Environmental Regulatory Compliance Research Articles

Data-driven, explainable machine learning model for predicting volatile organic compounds’ standard vaporization enthalpy

The accurate prediction of standard vaporization enthalpy (ΔvapHm°) for volatile organic compounds (VOCs) is of paramount importance in environmental chemistry, industrial applications and regulatory compliance. To overcome traditional experimental methods for predicting ΔvapHm° of VOCs, machine learning (ML) models enable a high-throughput, cost-effective property estimation. But despite a rising momentum, existing ML algorithms still present limitations in prediction accuracy and broad chemical applications.In this work, we present a data driven, explainable supervised ML model to predict ΔvapHm° of VOCs. The model was built on an established experimental database of 2410 unique molecules and 223 VOCs categorized by chemical groups. Using supervised ML regression algorithms, the Random Forest successfully predicted VOCs' ΔvapHm° with a mean absolute error of 3.02 kJ mol−1 and a 95% test score. The model was successfully validated through the prediction of ΔvapHm° for a known database of VOCs and through molecular group hold-out tests. Through chemical feature importance analysis, this explainable model revealed that VOC polarizability, connectivity indexes and electrotopological state are key for the model's prediction accuracy. We thus present a replicable and explainable model, which can be further expanded towards the prediction of other thermodynamic properties of VOCs.

Environmental stewardship and corporate social responsibility: A review of case studies from the oil and gas sector

This review presents a comprehensive review of case studies focusing on environmental stewardship and corporate social responsibility (CSR) within the oil and gas sector. The oil and gas industry plays a pivotal role in global energy production, yet its operations often pose significant environmental and social challenges. In response, companies in this sector are increasingly embracing environmental stewardship and CSR principles to mitigate negative impacts and foster sustainable practices. The review examines a diverse range of case studies from various regions and contexts, highlighting both successful initiatives and notable challenges faced by oil and gas companies in integrating environmental stewardship and CSR into their operations. Key themes explored include environmental conservation efforts, community engagement, stakeholder collaboration, regulatory compliance, and technological innovation. Several case studies demonstrate innovative approaches adopted by oil and gas companies to minimize environmental degradation, such as implementing advanced technologies for emission reduction, investing in renewable energy projects, and restoring ecosystems affected by exploration and extraction activities. Moreover, successful CSR programs are showcased, emphasizing community development initiatives, education, healthcare, and infrastructure improvement projects aimed at enhancing the quality of life for local populations impacted by oil and gas operations. However, challenges persist, including balancing economic interests with environmental and social responsibilities, navigating complex regulatory landscapes, and addressing stakeholder concerns effectively. Despite these challenges, the case studies underscore the importance of proactive engagement, transparent communication, and continuous improvement in fostering environmental stewardship and CSR within the oil and gas sector. The review offers insights into best practices, lessons learned, and future directions for promoting sustainability and responsible business practices in the oil and gas industry, thereby contributing to the broader discourse on corporate environmental responsibility and societal impact mitigation.

Implementation of Green Supply Chain Management Practices

This research investigates the barriers to effective Green Supply Chain Management (GSCM) practices, focusing on the critical roles of environmental awareness, financial constraints, and regulatory compliance in organizations. It utilizes a mixed-methods approach, combining quantitative data from structured questionnaires with qualitative insights from expert interviews and case studies. The study begins with a comprehensive literature review to frame the hypotheses, followed by empirical data collection to evaluate these hypotheses. The findings are analyzed using statistical methods, including hypothesis testing and regression analysis, and are further enriched with expert opinions. Cronbach’s Alpha values are used to assess the reliability of measurement instruments for various factors, including Environmental Awareness, Financial Constraints, and Regulatory Compliance. The research culminates in presenting actionable strategies and recommendations for overcoming identified barriers, thereby promoting the adoption of GSCM practices in industries, particularly in the context of organizational culture and regulatory environments. The research aims to provide actionable recommendations based on validated hypotheses and case study findings to enhance the adoption of GSCM practices in underdeveloped nations.

