Hasil untuk "Environmental pollution"

Minjun Jo, Yong-Hyun Kim

Tactile toys are handled at close range for prolonged periods, posing potential inhalation risks from volatile organic compounds (VOCs); however, product-specific emission standards are currently absent. We quantified VOCs emitted from nine commercial tactile toys using thermal desorption-gas chromatography-mass spectrometry. Emissions were evaluated using a two-dimensional classification (functional groups and hydrocarbon backbones) and normalized by product mass and surface area. Total VOC concentrations ranged from 24.8 to 775 μg m–3 g–1. Within a given product, increasing the material quantity resulted in highly linear increases in most emitted VOCs (R2 > 0.9), confirming a predictable “dose-with-use” behavior. Across products, class-specific scaling was evident: aromatics scaled with mass (R2 = 0.8234), while sulfur-containing compounds scaled with both mass and surface area (R2 > 0.8362). Stratification by sensory attributes revealed that sticky and sweet-scented products exhibited significant scaling for ethers and alcohols, likely driven by high free volume and surface-localized additives. Hazardous process-related residues, including dimethylformamide and methylene chloride (identified via NIST library search with >95% similarity), were detected at levels that, in screening-level comparisons, significantly exceeded the US EPA Reference Concentrations. These findings characterize the “initial burst” of high-concentration VOCs encountered upon product unpacking, providing a critical benchmark for acute exposure risks. This research underscores the importance of controlling residual solvents and highlights the urgent need for standardized, product-specific emission testing and safety guidelines for tactile toys.

Airong Zhang, Christina Maxwell, Peggy Schrobback et al.

Global seafood consumption has increased steadily over the past decade, making it the most traded animal protein worldwide. To meet growing demand, seafood production must expand. Yet, this growth poses significant environmental risks, including habitat loss, water pollution, and species depletion. Ensuring sustainable production is therefore critical, with certification schemes playing a key role in communicating sustainability to consumers. However, consumer trust in these certifications varies widely. This study investigates consumer trust in four types of certification agencies for seafood imported from developed countries: Exporting country government agencies, exporting country certification agencies, international certification agencies, and local certification agencies. An online survey (N = 12,222) was conducted across 12 markets: Australia, mainland China, Hong Kong (China), India, Indonesia, Japan, New Zealand, Singapore, South Korea, Taiwan, the USA, and Vietnam. The results indicated that sustainability certifications are valued across all markets, with particularly elevated importance observed in comparatively lower-income markets as indicated by GDP per capita (mainland China, India, Indonesia, Vietnam), where trust in all certification types was notably higher. Conversely, Japan and Taiwan exhibited the lowest trust levels. Within-market analysis identified three distinct trust preference groups: the Local Preference Group (Australia, Japan, USA, New Zealand, Singapore), the International Preference Group (Indonesia, Hong Kong, Taiwan, Vietnam), and the Equal Preference Group (mainland China, India, South Korea). These findings offer actionable insights for seafood businesses, importers, and exporters to tailor certification strategies to market-specific trust patterns, ultimately supporting the promotion of sustainable seafood consumption globally.

Zehong Yan, Peng Qi, Wynne Hsu et al.

While large generative artificial intelligence (GenAI) models have achieved significant success, they also raise growing concerns about online information security due to their potential misuse for generating deceptive content. Out-of-context (OOC) multimodal misinformation detection, which often retrieves Web evidence to identify the repurposing of images in false contexts, faces the issue of reasoning over GenAI-polluted evidence to derive accurate predictions. Existing works simulate GenAI-powered pollution at the claim level with stylistic rewriting to conceal linguistic cues, and ignore evidence-level pollution for such information-seeking applications. In this work, we investigate how polluted evidence affects the performance of existing OOC detectors, revealing a performance degradation of more than 9 percentage points. We propose two strategies, cross-modal evidence reranking and cross-modal claim-evidence reasoning, to address the challenges posed by polluted evidence. Extensive experiments on two benchmark datasets show that these strategies can effectively enhance the robustness of existing out-of-context detectors amidst polluted evidence.

