Impact Assessment Studies Research Articles

A Study on the Introduction of Impact Assessment System for Coastal Erosion

Recently, the impact of climate change with sea levels rise, abnormal high waves, and continuous construction of artificial structures such as ports and harbors, has led to an increasing trend in coastal erosion. In this study, the scope and method of Environmental Impact Assessment, Utilization of Sea Areas, Disaster Impact Assessment, and Risk Assessment of Coastal Disasters System, which are carried out during development projects and erosion reduction projects carried out on the coast, are analyzed to identify each problem. , we proposed a plan to introduce the Impact Assessment System for Coastal Erosion, which can minimize the impact of coastal erosion by deriving improvement measures.

Environmental Impact Assessment of Onshore Wind Farms in the Region of Central Greece Using a Modified RIAM Method

Wind energy is one of the most basic forms of renewable energy, which shows an increasing rate of development worldwide and also at the European level. However, this rapid deployment of wind farms makes the need for an impact assessment of this type of projects on the natural and man-made environment imperative. The present paper aims to identify and assess the environmental impacts of wind farm projects in the Region of Central Greece. A modified Rapid Impact Assessment Matrix (RIAM) method is used for this purpose. The methodology includes the identification of the existing onshore wind farm projects in the study area, the appropriate modifications of the RIAM method to respond to the characteristics of the projects and the study area, the qualitative assessment of their potential impacts during construction and operational phases and the computation of the Environmental Performance Grade (EPG) of projects based on the pro-posed modified RIAM method. The results reveal that although there are some slight negative impacts on the natural environment of the study area, the examined wind farms contribute positively both to the atmosphere and to the socio-economic environment of the study. This study extends the potential for using RIAM as a tool in environmental impact assessment studies of renewable energy projects.

Advancing energy transition with novel biomass-solar based multigeneration energy system using hydrogen and storage options for sustainable cities

An integrated energy system is designed to produce various useful products, such as hydrogen, electricity, heat and cooling. This integrated plant utilizes various subsystems; solar power system, biomass energy system, steam Rankine cycle (SRC), Brayton cycle (BC), organic Rankine cycle (ORC), double-effect absorption system (DEAS), reverse osmosis system, and sonohydrogen production unit. The specific energetic, exergetic, economic and environmental impact assessment studies are carried out to evaluate the system's performance and sustainability. The engineering equation solver (EES) is used for these studies. The energy efficiencies for the BC, ORC and SRC are recorded as 29.69 %, 10.49 %, and 30 %, respectively. In regard to exergy efficiency, the BC, ORC and SRC achieve the following: 46.74 %, 62.73 %, and 53.43 %, respectively. Furthermore, the DEAS attains energetic and exergetic COPs of 1.67 and 0.65, respectively. Additionally, the overall system's energy and exergy efficiencies are found to be 37.68 % and 71.25 %, respectively. The results from the thermal energy storage system indicate that the heat production begins at 7:00 a.m., and the charging of the storage unit commences two hours after and continues until 5:00 p.m., in coinciding with the availability of sunlight. The economic analysis demonstrates that with an initial investment of $53.80 million, the integrated multigeneration system achieves a net present value ranging from $6.87 million to $173.4 million across different hydrogen selling prices, from $7000 to $13,000 per ton up to 2054.

Educational Innovation and Digital Transformation: Interconnection and Prospects for Ukraine

The integration of educational innovation and digital transformation has become increasingly crucial in reshaping educational landscapes globally. In the context of Ukraine, where the education system faces numerous challenges, understanding the interconnection between these concepts is paramount for driving meaningful change and fostering socio-economic development. This research aims to explore the interconnection between educational innovation and digital transformation, specifically focusing on its implications and prospects for Ukraine's education sector. The research employs a comprehensive literature review approach, drawing upon scholarly works and empirical studies related to educational innovation and digital transformation. Comparative analyses and impact assessment studies are utilized to provide a nuanced understanding of the complex dynamics at play. The study reveals the critical significance of embracing educational innovation and digital transformation in Ukraine. It highlights the potential of digital technologies to enhance teaching and learning practices, improve educational outcomes, and foster socio-economic development. Furthermore, the results identify key factors and opportunities associated with the integration of digital initiatives, offering insights into effective strategies and policy interventions. In conclusion, educational innovation and digital transformation represent more than fleeting trends; they are essential routes toward cultivating a robust, flexible, and globally competitive education system in Ukraine. Through embracing innovation, nurturing digital literacy, and placing a premium on educational reform, Ukraine can assert its leadership in educational excellence and secure the prosperity of forthcoming generations. The findings of this research provide valuable guidance for policymakers, educators, and stakeholders in Ukraine's education sector. By understanding the implications of educational innovation and digital transformation, stakeholders can enact evidence-based reforms, implement effective interventions, and propel Ukraine towards a more prosperous and knowledge-driven future.