Graphene’s Role in the Clean-Up Act: Progress in Industrial Wastewater Treatment

Water scarcity and environmental pollution are the two pressing global challenges that demand innovative solutions. In recent years, graphene-based nanomaterials have emerged as promising candidates for revolutionizing the field of water purification, particularly in the treatment of industrial wastewater. This review article, the first part of a two-part series, comprehensively explores the applications, synthesis methods and mechanisms of graphene-based nanomaterials for industrial wastewater treatment. Industrial activities generate vast quantities of wastewater contaminated with a myriad of organic and inorganic pollutants, heavy metals and dyes. Traditional water treatment methods often fall short in efficiently removing these contaminants, leading to significant environmental repercussions. In contrast, graphene-based nanomaterials exhibit exceptional properties, including a high specific surface area, excellent electrical conductivity and superior mechanical strength, making them highly attractive for wastewater treatment applications. This article begins by providing an overview of the properties of graphene and its derivatives, such as graphene oxide (GO) and reduced graphene oxide (rGO), which form the foundation of graphene-based nanomaterials. Our discussion focuses on the many approaches to the synthesis of these nanomaterials, with particular attention paid to their scalability, cost-effectiveness, and influence on the environment. This review focuses on the various applications of graphene-based nanomaterials in the in the removal of organic pollutants and dyes through adsorption, coagulation and photocatalysis. The unique structural and chemical properties of graphene-based nanomaterials enable them to selectively adsorb pollutants, even in the presence of competing ions, making them highly efficient in complex wastewater matrices. Furthermore, we explore the mechanistic aspects of pollutant removal by graphene-based nanomaterials, elucidating the role of surface functionalization, intermolecular interactions and photocatalytic processes. In addition to their pollutant removal capabilities, graphene-based nanomaterials also exhibit remarkable regeneration potential, making them economically sustainable for long-term industrial wastewater treatment applications. The challenges associated with large-scale implementation, including cost considerations, environmental impact assessments and regulatory compliance are also discussed. This review aims to provide a comprehensive understanding of the current state of research in graphene-based nanomaterials for industrial wastewater treatment. By critically evaluating the existing iterature, this review serves as a valuable resource for researchers and practitioners seeking to advance sustainable and effective strategies for the industrial wastewater treatment through the integration of graphene-based nanomaterials.

Exploring chlorination as a removal process for antiretroviral drugs (Nevirapine and Efavirenz) from water: Effect of operational parameters, kinetics, and trihalomethane formation

This study investigates the removal of antiretroviral drugs (ARVs), Nevirapine (NVP) and Efavirenz (EFV), from drinking water through chlorination, focusing on the influence of pH, temperature, chlorine concentration, and ARV initial concentration on the degradation kinetics and trihalomethane (THM) formation. At 25 °C and an initial concentration of 100 μg/L, the degradation trends for both ARVs were examined across varying pH levels. EFV exhibited greater pH sensitivity, with removal increasing from 37 % at pH 5.5 to 68 % at pH 8, while NVP removal increased only from 40 % at pH 5.5 to 48 % at pH 8. Temperature also played an essential role, as the removal of both ARVs increased with rising temperature, indicating an endothermic reaction. Higher chlorine concentrations resulted in increased removal, >90 % at 5 mg/L for both ARVs. Kinetic analysis revealed second-order behaviour, with higher rate constants observed at pH 5.5–7 for NVP and pH 7–8 for EFV. The intrinsic chlorination rate constants for both ARVs were estimated. The calculated half-lives indicated slow removal. The study also assessed contact time for NVP and EFV in a plug-flow reactor (PFR) and continuous stirred tank reactor model (CSTR). Also considering hydraulic residence time (HRT) rather than reaction time to assess the average amount of time that the ARVs spent in the selected reactors. The HRT for a CSTR was lower than the PFR, and the estimated HRT for a CSTR was a feasible value. The minimum HRT came out to 1.56 h (pH 7.5 and a temperature of 25 °C) for NVP and 1.07 h (pH 7 and a temperature of 25 °C) for EFV. Finally, THM formation was observed, with chloroform, dibromochloromethane and bromoform detected. Among the three THMs, the most significant change occurred between 4 and 6 h, with chloroform levels increasing from 31.59 μg/L to 63.49 μg/L. This study underscores the influence of operational parameters on ARV removal via chlorination. Highlighting pH sensitivity, temperature control, precise chlorine dosage, and environmental concerns such as trihalomethane formation ensures effective disinfection while minimizing negative impacts on both water quality and the environment. Emphasizing the importance of a comprehensive approach to ARV removal in water treatment processes is a proactive measure that integrates considerations of environmental impact, public health, regulatory compliance, and long-term sustainability into the design and operation of water treatment facilities.

