Indicators Of Environmental Quality Research Articles

Analisis Environmental Kuznets Curve (Menyeimbangkan Industri Hijau dan Degradasi Lingkungan di Indonesia)

Indonesia has expanded and adapted to international market trends in tandem with the advancement of its industry. Various factors, such as industrialization, urbanization, and the exploitation of natural resources, are responsible for this growth. However, these activities have also led to environmental degradation in many parts of Indonesia. Deforestation is one of the most significant environmental issues that Indonesia is currently grappling with. The production structure of developing countries can exacerbate the relationship between environmental degradation and economic growth, which can be detrimental to the environment. The primary objective of this study is to examine the relationship between environmental degradation and green economic growth, with a particular emphasis on Gross Domestic Product (GDP), using the Environmental Kuznets Curve (EKC) model. This model posits a reversible relationship between per capita income and environmental quality. The novelty of this study lies in the development of better indicators to measure EKC and Green GDP. These indicators cover a wide range of aspects, from air and water quality, and biodiversity levels, to energy consumption. The Pearson correlation analysis was employed to examine the correlation between GDP and IKLH in Indonesia from 2010 to 2022. The analysis yielded positive and robust correlations between GDP and IKLH. Consequently, the higher the GDP, the greater the IKLL or the less environmental degradation. An advance in the economy during the industrial era in Indonesia is indicated by the increase in the country's GDP growth rate. The short-term and long-term impact of economic expansion on the environmental quality index of life suggests that there is a reduction in environmental degradation. The concept of Green GDP should be proposed as an alternative indicator that considers asset depreciation, non-market economy, and environmental damage caused by economic growth.

Suitability analysis of ecological park site selection in small and medium-sized cities based on multi-source geographic big data

In the context of rapid urbanization, the scientific planning and development of ecological parks in small- to medium-sized cities are essential for enhancing the well-being of city dwellers and optimizing the ecological quality of urban environments. Traditional site suitability methods, however, are increasingly limited due to data resolution constraints and the challenges of balancing ecological protection, urban development, and socio-economic interests, which hardly provide insights for ecological park planning in small and medium-sized cities. This study addresses these limitations by employing a multi-source geographic big data framework, and applying it in Yongji City, Shanxi Province, by integrating remote sensing, Points of Interest, and land use data, a detailed 10m × 10m spatial grid was used for analysis. A comprehensive three-dimensional evaluation framework was developed, comprising ecological, infrastructural, and socio-economic factors, represented by 11 indicators. Points of Interest data have effectively assessed infrastructural configurations necessary for urban ecological parks, while remote sensing data provides critical insights into surface temperature and vegetation cover, which provide high-resolution indicators of environmental quality in urban and sub-urban regions. The site suitability analysis results reveal that hydrophilic landscapes, such as the Yellow River mudflats and Wuxing Lake wetlands, were identified as optimal areas for ecological park development due to their cooling effects and ecological benefits. Zone C, located southwest of Wuxing Lake, emerged as the ideal site due to its abundant natural assets and high accessibility, with a phased development strategy of other recommended sites based on their suitability. This research establishes a data-integrated framework that advances the methodology for urban ecological park planning in small- to medium-sized cities, providing both theoretical and practical insights that can inform similar projects in other urban contexts.

Spatial Dependencies in Environmental Quality: Identifying Key Determinants

Introduction/Main Objectives: Environmental quality is essential to human development because it reflects the condition of our natural surroundings. Background Problems: Understanding the determinants of environmental quality is crucial for Indonesia as it helps identify the key factors influencing environmental quality. Novelty: Spatial models offer detailed, locationspecific insights but require extensive data and computational resources, while non-spatial models provide a broader overview with simpler data requirements but may miss important spatial nuances. This study seeks to identify the determinants of environmental quality in regencies and municipalities on Java Island, incorporating spatial effects into the analysis. Research Methods: The dependent variable is environmental quality index. The independent variables are GRDP in industrial sector, GRDP in agricultural sector, urban population rate, population density, and poverty rate. We applied spatially lag regression model using contiguity spatial weight matrix. Finding/Results: This study shows the spatially lag regression model outperforms the OLS model. GRDP in the industrial sector, GRDP in the agricultural sector, urban population rate, and population density have negative effects, suggesting the increases in these variables were associated with lower environmental quality. About 40%–44% of each variable's effect on environmental quality is due to spatial spillover effects.

