Effective Mitigation Measures Research Articles

Sequence Deep Learning for Seismic Ground Response Modeling: 1D-CNN, LSTM, and Transformer Approach

Accurate seismic ground response analysis is crucial for the design and safety of civil infrastructure and establishing effective mitigation measures against seismic risks and hazards. This is a complex process due to the nonlinear soil properties and complicated underground geometries. As a simplified approach, the one-dimensional wave propagation model, which assumes that seismic waves travel vertically through a horizontally layered medium, is widely adopted for its reasonable performance in many practical applications. This study explores the potential of sequence deep learning models, specifically 1D convolutional neural networks (1D-CNNs), long short-term memory (LSTM) networks, and transformers, as an alternative for seismic ground response modeling. Utilizing ground motion data from the Kiban Kyoshin Network (KiK-net), we train these models to predict ground surface acceleration response spectra based on bedrock motions. The performance of the data-driven models is compared with the conventional equivalent-linear analysis model, SHAKE2000. The results demonstrate that the deep learning models outperform the physics-based model across various sites, with the transformer model exhibiting the smallest average prediction error due to its ability to capture long-range dependencies. The 1D-CNN model also shows a promising performance, albeit with occasional higher errors than the other models. All the data-driven models exhibit efficient computation times of less than 0.4 s for estimation. These findings highlight the potential of sequence deep learning approaches for seismic ground response modeling.

Potential use of methane gas from the Villavicencio sanitary landfill, Colombia

The study evaluates the generation and recovery capacity of methane at the Villavicencio Landfill in Colombia, using the LandGEM model. It shows a significant increase in methane generation, rising from about 1.5 million cubic meters in 2010 to over 8.5 million in 2020, indicating a growing urgency to implement effective mitigation measures. It was estimated that by the year 2042, the electrical energy production from methane could be 248.067 kW/day, capable of supplying about 43.705 homes monthly. Additionally, thermal energy generation would be 468.572 kWh/day, useful for industrial processes. Management scenarios were proposed, where, for example, operational optimization could increase electric production to 342.333 kW/day, benefiting more than 60.000 homes monthly. The conclusions highlight the direct correlation between the amount of waste and methane generation, and the significant potential for converting these emissions into energy, pointing towards regional energy self-sufficiency and sustainability. Methane recovery represents a valuable alternative to the dependence on fossil fuels and for the development of a circular economy.

The Extraction and Characterization of Microplastics of Biocompost and Water Samples Collected from the Different Semi-Urban Agronurseries

ABSTRACT Biocomposting at national and regional levels has recently been recognized as one of the feasible, nature-based solutions to prevent the accumulation and reuse of biodegradable waste in enhanced and effective mitigation measures for urban and semi-urban waste management. Recent research has mainly focused on organic compost contamination, as the negative effects of MP on soil systems have been extensively studied. According to current research, organic compost used as fertilizer on farmland contains many microplastics. In this context, microplastics (MPs) have been regarded as a global environmental problem and an emerging soil contaminant. The physico-chemical properties of water and compost samples were analyzed by APHA and AOAC methods. The extraction of microplastics was done using the density separation. In the current study, agricultural waste-based biocompost and water samples used for the production of biocompost were collected from four different agricultural nurseries in semi-urban areas of the Coimbatore city. The physicochemical properties (including heavy metal content) of the biocompost and water samples tested were on par/equal/lower than Indian standards. Interestingly, in the biocompost samples, 85% of the microplastic fragments and 15% of the fiber types were identified only in BC-B and BC-C, respectively, with different colors such as red, brown, blue, light yellow and transparency. However, no microplastics were found in the biocompost samples of BC-A and BC-D. Microplastic polymers such as polymethyl methacrylate (PMMA), polypropylene (PP), and ethylene vinyl acetate (EVA) were identified through ATR-FTIR analysis. The results suggest that semi-urban agricultural gardening may lead to the accumulation of microplastics in terrestrial environments, which may negatively impact soil and plant health. This study contributes to growing research into microplastic contamination in organic compost and its potential impact on agriculture and terrestrial ecosystems.

