Severe Pollution Research Articles

디자인 씽킹을 적용한 친환경 건축 디자인교육 프로그램 개발 및 효과성 분석 - 중학교 1학년 자유학기제 예술·체육 활동 적용을 중심으로

The recently fast urban growth is leading to being deepened the severe environmental pollution and to being damaged the earth. According to the importance of the global sustainable power generation energy amid this destruction, the eco-friendly education is being carried out. Hence, in the wake of recognizing this issue, this study developed the eco-friendly architectural design education program by connecting the 2022 Revised Curriculum with the achievement standard for a free-semester system in middle school and applied it to the first grade of M middle school during the period of 5 weeks starting from April 29. And to verify effectiveness, the pre and post questionnaires and the student participation reviews were confirmed targeting 43 first graders of M middle school in Jungnang-gu, Seoul who take free semester arts and sports classes for 5 weeks from April 29, 2024 to May 20. As the pre and post survey questions include totally 3 realms such as ‘perception, problem-solving, environment’ in terms of the design thinking and the environmental problem, the item number corresponds to 10 pieces. As a result of t-test in the questions of all realms regarding ‘perception, problem-solving, environment,’ it could be known to have gotten higher after proceeding with the program at the significance level. This outcome shows that the implementation of a class with the application of design thinking leads to being capable of solving a problem by applying and using it even in daily life. It urgently needs the participation in social problem solving and the transformation of school education into self-directed experimental and practical education. In this situation, this study is expected to be likely able to be used as basic data that suggests the directivity of new design education.

Influences of hybrid fiber on functional and drilling characteristics study of polymer hybrid Nanocomposite

The severe environmental pollution related to the manufacturing, recycling and disposal of metal-based and synthetic fiber-based composites has a major impact on human and animal life. A wide range of studies are conducted on alternative materials in order to reduce greenhouse gas emissions. Various industries are focusing on using natural fibers from banana, jute, coir, hemp, pineapple, areca, kenaf, Sterculia foetida and Delonix regia that are the key sources of different components for developing nanocomposites. Drilling is a vital factor in the assembly process of composites. The amorphous structure of the natural fibers causes the formation of cracks at the entry and exit sides of the drilled hole. So, in the present work a nanocomposite was synthesized and optimized the machining parameters, which affect the surface finish of the hole at the entry, exit and inner surface of the drilled hole. The effect of the hybridization of glass fiber with the pineapple leaf fiber and areca fiber was studied in terms of tensile properties, delamination around the hole and surface roughness. The microstructure of the holes was studied by Scanning Electron Microscopy.

Environmental and Climatic Conditions Impacting Cardiovascular Health in Low-Income Countries like Pakistan

The relationship between environmental conditions, climate change, and public health is becoming increasingly critical, especially in low-income countries like Pakistan. Severe air pollution, driven by industrial emissions and vehicular exhaust, poses significant health risks, particularly to cardiovascular health. Prolonged exposure to pollutants like PM2.5 is linked to higher rates of cardiovascular diseases (CVDs) such as stroke and ischemic heart disease. Additionally, climate change has exacerbated these issues, with extreme weather events like heatwaves and floods further straining cardiovascular systems. Addressing these challenges requires coordinated public health initiatives, stricter environmental regulations, and community engagement to raise awareness and promote sustainable practices. Enhanced research and international collaboration are essential to mitigate the adverse health impacts of climate change and environmental degradation on Pakistan's population.

Time Series Forecasting of Air Quality Index in Lahore : A Machine Learning Perspective with Facebook Prophet Model

This research investigates the rising problem of air pollution, which is a serious issue affecting people's health and the environment on a global scale. Focusing on Lahore, Pakistan, a city facing severe pollution, the research examines the Air Quality Index (AQI) from May 2019 to December 2023. Using the Facebook Prophet model for time-series forecasting, the analysis reveals trends at monthly, weekly, and hourly intervals. Peak AQI concentrations are identified in winter months, notably December and January, aligning with hazardous smog levels. Weekly trends show minimum AQI on weekends, particularly Saturday and Sunday. The hourly trend points to peak AQI concentrations between 7:00 and 09:00 AM, correlating with morning traffic and emphasizing the role of vehicular emissions in air quality degradation. These forecasts are crucial for anticipating and mitigating the adverse impact of air pollution on human health. This research underscores the critical need for comprehensive strategies to address air pollution, acknowledging the Lahore High Court and Government's initiatives, such as artificial rain experimentation, closure of commercial markets by 10 PM, ban on cutting trees and smoke-emitting vehicles. In summary, this research significantly contributes to understanding and tackling the increasingly urgent challenges associated with air quality.