Prioritizing Urban River Restoration Management Practices: A Cross-Evaluation Using the Criticality Index for Watershed Restoration (CIWR) and Opportunity Layers

Urbanization exerts significant stress on urban river ecosystems, leading to their degradation and the loss of environmental functions. Several studies have focused on restoring these urban rivers to enhance environmental quality and contribute to overall city well-being. However, such restoration efforts encounter economic, environmental, and social challenges. This study proposes a methodological framework to aid public managers in prioritizing areas for urban river restoration. The approach integrates the concept of environmental services with urban development opportunities to address these dual demands. Central to this framework is the introduction of the criticality index for watershed restoration (CIWR), which categorizes watershed areas based on environmental quality indicators, using river restoration as a guiding principle. Additionally, legally protected environmental areas were considered as opportunity layers. This study used geographic information systems (GIS) to manage and overlay datasets for a case study in the João Mendes Watershed in Niterói, southeast Brazil, which illustrated the use of the CIWR. By intersecting this framework with the opportunity layers, priority locations were identified for potential river restoration management practices. The results indicated that the overall criticality condition of this watershed for river restoration is low. The study further discusses potential measures for river restoration in the identified priority areas, underscoring the importance of strategic planning in urban environmental management. The CIWR proved to be an easily applicable and replicable management decision tool for comparing watersheds and assessing deficient environmental services, with both numerical and spatial results. Its use, combined with the “opportunity” layer, enables public managers to define priority areas for river restoration practices based on clear and objective criteria.

The problems of environmental quality in Indonesia: Do education levels matter?

Abstract Environmental degradation has emerged as a significant global concern in both emerging and industrialized nations. Immense body of economic literature have verified the probable factors that may become the reasons for environmental degradation and some studies have shown that education is a crucial aspect in restoring the environmental quality. This study aims to understand the impact of different levels of education on environmental quality in Indonesia by Utilizing the Dynamic Ordinary Least Squares (DOLS) regression method for the time frame spanning from 1996 to 2021. The current research employs load capacity factor as a replacement indicator for environmental quality. This study concludes that higher population with basic education level will reduce the environmental quality, while higher population with intermediate education increase the environmental quality. Finally, this study also finds that higher population with advanced education level will harm the environmental quality. Based on the results, it is important for the Government to create compulsory environmental-friendly curricula in all levels of education that supports the reduction of environmental problems in Indonesia.

A new locally collected environmental quality indicator for rainforests

Measuring environmental degradation with bioindicators, landscape metrics, and remote sensing helps understand impact on biota. However, data on anthropogenic pressures such as plant exploitation, poaching and invasive species are crucial. We created an Anthropogenic Influence Index (AII) for medium and large mammals at the Atlantic Forest based on local environmental quality indicators and tested its correlation with existing indices, such as the Global Human Influence Index (GHII), landscape metrics and social-economic indicators. We found no correlation between the AII and the GHII, indicating that remote sensing-collected data may not reflect local and specific anthropogenic impacts on the environment. In addition, there was a correlation between the AII and the Human Development Index, drawing attention to the direct relationship between income, education and life expectancy and the incidence of environmental impacts. Thus, the AII appears to better capture local nuances of environmental impacts, particularly those significant for medium and large mammals, compared to other indicators such as GHII, human density, and landscape metrics.

