Hasil untuk "Environmental technology. Sanitary engineering"

Suman Chandra Paul, Md. Sherazul Islam, Md. Kaikobad et al.

Oleksandr Kosenkov, Ehsan Zabardast, Jannik Fischbach et al.

Implementing privacy by design (PbD) according to the General Data Protection Regulation (GDPR) is met with a growing number of requirements engineering (RE) approaches. However, the question of which RE method for PbD fits best the goals of organisations remains a challenge. We report our endeavor to close this gap by synthesizing a goal-centric approach for PbD methods assessment. We used literature review, interviews, and validation with practitioners to achieve the goal of our study. As practitioners do not approach PbD systematically, we suggest that RE methods for PbD should be assessed against organisational goals, rather than process characteristics only. We hope that, when further developed, the goal-centric approach could support the development, selection, and tailoring of RE practices for PbD.

K. Ganesh, Deqing Zhang, Scott J. Miller et al.

F more than three decades, Green Chemistry has provided a framework for chemists and chemical engineers to do their part in contributing to the broad scope of global sustainability. American Chemical Society journals are a great venue for these scientists to share their latest results and provide a resource to the chemistry community and beyond for understanding current problems and envisioning solutions. We believe this is an opportune time to highlight some of the leading articles on the broad theme of Green Chemistry being published today through a Virtual Issue of selected works from nine ACS chemistry and engineering journals. The inception of this Virtual Issue is no coincidence. We have timed it to the 2021 Green Chemistry & Engineering Conference taking place virtually June 14−June 18. Now celebrating its 25th edition, we have seen progress toward more sustainable chemistries being showcased and celebrated at each GC&E conference. The theme of this year’s meeting, “Sustainable Production to Advance the Circular Economy”, is particularly bold. It highlights the recognition that contributions must take into account a systems approach to reducing environmental impact through intentional design of chemical products, not just considering how raw materials are sourced and in the manufacture and use of industrial and consumer goods but also how these materials and goods may be reused, recycled, or upcycled. The embrace of life-cycle thinking as a goal among the Green Chemistry community comes at the backdrop of the realization of limited resources and a climate crisis the likes of which most of us still fail to fully comprehend. We believe these selected articles are stepping stones on the pathway to advance closed-loop economies while still serving as models for innovation at a fundamental level within their respective chemistry subdisciplines. The drive for efficiency in organic synthesis merges the best of the idealisms of the Enlightenment and the Renaissance. Certainly, there is a premium on rationalism, with an aspiration of mechanistically sound reaction design and process development. But at the same time, the aesthetic appeal of the new ideas that culminate in the advances we now see routinely is unmistakable. There is no constraint on curiosity when we consider the boundary conditions of efficient, environmentally benign processes. On the contrary, these considerations spawn new concepts and approaches, ranging from postmodern expansions of photochemistry, reconsideration of seminal thinking about solvation, importation of physical and mechanical phenomena, to reaction developmentthe creativity born of efficiency considerations now drives major technology innovation in chemistry. The Journal of Organic Chemistry and Organic Letters are delighted to participate in this Virtual Issue with a selection of perspectives, research articles, and letters that highlight just some of the most impactful science in this arena, across a very wide swath of chemical space. Organometallics, a journal with a long-standing history of reporting fundamental advances in organometallic chemistry, catalysis, and materials, has selected contributions to this Virtual Issue that best highlight the diverse nature of this type of organometallic chemistry and that are likely to impact development of more sustainable chemical processes and the transition to a circular economy. ACS Sustainable Chemistry & Engineering is a world leader in publishing groundbreaking research that addresses the challenges of sustainability, advancing the principles of Green Chemistry and Green Engineering with global reach and impact. Key coverage includes catalysis with emerging feedstocks and synthetic methods for preparing materials and chemicals in a sustainable way to help bring critical innovations from a research setting to commercialization. The journal takes pride in its central role in promoting innovations that will enable the implementation of a circular economy. Industrial & Engineering Chemistry Research publishes many, many papers in the Green Chemistry and sustainability space as these are core considerations in applied chemistry and chemical engineering. The ten articles in this Virtual Issue are just the tip of the iceberg and represent the types of papers readers can find in I&EC Research. We would encourage those interested in the Virtual Issue to browse through other recent issues of the journal, where they will quickly find other articles aligned with the themes of the conference. Contributions from Environmental Science & Technology and Environmental Science & Technology Letters clearly illustrate the interdisciplinary systems approach that is required to address key environmental challenges that impede sustainability effortsfrom remediation of pollution to design of next-generation safer and functional chemicals. Several of the high-impact contributions selected have been the subject of media coverage. Contributions from ACS Omega, an interdisciplinary open-access journal, were selected to highlight the potential impact of open-source publications and their importance in connecting scientists across industry and academia. With a similar goal, Organic Process Research & Development has a tradition of bridging industrial and academic research. Its focus on process