Adapting an environmental impact assessment method for open pit mines in Myanmar: A modified semi-mathematical Folchi approach

Since 1970, the global adoption of Environmental Impact Assessment (EIA) has fostered the development of multiple EIA methodologies, ranging from sample techniques to scientific approaches, for assessing environmental impacts. These methodologies encompass diverse models such as Ad hoc, matrices, checklist, network, overlay, mathematical, simulation, and dispersion models. Among these, the Folchi method is one of the quantitative matrix methods, assigning magnitudes to each impacting factor based on different possible scenarios. In this method, a matrix consisting of weighting factors is systematically utilized to quantify and standardize the effect of each impacting factor on various environmental components. Myanmar, as a developing nation that has recently implemented EIA practices, has encountered significant challenges in the realm of EIA, particularly concerning methodologies for impact evaluation, assessment, and the formulation of effective mitigation measures for various development projects. To address these challenges, this study introduces an adapted semi-mathematical Folchi EIA method, demonstrating its application in open-pit mines across Myanmar. Adjustments were made to integrate domestic environmental guidelines and EIA procedures, often overlooked in previous studies. The assessment of impact magnitude prioritizes sensitivity, project type and size, and pollution thresholds. Additionally, the correlation weights (nil, minimum, medium, maximum) between impact factors and environmental components were also adjusted based on the project's nature and regional conditions. The findings of this study revealed both positive and negative environmental impacts associated with the four case study mines. Decision-makers and stakeholders can utilize this approach in decision making process, advancing sustainable development. With suitable adaptation, this approach can facilitate a rapid and comprehensive assessment of diverse environmental and social impacts associated with various development projects in the country.

Adapting an environmental impact assessment method for open pit mines in Myanmar: A modified semi-mathematical Folchi approach

Since 1970, the global adoption of Environmental Impact Assessment (EIA) has fostered the development of multiple EIA methodologies, ranging from sample techniques to scientific approaches, for assessing environmental impacts. These methodologies encompass diverse models such as Ad hoc, matrices, checklist, network, overlay, mathematical, simulation, and dispersion models. Among these, the Folchi method is one of the quantitative matrix methods, assigning magnitudes to each impacting factor based on different possible scenarios. In this method, a matrix consisting of weighting factors is systematically utilized to quantify and standardize the effect of each impacting factor on various environmental components. Myanmar, as a developing nation that has recently implemented EIA practices, has encountered significant challenges in the realm of EIA, particularly concerning methodologies for impact evaluation, assessment, and the formulation of effective mitigation measures for various development projects. To address these challenges, this study introduces an adapted semi-mathematical Folchi EIA method, demonstrating its application in open-pit mines across Myanmar. Adjustments were made to integrate domestic environmental guidelines and EIA procedures, often overlooked in previous studies. The assessment of impact magnitude prioritizes sensitivity, project type and size, and pollution thresholds. Additionally, the correlation weights (nil, minimum, medium, maximum) between impact factors and environmental components were also adjusted based on the project's nature and regional conditions. The findings of this study revealed both positive and negative environmental impacts associated with the four case study mines. Decision-makers and stakeholders can utilize this approach in decision making process, advancing sustainable development. With suitable adaptation, this approach can facilitate a rapid and comprehensive assessment of diverse environmental and social impacts associated with various development projects in the country.

Provincial emission inventory of atmospheric polycyclic aromatic hydrocarbons (PAHs) in China