Impact of Fish Feed Formulated with Microalgae Biomass in Experimental Tanks with (Oreochromis Niloticus) Tilapia Culture

This project aims to evaluate a fish feed developed in CIATEJ with little modification, which included algal biomass and vegetal protein. This product was tested at the laboratory scale and the pilot-scale upscaling was needed for use with impact assessment studies in real ambient conditions. This food has antioxidant capacity due to the inclusion of microalgae. Additionally, it is nutritionally balanced with plant-based protein sources, partially replacing fishmeal. The feed, compared to commercial feed, has a higher protein content (5%) and lower fat content (3%). Evaluating this feed was of great importance to corroborate its consumption, which can reduce oxidative stress, reduce water contamination, and improve the growth rate and quality of the meat in fish. FCR values of almost 1 were reported here, indicating the more efficient utilization of formulated feed by Oreochromis niloticus. The main component of tilapia meat was moisture 74.31%, followed by protein 14.44%, lipids 6.24%, carbohydrates 0.10%, fibre 1.39%, and ash 3.62%. in experimental feed. In our results in fish filate, we found a 12% increase in protein percentage and a 29% decrease in fat percentage compared to the commercial feed, as expected from the higher protein and lower fat formulated feed. The amount of protein increment in fish filet we achieved in 2 months, the experimental diets significantly influenced the content of polyunsaturated fatty acids at 2.4% while saturated fatty acids were 1.3%. Omega 6 and Omega 9 were 2.33% and 1.73% respectively. The polyunsaturated fatty acid/saturated fatty acid ratio was also higher.

The Socio-Economic Impact of Foot and Mouth Disease (FMD) on Livestock Farming in Sierra Leone, an Empirical Evidence from Six (6) Districts

As a highly infectious disease, Foot and Mouth disease (FMD) has been eradicated by many wealthy nations but remains endemic in most of the world especially countries in Sub-Saharan Africa1. When FMD outbreaks occur in disease free countries and zones that produce livestock for export, the economic impact is clear to see; however, the impact of the disease in endemic countries is more controversial, particularly when compared to diseases that cause greater mortality. Taking into account the limited resources of veterinary services for the implementation of animal disease surveillance anywhere and anytime in Sierra Leone, a socio-economic impact assessment study was conducted to quantify the impacts, spread and occurrence of the disease, in order to target and put in place precautionary control measures including targeted surveillance. The main socio-economic impact question of the study was “What is the social and economic impact of FMD in the districts under review. The study was conducted in 6 districts in the North and East of Sierra Leone. A total of 240 respondents using purposive sampling were interviewed to elicit information on the main socio-economic variables that informed the study. The study established (80%) of the sampled farmers are livestock farmers, while 32 people (13.3%) are crop farmers who mainly practice subsistence farming. The study proved that the yearly income from the sales of livestock both especially large ruminants increase to 154 (64.2%). This percentage plummeted when FMD struck in 2018-2019. The study showed that (55.8% of the household indicated that their cattle suffered from Foot and Mouth Disease (FMD) during the outbreak of July-August 2018-2019, while goats and sheep suffered Peste des Petits Ruminants (PPR) with households reporting (70.8%) and 162 (68%) of Infection rates before the commencement of this study. The study recommended that the veterinary division of maintain and improve on active surveillance of FMD, update surveillance plan targeting priority districts and hotspots of FMD outbreak such as livestock markets to maintain the current status of Low risk to prevent social and economic impacts’

Quantifying the effects of future environmental changes on water supply and hydropower generation benefits of cascade reservoirs in the Yellow River Basin within the framework of reservoir water supply and demand uncertainty