Enhanced Hydrophobicity and Oleophilicity of Modified Activated Carbons Derived from Agro-Wastes Biomass for the Removal of Crude Oil from Aqueous Medium

Crude oil spillage has tremendous environmental impacts and poses severe pollution problems worldwide due to the continuous activities and operations in the oil and gas sector. This has resulted in the urgent need for clean-up techniques such as the use of natural adsorbents which is considered a relatively low-cost, readily-available, efficient, eco-friendly, and easy-to-deploy mode of addressing oil spillage due to its high oil sorption capacity/efficiency, high oil selectivity, oleophilic, enduring, reusability and biodegradable properties. Empty palm fruit bunch and coconut coir were used as precursors to produce activated carbons for oil spill remediation. The influence of varying parameters was investigated using a batch experimental procedure resulting in the crude oil adsorption capacity increasing with a corresponding increase in contact time, initial oil concentration, temperature, agitation speed, and particle size but decreasing in adsorbent dosage. The combination of surface morphological modification and hydrophobicity enhancement resulted in significantly improved adsorption capacity for crude oil removal (2710.0 mg/g and 4859.5 mg/g for EPFBAC<SUB>LA</SUB> and CCAC<SUB>L.A</SUB> respectively), as evidenced by both FTIR and SEM analyses. The experimental isotherm data were analysed using various isotherm models and the best-fitted isotherm model was the Freundlich model with a correlation coefficient (R<sup>2 </sup>= 0.991 and R<sup>2 </sup>= 0.999) for EPFB<SUB>L.A</SUB> and CCAC<SUB>L.A</SUB> respectively. The kinetic behaviour of the adsorption process was best described by pseudo-second order with R<sup>2</sup> values of 0.970 and 0.999 for EPFBAC<SUB>LA</SUB> and CCAC<SUB>L.A</SUB> respectively while Boyd model revealed that the adsorption was controlled by an internal transport mechanism and film diffusion was the rate-limiting step. The crude oil adsorption was chemisorption and endothermic owing to the positive enthalpy values (ΔH<sup>o</sup> = 183.890 KJ/mol for EPFBAC<SUB>L.A </SUB>and ΔH<sup>o</sup> = 69.656 KJ/mol for CCAC<SUB>L.A</SUB>), the positive value of entropy suggested that the adsorption process was accompanied by an increase in the degree of randomness or disorder at the interface between the adsorbent and the adsorbate. A temperature rise led to a decline in Gibbs energy (ΔG<sup>o</sup>), suggesting that adsorption became more feasible and spontaneous at higher temperatures and the significant activation energies indicated the existence of a substantial energy barrier that must be overcome to initiate the reaction. The results showed the significant capability of the prepared adsorbents to be used as a low-cost, re-generable and eco-friendly adsorbent in oil spill clean-up and is recommended to exploit its usage on a large scale.

Fabrication of a ZIF-8/PVA Membrane on PVDF Fiber by Spray for the Highly Efficient Separation of Oil-in-Water Emulsions.

In human life and production, excessive oily wastewaters containing detergents are produced and discharged, causing severe environmental pollution and water resource problems. A metal-organic framework (MOF)-based membrane is an economical and environmentally friendly tool for emulsion separation but is limited by a complex preparation process and poor flexibility. Herein, we developed a simple method to synthesize a MOF-based mixed-matrix membrane (MMM) by spray and fabricated the membrane on poly(vinylidene fluoride) (PVDF) fibers via postdeposition and in situ growth manners. The prepared ZIF-8/PVA MMMs have uniform distribution of ZIF-8 particles and poly(vinyl alcohol) (PVA) on the PVDF fibers. PVA improved the adhesion between the ZIF-8 particles and between the MOF layer and PVDF fiber, endowing the separation membrane with high flexibility and bendability. The prepared ZIF-8/PVA membrane exhibited hydrophilicity and underwater superoleophobicity, which showed high separation efficiency and considerable water flux for emulsions, emulsion containing dye, and surfactant-stabilized emulsion. In addition, the fabricated ZIF-8/PVA/PVDF fibers exhibited good antifouling property and flexibility and can maintain stable separation efficiency after working several times and even under bending, demonstrating the stability and potentiality of the ZIF-8/PVA/PVDF fibers in practical applications. This work paves a new avenue for the synthesis and application of MOF-based MMMs.