China, as the largest global emitter of atmospheric polycyclic aromatic hydrocarbons (PAHs), exhibits significant variation in energy structure and technological capabilities among provinces. It is vital to construct a provincial-level emission inventory of PAHs, fully considering these provincial disparities, for assessing the environmental budgets and instituting effective mitigation measures. This study constructed a dataset of provincial PAHs emission factors based on downscaling estimates by incorporating the Human Development Index (HDI). These emission factors were combined with the latest activity rate data to estimate PAHs emissions from individual provinces in China from 2007 to 2017. The national total PAHs emissions in our study were 11.8–12.3% higher than the previous emission inventory results. The validation results indicated that the inventory-based PAHs emissions were significantly correlated with the simulated emissions by an atmospheric box model and watershed model. From 2007 to 2017, nearly three-quarters of provinces declined in PAHs emissions resulting from technological advancements and environmental standard improvements, leading to a 34.4% reduction (from 118.5 to 77.8 Gg) of the national total. The industrial sector was consistently the dominant contributor (51.9–66.4%) with a growing trend in its share. This growth was dominantly contributed by less developed provinces, such as Heilongjiang, Ningxia, and Qinghai, indicating that there was a shift of industrial sectors and associated PAHs emissions from highly concentrated industrial regions to nascent industrial regions. This study provides essential data support for a comprehensive understanding of each province's emission responsibilities regarding PAHs and for assessing the potential risks that PAHs pose to human health and ecosystems in these provinces.

Climate Change, Human Rights, and Private Capital: The Obligation of States to Close the Climate Investment Gap

Abstract Climate change affects humanity in many ways, such as rising sea levels, water shortages, agricultural droughts, and the displacement of people. Thus, climate change threatens the enjoyment of human rights. States must therefore put in place effective mitigation and adaptation measures to combat climate change. But since no public budget can finance those transformation efforts, combatting climate change requires large sums of private capital. However, the international community has identified a multi-trillion dollar ‘climate investment gap’. Against this backdrop, the present contribution argues that international human rights obligations call on states to urgently redirect private investment flows into climate mitigation and adaptation measures. The existence of such an obligation and its impact on concrete policy decisions is then illustrated by three practical examples: the announced withdrawal of European states from the Energy Charter Treaty, Austria’s windfall tax on energy profits, and the US Inflation Reduction Act.

LITERASI INFORMASI PEGAWAI BADAN PENANGGULANGAN BENCANA DAERAH KARAWANG MENGENAI MITIGASI BENCANA ABRASI KECAMATAN CIBUAYA

(Objectives) The coastal area of Karawang Regency, in Cibuaya, has been experiencing abrasion since 2017, causing damage to 177 housing units with different levels of damage. To address this issue, the government needs to implement effective mitigation measures, including providing information. This research aims to understand the role of information literacy in reducing disaster risk in the area. This research is how the ability of BPBD Karawang employees to search, evaluate and create information related to abrasion disaster mitigation in Cibuaya kec. To find out the information literacy skills of BPBD Karawang employees in improving employee information literacy in finding relevant information sources according to employee needs, so that BPBD Karawang employees can provide information and knowledge for the community in the Cibuaya area. (Method) This research uses a qualitative method with a case study type. In this context, the data was used to understand and analyze how BPBD Karawang employees use and create information about abrasion disasters, and how they evaluate the information to ensure relevance and accuracy. (Findings) This research shows that BPBD Karawang employees have good information literacy skills in searching, evaluating and creating information related to abrasion disaster mitigation. However, there are still some obstacles in managing disaster data and disseminating information through the website. Therefore, it is necessary to improve access and human resources to manage information on the website and the Prevention and Preparedness field so that the dissemination of disaster information is more effective and comprehensive.

Occurrence of common frog (Rana temporaria) and common toad (Bufo bufo) adults and metamorphs in agricultural fields in Germany: Potential for exposure to plant protection products.

To characterize the potential for exposure of amphibian terrestrial life stages to plant protection products (PPP), we studied the occurrence and habitat use of adult and metamorph common frogs (Rana temporaria) and common toads (Bufo bufo) in an agricultural landscape in Germany. The four selected study sites were breeding ponds with approximately 80% agricultural land within a 1-km radius. Adults were monitored by radio tracking for two years, and metamorph numbers were assessed for one summer using pitfall traps alongside drift fences. The results demonstrate that adults were rarely present in arable fields at any of the sites (overall 0.5% and 4% of total observations for frogs and toads, respectively). Metamorph captures in arable fields were more variable, ranging from 1.2% to 38.8% (frogs) and from 0.0% to 26.1% (toads) across study sites. Unsurprisingly, most captures in arable fields for both toad and frog metamorphs occurred at the site where the pond was completely surrounded by arable fields. Overall, the presence of adult amphibians in arable fields was limited and, for the metamorphs, occurred primarily when crops were denser and PPP spray interception higher. Diurnal hiding behavior was observed with the highest activity recorded at night, further reducing the risk of dermal exposure from direct PPP overspraying. In addition, it appeared that alternative habitats, such as woody structures or water bodies in the broader surrounding area, were preferred by the animals over the arable areas. The use of buffer zones around water bodies in agricultural areas would be an effective risk mitigation measure to protect terrestrial adults and metamorphs residing there and would reduce spray drift entry into water bodies during PPP application. It is hoped that these results will contribute to the discussion of risk assessment and mitigation options for amphibians. Integr Environ Assess Manag 2024;00:1-13. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Geological survey techniques and carbon storage: Optimizing renewable energy site selection and carbon sequestration