Habeeb Balogun, Yahaya Zakari

Air pollution forecasting is critical for proactive environmental management, yet data irregularities and scarcity remain major challenges in low-resource regions. Northern Nigeria faces high levels of air pollutants, but few studies have systematically compared the performance of advanced machine learning models under such constraints. This study evaluates Long Short-Term Memory (LSTM) networks and the Facebook Prophet model for forecasting multiple pollutants (CO, SO2, SO4) using monthly observational data from 2018 to 2023 across 19 states. Results show that Prophet often matches or exceeds LSTM's accuracy, particularly in series dominated by seasonal and long-term trends, while LSTM performs better in datasets with abrupt structural changes. These findings challenge the assumption that deep learning models inherently outperform simpler approaches, highlighting the importance of model-data alignment. For policymakers and practitioners in resource-constrained settings, this work supports adopting context-sensitive, computationally efficient forecasting methods over complexity for its own sake.

Tianxu Wang, Jiwoon Sim, Hao Wang

Personality traits, such as boldness and shyness, play a significant role in shaping the survival strategies of animals. Industrial pollution has long posed serious threats to ecosystems and is typically distributed heterogeneously. However, how animals with different personalities respond to spatially heterogeneous pollution remains largely unexplored. In this study, we introduce a prey-taxis model with nonlinear cross-diffusion to examine population dynamics in such environments. The global existence of classical solutions is established by deriving initial bounds through energy estimates and improving solution regularity via heat kernel properties and a bootstrap process. Our findings reveal that behavior, population structure, and spatial distribution are heavily influenced by pollution. Bold individuals maintain a competitive advantage in pollution-free or very low-toxin environments, whereas shy individuals become dominant in regions with low to moderate toxin levels. In highly polluted areas, no populations can survive. The spatial pattern of the population is also closely tied to the distribution of toxins. Grazers tend to move along toxin gradient and exhibit periodic behavior. As toxin concentrations rise, aggregation behavior becomes increasingly pronounced across all species. Interestingly, the total population in polluted areas may initially increase when toxin levels are low to moderate, but eventually declines, leading to extinction as toxin levels continue to rise.

Joshua Taylor

We design a model-predictive controller for managing the actuators in sewer networks. It minimizes flooding and combined-sewer overflow during rain and pollution at other times. To make the problem tractable, we use a convex relaxation of the microbial growth kinetics and a physically motivated linearization of the mass flow bilinearities. With these approximations, the trajectory optimization in each control period is a second-order cone program. In simulation, the controller releases roughly 15% less pollutant mass than a conventional controller while treating nearly the same volume of flow. It does so by better balancing the flow over the treatment plants and over time.

Théophile Chaumont-Frelet, Patrick Henning

In this paper, we investigate the approximation properties of solutions to the Ginzburg-Landau equation (GLE) in finite element spaces. Special attention is given to how the errors are influenced by coupling the mesh size $h$ and the polynomial degree $p$ of the finite element space to the size of the so-called Ginzburg-Landau material parameter $κ$. As observed in previous works, the finite element approximations to the GLE are suffering from a numerical pollution effect, that is, the best-approximation error in the finite element space converges under mild coupling conditions between $h$ and $κ$, whereas the actual finite element solutions possess poor accuracy in a large pre-asymptotic regime which depends on $κ$. In this paper, we provide a new error analysis that allows us to quantify the pre-asymptotic regime and the corresponding pollution effect in terms of explicit resolution conditions. In particular, we are able to prove that higher polynomial degrees reduce the pollution effect, i.e., the accuracy of the best-approximation is achieved under relaxed conditions for the mesh size. We provide both error estimates in the $H^1$- and the $L^2$-norm and we illustrate our findings with numerical examples.