Chi Zhang, Yi Li, Danmeng Shuai et al.

Abstract Achieving efficient disinfection of waterborne pathogens with minimized harmful disinfection byproducts demands a facile, cost-effective, and environmentally friendly technology. Recently, photocatalytic water disinfection has attracted an ever-growing worldwide attention due to its powerful oxidative capability and promising potential in solar energy utilization. Among waterborne pathogens, viruses, which have been found with very small sizes, high risks of illness, and resistant to environmental inactivation/decomposition, pose a great threat to public health. Over the past a few decades, efforts have been made to employ photocatalysis to achieve effective viral inactivation. Though photocatalysis has been comprehensively reviewed for bacterial disinfection, photocatalytic disinfection of viruses with quite different compositions, structures, and resistance to oxidative stress compared to bacteria was not systematically documented. Here, we present an overview of antiviral effects of a wide range of photocatalysts, including TiO2-based, metal-containing (other than TiO2), and metal-free photocatalysts. Moreover, the development of photocatalytic reactors for viral inactivation is summarized to promote practical engineering applications for water disinfection. In addition, key mechanisms that determine the performance of photocatalytic viral disinfection are reviewed. Future perspectives of research opportunities and challenges in photocatalytic viral disinfection are also included. This review will shed light on the development and implementation of sustainable disinfection strategies for controlling waterborne viruses in the future.

Justus Bogner, Roberto Verdecchia

From its early foundations in the 1970s, empirical software engineering (ESE) has evolved into a mature research discipline that embraces a plethora of different topics, methodologies, and industrial practices. Despite its remarkable progress, the ESE research field still needs to keep evolving, as new impediments, shortcoming, and technologies emerge. Research reproducibility, limited external validity, subjectivity of reviews, and porting research results to industrial practices are just some examples of the drivers for improvements to ESE research. Additionally, several facets of ESE research are not documented very explicitly, which makes it difficult for newcomers to pick them up. With this new regular ACM SIGSOFT SEN column (SEN-ESE), we introduce a venue for discussing meta-aspects of ESE research, ranging from general topics such as the nature and best practices for replication packages, to more nuanced themes such as statistical methods, interview transcription tools, and publishing interdisciplinary research. Our aim for the column is to be a place where we can regularly spark conversations on ESE topics that might not often be touched upon or are left implicit. Contributions to this column will be grounded in expert interviews, focus groups, surveys, and position pieces, with the goal of encouraging reflection and improvement in how we conduct, communicate, teach, and ultimately improve ESE research. Finally, we invite feedback from the ESE community on challenging, controversial, or underexplored topics, as well as suggestions for voices you would like to hear from. While we cannot promise to act on every idea, we aim to shape this column around the community interests and are grateful for all contributions.