Inflow and water demand prediction plays an important role in reservoir operation rulemaking. Uncertainties in meteorological and hydrological modeling increase the complexity of inflow and water demand prediction, which are not sufficiently considered in conventional inflow and water demand prediction. Thus, this study took cascade reservoirs as the research object. These cascade reservoirs were located in the mainstream of the Yellow River Basin (YRB). A three-step framework was proposed: (1) developing a distributed Soil & Water Assessment Tool (SWAT) model to determine historical and future water availability in the reservoirs; (2) constructing the AquaCrop agricultural irrigation water demand model to predict future water demand of water users at 264 nodes (reservoirs and hydrological stations) in the YRB; (3) developing an optimal regulation model of cascade reservoirs in the YRB mainstream to quantitively determine the influence of future environmental changes on hydropower generation and water supply benefits of cascade reservoirs. The results indicate that the inflow of cascade reservoirs increased in the flood season and decreased significantly during the non-flood season compared with that in the historical period (1970–2016). However, there was a slight increase in the agricultural irrigation water demand, and the contradiction became more prominent between water resource supply and demand. During the future period (2020–2050), the guaranteed rate of hydropower generation and water supply in the YRB’s lower reaches will increase significantly. Uncertainties in climate models greatly impact hydropower generation benefits and reservoir water supply, especially in the flood season. These findings can facilitate the understanding of the complexity of hydropower management and production of cascade reservoirs under future environmental changes (inflow and demand) and encourage the use of regulation models for impact assessment studies and adaptive reservoir management to mitigate climate change.

The Influence of Successful Treatment of Stress Urinary Incontinence and Pelvic Organ Prolapse on Depression, Anxiety, and Insomnia-A Prospective Intervention Impact Assessment Study.

Introduction: The association between pelvic floor disorders (PFDs) and psychiatric conditions is an area of emerging interest. The causal direction of this relationship, however, remains ambiguous; it is unclear whether PFDs directly contribute to the deterioration of mental health or if pre-existing psychiatric conditions such as depression exacerbate the symptoms of PFDs. This study aimed to evaluate the effects of successful surgical treatment for stress urinary incontinence (SUI) and pelvic organ prolapse (POP) on symptoms of depression, anxiety, and insomnia. Materials and Methods: This investigation focused on patients who underwent successful surgical interventions for SUI and POP. Both subjective and objective symptoms of PFDs, along with psychiatric status, were assessed before and after the surgical procedures. Results: This study found that successful surgical treatment of SUI and POP led to a significant reduction in anxiety scores. Additionally, in patients with SUI, successful treatment was objectively associated with a decrease in the severity of insomnia. Alleviation of symptoms associated with the lower urinary tract, prolapse, and colorectal-anal region following POP surgery was correlated with improvements in depression and anxiety but not insomnia. Subjectively assessed improvements in SUI subjective symptoms were linked to reductions in the severity of depression, anxiety, and insomnia in patients who underwent anti-incontinence surgery. Conclusions: These findings suggest a potential cause-and-effect relationship between PFDs and certain psychiatric disorders, highlighting the importance of successful treatment of PFDs in mitigating symptoms of depression, anxiety, and insomnia.

Expression of concern: Excess mortality attributed to heat and cold: a health impact assessment study in 854 cities in Europe

Expression of concern: Excess mortality attributed to heat and cold: a health impact assessment study in 854 cities in Europe

Carbon intensity of mass timber materials: impacts of sourcing and transportation

Mass timber construction is widely considered a promising alternative construction method to reduce buildings’ total life-cycle carbon emissions because wood is a carbon sink. Cross-laminated timber (CLT) panels, manufactured by gluing lumber layers with grains at right angles, are potential low-carbon alternatives to carbon-intensive concrete and steel construction. However, most environmental impact assessment studies do not consider variation in transportation impacts within the CLT supply chain when calculating life-cycle impacts. This study investigates the embodied primary energy and the global warming potential (GWP) of CLT supply chain decisions regarding the type of timber species used, the U.S. region it is sourced from, and the location of the CLT mill. Longer transport distances in the supply chain for timber and CLT panels can contribute as much as 923 MJ/m2 (20%) of the embodied primary energy of a CLT building, and the use of a higher-density timber species increases this contribution to 1246 MJ/m2 (24%), with most of that energy derived from fossil energy sources. For perspective, the GWP of a building whose CLT panels and timber have been transported by truck over 6,000 km (252–270 kgCO2/m2) is greater than the GWP of an equivalent reinforced concrete (RC) building (245 kgCO2/m2). Thus, factors like the location of CLT processing facilities and the type of timber species can significantly impact the overall life-cycle assessment and, if chosen appropriately, can mitigate the environmental impacts of CLT construction.