Ricardo Baettig, Ben Ingram

This study presents a comprehensive latitudinal analysis of air particulate matter (PM) across an 1400 km pollution corridor spanning Chile’s central-southern zone. We systematically analyzed PM_2.5 and PM₁₀ concentrations across eight major urban centers (2014–2015), providing crucial pre-Paris Agreement baseline data for South America’s most extensive air quality monitoring network. Our analysis reveals significant pollution gradients, with Coyhaique ranking one of the world’s most severely polluted cities (95th percentile globally, WHO database) and demonstrating an extreme 86% fine particulate matter ratio that far exceeds international urban standards. Residential wood combustion (RWC) demonstrates systematic correlations with fine PM concentrations (R² > 0.96), suggesting RWC is the dominant pollution driver across multiple climate zones. The documented pollution patterns represent a concerning continental-scale environmental pattern, with 4900–6500 annual premature deaths directly attributable to PM_2.5 exposure-one of the highest per-capita pollution mortality rates in South America. This work provides a methodological framework applicable to mountain-valley pollution systems globally while addressing critical knowledge gaps in regional air quality science. The evidence indicates the need for urgent implementation of comprehensive wood combustion control strategies and positions this research as essential baseline documentation for both national air quality policy and international climate change assessment frameworks.

Hankun He, Benjamin Schäfer, Christian Beck

Outdoor air pollution is estimated to cause a huge number of premature deaths worldwide, it catalyses many diseases on a variety of time scales, and it has a detrimental effect on the environment. In light of these impacts it is necessary to obtain a better understanding of the dynamics and statistics of measured air pollution concentrations, including temporal fluctuations of observed concentrations and spatial heterogeneities. Here we present an extensive analysis for measured data from Europe. The observed probability density functions (PDFs) of air pollution concentrations depend very much on the spatial location and on the pollutant substance. We analyse a large number of time series data from 3544 different European monitoring sites and show that the PDFs of nitric oxide ($NO$), nitrogen dioxide ($NO_{2}$) and particulate matter ($PM_{10}$ and $PM_{2.5}$) concentrations generically exhibit heavy tails. These are asymptotically well approximated by $q$-exponential distributions with a given entropic index $q$ and width parameter $λ$. We observe that the power-law parameter $q$ and the width parameter $λ$ vary widely for the different spatial locations. We present the results of our data analysis in the form of a map that shows which parameters $q$ and $λ$ are most relevant in a given region. A variety of interesting spatial patterns is observed that correlate to properties of the geographical region. We also present results on typical time scales associated with the dynamical behaviour.

Dang Pham, Hanno Rein

Observations point to old white dwarfs (WDs) accreting metals at a relatively constant rate over 8~Gyrs. Exo-Oort clouds around WDs have been proposed as potential reservoirs of materials, with galactic tide as a mechanism to deliver distant comets to the WD's Roche limit. In this work, we characterise the dynamics of comets around a WD with a companion having semi-major axes on the orders of 10 - 100 AU. We develop simulation techniques capable of integrating a large number ($10^8$) of objects over a 1 Gyr timescale. Our simulations include galactic tide and are capable of resolving close-interactions with a massive companion. Through simulations, we study the accretion rate of exo-Oort cloud comets into a WD's Roche limit. We also characterise the dynamics of precession and scattering induced on a comet by a massive companion. We find that (i) WD pollution by an exo-Oort cloud can be sustained over a Gyr timescale, (ii) an exo-Oort cloud with structure like our own Solar System's is capable of delivering materials into an isolated WD with pollution rate $\sim 10^8 \mathrm{~g~s^{-1}}$, (iii) adding a planetary-mass companion reduces the pollution rate to $\sim 10^7 \mathrm{~g~s^{-1}}$, and (iv) if the companion is stellar-mass, with $M_p \gtrsim 0.1 M_\odot$, the pollution rate reduces to $\sim 3 \times 10^5 \mathrm{~g~s^{-1}}$ due to a combination of precession induced on a comet by the companion, a strong scattering barrier, and low-likelihood of direct collisions of comets with the companion.

