of law enforcement, lack of stakeholder communication, lack of management commitment, lack of interests, corruption, and financial debts are some of the barriers of CSR addressed in the MENA region, whereas cost/benefit ratio, lack of customer interest, and lack of scientific frameworks are special barriers in Western countries. (4) Conclusions: Although researchers in Western countries have more focus on the energy sector, there is a lack of research about the drivers and barriers of CSR in the MENA region in several industries, including oil and gas.

Urbanization and carbon dioxide (CO2) emission nexus in the CEMAC countries

PurposeThis study investigates the relationship between urbanization and carbon dioxide emission in the Central African Economic and Monetary Community from 1990 to 2019. The literature reveals that the relationship between urbanization and carbon dioxide emissions is still debatable and the existing findings are inconclusive.Design/methodology/approachCarbon dioxide is the regressand; while, urbanization, gross domestic product (GDP) and financial development (FD), rule of law (ROL) and government effectiveness (GEF) are the regressors. Johansen Fisher and Kao residual co-integration tests alongside the fully modified and dynamic ordinary least squares.FindingsThe results show a significant positive relationship between urbanization and carbon dioxide emissions. The causality tests results show that carbon dioxide granger causes urbanization, GDP and FD unit directionally.Research limitations/implicationsThe countries' governments should effectively improve their legal systems to regulate carbon dioxide emissions. Urbanization laws should be implemented to limit urbanization environmental deteriorating effects on carbon dioxide emissions. This occurs as the countries practiced unregulated urbanization which increases population's environmental impacts. The study recommends sustainable green urbanization policies for environmental conservation through tree planting and horticulture. Balance development in urban and rural areas is vital to decongest the urban cities' pressure in the states. The governments should motivate the private sector with rural investments captivating policies to limit rural urban migration.Originality/valueThe findings contribute value by supporting a positive link between urbanization and carbon dioxide emissions in the CEMAC zone. The causality tests findings confirm the view that carbon dioxide granger causes urbanization, GDP and FD unit directionally. This value addition is essential to the governments and policy makers to mitigate urbanization and carbon dioxide emissions in the CEMAC region.

Biophotocatalytic Reduction of CO2 in Anaerobic Biogas Produced from Wastewater Treatment Using an Integrated System

This study presents the bio-photocatalytic upgrading of biogas utilising carbon dioxide (CO2) as a potential option for beginning fossil fuel depletion and the associated environmental risks in the pursuit of sustainable development. Herein, magnetite photocatalyst (Fe-TiO2) was employed with an integrated anaerobic-photomagnetic system for the decontamination of municipality wastewater for biogas production. The Fe-TiO2 photocatalyst used, manufactured via a co-precipitation technique, had a specific surface area of 62.73 m2/g, micropore volume of 0.017 cm3/g and pore size of 1.337 nm. The results showed that using the ultraviolet-visible (UV-Vis) photomagnetic system as a post-treatment to the anaerobic digestion (AD) process was very effective with over 85% reduction in colour, chemical oxygen demand (COD) and turbidity. With an organic loading rate (OLR) of 0.394 kg COD/L·d and hydraulic retention time (HTR) of 21 days, a 92% degradation of the organic content (1.64 kgCOD/L) was attained. This maximised the bioenergy production to 5.52 kWh/m3 with over 10% excess energy to offset the energy demand of the UV-Vis lamp. Assuming 33% of the bioenergy produced was used as electricity to power the UV-Vis lamp, the CO2 emission reduction was 1.74 kg CO2 e/m3, with good potential for environmental conservation.

Sustainable Electrochemical NO Capture and Storage System Based on the Reversible Fe2+/Fe3+-EDTA Redox Reaction

The removal of nitric oxide (NO), which is an aggregation agent for fine dust that causes air pollution, from exhaust gas has been considered an important treatment in the context of environmental conservation. Herein, we propose a sustainable electrochemical NO removal system based on the reversible Fe2+/Fe3+-ethylenediamine tetraacetic acid (EDTA) redox reaction, which enables continuous NO capture and storage at ambient temperature without the addition of any sacrificial agents. We have designed a flow-type reaction system in which the NO absorption and emission can be separately conducted in the individual reservoirs of the catholyte and anolyte with the continuous regeneration of Fe2+-EDTA by the electrochemical reduction in Fe3+-EDTA. A continuous flow reaction using a silver cathode and glassy carbon anode showed that the concentrations of Fe2+ and Fe3+-EDTA in the electrolyte were successfully maintained at a 1:1 ratio, which demonstrates that the proposed system can be applied for continuous NO capture and storage.

Analyzing relationships between air pollutants and Covid-19 cases during lockdowns in Iran using Sentinel-5 data

Introduction: Air quality improvement was an unparalleled environmental consequence of the Covid-19 global crisis in many regions. Numerous researches have been conducted on the influence of national quarantines on air pollution and the relationship between the abundance of infected cases and mortality caused by this pandemic with air pollutants; however, these investigations are limited in Iran. The present study aims to investigate the correlation between Covid-19 cases and air pollution from a statistical viewpoint in order to evaluate the performance of multiple national lockdowns from February 2020 to August 2021 through measuring changes in air pollutants in the 31 provinces of Iran. Materials and methods: We applied a remote sensing method by employing Sentinel-5P satellite data to analyze changes in PM2.5, CO, and O3 during the three public quarantine periods and their two months earlier. Results: We recognized a considerable positive correlation between PM2.5 and the infected cases (r=0.63, p=0.001) and victims (r=0.41, p=0.001). Moreover, we compared the efficiency of lockdowns and supposed lockdown 2 (November-December 2020) as an only effective quarantine due to a dramatic reduction in PM2.5 (21.2%), CO (0.8%), the infected cases (48.7%), and victims (66.9%) in comparison to the average of its next two months. Conclusion: Governments should handle the outbreak of Covid-19 by implementing efficient quarantines, as well as environmental conservation strategies.

Mapping Deforestation in Cerrado Based on Hybrid Deep Learning Architecture and Medium Spatial Resolution Satellite Time Series

Cerrado is the second largest biome in Brazil, covering about 2 million km2. This biome has experienced land use and land cover changes at high rates due to agricultural expansion so that more than 50% of its natural vegetation has already been removed. Therefore, it is crucial to provide technology capable of controlling and monitoring the Cerrado vegetation suppression in order to undertake the environmental conservation policies. Within this context, this work aims to develop a new methodology to detect deforestation in Cerrado through the combination of two Deep Learning (DL) architectures, Long Short-Term Memory (LSTM) and U-Net, and using Landsat and Sentinel image time series. In our proposed method, the LSTM evaluates the time series in relation to the time axis to create a deforestation probability map, which is spatially analyzed by the U-Net algorithm alongside the terrain slope to produce final deforestation maps. The method was applied in two different study areas, which better represent the main deforestation patterns present in Cerrado. The resultant deforestation maps based on cost-free Sentinel-2 images achieved high accuracy metrics, peaking at an overall accuracy of 99.81%±0.21 and F1-Score of 0.8795±0.1180. In addition, the proposed method showed strong potential to automate the PRODES project, which provides the official Cerrado yearly deforestation maps based on visual interpretation.