Role of meteorology and air pollution on fog conditions over Delhi during the peak winter 2024

Severe air pollution and foggy conditions during winter are persistent challenges, pose significant health hazards, and disrupt daily routines worldwide. In this study, we have investigated the conditions favoring the prolonged fog events in Delhi during January 2024 using observations, back trajectories, and reanalysis datasets. Analysis of visibility observations reveals that foggy (54, 121, 139, and 372 half-hours of very dense, dense, moderate, and shallow fog, respectively) conditions persisted in Delhi for 46 % of the time during the study period. The existence of 3–4 days of cold wave to severe cold wave conditions and the lack of passage of strong western disturbances across north and northwest India have also favored the prolonged fog formation. In addition, high relative humidity (>80 %), shallow boundary layer (216 m), stable weather conditions such as the absence of significant surface winds, the existence of cold wave to severe cold wave, temperature inversion (up to 4 °C), poor ventilation, and presence of high particulate matter (PM10: 298 μg/m3 and PM2.5: 182 μg/m3) facilitated the fog formation. Further, analyses reveal a spurt in daily particulate matter (PM10: 603 μg/m3 and PM2.5: 420 μg/m3; 13.4 and 28 times, respectively, exceeded the WHO air quality guideline levels) along with 4.5 h of zero visibility on 14th January. The analysis of particulate matter reveals the dominance of fine particles from nearby regions, which could have originated from the large-scale anthropogenic open biomass burning used for heating activities. The results derived from this study indicate the need for an accurate representation of the local anthropogenic emissions in the atmospheric models to improve the predictability of air quality and fog and provide insights into the need for their control, particularly during such extreme events.

Stochastic dynamics mass spectrometric and Fourier transform infrared spectroscopic structural analyses of composite biodegradable plastics

<p>The (partial) replacement of synthetic polymers with bioplastics is due to increased production of conventional packaging plastics causing for severe environmental pollution with plastics waste. The bioplastics, however, represent complex mixtures of known and unknown (bio)polymers, fillers, plasticizers, stabilizers, flame retardant, pigments, antioxidants, hydrophobic polymers such as poly(lactic acid), polyethylene, polyesters, glycol, or poly(butylene succinate), and little is known of their chemical safety for both the environment and the human health. Polymerization reactions of bioplastics can produce no intentionally added chemicals to the bulk material, which could be toxic, as well. When polymers are used to food packing, then the latter chemicals could also migrate from the polymer to food. This fact compromises the safety for consumers, as well. The scarce data on chemical safety of bioplastics makes a gap in knowledge of their toxicity to humans and environment. Thus, development of exact analytical protocols for determining chemicals of bioplastics in environmental and food samples as well as packing polymers can only provide warrant for reliable conclusive evidence of their safety for both the human health and the environment. The task is compulsory according to legislation Directives valid to environmental protection, food control, and assessment of the risk to human health. The quantitative and structural determination of analytes is primary research task of analysis of polymers. The methods of mass spectrometry are fruitfully used for these purposes. Methodological development of exact analytical mass spectrometric tools for reliable structural analysis of bioplastics only guarantees their safety, efficacy, and quality to both humans and environment. This study, first, highlights innovative stochastic dynamics equations processing exactly mass spectrometric measurands and, thus, producing exact analyte quantification and 3D molecular and electronic structural analyses. There are determined synthetic polymers such as poly(ethylenglycol), poly(propylene glycol), and polyisoprene as well as biopolymers in bags for foodstuffs made from renewable cellulose and starch, and containing, in total within the 20,416–17,495 chemicals per sample of the composite biopolymers. Advantages of complementary employment in mass spectrometric methods and Fourier transform infrared spectroscopy is highlighted. The study utilizes ultra-high resolution electrospray ionization mass spectrometric and Fourier transform infrared spectroscopic data on biodegradable plastics bags for foodstuffs; high accuracy quantum chemical static methods, molecular dynamics; and chemometrics. There is achieved method performance |<em>r</em>| = 0.99981 determining poly(propylene glycol) in bag for foodstuff containing 20,416 species and using stochastic dynamics mass spectrometric formulas. The results highlight their great capability and applicability to the analytical science as well as relevance to both the fundamental research and to the industry.</p>