Administrative practices for improved environmental compliance of manufacturing small and medium-sized enterprises in South Africa

The main constraints on SME growth in developing countries are regulations and legislation. Poor administration of environmental regulatory compliance is shown by the high number of SMEs in the manufacturing sector closing down annually in developing economies. Therefore, the purpose of this study is to investigate the influence of administrative practices on environmental compliance by manufacturing SMEs in a developing country. This study adopted a quantitative research approach. A sample size of 215 administrative personnel and managers from manufacturing SMEs operating within Msunduzi Municipality, KwaZulu-Natal, South Africa, was selected. Managers and administrative personnel were selected to eliminate biased answers that favor organizations and because both may have had an opportunity to enforce administrative practices that adhere to environmental regulations. The sample size was selected using a probability sampling method. The study shows that respondents agree that environmental compliance is a mandatory practice for SMEs in the manufacturing sector. Although results show that SMEs are complying with environmental regulations, they still face challenges. The study further demonstrates a disregard for the organization and storage of assessment reports by administrative personnel working in manufacturing SMEs.

IMPLEMENTASI APLIKASI PENGENALAN SOP PENGOLAHAN LIMBAH INDUSTRI PT X BERBASIS ANDROID

The management and proper handling of industrial waste are crucial for environmental sustainability and regulatory compliance. This project presents the development and implementation of an Android-based application designed to recognize and facilitate the adherence to Standard Operating Procedures (SOPs) in the industrial waste processing operations of PT X. The application employs advanced image recognition and processing techniques to identify and validate SOPs associated with different waste processing tasks, ensuring that employees follow the prescribed guidelines accurately. By providing real-time guidance and verification, the application aims to enhance operational efficiency, reduce errors, and promote responsible waste management practices. This paper outlines the key features, technical aspects, and benefits of the application, underscoring its potential to contribute to a more sustainable and compliant industrial waste processing environment at PT X.

A digital twin framework for real-time ship routing considering decarbonization regulatory compliance

International Marine Organization is promoting stricter carbon emission reduction targets, and the influx of environmental regulations presents compliance risks for maritime sector. Stakeholders need to take decarbonization performance indicators into account in ship routing to maintain regulatory compliance. To meet decarbonization goals, a decision support method related to environmental regulatory compliance is necessary for voyage optimization. To this end, this paper presents a digital twin-enabled framework for real-time decarbonization regulatory compliance prognosis in ship routing. The proposed framework tracks real-time carbon intensity and identifies opportunities for reducing operational risks associated with decarbonization goals. The digital twin approach leverage real-time environmental and operational data for improved estimation of vessel-specific regulatory compliance probability along the voyage. An improved dynamic programming algorithm is used for ship routing. The presented framework is versatile in dealing with various decarbonization regulations to provide routing decision support. An illustrated case of a container ship sailing across the South China sea is presented to demonstrate the applicability of the framework.

A multicriteria DM framework in the eco-management of operations: a case of organic waste reuse

This article presents a case study for decision-making regarding the reuse of organic waste. It introduces a framework for eco-management operations using a multi-criteria approach based on the perspective of organizational stakeholders. Applying the Analytical Hierarchical Process (AHP) it was possible to prioritize options in an environmentally sustainable and economically viable way. The framework integrates several criteria, such as environmental impact, economic viability, social acceptability and regulatory compliance, to provide a comprehensive and robust assessment of alternatives. A decision model is developed to identify the main concern attributes for determining the most suitable process for organic waste treatment. Empirical data has been collected from a central supplier located in the metropolitan region, in Chile. This supplier site contributes as an externality approximately 50% of the waste of the neighborhood where it is located and approximately 10% of the operational costs for the organization. The procedure is followed according to the methodological approach of the study including the experience and perspectives of the actors of the organization. The case study results indicate the efficacy and practicality of the multi-criteria framework in supporting eco-management decision-making processes.