Unravelling integrated groundwater management in pollution-prone agricultural cities: A synergistic approach combining probabilistic risk, source apportionment and artificial intelligence

Groundwater is vital for agricultural cities, but intensive farming and fertilizer use have increased contamination risks, particularly for non-carcinogenic health hazards. This study reveals the sources of contaminants in groundwater, their health impacts, and targeted strategies in such cities. The study analyzed 115 groundwater samples, with the main groundwater chemical type being HCO₃-Na·Ca. Significant exceedances were found in Mg²⁺, HCO₃−, F−, total hardness (TH), and Mn, with HCO₃− and Mg²⁺ surpassing standards in nearly all samples. The average Comprehensive Environmental Water Quality Index (CEWQI) was 100.68, indicating that overall groundwater quality in the study area is good. High-quality water is mainly found near reservoirs and rivers, while urban and eastern regions have relatively poorer water quality. The proportion of groundwater unsuitable for drinking is low. Monte Carlo risk assessments revealed that F− and NO₃− pose non-carcinogenic risks to both adults and children, with NO₃− presenting a higher potential health risk. The Positive Matrix Factorization (PMF) model identified that groundwater pollution primarily results from natural geological processes and human activities, with agriculture being the major anthropogenic factor. AI-based zoning strategies highlighted industrial areas and high-fluoride zones as critical areas requiring enhanced prevention and control measures.

Nuclear abnormalities and DNA damage indicate different genotoxic stress responses of marsh frogs (Pelophylax ridibundus, Pallas 1771) to industrial and agricultural water pollution in South Bulgaria.

Amphibians are continuously exposed to pollutants and anthropogenic stressors in their natural habitats, representing a significant challenge to their survival. This study aimed to quantify the extent of DNA damage caused by chronic industrial and agrochemical surface water pollution in wild populations of the marsh frog (Pelophylax ridibundus). The observed genotoxic effects on the marsh frog DNA, manifesting as abnormalities in erythrocyte nuclei, micronuclei, and DNA strand breaks, demonstrate a clear cause-and-effect relationship with surface water parameters, heavy metals, metalloids, and pesticides. The most prevalent nuclear abnormalities observed were notched and blebbed nuclei and nuclear buds, indicative of chromosomal instability. The significant correlation between cadmium, lead, and copper contamination and the increased frequency of DNA breakage in the marsh frogs from the industrial site indicates that heavy metal contamination has a higher genotoxic potential than pesticide contamination. These findings underscore the vulnerability of amphibians inhabiting heavy metal-contaminated wetlands to genotoxic stress due to their lower tolerance to environmental genotoxins. Therefore, using in situ assays to detect erythrocyte nuclear abnormalities and DNA damage in P. ridibundus could serve as a reliable indicator of environmental quality and provide early detection of anthropogenic pollution.

Emerging contaminants as indicators of short-term environmental changes in an eutrophicated coastal lagoon

This research aimed to assess the potential of emerging contaminants as environmental quality indicators for short-term monitoring programs, in contrast with traditional contaminants. Thirteen sediment samples from from Piratininga, a coastal lagoon subjected to anthropogenic impact, were analyzed for the following compounds: napropamide, diclofenac, naproxen, triclosan, ibuprofen, 17β-estradiol, bisphenol A, nadolol, ethofibrate and carbamazepine. The developed method, which included solid phase extraction, derivatization, and analysis by gas chromatography–mass spectrometry, demonstrated robustness and suitability with quantification limits between 0.32 and 1.49 ng g−1. The concentrations of etofibrate, nadolol, napropamide and diclofenac were below the quantification limits for all the analyzed samples. The highest concentration was reported for bisphenol A (4.76 ± 0.44 ng g−1), followed by 17β-estradiol (2.88 ± 0.65 ng g−1), ibuprofen (2.70 ± 1.67 ng g−1) and triclosan (1.5 ± 0.43 ng g−1). The detected concentrations, spatial distribution, and local climatic conditions with distinct dry and wet seasons indicate the feasibility of biannual environmental quality monitoring. By evaluating the concentrations and statistical treatment, the use of contaminants of emerging concern as short-term indicators proved promising, leading to an optimized monitoring program from nine to three compounds (bisphenol A, ibuprofen and triclosan) and a sampling grid reduced from 13 to 4 points.