Priority areas identification for arable soil pollution prevention based on the accumulative risk of heavy metals

Preventing impending heavy metal pollution in arable soil is crucial for ensuring food security and avoiding challenging remediation. The key to effective prevention strategies lies in proactive identifying currently unpolluted regions that are susceptible to future pollution, which current methods, predicated on the assessment of static pollution status, inadequately characterize the potential accumulative changes in soil heavy metals. In this paper, we proposed a framework for identifying priority areas based on the discrepancy between pollution status and accumulative risk, by considering the specific factors that influence heavy metal accumulation in soil. We applied this framework to a region of Xiangtan County to pinpoint priority areas for preventing impending pollution. The result revealed certain areas exhibited a relatively higher accumulative risk of heavy metal pollution, despite not having reached severe pollution levels for the heavy metals Arsenic (As), Cadmium (Cd), Chromium (Cr), Mercury (Hg), and Lead (Pb), among which the area ratio reached nearly 6 %, 36 %, 1 %, 3 %, 4 %, respectively. The priority areas for preventing Cd pollution were primarily concentrated in the mid-southern, mid-western, and eastern regions, while that of the other four heavy metals were predominantly distributed in the mid-northern regions with varying continuous ranges. Moreover, we prioritized the main pollution risks for comprehensive prevention in the following order: Cd, As, Pb, Hg, and Cr, and investigated the key factors contributing to the pollution of these heavy metals. The insights presented in this study have significant implications for soil environmental quality management, offering valuable guidance for implementing precise measures to prevent heavy metal pollution and efficiently control pollution sources.

Grave-to-cradle dry reforming of plastics via Joule heating

Both plastics and CO2 are waste carbon resources, and their accumulation in nature has led to severe environmental pollution. However, simultaneously converting plastic waste and CO2 into value-added chemicals remains a challenge. Here we demonstrate a catalytic reforming process that converts plastics and CO2 into syngas over an electrified FeCrAl heating wire. The temperature of the electrified heating wire can quickly exceed 800 °C, facilitating the decomposition of polyethylene into gaseous hydrocarbons. The high-temperature heating wire promote the CO2 deoxygenation, resulting in the generation of CO, as well as the dehydrogenation of gaseous hydrocarbons. Significantly, the additional O species from CO2 and the carbon species from hydrocarbons can react to form CO, maintaining the high catalytic activity of the electrified heating wire. This novel approach is of paramount to achieving a circular economy in addressing the ongoing environmental crisis caused by the accumulation of plastic waste and excessive CO2 emissions.

Assessment of Multiple Planetary Boundary Layer Height Retrieval Methods and Their Impact on PM2.5 and Its Chemical Compositions throughout a Year in Nanjing

In this study, we investigate the planetary boundary layer height (PBLH) using micro-pulse lidar (MPL) and microwave radiometer (MWR) methods, examining its relationship with the mass concentration of particles less than 2.5 µm in aerodynamic diameter (PM2.5) and its chemical compositions. Long-term PBLH retrieval results are presented derived from the MPL and the MWR, including its seasonal and diurnal variations, showing a superior performance regarding the MPL in terms of reliability and consistency with PM2.5. Also examined are the relationships between the two types of PBLHs and PM2.5. Unlike the PBLH derived from the MPL, the PBLH derived from the MWR does not have a negative correlation under severe pollution conditions. Furthermore, this study explores the effects of the PBLH on different aerosol chemical compositions, with the most pronounced impact observed on primary aerosols and relatively minimal influence on secondary aerosols, especially secondary organics during spring. This study underscores disparities in PBLH retrievals by different instruments during long-term observations and unveils distinct relationships between the PBLH and aerosol chemical compositions. Moreover, it highlights the greater influence of the PBLH on primary pollutants, laying the groundwork for future research in this field.