Geological survey techniques play a crucial role in optimizing site selection for renewable energy projects and identifying suitable locations for carbon storage to mitigate climate change. This abstract provides an overview of how geological survey techniques can be used to achieve these objectives. Renewable energy development, particularly solar and wind power, requires careful site selection to maximize energy generation efficiency and minimize environmental impacts. Geological surveys are instrumental in assessing factors such as subsurface geology, topography, soil composition, and hydrological conditions. These surveys help identify suitable locations with optimal wind or solar resources and geologic conditions for infrastructure development. Additionally, geological surveys are essential for identifying suitable sites for carbon storage, a critical component of carbon capture and storage (CCS) technologies aimed at reducing greenhouse gas emissions. Geological formations, such as deep saline aquifers, depleted oil and gas reservoirs, and unmineable coal seams, can serve as storage reservoirs for captured carbon dioxide (CO2). Geological surveys help characterize these formations to assess their suitability for long-term CO2 storage, considering factors such as porosity, permeability, and sealing integrity. Optimizing site selection for renewable energy projects and carbon storage requires a comprehensive understanding of subsurface geology and environmental conditions. Advanced geological survey techniques, such as seismic imaging, remote sensing, and geophysical surveys, are essential for acquiring detailed subsurface data. These techniques enable scientists and engineers to assess site suitability, evaluate risks, and design effective mitigation measures. In conclusion, geological survey techniques are invaluable tools for optimizing site selection for renewable energy projects and identifying suitable locations for carbon storage. By leveraging these techniques, stakeholders can make informed decisions that promote sustainable energy development and mitigate the impacts of climate change.

Evaluating the effectiveness of mitigation measures in environmental impact assessments: A comprehensive review of development projects in Korea

Rapid urbanization and development projects in Korea have posed significant threats to biodiversity; thus, effective mitigation measures are required to preserve natural habitats. Nevertheless, the factors underlying variations in mitigation measure effectiveness according to the disturbance level and surrounding environmental conditions have not been clarified. This study evaluated the effectiveness of mitigation measures implemented in environmental impact assessments (EIAs) of development projects in Korea, with a focus on their effectiveness with respect to the disturbance level and surrounding environmental conditions. A review of 288 EIA reports from selected projects that implemented all 10 mitigation measures classified according to the Wildlife Conservation Comprehensive Plan was conducted. Using the biodiversity tipping point framework, the effects of mitigation measures on biodiversity were categorized into four levels and analyzed. Analysis of variance and redundancy analysis were then performed to discern the variance in mitigation measure effectiveness in terms of the disturbance level, surrounding environment, and species. The results revealed significant variations in the effectiveness of mitigation measures depending on the surrounding environment and disturbance level. Linear projects exhibited a clear impact on various species as the disturbance level increased, whereas area-based projects did not exhibit such pronounced effects. All species demonstrated a negative relationship with development duration, development area, and distance from urban centers. Notably, avian and amphibian species showed a strong negative correlation with the digital elevation model while reptiles and mammals exhibited a strong positive relationship with pre-development biodiversity and distance from protected areas, respectively. Mitigation measures play a key role in alleviating the adverse effects of development projects; therefore, our findings indicate the need for spatially tailored mitigation plans to augment their effectiveness.