The synthesis of logistics performance and technological innovation on environmental quality

PurposeThis study aims to examine the impact of logistics performance and technological innovation on environmental quality in Africa, focusing on carbon dioxide (CO2) emissions and renewable energy consumption as indicators of environmental quality.Design/methodology/approachThe study employs a panel data analysis of 43 African countries over the period 1990–2021. Data on logistics performance, technological innovation, CO2 emissions, and renewable energy consumption are sourced from the World Development Indicators database of the World Bank. Grounded in the Triple Bottom Line (TBL) framework, which integrates economic, social and environmental dimensions of sustainability, the analysis utilises the generalised method of moments (GMM) technique to address the issue of endogeneity.FindingsThe regression results reveal significant relationships between logistics performance, technological innovation and environmental quality indicators. Logistics performance demonstrates a negative impact on CO2 emissions, while technological innovation positively influences renewable energy consumption. The interactive effect of logistics performance and technological innovation mitigates CO2 emissions, aligning with the TBL framework’s environmental dimension by promoting sustainability. Furthermore, trade openness exhibits a significant negative effect on both CO2 emissions and renewable energy consumption. The findings highlight the potential synergies between logistics performance and technological innovation in driving environmental sustainability while offering economic benefits and addressing social well-being.Practical implicationsThe findings suggest the importance of prioritising investments in enhancing logistics performance and fostering technological innovation to achieve environmental sustainability goals in Africa.Originality/valueTo the best of the researchers’ knowledge, this study presents an initial attempt to examine the nexus between logistics performance and environmental quality in Africa using the logistics performance index. Furthermore, beyond assessing the individual effects of logistics performance and technological innovation on environmental quality, we delve into their interactive dynamics, adding novelty to the study.

A measurement study of the environmental quality and medical expenditures of elderly individuals: causal inference based on machine learning

BackgroundThe global surge of environmental pollution exacerbates health issues, disease incidence, and economic strain. In China, the increasing healthcare costs of the elderly population necessitate addressing this challenge as part of the “Healthy China” strategy. We explore the impact of environmental quality on elderly healthcare expenses.MethodsThis study devised a comprehensive environmental quality index for 30 Chinese provinces, excluding Tibet, which was correlated with medical expenses for individuals older than 60 years, using China Family Panel Studies (CFPS) data. Because the traditional econometric model cannot solve the endogeneity problem and the selection of instrumental variables is subjective, a new machine learning algorithm is adopted based on the traditional ordinary least squares (OLS) model and the fixed effect model to conduct causal analysis to ensure the reliability of the results. Finally, heterogeneity analysis was conducted based on the generalized random forest algorithm.ResultsSouthern provinces such as Jiangxi and Guangxi exhibited superior environmental qualities. A regional analysis revealed a gradient where environmental quality decreased from west to east and from south to north. Both conventional and machine learning methodologies underscored a pivotal finding: enhanced environmental qualities significantly curtail elderly healthcare expenses. A heterogeneity assessment revealed that such improvements predominantly benefit elderly people in the eastern and central regions, with marginal impacts in the west. For different groups, the improvement of environmental quality can significantly reduce the medical expenditure of people aged 60 to 75, with bedtime hours between 9 and 11 PM and a lower household income.ConclusionsThis study, employing machine learning and traditional models, demonstrates that enhancements in environmental quality significantly reduce medical costs for the elderly in China, especially in the eastern and central regions, and among demographics such as individuals aged 60–75 and low-income households. These findings underscore the potential of environmental policies to lower medical costs within the “Healthy China” initiative framework. However, the study’s scope is limited by the environmental quality index and the extent of data coverage, indicating a need for further research expansion.