Allysson Allex Araújo, Marcos Kalinowski, Maria Teresa Baldassarre

In recent years, Software Engineering (SE) scholars and practitioners have emphasized the importance of integrating soft skills into SE education. However, teaching and learning soft skills are complex, as they cannot be acquired passively through raw knowledge acquisition. On the other hand, hackathons have attracted increasing attention due to their experiential, collaborative, and intensive nature, which certain tasks could be similar to real-world software development. This paper aims to discuss the idea of hackathons as an educational strategy for shaping SE students' soft skills in practice. Initially, we overview the existing literature on soft skills and hackathons in SE education. Then, we report preliminary empirical evidence from a seven-day hybrid hackathon involving 40 students. We assess how the hackathon experience promoted innovative and creative thinking, collaboration and teamwork, and knowledge application among participants through a structured questionnaire designed to evaluate students' self-awareness. Lastly, our findings and new directions are analyzed through the lens of Self-Determination Theory, which offers a psychological lens to understand human behavior. This paper contributes to academia by advocating the potential of hackathons in SE education and proposing concrete plans for future research within SDT. For industry, our discussion has implications around developing soft skills in future SE professionals, thereby enhancing their employability and readiness in the software market.

Christoph Treude, Marco A. Gerosa

Artificial intelligence (AI), including large language models and generative AI, is emerging as a significant force in software development, offering developers powerful tools that span the entire development lifecycle. Although software engineering research has extensively studied AI tools in software development, the specific types of interactions between developers and these AI-powered tools have only recently begun to receive attention. Understanding and improving these interactions has the potential to enhance productivity, trust, and efficiency in AI-driven workflows. In this paper, we propose a taxonomy of interaction types between developers and AI tools, identifying eleven distinct interaction types, such as auto-complete code suggestions, command-driven actions, and conversational assistance. Building on this taxonomy, we outline a research agenda focused on optimizing AI interactions, improving developer control, and addressing trust and usability challenges in AI-assisted development. By establishing a structured foundation for studying developer-AI interactions, this paper aims to stimulate research on creating more effective, adaptive AI tools for software development.

Jonathan Ullrich, Matthias Koch, Andreas Vogelsang

With the advent of generative LLMs and their advanced code generation capabilities, some people already envision the end of traditional software engineering, as LLMs may be able to produce high-quality code based solely on the requirements a domain expert feeds into the system. The feasibility of this vision can be assessed by understanding how developers currently incorporate requirements when using LLMs for code generation-a topic that remains largely unexplored. We interviewed 18 practitioners from 14 companies to understand how they (re)use information from requirements and other design artifacts to feed LLMs when generating code. Based on our findings, we propose a theory that explains the processes developers employ and the artifacts they rely on. Our theory suggests that requirements, as typically documented, are too abstract for direct input into LLMs. Instead, they must first be manually decomposed into programming tasks, which are then enriched with design decisions and architectural constraints before being used in prompts. Our study highlights that fundamental RE work is still necessary when LLMs are used to generate code. Our theory is important for contextualizing scientific approaches to automating requirements-centric SE tasks.

Maarten Vlaswinkel, Duarte Antunes, Frank Willems

Decarbonization of the transport sector sets increasingly strict demands to maximize thermal efficiency and minimize greenhouse gas emissions of Internal Combustion Engines. This has led to complex engines with a surge in the number of corresponding tunable parameters in actuator set points and control settings. Automated calibration is therefore essential to keep development time and costs at acceptable levels. In this work, an innovative self-learning calibration method is presented based on in-cylinder pressure curve shaping. This method combines Principal Component Decomposition with constrained Bayesian Optimization. To realize maximal thermal engine efficiency, the optimization problem aims at minimizing the difference between the actual in-cylinder pressure curve and an Idealized Thermodynamic Cycle. By continuously updating a Gaussian Process Regression model of the pressure's Principal Components weights using measurements of the actual operating conditions, the mean in-cylinder pressure curve as well as its uncertainty bounds are learned. This information drives the optimization of calibration parameters, which are automatically adapted while dealing with the risks and uncertainties associated with operational safety and combustion stability. This data-driven method does not require prior knowledge of the system. The proposed method is successfully demonstrated in simulation using a Reactivity Controlled Compression Ignition engine model. The difference between the Gross Indicated Efficiency of the optimal solution found and the true optimum is 0.017%. For this complex engine, the optimal solution was found after 64.4s, which is relatively fast compared to conventional calibration methods.