A case study of charitable investment impact assessment

AbstractThe Pablove Foundation has been raising resources since 2008 to fight childhood cancer by investing in underfunded, cutting‐edge pediatric cancer research, and a participatory arts program that improves the lives of children being treated for cancer. Given numerous challenges in determining investment impact, the Foundation created key metrics such as the quality of grant recipients' contributions to the research literature, and the amount of subsequent cancer‐related research funding generated. Evaluating the effect of the Foundation's participatory art program has been difficult given the pandemic‐driven shift from in‐person sessions to virtual classes. Nonetheless, standard client survey feedback suggests that the virtual classes are not only functioning quite well, but also that accessibility is enhanced. It is clear that imaginative thinking is as important in assessment as it is in implementing medical research funding and arts programming. Practical implications of these findings for evaluation/assessment efforts by other foundations, nonprofit organizations, and development staff are examined.

Evolution of Information Technology in Industry: A Systematic Literature Review

Aim/Purpose. This study addresses the research question: “What are the developmental phases of Information Technology in the industry?” Existing research has explored the impact of Information Technology (IT) on specific industries. However, it is essential to understand the evolution of IT within industries, its influence on the workforce, and technological advancements. Addressing this knowledge gap will enhance future workforce development and IT integration across diverse sectors. Background. IT can significantly transform industries and drive innovation to meet client demands. Understanding IT phases in industry through literature helps governments and businesses worldwide recognize its importance. This knowledge can guide strategies to address the shortage of highly skilled workers by prioritizing education and training programs to meet future demands. Methodology The methodology involved a systematic literature review of 110 IEEE Xplore, ACM Digital Library, and Google Scholar articles. Thematic analysis was used to understand the development of IT in distinct phases since the 1990s. This development has resulted in a continuous demand for new workforce skills and evolving customer expectations. Contribution. This study aims to fill the knowledge gap by enhancing our understanding of how evolving IT influences the industry and shapes IT jobs and skills. It provides a historical perspective, illustrating how IT advancements have led to new applications to meet changing needs. Additionally, the study identifies patterns in the evolving IT skill requirements due to technological advancements and discusses implications for curriculum development and higher education. Findings. The study identified three significant phases through a systematic literature review and thematic analysis. The first phase, “Advent of Industry IT” (1990-2000), established the digital framework and built essential systems and infrastructure. The second phase, “Connectivity & Information Revolution” (2000-2010), saw exponential internet growth, transforming information access and communication. The third phase, “Emerging Industry IT” (2010-present), focuses on artificial intelligence, automation, and data-driven insights, continuing to disrupt and transform industries. Recommendations for Practitioners. The changing phases of IT within the industry should inform the development of innovative programs. These programs should address diverse skill sets across eras, preparing the workforce for evolving job roles in various sectors, such as healthcare in North America, automotive manufacturing in Japan, telecommunications in Africa, and innovations in other parts of the world. Recommendations for Researchers. Researchers can conduct longitudinal studies to explore the ongoing evolution of IT, tracking its trajectory beyond current delineated phases to understand future trends. Comparative studies across various industries can assess how IT evolution varies among sectors and delve deeper into its practical implications. Researchers can also conduct impact assessment studies to determine how various IT phases directly affect organizational strategy, worker dynamics, and organizational structures across industries. Examples include logistics in the Netherlands, retail in the United Kingdom, and agriculture in Brazil. Impact on Society. Policymakers and planners can use knowledge of these phases to predict technological shifts and industry trends. This knowledge helps develop strategies and policies supporting entrepreneurship, education and training alignment, technical innovation, economic growth, and job creation in line with the changing IT landscape. Examples of policies include Singapore’s Smart Nation initiative, Germany’s Industry 4.0 strategy, Ghana’s digitization efforts, and India’s Digital India campaign. Future Research. Future research can provide a thorough understanding of the evolutionary patterns of IT within sectors by validating the study through various datasets and conducting in-depth examinations of individual industries. This will contribute to a deeper understanding of sector-specific IT evolution and their varying impact on societal interactions and industry dynamics. Comparative studies across various sectors, such as logistics in the Netherlands, retail in the United Kingdom, and agriculture in Brazil, can assess how IT evolution varies.