Aiden Price, Kerrie Mengersen, Michael Rigby et al.

Extreme natural hazards are increasing in frequency and intensity. These natural changes in our environment, combined with man-made pollution, have substantial economic, social and health impacts globally. The impact of the environment on human health (environmental health) is becoming well understood in international research literature. However, there are significant barriers to understanding key characteristics of this impact, related to substantial data volumes, data access rights and the time required to compile and compare data over regions and time. This study aims to reduce these barriers in Australia by creating an open data repository of national environmental health data and presenting a methodology for the production of health outcome-weighted population vulnerability indices related to extreme heat, extreme cold and air pollution at various temporal and geographical resolutions. Current state-of-the-art methods for the calculation of vulnerability indices include equal weight percentile ranking and the use of principal component analysis (PCA). The weighted vulnerability index methodology proposed in this study offers an advantage over others in the literature by considering health outcomes in the calculation process. The resulting vulnerability percentiles more clearly align population sensitivity and adaptive capacity with health risks. The temporal and spatial resolutions of the indices enable national monitoring on a scale never before seen across Australia. Additionally, we show that a weekly temporal resolution can be used to identify spikes in vulnerability due to changes in relative national environmental exposure.

Guoqi ZHANG, Di MENG, Bin XIA et al.

Plastic products are widely used in human daily life, while facilitating human life, plastics have also produced many negative effects due to the lack of effective recovery measures, plastic pollution has become an important environmental issue of global concern. Marine plastics can be degraded into smaller microplastics (MPs) through various ways under the influence of environmental factors. They can be ingested by marine organisms mixed with food sources, and then accumulated in the body, causing serious negative effects on marine lifes and marine ecology. Recently, it has been proved that the Changshan Islands sediments contain a certain amount of MPs, the content reached 133.14 to 499.82 n/kg. Changshan Islands is one of the eight major islands in China. It is located at the confluence of the Yellow Sea and the Bohai Sea, and has a unique geographical location. The fish community between the islands is rich in species, especially in many migratory species, and high in species diversity. The seasonal change of fish species composition and dominant species is obvious. It has been proved MPs can cause a certain degree of harm to marine organisms. Therefore, the distribution of MPs in organisms in the Changshan Islands sea area deserves to be studied. In this study, the MPs in the gastrointestinal tracts and muscles of wild fish were digested and separated after collecting them from the marine culture zone of Changshan Islands. The results showed that MPs were detected existing in the gastrointestinal tracts of all fish, but not in muscle tissues. The reason may be that MPs are too large to be endocytosed by intestinal epithelial cells, and thus can not participate in the blood circulation of fish. The abundance of MPs in the gastrointestinal tracts of seven species of marine wild fish ranged from 0.19 to 3.79 items/individual. The abundance of MPs in Coilia nasus is the highest among all fish, this phenomenon may be related to the living environment and predation habits of C. nasus, which living in the bottom of the sea. The MPs in sediments will undergo a cyclic process of suspension, sedimentation and resuspension under the flow of seawater, thus greatly increasing the exposure and intake risk of MPs by bottom organisms, such as C. nasus. The shape of MPs was dominated by the fiber, and the color was mostly transparent, which size is mainly less than 300 μm. The reason may be that the individual size of fish collected in this survey is small, and larger-sized MPs cannot enter into the gastrointestinal tract of fish through feeding. Large plastics in the environment are broken under the photooxidation, wave action, physical wear and alternating freeze-thaw. The different shapes of MPs detected in this study may be derived from the decomposition of these large plastics. Fibers are the predominant form of MPs encountered in global wildlife studies. It could also be because fibrous MPs are the most abundant in the marine environment. Additionally, MPs Fibers can be bended or intertwined with food, possibly due to long-term accumulation for the slower fibers excretion, increasing the chance of being ingested by organisms. The types of polymers detected were cellophane, cellulose and polyethylene, among which cellophane had the highest content. Cellophane is an organic cellulose-based polymer that has been used in food packaging and cigarette packaging. It is also used as a release agent in the manufacture of glass fiber and rubber products, or as a coating in combination with synthetic polymers. There was no obvious toxic effect on cellulose and cellulite. The polymer hazard index (PHI) is an important criterion for risk assessment of MPs, and is based primarily on the percentage content of a given polymer and the polymer's hazard fraction for ecological and health risk assessment. The potential risk of MPs to humans can be estimated by the polymer hazard index. The higher the polymer hazard index, the higher the ecological risk in the sea area. The toxicity coefficient of polyethylene is 10, the toxicity grade is grade II, the hazard index is low, and it belongs to the low risk polymer. Moreover, people usually discard the gastrointestinal tract of fish before eating, thus the MPs in the fishes of Changshan Islands, and the safety factor of fish products in Changshan Islands is higher. In this study, through the collection of wild fish in Changshan Islands, the MPs in gastrointestinal tract and muscle tissue were extracted, and the abundance and type of MPs were analyzed. The pollution status of MPs in fish in the adjacent waters of Changshan Islands was clarified, which provided basic data for exploring the impact of MPs on the ecological environment safety of Changshan Islands ecosystem. Further research on the distribution of MPs in other wild organisms, such as shellfish, and in other economically viable locations should be considered, which can provide a scientific basis for the analysis of MP pollution levels and the formulation of prevention and control strategies in the marine environment.