Zeng Meng, Gang Li, Xuan Wang et al.

Tae Lee, T. Speth, M. Nadagouda

The development of remediation technology for Per- and poly-fluoroalkyl substances (PFAS) has become one of the nation's top research priorities as adverse impacts to environmental and human health have been increasingly identified. Of various water treatment routes, high-pressure membrane processes such as nanofiltration (NF) and reverse osmosis (RO) are considered most promising by virtue of the excellent rejection of both short- and long-chain PFAS and the proven technological maturity demonstrated with various water sources. Consequently, research activities have rapidly increased to accommodate research needs to advance NF and RO processes targeting PFAS removal from the aquatic environment. Therefore, the present review highlights recent findings in the areas of (a) rejection mechanism for PFAS, (b) the effects of membrane property and the water matrix, (c) challenges in high-recovery operation due to adsorption of PFAS and subsequent membrane fouling or scaling, and (d) complementary technologies to overcome the significant challenge to manage or treat a large volume of the waste stream from NF and RO. Overall, this review emphasizes research opportunities to develop engineering solutions that can be implemented in practical water treatment applications to address the imminent threat from PFAS.

Yuan Yao, Kai Lan, Thomas E. Graedel et al.

Various technologies and strategies have been proposed to decarbonize the chemical industry. Assessing the decarbonization, environmental, and economic implications of these technologies and strategies is critical to identifying pathways to a more sustainable industrial future. This study reviews recent advancements and integration of systems analysis models, including process analysis, material flow analysis, life cycle assessment, techno-economic analysis, and machine learning. These models are categorized based on analytical methods and application scales (i.e., micro-, meso-, and macroscale) for promising decarbonization technologies (e.g., carbon capture, storage, and utilization, biomass feedstock, and electrification) and circular economy strategies. Incorporating forward-looking, data-driven approaches into existing models allows for optimizing complex industrial systems and assessing future impacts. Although advances in industrial ecology-, economic-, and planetary boundary-based modeling support a more holistic systems-level assessment, more effects are needed to consider impacts on ecosystems. Effective applications of these advanced, integrated models require cross-disciplinary collaborations across chemical engineering, industrial ecology, and economics. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering , Volume 15 is June 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

S. Ray, Kashish Parihar, Nishu Goyal et al.

Rampant use of fertilizers and pesticides for boosting agricultural crop productivity has proven detrimental impact on land, water, and air quality globally. Although fertilizers and pesticides ensure greater food security, their unscientific management negatively impacts soil fertility, structure of soil microbiome and ultimately human health and hygiene. Pesticides exert varying impacts on soil properties and microbial community functions, contingent on factors such as their chemical structure, mode of action, toxicity, and dose-response characteristics. The diversity of bacterial responses to different pesticides presents a valuable opportunity for pesticide remediation. In this context, OMICS technologies are currently under development, and notable advancements in gene editing, including CRISPR technologies, have facilitated bacterial engineering, opening promising avenues for reducing toxicity and enhancing biological remediation. This paper provides a holistic overview of pesticide dynamics, with a specific focus on organophosphate, organochlorine, and pyrethroids. It covers their occurrence, activity, and potential mitigation strategies, with an emphasis on the microbial degradation route. Subsequently, the pesticide degradation pathways, associated genes and regulatory mechanisms, associated OMICS approaches in soil microbes with a special emphasis on CRSPR/Cas9 are also being discussed. Here, we analyze key environmental factors that significantly impact pesticide degradation mechanisms and underscore the urgency of developing alternative strategies to diminish our reliance on synthetic chemicals.