Suicide risk assessment tools and prediction models: new evidence, methodological innovations, outdated criticisms

The number of prediction models for suicide-related outcomes has grown substantially in recent years. These models aim to assist in stratifying risk, improve clinical decision-making, and facilitate a personalised medicine...

EVALUATION OF DUST EMISSION RATE FROM LANDFILL MINING ACTIVITIES

Mining operations are one of the most significant sources of particulate emissions in the atmosphere. Landfill mining (LFM) process activities, including excavation, screening, shredding, and equipment handling, have the potential to emit particulate matter into the environment as short-term episodic emissions during operational periods. Previous investigations show that LFM activities can potentially cause human health and environmental impacts through exposure of these emissions. This paper evaluates the dust emission rate of such activities to understand factors responsible for higher emissions rate and determine where any pressure points exist in order to mitigate risk. Nine empirical formulas were adopted from surface mining activities, including point, line, and area sources of activity. Parameters identified in the equations were adjusted to LFM application conditions. From emission results, it is observed that point source activities were the major sources of emission. The study area was divided into multiple phases and one phase cumulative for the maximum/average/minimum point sources emissions over the lifetime of the landfill mining operation calculated in this study are approximately 5.04 tonnes (t) / 3.23 (t) / 1.61 (t), respectively. However, the one phase cumulative for the maximum/average/minimum line sources emissions over the lifetime of the landfill mining operation are approximately 100.8 (kg/m) / 40.32 (kg/m) / 20.16 (kg/m), respectively. Mitigation measures to control high emission rate of LFM related activity, such as utilising tankers or bowsers to spray water around the LFM area, to control airborne emissions, should be considered. The results of this research are expected to inform air dispersion modelling for environmental impact assessment studies of air pollution.

Lapse rate-adjusted bias correction for CMIP6 GCM precipitation data: An application to the Monsoon Asia Region.

Bias correction (BC) of General Circulation Models (GCMs) variables is a common practice when it is being used for climate impact assessment studies at regional scales. The present study proposes a bias correction method (LR-Reg) that first adjusts the original GCM precipitation for local lapse rate corrections and later bias corrects the lapse rate-adjusted GCMs precipitation data with linear regression coefficients. We evaluated LR-Reg BC method in comparison to Linear Scaling (LS) and Quantile Mapping (QMap) BC methods, and NASA's downscaled NEX data for Monsoon Asia region. This study used Coupled Model Intercomparison Project Phase 6 (CMIP6)-based MIROC6 GCM precipitation with historical and projected shared socio-economic pathways (SSP) scenarios (SSP245 and SSP585) datasets. The BC comparison results show that the relative percentage reduction in mean absolute error (MAE) values of LR-Reg over LS-BC was up to 10-30% while this relative reduction in MAE values of LR-Reg was 30-50% over QMap-BC and 75-100% over NASA's NEX-data. The future projected precipitation over Monsoon Asia during dry season shows more decreased precipitation by up to 100% mostly in the south Asia while during wet season shows more increased precipitation by up to 50% mostly in the northeastern China and in the Himalayan belts with respect to the baseline condition (1970-2005). The results on the average precipitation per 0.25 degree increase in latitude analysis shows that the maximums of average monsoon precipitation during baseline period occur at 0 and 25 degree latitudes while the projected monsoon precipitation during both SSP scenarios occurs at 10 and 20 degree latitudes which clearly shows an inward shift in the latitude axis for the projected precipitation in the Monsoon Asia.

