Short Communication
Jennifer Zheng
Abstract
The article delves into the overlooked long-term repercussions of oil spills on water ecosystems, particularly focusing on microbial communities and environmental recovery post-disasters. Highlighting five major US oil spills, it unveils how crude oil's enduring effects persist well beyond initial cleanup, ...
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The article delves into the overlooked long-term repercussions of oil spills on water ecosystems, particularly focusing on microbial communities and environmental recovery post-disasters. Highlighting five major US oil spills, it unveils how crude oil's enduring effects persist well beyond initial cleanup, impacting microbial foundations crucial for ecosystem health. As global energy demands surge, petroleum remains a primary source, emphasizing the dire environmental consequences of spills during transportation. While immediate impacts on species are extensively studied, the report probes into the extended aftermath, spotlighting the harm to marine phytoplankton—essential for Earth's carbon cycle.Revelations from disasters like the Exxon Valdez and Deepwater Horizon unveil remnants of crude oil that endure for decades, undermining microbial communities and hindering ecosystem revival. Such residues, trapped in sediments, disrupt oxygen and nutrient levels, impeding microbial degradation and slowing removal rates. Harmful algae blooms proliferate, disrupting ecosystems and posing risks to marine life and human health. The article emphasizes the cyclical harm: oil's persistence weakens beneficial microbes, exacerbating future damage from subsequent stressors.Examining compounded environmental disasters showcases the lasting impact on coastlines, with shoreline retreat and marsh ecosystem losses doubling post-spill. Such crises, examined through the lens of Hurricane Katrina's legacy, amplify erosion rates, permanently altering recovery baselines. The article underscores the need for intervention strategies, emphasizing the importance of replenishing microbial communities and reevaluating recovery tactics post-spills. It advocates for a shift towards cleaner energy sources to mitigate further harm to water ecosystems.
Review Paper
Pankoz Chandra Roy; Arifin Sultana; Md. Yeakub Ali
Abstract
This study examines the concept of data-driven smart ecological urbanism, which aims to promote sustainable and environmentally conscious urban growth through the use of data-driven technology. The authors offer a thorough review of the current literature on the topic, particularly highlighting the advantages ...
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This study examines the concept of data-driven smart ecological urbanism, which aims to promote sustainable and environmentally conscious urban growth through the use of data-driven technology. The authors offer a thorough review of the current literature on the topic, particularly highlighting the advantages and challenges of data-driven methodologies in urbanism. They argue that data-driven urbanism can offer invaluable insights into ecological concerns and pinpoint areas that require development. However, they also underscore concerns related to data privacy, over-reliance on technology, and potential unexpected outcomes. This study reveals the potential of data-driven smart ecological urbanism, emphasizing the necessity of a cautious and analytical approach to ensure its sustainable and socially equitable application. This paper suggests that adopting data-driven smart ecological urbanism can substantially improve a city's sustainability and livability by providing deeper insights into the ecological ramifications of urban expansion. The integration of data analytics and machine learning bolsters cities' capacity to deliver more accurate environmental forecasts, paving the way for targeted interventions that mitigate negative impacts and promote urban resilience, and sustainability. Nevertheless, the incorporation of data-driven technology in urban planning is not without challenges. For data-driven urbanism to truly embody social justice and sustainability, it is crucial to address issues related to data privacy and security, unforeseen consequences, and dependency on technology. Without a comprehensive analysis of these concerns, the application of data-driven smart ecological urbanism might inadvertently introduce adverse effects on marginalized communities and fall short of its potential in supporting sustainable urban growth.
ORIGINAL RESEARCH ARTICLE
Mayra Ivelisse Rodriguez Gonzalez; Kevin Gabriel Torres Garrido
Abstract
Geospatial data analytics is an essential tool in the toolbox of contemporary forest engineering and natural resource management. Beyond its application in estimating wood and fiber production, geospatial data analytics also proves indispensable in conservation planning. By leveraging a myriad of geospatial ...
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Geospatial data analytics is an essential tool in the toolbox of contemporary forest engineering and natural resource management. Beyond its application in estimating wood and fiber production, geospatial data analytics also proves indispensable in conservation planning. By leveraging a myriad of geospatial datasets, forest engineers and natural resource managers make well-informed decisions regarding forest restoration and carbon sequestration that foster environmental sustainability. However, one often-underestimated aspect of geospatial data analytics is its potential to help identify and address issues of distributive justice relating to forest resources and associated benefits. Thus, this article outlines a roadmap for forest engineers and natural resource managers to harness geospatial data effectively to simultaneously promote environmental sustainability and distributive justice – that is, the fair and equitable allocation of natural resources, nature’s benefits, and environmental burdens. The approach involves defining local concerns and priorities through community engagement to guide spatial data gathering, determining spatial and temporal scales of assessment, accessing and preprocessing data sources, developing prioritization indexes, performing relevant analytical tests, and creating opportunities for data return prior to decision making. Through this methodological approach, forest engineers and natural resource managers can harness the power of geospatial data to model and synthesize information, assess ecosystem services, evaluate community risks, and identify environmental hazards. In a world where data is abundant but its transformation into actionable insights is often lacking, this overview aims to illuminate the potential of geospatial data analytics as a tool that can simultaneously advance environmental sustainability and distributive justice.