Al Mamun Pranto, Usama Ibn Aziz, Lipon Chandra Das, Sanjib Ghosh and Anisul Islam

This work explores the detailed study of Bangladeshi precipitation patterns, with a particular emphasis on modeling annual rainfall changes in six coastal cities using Markov chains. To create a robust Markov chain model with four distinct precipitation states and provide insight into the transition probabilities between these states, the study integrates historical rainfall data spanning nearly three decades (1994–2023). The stationary test statistic (χ²) was computed for a selected number of coastal stations, and transition probabilities between distinct rainfall states were predicted using this historical data. The findings reveal that the observed values of the test statistic, χ², are significant for all coastal stations, indicating a reliable model fit. These results underscore the importance of understanding the temporal evolution of precipitation patterns, which is crucial for effective water resource management, agricultural planning, and disaster preparedness in the region. The study highlights the dynamic nature of rainfall patterns and the necessity for adaptive strategies to mitigate the impacts of climate variability. Furthermore, this research emphasizes the interconnectedness of climate studies and the critical need for enhanced data-gathering methods and international collaboration to bridge knowledge gaps regarding climate variability. By referencing a comprehensive range of scholarly works on climate change, extreme rainfall events, and variability in precipitation patterns, the study provides a thorough overview of the current research landscape in this field. In conclusion, this study not only contributes to the understanding of precipitation dynamics in Bangladeshi coastal cities but also offers valuable insights for policymakers and stakeholders involved in climate adaptation and resilience planning. The integration of Markov chain models with extensive historical data sets serves as a powerful tool for predicting future rainfall trends and developing informed strategies to address the challenges posed by changing precipitation patterns.

Omar Djoukbala, Salim Djerbouai, Saeed Alqadhi et al.

Soil erosion significantly impacts dam functionality by leading to reservoir siltation, reducing capacity, and heightening flood risks. This study aims to map soil erosion within a Geographic Information Systems (GIS) framework to estimate the siltation of the K'sob dam and compare these estimates with bathymetric observations. Focused on one of the Hodna basin’s sub-basins, the K'sob watershed (1477 km2), the assessment utilizes the Revised Universal Soil Loss Equation (RUSLE) integrated with GIS and remote sensing data to predict the spatial distribution of soil erosion. Remote sensing data were pivotal in updating land cover parameters critical for RUSLE, enhancing the precision of our erosion predictions. Our results indicate an average annual soil erosion rate of 7.83 t/ha, with variations ranging from 0 to 224 t/ha/year. With a typical relative error of about 13% in predictions, these figures confirm the robustness of our methodology. These insights are crucial for crafting mitigation strategies in areas facing high to extreme soil loss and will assist governmental agencies in prioritizing actions and formulating effective soil erosion management policies. Future studies should explore the integration of real-time data and advanced modeling techniques to further refine these predictions and expand their applicability in similar environmental assessments.

Thomas Röckmann, Maarten van Herpen, Chloe Brashear et al.

The reaction of CH _4 with chlorine (Cl) radicals in the atmosphere is associated with an extraordinarily strong isotopic fractionation, where ^12 CH _4 reacts about 70 ‰ faster with Cl than ^13 CH _4 . Therefore, although the Cl-based sink of CH _4 constitutes only a small contribution to its total removal rate, the uncertainty in this small sink has been identified as one of the two largest uncertainties of isotope-based CH _4 source apportionment at the global scale. The uncertainty arises from the fact that Cl levels in the atmosphere are so low that they cannot be detected directly. One very sensitive indirect method to identify and quantify the CH _4 + Cl reaction in the atmosphere is the detection of the extremely ^13 C-depleted reaction product carbon monoxide (CO) from this reaction. This article reviews the concept of this approach, its successful application in the atmosphere, its challenges and opportunities for identifying and quantifying Cl-based removal of CH _4 at the regional and global scale and its potential to detect and evaluate possible attempts to enhance CH _4 removal from the atmosphere.