A review of the relationships between safety risk factors, practical solutions, and sustainable construction

Sustainability encompasses environmental, economic, and social dimensions, with safety standing as a crucial facet within the construction industry's social sustainability framework. This study addresses this vital concern by comprehensively analyzing published research on prominent safety risk factors and effective mitigation measures in construction projects, considering their influence on the industry's sustainability. A systematic literature review spanning 2008 to 2023 examined 32 pertinent articles from reputable journals. The review revealed 25 identified safety risk factors and 20 corresponding effective measures. These were categorised into labour, environmental, technical, and financial risks, forming the basis for a network diagram illustrating their interrelationships and associated mitigation strategies. Moreover, the study introduced a sustainability criterion, evaluating the various safety risk factor categories, and highlighting labour and environmental risks as the most significant concerns among the factors assessed. Finally, the research proposes future research directions aimed at elevating safety and sustainability within construction projects.

Assessing desertification vulnerability and mitigation strategies in northern Nigeria: A comprehensive approach

Desertification constitutes a grave threat to the environmental and socio-economic stability of desertification frontline states in Northern Nigeria. From 2003 to 2020, this research comprehensively analyzes desertification vulnerability, integrating parameters such as NDVI, LST, TVDI, MSAVI, and Albedo. Key factors contributing to land degradation are identified, along with the spatial patterns and trends of desertification over the two-decade period. The consequences are profound, with Northern Nigeria's ecosystem experiencing a steady decline in vegetation cover. Agriculture, vital to the region's economy, faces increased aridity and reduced arable land, jeopardizing food security. Diminishing water resources exacerbates scarcity issues, placing additional strain on communities. These environmental changes lead to severe socio-economic implications, including displacement, loss of livelihoods, and heightened vulnerability to climate-related risks. Urgent, comprehensive, and strategic interventions are imperative. Policy recommendations underscore revising and enforcing land use regulations, promoting sustainable agricultural practices, and establishing monitoring systems to guide decision-making. This research contributes practical strategies to enhance the resilience of desertification frontline states, safeguard livelihoods, and align with Nigeria's sustainable development objectives. Findings from the study indicate that only a tiny percentage (6.7 %) of the study area remains unaffected by desertification. Moreover, 13.3 % exhibit light vulnerability, 20 % demonstrate moderate exposure, and 60 % fall into the severe (26.7 %) and compelling (33.3 %) vulnerability categories. These statistics underscore the gravity of desertification in the study area, emphasizing the urgent need for effective mitigation measures to address its impact comprehensively.

The Risk of SARS-CoV-2 Transmission in Community Indoor Settings: A Systematic Review and Meta-Analysis.

Quantifying the risk of SARS-CoV-2 transmission in indoor settings is crucial for developing effective non-vaccine prevention strategies and policies. However, summary evidence on the transmission risks in settings other than households, schools, elderly care and healthcare facilities is limited. We conducted a systematic review to estimate the secondary attack rates (SARs) of SARS-CoV-2 and the factors modifying transmission risk in community indoor settings. We searched Medline, Scopus, Web of Science, WHO COVID-19 Research Database, MedrXiv, and BiorXiv from January 1, 2020, to February 20, 2023. We included articles with original data for estimating SARS-CoV-2 SARs. We estimated the overall and setting-specific SARs using the inverse variance method for random-effects meta-analyses. We included 34 studies with data on 577 index cases, 898 secondary cases, and 9173 contacts. The pooled SAR for community indoor settings was 20.4% (95% confidence interval [CI] 12.0-32.5%). The setting-specific SARs were highest for singing events (SAR 44.9%, 95% CI 14.5-79.7%), indoor meetings and entertainment venues (31.9%, 10.4-65.3%), and fitness centers (28.9%, 9.9-60.1%). We found no difference in SARs by index case, viral, and setting-specific characteristics. The risk of SARS-CoV-2 transmission was highest in indoor settings where singing and exercising occurred. Effective mitigation measures such as assessing and improving ventilation should be considered to reduce the risk of transmission in high-risk settings. Future studies should systematically assess and report the host, viral, and setting-specific characteristics that may modify the transmission risks of SARS-CoV-2 and other respiratory viruses in indoor environments.