Strategies for Sustainable Tourism Business Development: A Comprehensive Analysis

This research paper explores the dynamic landscape of tourism as a business and focuses on strategic approaches for sustainable development. In an era marked by globalization and heightened competition, tourism businesses are confronted with multifaceted challenges, ranging from environmental concerns to shifting consumer preferences. This paper delves into key strategies employed by successful tourism enterprises to navigate these challenges and ensure long-term viability.The research begins by examining the current state of the global tourism industry, emphasizing its economic significance and its impact on local communities. Subsequently, it delves into the evolution of consumer behavior within the tourism sector, shedding light on emerging trends and preferences. Through a detailed analysis of case studies and industry best practices, the paper identifies successful business models that prioritize environmental sustainability, community engagement, and cultural preservation. Furthermore, the research investigates the role of technology in shaping tourism experiences and streamlining business operations. The integration of digital platforms, artificial intelligence, and data analytics is explored as a means to enhance customer satisfaction, optimize resource utilization, and foster innovation in the tourism sector. Additionally, the paper examines policy frameworks and regulations that influence tourism businesses, emphasizing the need for a collaborative approach between the public and private sectors. The impact of government initiatives on sustainable tourism practices and the role of certification programs in fostering responsible business conduct are discussed. This research paper provides a comprehensive overview of the strategies essential for sustainable tourism business development. By integrating insights from various dimensions, including environmental responsibility, technological innovation, and regulatory compliance, businesses can position themselves for success in a rapidly evolving global tourism landscape. The findings of this study contribute valuable insights to academia, industry practitioners, and policymakers seeking to foster a resilient and sustainable tourism sector.

Optimizing Battery Manufacturing Decision-Making Using Lifecycle Assessment

The global demand for batteries is projected to increase by 25% annually, reaching ~2,600 GWh in 2030. As the world shifts to electric mobility, particularly EVs, to reduce greenhouse gas emissions and mitigate the effects of climate change, research efforts on recycling and recovery of critical elements from lithium-ion batteries (LIB) have increased, leading to the development and advancement of technologies that utilize conventional and state-of-the-art recycling processes. Hydrometallurgical processing continues to be the most widely used method for recycling metals from LIB, but over the last few years, direct recycling has gained attention as a more sustainable and efficient process. While direct-recycling technologies are promising, most direct-recycling processes remain small in scale and are costly in terms of the equipment needed to recover metals from spent LIB. As such, materials selection in battery manufacturing and overall battery chemistry and design have become increasingly important. The development of new battery chemistries that are less reliant on critical metals, such as cobalt, has become a prominent area of interest, and material criticality has become a major driver for battery recycling and reuse.Battery manufacturing is at a crossroads of decision-making with growing demands that overshadow available resources, reliance on imports, challenges in developing sustainable recycling processes that achieve increasingly stringent materials specifications, changing environmental regulations, and the need to identify and reduce potential environmental impacts for this growing waste stream. The best solutions will engage stakeholders from a variety of specialties who consider the battery lifecycle and the impact of each decision on the entire battery lifecycle. This presentation highlights one set of challenges - tradeoffs in materials selection with environmental regulatory compliance burdens and risks.