Unraveling the complex interactions between ozone pollution and agricultural productivity in China's main winter wheat region using an interpretable machine learning framework

Surface ozone has become a significant atmospheric pollutant in China, exerting a profound impact on crop production and posing a serious threat to food security. Previous studies have extensively explored the physiological mechanisms of ozone damage to plants. However, the effects of ozone interactions with other environmental factors, such as climate change, on agricultural productivity at the regional scale, particularly under natural conditions, remain insufficiently understood. In this study, we employed an interpretable machine learning framework, specifically the eXtreme Gradient Boosting (XGBoost) algorithm enhanced by SHapley Additive exPlanations (SHAP), to investigate the influence of ozone and its interactions with environmental factors on crop production in China's primary winter wheat region. Additionally, a structural equation model was developed to elucidate the mechanisms driving these interactions. Our findings demonstrate that ozone pollution exerts a significant negative effect on winter wheat productivity (r = −0.47, P < 0.001), with productivity losses escalating from −12.28 % to −22.09 % as ozone levels increase. Notably, the impact of ozone is spatially heterogeneous, with western Shandong province identified as a hotspot for ozone-induced damage. Furthermore, our results confirm the complexity of the relationship between ozone pollution and agricultural productivity, which is influenced by multiple interacting environmental factors. Specifically, we found that severe ozone pollution, when combined with high aerosol concentrations or elevated temperatures, significantly exacerbates crop productivity losses, although drought conditions can partially mitigate these adverse effects. Our study highlights the importance of incorporating the interactive effects of air pollution and climate change into future crop models. The comprehensive framework developed in this study, which integrates statistical modeling with explainable machine learning, provides a valuable methodological reference for quantitatively assessing the impact of air pollution on crop productivity at a regional scale.

An annual result of outdoor and indoor PM 2.5 analysis in two different building types in Ulaanbaatar, Mongolia.

Air pollution has been a significant environmental and public health concern in Ulaanbaatar, the capital city of Mongolia, for many years. The city experiences severe air pollution, particularly during the winter months. This study investigated the annual trends of outdoor and indoor PM2.5 concentrations at two neighboring sites in Ulaanbaatar: an office and a household, using low-cost sensors. Both locations exhibited similar fluctuations in outdoor PM2.5 concentrations over time, with ambient PM2.5 levels beginning to rise in October and declining in April. During the mid-term of the heating season (November to February), hourly averaged PM2.5 concentrations were exceptionally high, with peak pollution events exceeding ~ 1000µg/m3. Notably, PM2.5 concentrations were elevated during this heating season period. Time-activity patterns showed a decrease in PM2.5 concentrations during the periods of 06:00-08:00 and 14:00-18:00. Furthermore, the study found that the indoor environment could remain safe when windows were well-sealed, even under severe outdoor pollution conditions. Overall, this study provided accurate insights into the annual patterns of PM2.5 concentrations and demonstrated their fluctuations during the heating season when pollution levels were particularly high. The findings offer valuable recommendations for individuals to consider when going outside and for taking actions to improve indoor air quality in Ulaanbaatar.

Techno-economic-environmental analysis based on life cycle carbon accounting and pollutants audit for cleaner production of electrolytic manganese

The electrolytic manganese metal (EMM) industry faces significant environmental challenges, including substantial resource and energy consumption, severe pollution, and high CO2 emissions. This study introduced a novel approach for developing collaborative strategies aimed at mitigating pollutants and CO2 emissions. Through the implementation of life cycle carbon accounting and critical pollutant audits, a process enhancement program incorporating 17 advanced technologies was developed. Aligned with the principles of cleaner production, this project effectively mitigates the environmental burden at the source and offers viable solutions for addressing prominent emissions, such as manganese residue and acid fog. Furthermore, the marginal abatement cost curves demonstrate the economic practicality and applicability of these measures. This study provides a strategic blueprint for achieving sustainable green development in China’s EMM industry and offers valuable guidelines for formulating relevant environmental policies.