ZHANG Wei, LUO Xubiao, OUYANG Ting et al.

The efficient removal of low concentration, recalcitrant, and highly toxic organic heavy metal complexes in industrial wastewater is a hot issue in the field of heavy metal pollution control. Adsorption method has received considerable attention in the treatment of organic heavy metal complexes pollution due to its advantages of low cost, high efficiency and easy operation. This paper elaborated on the development situation and research progress of mainstream adsorbents in recent years in the field of removing typical EDTA-complexed heavy metals in water, commented on the advantages and disadvantages of different types of adsorbents and corresponding performance optimization methods, and summarized the reaction mechanisms of relevant adsorbents. The advantages and limitations of traditional organic heavy metal complexes pollution treatment technology and current new adsorption technology were compared, which provided a beneficial reference for reasonable selection of the best type of adsorbent in complex environments. The application performance and development potential of new adsorbents in the field of actual wastewater treatment contaminated with organic heavy metal complexes were listed. The priorities of future research and development directions of new adsorbents were envisioned to provide reference for the treatment of wastewater containing organic heavy metal complexes by adsorption.

Cong Yang, Peng Xia, Lingyun Zhao et al.

The Chinese medicine residue (CMR) is composed of wet substances, so using hydrothermal carbonization (HTC) to recover renewable energy from the residue is a suitable treatment method. Chromium (Cr), a kind of heavy metal element, is enriched in hydrochar and severely restricts its effective utilization. An in-depth analysis of the migration path and mechanism of Cr in hydrochar is helpful in promoting energy utilization for CMR. Here, licorice, a significant Chinese medicine, was selected as the example to analyze the evolutions of its pore and chemical structures and their effects on the migration mechanism of Cr during the HTC process. The products obtained under various HTC conditions were analyzed using nitrogen adsorption, FTIR, and 13C NMR. The results show that, considering reaction time and relevant reactions as the primary factors during the HTC process, the migration pathway of Cr in hydrochar undergoes two stages, and they are the accompanying migration stage and the recovery aggregation stage. Active adsorption sites for Cr may exist within the pore structure of hydrochar. In the HTC process, hydrolysis, decarboxylation, and decarbonylation reactions are the direct drivers of Cr migration, while aromatization is the underlying cause of Cr recovery and aggregation. It is hypothesized that Cr catalyzes the acetylene cyclotrimerization reaction, thereby promoting the formation of aromatic structures in hydrochar and integrating into the hydrochar carbon skeleton.

Emeralda Sesari, Federica Sarro, Ayushi Rastogi

Software practitioners discuss problems at work with peers, in-person and online. These discussions can be technical (e.g., how to fix a bug?) and social (e.g., how to assign work fairly?). While there is a growing body of knowledge exploring fairness problems and solutions in the human and social factors of software engineering, most focus has been on specific problems. This study provides fairness discussions by software practitioners on Stack Exchange sites. We present an exploratory study presenting the fairness experience of software practitioners and fairness expectations in software teams. We also want to identify the fairness aspects software practitioners talk about the most. For example, do they care more about fairness in income or how they are treated in the workplace? Our investigation of fairness discussions on eight Stack Exchange sites resulted in a list of 136 posts (28 questions and 108 answers) manually curated from 4,178 candidate posts. The study reveals that the majority of fairness discussions (24 posts) revolve around the topic of income suggesting that many software practitioners are highly interested in matters related to their pay and how it is fairly distributed. Further, we noted that while not discussed as often, discussions on fairness in recruitment tend to receive the highest number of views and scores. Interestingly, the study shows that unfairness experiences extend beyond the protected attributes. In this study, only 25 out of 136 posts mention protected attributes, with gender mainly being discussed.