Ammonia – an assessment of potential environmental impacts including prevention and mitigation measures

Ammonia (chemical formula NH3) is one of the most widely produced chemicals for industrial and agricultural uses. Ammonia has gained attention as a potential hydrogen and energy carrier, and low carbon substitute fuel for rail and maritime transport. The potential of ammonia for new use cases may lead to an increased footprint of potential environmental impacts. The physical and chemical properties of ammonia offer significant benefits for transportation and storage, but challenges remain due to its highly toxic nature and uses outside of dedicated industrial precincts. Ammonia is typically liquefied to increase density for ready storage and transportation. Unplanned releases of liquid ammonia will result in immediate environmental impacts. Unplanned releases may adversely affect receptor species in aquatic and terrestrial environments, human health, as well as the reputation of the responsible organisation. Dispersion of ammonia into the environment depends on factors that include mixture density, temperature, humidity, wind and wave action, and release mode and direction. Understanding the fate of ammonia is fundamental to adoption of effective mitigation measures. Consequently, it is necessary to understand the behaviour of ammonia in the environment, how unplanned releases can be minimised, and how they can be combatted, in order to appraise its suitability as a low carbon liquid transport fuel. This paper assesses the risks posed by ammonia spills, its fate in aquatic environments, and the applicability of available spill models. It also addresses management measures for the prevention and mitigation of spills noting the highly soluble and toxic nature of the chemical.

Oil Spillage Monitoring in Nigeria and the Role of Remote Sensing - An Overview

Oil spillage poses a persistent challenge in Nigeria most especially in oil-rich Niger Delta region, necessitating effective monitoring and mitigation measures. This study provides an overview of oil spill monitoring in Nigeria, emphasizing the pivotal role of remote sensing technology. Leveraging data from the NOSDRA Oil Spill Monitoring website, spanning 2016 to 2020, variations in spill occurrences among oil companies are analyzed. In 2016, a total of 42,741.25 barrels were spilled across 689 incidents, with NPDC emerging as the top spillage contributor. Similarly, 2017 witnessed 35,076.62 barrels spilled across 604 incidents, with NPDC and SPDC maintaining dominance. The trend continued in 2018, with SPDC recording the highest volume of spills among the top six contributing companies. However, in 2019, spillage increased, led by SPDC, followed closely by Heritage Energy Operational Services Limited and Aiteo. Conversely, 2020 saw a decrease in spillage, albeit SPDC retained its lead. These findings underscore the critical need for enhanced monitoring and regulatory enforcement to mitigate the environmental and socio-economic impacts of oil spills in Nigeria. However, proactive measures are needed to strengthen regulatory oversight, improve spill response capabilities, and promote transparency and accountability within the petroleum industry.

Impact of heavy metals on aquatic life and human health: a case study of River Ravi Pakistan

Heavy-metal contamination in river and ocean is a critical environmental issue that endangers marine ecosystems and human health. Therefore, conducting extensive research to devise effective mitigation measures is imperative. Sediment samples were taken randomly throughout the study area. Analysis was done to determine the presence of different metals, including arsenic, cadmium, chromium, nickel, copper, zinc, lead, and manganese. The assessment of different pollution levels was done by using various pollution indicators including “geo-accumulation index (Igeo), contamination factor (CF), enrichment factor (EF)” for accuracy. The Igeo measurement for Cd indicated varying pollution, ranging from moderate to significantly polluted, while Mn revealed no contamination. Elements such as Ni, Cr, Cu, and Zn showed a moderate level of contamination. The contamination factor values exhibited a range of 0.436 (Pb) to 7.637 (Cd), with average values spanning from 0.9176 (Mn) to 4.9714 (Cd), suggesting significant regional variation. EF exhibits a pattern of contamination comparable to that of Igeo. The noncarcinogenic risk associated with exposure to Cd and As exceeded the higher limit (HI > 1) for children and adults. Furthermore, the carcinogenic risk presented by pollutants such as copper (Cu), arsenic (As), nickel (Ni), cadmium (Cd), and chromium (Cr) was found to exceed the limits in children. In adults, only arsenic (As) and copper (Cu) were shown to represent a higher risk of cancer than the limit of 10−4. The PCA analysis revealed that two (PCs) accounted for more than 65% of the total variance in the River Ravi, as determined by eigenvalues greater than 1. This study underscores the importance of the ongoing monitoring and management of heavy-metal pollution to ensure sustainable marine ecosystem development and public health protection.