Enhanced adsorption of radioactive cesium from nuclear wastewater using ZIF-67 laminated 2D MXene Ti3C2

Development of nuclear industry has caused severe water pollution. Adsorptive removal of radionuclides from wastewater has been regarded as effective solution for environment. However, developing adsorbents with high adsorption capacity and selectivity for removal of radionuclides (such as 137Cs) is still a challenge. Herein, we adopted an in situ assemble strategy to construct a novel composite, in which zeolitic imidazolate framework (ZIF-67) was grafted into two-dimension (2D) layers of transition metal carbides/nitrides (MXenes) Ti3C2, and used it in adsorptive removal of Cs+ from wastewater. Laminated and pillaring effect of ZIF-67 increased interlayer spacing and specific surface area of Ti3C2, significantly enhancing Cs+ adsorption. MXenes matrix provided the main adsorptive sites and interaction to stabilize Cs+, while the hybrid ZIF-67 assisted adsorption. The adsorbent achieved 96.2 % removal for 5 mg·L-1 of Cs+ within 6 h, and 50.0 mg·g−1 of maximum adsorption capacity, with good recyclability for 4 times. Ion competition, kinetics and thermodynamics were studied in detail to obtain the behavior of Cs+ adsorption. Finally, adsorption mechanism was proposed that [Ti − O] − H+ and [Ti − O] groups of 2D Ti3C2 were main adsorptive sites to participate in ion exchange and complexation with Cs+, respectively, while 2-methylimidazole (2-MI) ligands in ZIF-67 were synergetic adsorption sites.

The Impact of Air Pollution Information on Individuals' Exercise Behavior: Empirical Study Using Wearable and Mobile Devices Data.

Physical exercise and exposure to air pollution have counteracting effects on individuals' health outcomes. Knowledge on individuals' real-time exercise behavior response to different pollution information sources remains inadequate. This study aims to examine the extent to which individuals avoid polluted air during exercise activities in response to different air pollution information sources. We used data on individuals' exercise behaviors captured by wearable and mobile devices in 83 Chinese cities over a 2-year time span. In our data set, 35.99% (5896/16,379) of individuals were female and 64% (10,483/16,379) were male, and their ages predominantly ranged from 18 to 50 years. We further augmented the exercise behavior data with air pollution information that included city-hourly level measures of the Air Quality Index and particulate matter 2.5 concentration (in µg/m3), and weather data that include city-hourly level measures of air temperature (ºC), dew point (ºC), wind speed (m/s), and wind direction (degrees). We used a linear panel fixed effect model to estimate individuals' exercise-aversion behaviors (ie, running exercise distance at individual-hour, city-hour, or city-day levels) and conducted robustness checks using the endogenous treatment effect model and regression discontinuity method. We examined if alternative air pollution information sources could moderate (ie, substitute or complement) the role of mainstream air pollution indicators. Our results show that individuals exhibit a reduction of running exercise behaviors by about 0.50 km (or 7.5%; P<.001) during instances of moderate to severe air pollution, and there is no evidence of reduced distances in instances of light air pollution. Furthermore, individuals' exercise-aversion behaviors in response to mainstream air pollution information are heightened by different alternative information sources, such as social connections and social media user-generated content about air pollution. Our results highlight the complementary role of different alternative information sources of air pollution in inducing individuals' aversion behaviors and the importance of using different information channels to increase public awareness beyond official air pollution alerts.

Endocytosis-Inspired Zwitterionic Gel Tape for High-Efficient and Sustainable Underoil Adhesion.

Marine oil exploration is important yet greatly increases the risk of oil leakage, which will result in severe environment pollution and economic losses. It is an urgent need to develop effective underoil adhesives. However, realizing underoil adhesion is even harder than those underwater, due to the stubborn attachment of a highly viscous oil layer on target surface. Here, inspired by endocytosis, a tough gel tape composed of zwitterionic polymer network and zwitterionic surfactants is developed. The amphiphilic surfactants can form micelle to capture the oil droplets and transport them from the interface to gel via electrostatic attraction of polymer backbone, mimicking the endocytosis and achieving robust underoil adhesion. Benefiting from the oil-resistance of polymer backbone, the gel further realizes a combination of i) long-term adhesion with high durability, ii) repeated adhesion in oil, and iii) renewable adhesion efficiency after exhausted use. The tape exhibits an ultra-high adhesive toughness of 2446.86 J m-2 to stainless steel in silicone oil after 30 days' oil-exposure; such value of adhesive toughness surpasses many of those achieved in underwater adhesion and is greater than underoil adhesion performance of commercial tape. The strategy illustrated here will motivate the design of sustainable and efficient adhesives for wet environments.