Assessment of the efficiency of functioning of the environmental management system of enterprises

Purpose. A multifactor model is developed to assess the efficiency level of an enterprise’s environmental management system, depending on the effectiveness of organizational environmental measures. Methodology. The authors’ method for determining a comprehensive criterion for monitoring the effectiveness of the environmental management system, which characterizes the efficiency of operation and determines the level of environmental safety of enterprises, is proposed and used. To solve the tasks, a complex research method was also used, which included the analysis and generalization of literary and patent sources, and analytical, experimental research using computer and mathematical modeling methods. Findings. According to the studies and calculations of the generalized environmental quality indicator – 0.64, 0.66 and 0.66, the largest negative impact on the environment is caused by the activities of enterprises in the Pecherskyi, Podilskyi, and Solomianskyi districts of Kyiv, respectively. The obtained data testify to the relationship between the effectiveness of the implemented environmental measures (saving and rational use of resources, application of environmental technologies, advanced training, and environmental competence of employees) and the level of efficiency of the environmental management system of enterprises. Originality. As a result of the studies conducted using actual data, a system of indicators of the generalized environmental quality indicator has been proposed for the first time, which allows determining the environmental efficiency and effectiveness of the implemented environmental measures to assess the effectiveness of the functioning of the implemented environmental management system of the enterprise. Practical value. Based on the research results, a technique is proposed to assess the effectiveness of the environmental management system of enterprises by determining a generalized environmental quality indicator in terms of reducing the negative impact of the enterprise’s activities on the environment. Such an assessment system will help the management of the enterprise to promptly introduce corrective actions to improve the efficiency of the environmental management system and increase the level of environmental safety.

Economic Growth and Environmental Quality: A Study on Mineral-Rich Provinces in Indonesia

Research Originality: This research focuses on Indonesia's mineral-rich provinces and offers originality through its comprehensive analysis of the bidirectional relationship between economic growth and environmental quality, using the Environmental Quality Index (EQI). Research Objectives: This study examines the relationship between economic growth and environmental quality in the Mineral Economy Provinces of Indonesia.Research Methods: The data used in this research is secondary data from 2015 to 2022. The analysis method employed is the simultaneous equation model using Two Stage Least Squares (2SLS).Empirical Results: The results show that in model 1, economic growth is significantly influenced by exogenous variables such as the environmental quality index, energy consumption, revenue sharing funds, investment, and population. In model 2, environmental quality is significantly influenced by exogenous variables such as GDP, mining output, energy consumption, and forest. Good environmental quality can enhance economic growth. Conversely, increased Economic growth can degrade environmental quality.Implications: The study's findings suggest that policymakers in Indonesia's mineral economy provinces should prioritize sustainable development to balance economic growth with environmental preservation.JEL Classification: Q43, Q50, Q56

Beaver dams in Mediterranean ecosystems: trait‐specific effects on macroinvertebrates

AbstractAfter centuries of extinction due to human persecution, Eurasian beavers Castor fiber L. have been released to Southern Europe in the last decades. Being ecosystem engineers, beavers have attracted great attention regarding restoration of aquatic and terrestrial ecosystems. Nonetheless, the effects of the species on aquatic invertebrates known to date are not univocal and mostly refer to central European riverine systems. Here, we evaluated the effects of beaver presence on aquatic macroinvertebrates for the first time in a Mediterranean riverine ecosystem, by applying a sound control‐impact sampling design and controlling for seasonal variation in macroinvertebrate assemblage composition. A significant variation in response to season was evident for macroinvertebrate communities, revealing distinct assemblages during spring and summer. Furthermore, the presence of beavers was also identified as a significant driver of species composition, as samples near the beaver dam showed significant variation from control sites. Macroinvertebrate community traits changed according to the relative position to the beaver dam, as control sites featured on average higher abundances of taxa with higher values of bioindication score, larger size, lower adaptation to drag, and were less frequently of introduced origins. Yet, these differences were strongly taxon‐ and season‐specific in their intensity and direction. Differences across sites were mainly driven by the relative abundances of few taxa—including both alien species and high environmental quality indicators—such as those from genera Potamopyrgus, Baetis, Habrophlebia, Ephemerella, Leuctra, and Radix, which explained about 70% of the observed divergence among conditions. Our results indicate that beavers and their engineering activity may induce highly variable species‐specific responses in macroinvertebrates, thus possibly representing a driver of environmental heterogeneity along Mediterranean rivers, and that both bioindicators and alien species may exploit such heterogeneity.