Efficient calibration of cost-efficient particulate matter sensors using machine learning and time-series alignment

Atmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure, highlighting the crucial need for monitoring PM levels to develop and implement effective risk mitigation measures. Notwithstanding, accurate measurement of PM concentration relies on expensive and cumbersome equipment. Despite the rising popularity of low-cost alternatives, their reliability remains questionable, given their sensitivity to environmental conditions, inherent instability, and manufacturing imperfections. This article proposes a novel approach to efficient correction of low-cost PM sensors. The primary calibration model is a feedforward artificial neural network (ANN), which directly renders predicted output of the corrected sensor based on environmental variables such as temperature, humidity, and atmospheric pressure. The ANN hyper-parameters are identified by aligning time series of prior reference and low-cost sensor readings, which enables the network to learn typical temporal changes of the sensor outcome as a function of the aforementioned parameters as well as operational relationships between the sensor and the reference device. The architecture of the ANN is optimized in terms of the number of neurons in each layer to enhance its generalization capability. Our methodology has been demonstrated using a custom-designed portable monitoring platform and reference data acquired from public stations in Gdansk. The results are indicative of excellent calibration reliability. The achieved correlation coefficients w.r.t. the reference readings are 0.86, 0.88, and 0.72 for PM1, PM10, and PM2.5, respectively, whereas RMSE values are only 3.0, 3.9, and 5.4 µg/m³.

Unintended Consequences of Technostress Mitigation: An Employee Perspective on the Effectiveness of Mitigation Measures

The continuous use of IT, even beyond regular office hours, is considered a cause of technostress, which impairs the health and performance of employees. To mitigate technostress, European countries have established the right to disconnect, and many organizations are struggling to identify and implement other effective measures. Based on a qualitative study (N=30) with 23 IT workers, five managers, and two CIOs, this study identifies eight technological, social, and cultural measures to mitigate common techno-stressors. By focusing on the employees' perspective, the results reveal the extent to which the measures actually work, showing that well-intended countermeasures, such as email restrictions, might have unintended negative and even harmful side effects. Our analysis shows that mitigation measures seldom work in isolation and without spillover effects. We conclude that although technostress mitigation is complex and mitigation measures adopted in isolation can fail and sometimes cause additional harm, employees still appreciate the effort.

Characterization and sources of childhood PAEs exposure from residential airborne dust in China cities

To explore the multicenter characteristics of endocrine-like phthalate esters (PAEs) in household dust and propose effective control strategies for global indoor public health. An on-site observational investigation was conducted in nine Chinese cities from 2018 to 2019. A total of 246 household dust samples were collected and analyzed for ten PAE congeners using Gas Chromatography-Mass Spectrometry (GC-MS). Questionnaires were used to gather information on building conditions, indoor behaviors, and ventilation habits. In residential dust from the nine cities, the total concentrations of the ten PAE congeners (∑PAEs) ranged from 0.921 to 29097.297 µg/g. Dicyclohexyl phthalate (DCHP) and di (2-ethylhexyl) phthalate (DEHP) were the dominant congeners in ∑PAEs. Childhood exposure to PAEs through dust ingestion was four orders of magnitude higher than through inhalation, with a carcinogenic risk of 5.47 × 10−6 for DEHP exposure in household dust. Higher ∑PAEs concentrations were associated with higher temperature, double glazing, wall paint usage, television and computer use, and indoor plant growth. This multicenter on-site investigation confirmed PAE pollution characteristics and uncovered the inacceptable risk of daily DEHP exposure in household dust under real living conditions. Effective mitigation measures based on household-related information, residential characteristics, decoration materials, and lifestyle should be taken to build a healthy household environment.