ORIGINAL RESEARCH ARTICLE
Oketayo Oyedele Oyebamiji; Suaib Olaniyan; Peter Opeyemi Idowu; Oluwatosin Ojo; Joel Oladepo
Abstract
This study investigated the concentrations of ten heavy metals (Cd, Cu, Cr, Co, Fe, Mn, Ni, Pb, Zn, and As) in soil samples from goldsmith workshops in Otun-Ekiti, Nigeria, using Flame Atomic Absorption Spectrometry (FAAS). Control samples were also collected outside the workshops for comparison. The ...
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This study investigated the concentrations of ten heavy metals (Cd, Cu, Cr, Co, Fe, Mn, Ni, Pb, Zn, and As) in soil samples from goldsmith workshops in Otun-Ekiti, Nigeria, using Flame Atomic Absorption Spectrometry (FAAS). Control samples were also collected outside the workshops for comparison. The metal levels in the workshop samples ranged from 0.009 to 0.056 mg/kg for Cd, 6.418 to 34.598 mg/kg for Cu, 0.876 to 4.978 mg/kg for Cr, 0.024 to 0.229 mg/kg for Co, 766.744 to 1062.958 mg/kg for Fe, 16.089 to 27.539 mg/kg for Mn, 0.666 to 1.435 mg/kg for Ni, 2.075 to 2.987 mg/kg for Pb, 24.474 to 36.310 mg/kg for Zn, and 0.012 to 0.117 mg/kg for As. The metal levels in the workshop samples were higher than the control samples (significant at p < 0.05). Chromium (Cr) had the highest hazard quotient, while zinc (Zn) had the lowest. The hazard indices (HQ and HI) were below acceptable levels, indicating a low likelihood of non-carcinogenic health risks. However, workshops at sites 2, 3, and 4 posed a medium cancer risk with Incremental Lifetime Cancer Risk (ILCR) values. The heavy metals were slightly enriched in Fe, Mn, Ni, Pb, and Zn, except for Zn in site 1. Overall, the study found slight soil contamination with heavy metals, suggesting unsuitability for farming in these areas.
ORIGINAL RESEARCH ARTICLE
Endalew Jibat Gemede; Feyera Senbeta; Tesfaye Zeleke; Fitsum Hagos
Abstract
Water governance embraces value-related principles such as public participation, accountability, integrity, and transparency. This study aimed to assess whether water governance practices in the Central Rift Valley of Ethiopia address transparency, accountability, and participation in irrigation water ...
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Water governance embraces value-related principles such as public participation, accountability, integrity, and transparency. This study aimed to assess whether water governance practices in the Central Rift Valley of Ethiopia address transparency, accountability, and participation in irrigation water service delivery. Key informant interviews, focused group discussions, field observation, and document reviews were used to gather data for the study. The NVivo 11 software program was used to organize, code, and analyze the data. The result indicates that water policies were enacted and institutional reforms were undertaken to ensure integrity and accountability in water resources service delivery. However, the policy and legal frameworks were not fully implemented at the grassroots level. Mechanisms that enable diagnoses and prevent poor transparency and integrity did not exist in irrigation water service supply. Transparency tracking mechanisms were missed in the study area. Gender equity in water service delivery such as access to water and irrigation technologies for females remains unaddressed. Stakeholders’ participation in water governance was not consistent and systematized. Hence, promoting legal and institutional frameworks that ensure accountability, tools, and systematic mechanisms that ensure integrity and transparency, capacitating regulatory institutions and coherent participation strategies needs more emphasis in the study area.
ORIGINAL RESEARCH ARTICLE
Shantha Kumar Dhanush; Mahadeva M Murthy; Ayyappa Sathish; Rinku Verma
Abstract
A study was conducted on Gubbi Lake to investigate the water quality using water quality indices (WQI), multivariate statistical technique and geospatial technology. 20 lake water samples were collected during pre-monsoon and post-monsoon seasons for examining physicochemical parameters. The results ...
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A study was conducted on Gubbi Lake to investigate the water quality using water quality indices (WQI), multivariate statistical technique and geospatial technology. 20 lake water samples were collected during pre-monsoon and post-monsoon seasons for examining physicochemical parameters. The results revealed that Biochemical Oxygen Demand measured in milligram per litre (8.5 mg/l and 5.3 mg/l in pre-monsoon and post-monsoon season respectively) exceeded the normal range of 5 mg/l and ammonia (1.24 mg/l and 0.6 mg/l during pre-monsoon and post-monsoon season respectively) exceeded acceptable limits recommended by the Bureau of Indian Standards in both seasons. The Canadian Council of Ministers of Environment WQI ranged from 66.7 to 81.13 with a recorded mean of 74.22 imparting ‘fair’ conditions. Apart from Kelly’s index, all the irrigation WQIs designated majority of water samples as suitable for irrigation. All the industrial WQIs conveyed the tendency to corrode except Larson and Skold index that indicated corrosion potential. The principal component analysis effectively diminished the complex water analysis dataset into 6 principal components each for pre-monsoon and post-monsoon seasons which explained 87.85 % and 89.80 % of total variance respectively. These components identified the pollution sources as primarily originating from anthropological activities like agricultural runoff, domestic sewage waters and natural weathering of rocks. Hence, the combined approach using above-mentioned methodologies proves to be indispensable in evaluating surface water quality. The findings of this study further underscore the necessity for prompt action by decision makers for well-being of both environment and public health.