Environmental Quality, Extreme Heat, and Healthcare Expenditures

Although the effects of the environment on human health are well-established, the literature on the relationship between the quality of the environment and expenditures on healthcare is relatively sparse and disjointed. In this study, the Environmental Quality Index developed by the Environmental Protection Agency and heatwave days were compared against per capita Medicare spending at the county level. A general additive model with a Markov Random Field smoothing term was used for the analysis to ensure that spatial dependence did not undermine model results. The Environmental Quality Index was found to hold a statistically significant (p < 0.05), multifaceted nonlinear association with spending, as was the average seasonal maximum heat index. The same was not true of heatwave days, however. In a secondary analysis on the individual domains of the index, the social and built environment components were significantly related to spending, but the air, water, and land domains were not. These results provide initial support for the simultaneous benefits of healthcare financing systems to mitigate some dimensions of poor environmental quality and consistently high air temperatures.

Neonicotinoids, Agriculture And Food Security Of Brazilian Honey: A Review

Pesticides used in agriculture have the function of controlling pests, diseases and preventing the development and growth of weeds, increasing the quality and productivity of crops. However, when they reach unwanted targets, such as bees, humans and other living beings, they cause harmful damage to ecosystems. Neonicotinoids, insecticides widely used in monocultures, such as soybeans and corn in Brazil, are especially harmful to bees, whether native or exotic, interfering with the foraging and pollination performance of plants. The global decline in the bee population is related to the use of insecticides, a fact that directly threatens the production of various foods. Honey, the main beekeeping product , is not only a source of food for bees, humans and other animals, but also an indicator of environmental quality, as its composition reflects the conditions of the environment in which it was produced, and determinations made therein can reveal the presence of contaminants such as pesticides and toxic metals providing information about ecosystem health and the presence of environmental contaminants. Furthermore, consuming pesticide-free foods is crucial for human health and environmental sustainability, as the intake of neonicotinoids is associated with several health problems such as hormonal disorders and nervous system diseases and is especially dangerous for children. This article reviews the neonicotinoid insecticides imidacloprid and thiamethoxam and the contamination they cause in the honey of bees Apis mellifera Linnaeus (1758) and Tetragonisca angustula Latreille (1811) in Brazil, evaluating the impacts of these insecticides on bees, the implications for ecosystems and safety to feed

Histological Based Environmental Monitoring of the Lower Nun River: Using the Histo-morphometry of Kidney, Gills, Liver, and Testes of Coptodon zillii

It is an ecotoxicological study aimed at using chemical and bio-monitoring methods to pollution status of the Lower Nun River (LNR) basin using the histo-morphometry of the Liver, Kidney, Gills, and the Testes of Coptodon zillii. Based on literature review on the environmental burdens of the LNR, the following Target Chemicals (TC) were chosen for the study: Cadmium (Cd), Chromium (Cr), Copper (Cu), Nickel (Ni) and Lead (Pb). The study involved the sampling of water, sediment and feral fish from two stations along the LNR, Peremabiri (PER) and Igbomotoru(IGB) – Experimental sites.Water and sediment samples were analyzed to ascertain the physico-chemical concentrations of potential contaminants, while the harvest fish organs of liver, kidney, gills and testes were subjected to histological study to ascertain the exposure effect. Control fishes were harvested from African Aqua-culture Centre (ARAC) – Reference Site. Analyzed sediment and water values were used to evaluate Environmental Water Quality Index (EWQI) and sediment quality, while the fish organs were analyzes and used for pollution certification and stratification. Study results showed that EWQI of PER was poor (41.9); sediment quality showed that Cr, CU and Pb were above the Maximum Allowable Toxicant Concentration (MATC) for fresh water body. Fish from IGB showed worse lesion prevalence and organ histopathologic Index (Iorg) when compared to PER, with ARAC having the best outcome. The environmental pollution status (EPS) LNR was normal at PER and was slightly polluted at IGB. The study gave credence to the use of histology as a biomarker to assess sublethal effects of environmental stressors, and in determination of the pollution status.