P. Duan, H. Li, Z. Ma et al.

<p>The 8.2 ka event has been extensively investigated as a remarkable single event but rarely considered as a part of multi-centennial climatic evolution. Here, we present absolutely dated speleothem multi-proxy records spanning 9.0–7.9 ka from Beijing in North China, near the northern limit of the East Asian summer monsoon (EASM) and thus sensitive to climate change, to provide evidence of the intensified multi-decadal climatic oscillations since 8.52 ka. Three extreme excursions characterized by inter-decadal consecutive <span class="inline-formula"><i>δ</i>¹⁸</span>O excursions exceeding <span class="inline-formula">±1<i>σ</i></span> are identified from 8.52 ka in our speleothem record. The earlier two are characterized by enriched <span class="inline-formula">¹⁸</span>O at <span class="inline-formula">∼8.50</span> and 8.20 ka, respectively, suggesting a prolonged arid event, which is supported by the positive trend in <span class="inline-formula"><i>δ</i>¹³</span>C values, increased trace element ratios, and lower growth rate. Following the 8.2 ka event, an excessive rebound immediately emerges in our <span class="inline-formula"><i>δ</i>¹⁸</span>O and trace element records but moderate in the <span class="inline-formula"><i>δ</i>¹³</span>C, probably suggesting pluvial conditions and nonlinear response of the local ecosystem. Following two similar severe droughts at 8.50 and 8.20 ka, the different behavior of <span class="inline-formula"><i>δ</i>¹³</span>C suggests the recovering degree of resilient ecosystem responding to different rebounded rainfall intensity. A comparison with other high-resolution records suggests that the two droughts–one pluvial pattern between 8.52 and 8.0 ka is of global significance instead of being a regional phenomenon, and is causally linked to the slowdown and acceleration of the Atlantic Meridional Overturning Circulation that was further dominated by the freshwater injections in the North Atlantic.</p>