Evaluation of CORDEX Africa regional climate models performance in simulating climatology of Zarima sub-basin northwestern Ethiopia

Climate models are basic tools to obtain reliable estimates of future climate change and its effects on the water resources and agriculture in given basin. However, all climate models are not equally valuable for all areas. Therefore, determining the most appropriate climate model for a specific study area is essential. This study examines the performance of 10 CORDEX-AFRICA-220 Regional Climate Models (RCMs), three downscaling institutional based ensembles mean (Reg ensemble, CCLM ensemble and REMOO ensemble) and the multi-model ensemble mean. The models were evaluated based on their ability in replicating the seasonal and annual rainfall, minimum and maximum temperature and inter-annual variability for the period of 1986–2005 using statistical metrics such as BIAS, Root Mean Square Error (RMSE), Pearson correlation coefficient (r), coefficient of variation (CV), Kling Gupta Efficiency (KGE) and Taylor diagram. The findings indicated that HadREMOO, MPI-Reg4-7, HadReg4-7, Reg ensemble, and multi-model ensemble mean performed relatively better in representing the mean annual observed rainfall at the Adiramets, Debarik Ketema, Niguse Maystebri, and Zarima stations, respectively. Whereas, NorESM-CCLM, MPI-CCLM, NorESM-Reg4-7, and NorESM-REMOO exhibited a weak performance in reproducing the observed mean annual rainfall at the Adiramets, Debarik Ketema Niguse, Maystebri, and Zarima stations, respectively. Similarly, RCMs generally capture the mean annual maximum temperature of climatic stationsof Zarima subbasin well. Specifically, the MPI-Reg4-7 simulation performs well in representing the mean annual observed maximum temperature at Adiramets and Maytsebri stations, while the Debarik and Ketema Niguse stations exhibit superior performance in the HadReg4-7 simulation and the Zarima station shows better representation in the CCLM ensemble simulations. The majority of the model simulations exhibit good representation of mean annual minimum temperature at Adiramets, Debarik, and Zarima stations. Specifically, CanESM-RCM, HadReg4-7, REMOOensemble, multi-model ensemble, and Regensemble simulations perform better at Adiramets, Debarik, Ketema niguse, Maystebri and Zarima stations respectively. This suggests that these models may have biases or shortcomings in capturing the temperature values in the subbasin. Furthermore, NorESM-CCLM at Adiramets, Ketema niguse, and Zarima stations, NorESM-REMOO at Debarik station, and HadReg4-7 at Maystebri station demonstrate poor performance in representing the observed mean minimum temprature. Majority of the RCMs, all institutional based ensemble means and the multi-model ensemble mean simulations overestimate the observed mean annual rainfall of the Zarima subbasin with minimum bias of 0.02 mm at Ketema niguse HadReg4-7and maximum bias of 2.81 mm at Maytsebri MPI-CCLM simulation. Similarly, HadReg4-7 simulation of Ketama Niguse MPI-CCLM showed a minimum 0.02 mm and Maytsebri simulation kiremit season mean rainfall showed a maximum bias of and 2.99 mm. Regarding mean annual and kiremit season maximum and minimum temperature of the Zarima subbasin were overestimated by majority of the simulation and the ensemble means. The correlation (r) of observed and model simulated mean annual and kiremit season rainfall was strong (0.60–0.79) and very strong (0.80–0.99) in the majority of the simulations except Ketema niguse station mean annual and kiremit season rainfall simulations of MPI-REMOO, NorESM-Reg4-7; Debarik station kiremit season rainfall of NorESM-CCLM and NorESM-REMOO, MPI-Reg4-7 and MPI-REMOO, which showed moderate correlation. The performance of the RCMs, institutional based ensemble means and multi-model ensemble mean were different in statistical metrics (BIAS, RMSE, r, CV and KGE) and Taylor diagram. Among the simulations and ensemble means, the multi-model ensemble mean was superiors in two or more of statistical metrics at each station of the Zarima subbasin except Maytsebri station kiremit season rainfall, where the CCLM ensemble was better. Consistently, the Taylor diagram showed that the multi-model ensemble was better in the replication of the areal annual and kiremit season rainfall, maximum and minimum temperature of the subbasin. This finding evidenced that selecting the best RCMs and ensemble mean is necessary for climate projection and climate change impact assessment study.