Study on the response mechanisms and evolution prediction of groundwater microbial-toxicological indicators.

This study aims to investigate the response mechanisms of groundwater microbial-toxicological indicators, specifically total bacteria count (TBC) and total coliform count (TCC), to water quality indicators and environmental conditions. Using data from a water source in the western plateau of China, a predictive model focusing on TBC and TCC was developed. An orthogonal experimental design was employed to manipulate environmental conditions such as temperature, pH, and porosity, facilitating laboratory experiments. These experiments measured pH, chemical oxygen demand (COD), oxidation-reduction potential (ORP), TBC, and TCC at varying depths and environmental conditions. Principal component analysis elucidated the mechanisms by which water quality indicators and environmental conditions affect groundwater microbial-toxicological indicators. A prediction model for these indicators in plateau regions was established based on a backpropagation neural network (BP-NN), using TBC and TCC as target variables and the newly extracted principal components as influencing factors. The results demonstrate that environmental conditions and water quality indicators primarily influence the evolution of groundwater microbial-toxicological indicators by altering the ionic charge quantities, redox conditions, and temperature of the groundwater. The predictive model for groundwater microbial-toxicological indicators shows trends consistent with experimental outcomes, with an average relative error of less than 15%, meeting engineering requirements. PRACTITIONER POINTS: The values of total bacteria count (TBC) and total coliform count (TCC) under different conditions were obtained by column experiments. The influence mechanism of environmental conditions and groundwater indicators on TBC and TCC was elaborated by principal component analysis. TBC and TCC prediction models were established through the investigation of water sources in a plateau area and laboratory experiments.

An integrated novel approach to the environmental health assessment of Bangladesh's coastal ecosystems

The coastal expanse of Bangladesh, situated along the Bay of Bengal, is a susceptible and low-lying area grappling with multiple environmental challenges. Various physicochemical parameters were employed in the assessment of water quality. The CCME Water Quality Index indicated the western coast as 70.13 (Fair), the Central coast as 42.2 (Poor), and the Eastern Coast as 64.6 (Marginal). This outcome was corroborated by the Environmental Quality Index, with the Western Coast ranked as (Good), the Eastern Coast as (Fair), and the Central Coast as (Poor). The analyzed parameters provided insights into pollution levels, water clarity, nutrient dynamics, and the overall health of the coastal ecosystems. Additionally, the study delved into heavy metal concentrations, encompassing arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), manganese (Mn), lead (Pb), and zinc (Zn). The eastern coast exhibited higher contamination compared to the other two regions, emphasizing potential risks to both the environment and human health. This study aimed to evaluate the environmental health risks and water quality in this region, introducing a novel Environmental Health Risk Index (EHRI) to gauge the overall environmental health conditions. According to the EHRI, the Western Coast exhibited good conditions (2.25), while the Central (3.625) and Eastern (3.5) Coasts were classified as not bad, with the Eastern Coast experiencing comparatively lesser impact. Based on these findings, several recommendations emerge, including the implementation of climate change adaptation strategies such as coastal protection measures, the advocacy of sustainable land use practices, and the enhancement of monitoring and management protocols for water quality.

Pembangunan Sistem Informasi Pelaporan Masalah Lingkungan Berbasis Web di Universitas Kristen Satya Wacana

Meeting environmental challenges necessitates the exploration of new and inventive solutions. The Environmental Quality Index (IKLH) report revealed an uptick in Indonesia's index to 72.42 in 2022 from 71.45 in 2021, despite a worsening air quality trend. Acknowledging the importance of Human Resource Management and "Go Green" education in promoting environmental consciousness, this paper proposes the adoption of Laravel for expeditious handling of environmental issues at UKSW. Through the utilization of the Waterfall model and UML methodology, the system integrates MVC architecture, streamlining the process of environmental problem reporting for students. Rigorous Black Box Testing ensures the seamless functionality of the system. Ultimately, this initiative seeks to fortify the university's environmental stewardship while advancing the Go Green campaign, thereby fostering a campus environment that is both pristine and sustainable.