Suhaib Al-Karawi, Aws Al-Taie

The outdoor insulators suffer external effects that adversely impact their performance and lifespan. Wettability and pollution have a negative role by increasing the likelihood of insulators surface flashover. Coatings are applied on the insulators to enhance surface hydrophobicity to cope with these external effects. Besides experimental testing, simulating the electric field distribution is a useful tool to study the insulator performance and where the surface discharges initiate. In this work, finite element method simulation is used for analyzing the electric field distribution of uncoated and coated insulators under different environmental conditions. The case of uniformly distributed wettability/pollution and perfect coating, with same thickness, on insulators surfaces is assumed. Cap and pin U40B-class porcelain 11 kV single disc and 33 kV three discs string insulators are considered. The studied coatings include two conventional hydrophobic, Al2O3 and RTV-SR, and one proposed superhydrophobic PTFE materials. The results of the maximum electric field of coated insulators are compared with respect to their equivalents of wet-polluted uncoated insulators. The proposed PTFE coating yielded the highest percentages of maximum electric field reduction compared to the other two conventional coatings. The PTFE coating for 11 kV single porcelain insulator yielded reduction for the maximum electric field by 84.754 % under rain condition and 98.848 % under fog condition while for 33 kV three discs string porcelain insulators, the percentages reached 84.288 % under rain condition and 97.315 % under fog condition. PTFE material has a good potential for insulator coating yielding less flashover likelihood and better insulator performance under pollution conditions.

Pamela Y. Vélez-Terreros, David Romero-Estévez, Gabriela S. Yánez-Jácome

Pollution from plastic debris and microplastics (MPs) is a worldwide issue. Classified as emerging contaminants, MPs have become widespread and have been found not only in terrestrial and aquatic ecosystems but also within the food chain, which affects both the environment and human health. Since the outbreak of COVID-19, the consumption of single-use plastics has drastically increased, intensifying mismanaged plastic waste in countries such as Ecuador. Therefore, the aim of this review is to 1) summarize the state of MP-related knowledge, focusing on studies conducted with environmental matrices, biota, and food, and 2) analyze the efforts by different national authorities and entities in Ecuador to control MP contamination. Results showed a limited number of studies have been done in Ecuador, which have mainly focused on the surface water of coastal areas, followed by studies on sediment and food. MPs were identified in all samples, indicating the lack of wastewater management policies, deficient management of solid wastes, and the contribution of anthropogenic activities such as artisanal fishing and aquaculture to water ecosystem pollution, which affects food webs. Moreover, studies have shown that food contamination can occur through atmospheric deposition of MPs; however, ingredients and inputs from food production, processing, and packaging, as well as food containers, contribute to MP occurrence in food. Further research is needed to develop more sensitive, precise, and reliable detection methods and assess MPs' impact on terrestrial and aquatic ecosystems, biota, and human health. In Ecuador specifically, implementing wastewater treatment plants in major cities, continuously monitoring MP coastal contamination, and establishing environmental and food safety regulations are crucial. Additionally, national authorities need to develop programs to raise public awareness of plastic use and its environmental effects, as well as MP exposure's effects on human health.

Heejun Shin, Danielle Braun, Kezia Irene et al.

We develop new methodology to improve our understanding of the causal effects of multivariate air pollution exposures on public health. Typically, exposure to air pollution for an individual is measured at their home geographic region, though people travel to different regions with potentially different levels of air pollution. To account for this, we incorporate estimates of the mobility of individuals from cell phone mobility data to get an improved estimate of their exposure to air pollution. We treat this as an interference problem, where individuals in one geographic region can be affected by exposures in other regions due to mobility into those areas. We propose policy-relevant estimands and derive expressions showing the extent of bias one would obtain by ignoring this mobility. We additionally highlight the benefits of the proposed interference framework relative to a measurement error framework for accounting for mobility. We develop novel estimation strategies to estimate causal effects that account for this spatial spillover utilizing flexible Bayesian methodology. Lastly, we use the proposed methodology to study the health effects of ambient air pollution on mortality among Medicare enrollees in the United States.

Van-Duc Le, Tien-Cuong Bui, Sang-Kyun Cha

Citywide Air Pollution Forecasting tries to precisely predict the air quality multiple hours ahead for the entire city. This topic is challenged since air pollution varies in a spatiotemporal manner and depends on many complicated factors. Our previous research has solved the problem by considering the whole city as an image and leveraged a Convolutional Long Short-Term Memory (ConvLSTM) model to learn the spatiotemporal features. However, an image-based representation may not be ideal as air pollution and other impact factors have natural graph structures. In this research, we argue that a Graph Convolutional Network (GCN) can efficiently represent the spatial features of air quality readings in the whole city. Specially, we extend the ConvLSTM model to a Spatiotemporal Graph Convolutional Recurrent Neural Network (Spatiotemporal GCRNN) model by tightly integrating a GCN architecture into an RNN structure for efficient learning spatiotemporal characteristics of air quality values and their influential factors. Our extensive experiments prove the proposed model has a better performance compare to the state-of-the-art ConvLSTM model for air pollution predicting while the number of parameters is much smaller. Moreover, our approach is also superior to a hybrid GCN-based method in a real-world air pollution dataset.