Solid waste open dumpsite mining in India and sustainable deployment through circular economy

ABSTRACT There are about 3159 open dump sites in India, which cause severe environmental pollution and are a danger to public health. This study demonstrates that the embedded resources in these dumpsites can be recovered profitably. The paper surveys the excavation, segregation, re-cycling and re-use of an open dumpsite containing legacy waste, at a cost of 8 $/m3 of rubbish, recovered, incinerable and inert fractions. A land reclamation of 3.16 ha yielding 1048 tonnes of refuse-derived fuel was achieved. This study demonstrates that dumpsite mining can be profitable while preventing the environmental hazards caused by existing waste dump sites in most Indian cities.

Characterizing and tracing the heavy metals' spatial distribution in karst surface river affected by acid mine drainage

A series of pollution problems have been caused by the drainage of closed coal mines. This study focuses on the XZ River in Guizhou Province, employing a comprehensive approach involving hydrochemical analysis, mathematical statistics, and one-dimensional water quality modeling to investigate the spatial evolution and source apportionment of heavy metals in karst surface rivers affected by AMD. The average pH, EC, and Eh values of groundwater and surface water in the XZ river basin were 6.27, 331 &lt;i&gt;μ&lt;/i&gt;s/cm, 230 mV and 3.86, 1671.57 &lt;i&gt;μ&lt;/i&gt;s/cm, 412.71 mV, respectively, indicating severe pollution of surface water by AMD. The study reveals that groundwater in the XZ River Basin is predominantly of the HCO&lt;sub&gt;3&lt;/sub&gt;-Ca-Mg type, shifting to HCO&lt;sub&gt;3&lt;/sub&gt;-SO&lt;sub&gt;4&lt;/sub&gt;-Ca-Mg type with the influx of acid mine wastewater. Utilizing statistical methods for source apportionment analysis indicated that downstream concentrations of Fe, Mn, Zn, Cu, As, and Sr most likely originate from tributaries. Further analysis through one-dimensional water quality simulation confirmed that downstream concentrations of Fe, Mn, Zn, Cu, As, and Sr are attributed to tributaries. This suggests that XZ River is affected by pollution from different coal mines, primarily from coal mine M4, followed by coal mine M1.

A Novel Strategy for Multitype Fault Diagnosis in Photovoltaic Systems Using Multiple Regression Analysis and Support Vector Machines

This study focuses on analyzing common fault types in photovoltaic (PV) modules, employing fault diagnosis methods based on machine learning technology to enhance the accuracy and efficiency of diagnosing faults in solar power systems. Initially, we collected relevant data from the solar power system and used data analysis techniques to identify system faults, designing a human-machine monitoring interface for practical application. Furthermore, the experimental results proved that the system could accurately identify eight major types of faults, including solar panel output circuits, energy storage batteries, maximum power point tracking (MPPT) controllers, inverters, dust accumulation, loosening of mounting rack screws, damage to the mounting rack foundation, and deformation of the mounting rack structure. Particularly in the detection of dust accumulation, we developed a new method of estimating power generation from multiple regression analysis (MRA), which closely aligns the estimated power output with the actual power output, highlighting the significant impact of dust accumulation on the efficiency of solar power systems. Next, by integrating voltmeters and support vector machines (SVM) into the solar PV array modules, we are able to quickly and accurately measure and locate short-circuit and open-circuit faults in bypass diodes. Ultimately, the proposed PV fault diagnosis strategy includes diagnostics for dust accumulation and mounting frame faults, making it particularly suitable for areas with severe air pollution and frequent earthquakes, providing a comprehensive fault diagnosis solution.