Experimental study on the effect of sound stimulation on hearing and behavior of juvenile black rockfish (Sebastes schlegelii)

Assessing the potential impacts of wind farm noise on fish is a crucial aspect of Environmental Impact Assessment (EIA) studies. There is increasing evidence of disturbances and effects on hearing and behavior in animals. The black rockfish (Sebastes schlegelii) is a commercially valuable rocky reef fish native to East Asia. However, empirical studies that measure the actual consequences are lacking. In this study, we used auditory evoked potentials (AEP) to assess the effects of dominant frequency noise emitted by offshore wind farms on the auditory sensitivity, hearing threshold, swimming, and feeding behavior of juvenile black rockfish. The experimental findings revealed that the most sensitive sound frequency was 200 Hz, with the lowest hearing threshold recorded at 86.4 ± 3.4 dB re 1 μPa. Following 3 and 7 days of exposure to 200 Hz noise at 110 dB, threshold shifts in black rockfish reached 19.0 dB and 13.3 dB, respectively. During the subsequent recovery phase, these shifts decreased to approximately 9.8 dB after 3 days, respectively. The noise-exposed group exhibited higher swimming duration, moving distance, and caudal fin swing frequency compared to the control group without noise exposure. Furthermore, noise prolonged the feeding rate of black rockfish. Our findings provide the first evidence of noise-induced temporary threshold shift and behavioral disturbances in juvenile black rockfish, implying potential fitness consequences associated with noise pollutant.

The Effect of Climate Change on the Hydropower Potential in the Kunhar River Watershed, Pakistan

Climate change plays a vital role in the hydrology of any river basin, which may have multidimensional consequences. There is a need to conduct climate change impact assessment studies with updated models and scenarios. This study aimed to assess the impact of climate change on the streamflow and hydropower in Pakistan’s Kunhar River basin. Three general circulation models (GCMs), under two Shared Socioeconomic Pathway scenarios (SSPs 2–45 and 5–85), the Soil and Water Assessment Tool, and the flow duration curve were used to project the change in climatic parameters, streamflow, and hydropower potential, respectively. The findings indicated that in the 2080s, the precipitation, maximum, and minimum temperatures are projected to increase by 10%, 2.0 °C, and 3.0 °C under the SSP 2–45 scenario and are projected to increase by 8%, 3.7 °C, and 4.4 °C under the SSP 5–85 scenario, respectively. The annual streamflow may increase by 15 to 11%, and the seasonal fluctuations are more likely to be dominant compared with the annual fluctuations. The hydropower potential will probably increase by 24 to 16% under the SSP 2–45 and 5–85 scenarios in the 2080s. However, seasonal changes in streamflow and hydropower may impact the hydropower plant operation in the basin. The Kunhar River’s hydrology may change from snow-fed to a rainfall–runoff river.

Is reuse always better than recycling? A critical analysis of the proposed European Regulation on Packaging and Packaging Waste and a debunking of its Impact Assessment study

Do impact studies guide policies, do policies direct impact studies, or are ideologies inspiring both? We analyse the proposed new European regulation on packaging and show that the expected benefits are much lower than those magnified by official declarations. Our debunk- ing of the Impact Assessment study, apart from the specific issues, raises concerns about how the European regulatory process is made. By doing so, he invites readers to reflect on the intricate relationship between impact studies, policy-making, and the ideological influences that may shape both.

Analysis of air quality issues and air quality management status in five major African cities

Poor air quality is one of the main dysfunctions of the rapid urbanisation process in Africa. Although the information is fragmented, the limited evidence available points out that air quality is a leading health risk in Africa, especially affecting the poorest, most vulnerable communities. In this study, we look into five cities in Africa to understand the nature of urban air quality issues and to delve into the initial responses. We report on the status of the main air quality management dimensions, including air quality standards and monitoring strategy/capabilities, emission inventories and air quality modelling, health impact assessment studies, communication practices, development and implementation of clean air action plans (in connection with other relevant strategies, i.e. climate change policies) and governance issues. We find that all cities have limited monitoring capabilities although communication strategies may differ substantially. While indoor pollution sources are declining in more developed economies, traffic is a growing concern in all five cities. In most cases, air quality issues are mostly related to PM2.5 and natural contributions worsen air pollution from road transport, biomass and open waste burning. While nationally-driven strategies, often based on large-scale engineering projects and financial schemes, may report substantial gains in early stages, multi-level governance and planning is likely to maximize benefits and provide a useful framework for the complex problem of air quality management in the long run. The integration of air quality plans in overarching strategies to tackle persistent poverty and social inequity is urgently needed.