Yu-Hsuan Ho, Zhewei Liu, Cheng-Chun Lee et al.

Understanding the key factors shaping environmental hazard exposures and their associated environmental injustice issues is vital for formulating equitable policy measures. Traditional perspectives on environmental injustice have primarily focused on the socioeconomic dimensions, often overlooking the influence of heterogeneous urban characteristics. This limited view may obstruct a comprehensive understanding of the complex nature of environmental justice and its relationship with urban design features. To address this gap, this study creates an interpretable machine learning model to examine the effects of various urban features and their non-linear interactions to the exposure disparities of three primary hazards: air pollution, urban heat, and flooding. The analysis trains and tests models with data from six metropolitan counties in the United States using Random Forest and XGBoost. The performance is used to measure the extent to which variations of urban features shape disparities in environmental hazard levels. In addition, the analysis of feature importance reveals features related to social-demographic characteristics as the most prominent urban features that shape hazard extent. Features related to infrastructure distribution and land cover are relatively important for urban heat and air pollution exposure respectively. Moreover, we evaluate the models' transferability across different regions and hazards. The results highlight limited transferability, underscoring the intricate differences among hazards and regions and the way in which urban features shape hazard exposures. The insights gleaned from this study offer fresh perspectives on the relationship among urban features and their interplay with environmental hazard exposure disparities, informing the development of more integrated urban design policies to enhance social equity and environmental injustice issues.

Jayson M. Victoriano, Manuel Luis C. Delos Santos, Albert A. Vinluan et al.

This study aims to predict the pollution level that threatens the Marilao River, located in the province of Bulacan, Philippines. The inhabitants of this area are now being exposed to pollution. Contamination of this waterway comes from both formal and informal industries, such as a used lead-acid battery, open dumpsites metal refining, and other toxic metals. Using various water quality parameters like Dissolved Oxygen (DO), Potential of Hydrogen (pH), Biochemical Oxygen Demand (BOD) and Total Suspended Solids (TSS) were the basis for predicting the pollution level. This study used the Data Mining technique based on the sample data collected from January of 2013 to November of 2017. These were used as a training data and test results to predict the river condition with its corresponding pollution level classification indicated with the used of colors such as Green for Normal, Yellow for Average, Orange for Polluted and Red for Highly Polluted. The model got an accuracy of 91.75% with a Kappa value of 0.8115, interpreted as Strong in terms of the level of agreement.

Widya Ayu Nirmala Sari

Based on the 1945 Constitution Article 1 paragraph 3, Indonesia is a state ruled by law since the constitution of Indonesia incorporated several legal systems. The law should be fair, impartial to those in power and not intimidate the weak. However, the law is often misused and traded for the interests of those in power. This study aims to find out how the law is enforced against PT Rayon Utama Makmur that has harmed local residents for causing environmental pollution as a result of the textile factory activities. Data are collected from literature. The theory used is the conflict theory of Karl Marx given that there was a conflict of interest between PT Rayon Utama Makmur and the local residents. The results of the study indicate that the law enforcement against PT Rayon Utama Makmur is still very weak. After being proven to have polluted the environment by dumping the factory waste into the river thus endangering the health of the residents, PT Rayon Utama Makmur did not receive any significant sanctions so that it did not cause a deterrent effect for the company. The weak law enforcement for PT Rayon Utama Makmur caused injustice for the residents. And that gradually triggered a conflict between the residents and the company.