A Cluster-Based Technique for Identifying and Grouping Oily Waste Types Generated From Marine Oil Spill Response Operations

In the event of a marine oil spill and its subsequent response operations, different types of oily wastes are generated in large quantities, and their management is a significant challenge that oil spill responders face. The goal of this study is to develop a comprehensive pattern recognition modeling framework for deriving and grouping a set of unique clusters that separate different types of oily wastes from each other. The main idea is to group oily wastes based on their unique characteristics, such as the percentage of oil, percentage of water, percentage of mineral matter, and percentage of organic matter. Each cluster has a relatively homogeneous pattern of pollution characteristics. Prior to implementing the cluster analysis technique, it is important to evaluate and transform the raw oily waste data using well-defined criteria. An advanced machine learning technique, fuzzy C-means clustering algorithm, is employed to classify the oily wastes. The Kolmogorov–Smirnov tests are employed to examine the statistical significance of clustered data. Results show a heterogeneous diversity in seven identified clusters in relation to different types of oily wastes. The cluster-based analysis method presented in this article is an integral part of an integrated optimization-based model which will provide valuable inputs for adjustment of the existing management practices, enhancement of short-term pollution control strategies, and development of long-term oily waste management policies. The output of this study would provide a better tool to waste characterization and sorting steps that are required to immediately separate recovered waste to support downstream response efforts. This result of this study also supports the overall goal of minimizing impact on the environment by ensuring the maximum amount of recovered waste can be recycled or disposed in an environmentally friendly fashion. Moreover, properly classified, sorted, and labeled waste will greatly help with downstream steps of packaging, transportation, and tracking of waste, and as a result, it will minimize total waste management time and costs, under the constraints involving waste storage and transport capacities, waste pre-treatment and treatment facility capacities, and environmental regulatory compliance, as well as other operational and logistic constraints.

Application of Neural Networks and Regression Modelling to Enable Environmental Regulatory Compliance and Energy Optimisation in a Sequencing Batch Reactor

Real-time control of wastewater treatment plants (WWTPs) can have significant environmental and cost advantages. However, its application to small and decentralised WWTPs, which typically have highly varying influent characteristics, remains limited to date due to cost, reliability and technical restrictions. In this study, a methodology was developed using numerical models that can improve sustainability, in real time, by enhancing wastewater treatment whilst also optimising operational and energy efficiency. The methodology leverages neural network and regression modelling to determine a suitable soft sensor for the prediction of ammonium-nitrogen trends. This study is based on a case-study decentralised WWTP employing sequencing batch reactor (SBR) treatment and uses pH and oxidation-reduction potential sensors as proxies for ammonium-nitrogen sensors. In the proposed method, data were pre-processed into 15 input variables and analysed using multi-layer neural network (MLNN) and regression models, creating 176 soft sensors. Each soft sensor was then analysed and ranked to determine the most suitable soft sensor for the WWTP. It was determined that the most suitable soft sensor for this WWTP would achieve a 67% cycle-time saving and 51% electricity saving for each treatment cycle while meeting the criteria set for ammonium discharges. This proposed soft sensor selection methodology can be applied, in full or in part, to existing or new WWTPs, potentially increasing the adoption of real-time control technologies, thus enhancing their overall effluent quality and energy performance.

Análisis de información y factores de desempeño ambiental y de economía circular en empresas peruanas

Peruvian companies with significant sustainability impact have a significant development in their environmental information. Based on this, this research aims to analyze the level of disclosure of environmental performance information according to the Global Reporting Initiative (GRI) and circular economy (CE) practices. Similarly, determine its relationship with the size and business sector for those companies that published their sustainability report, and analyze the results within the framework of legitimacy and institutional theories. A quantitative investigation was carried out by means of a content analysis of the sustainability reports to determine the indices of the level of disclosure of said information, description and relationship of the variables indicated. This level of environmental disclosure is not met in all aspects of GRI. In fact, the results indicated greater compliance in the dissemination of environmental waste management, water, transport and regulatory compliance indicators, an institutional influence by type of business activity was observed. On the other hand, CE practices also did not show a high degree of disclosure, while input consumption reduction and waste management practices showed greater disclosure. The business sector presented a relationship with the level of environmental information, however, neither the size nor the sector of the companies were related to the CE information.

Analysis of vegetation recovery in areas impacted by bauxite mining in the Amazon Forest

Mining activity is essential for the Brazilian economy, representing 21% of exports in 2018, but it causes several environmental impacts, including deforestation. To minimize these impacts, replanting techniques are applied for environmental recovery and regulatory compliance. In this context, this study aims to monitor vegetation recovery in decommissioned bauxite mining areas located in the Amazon rainforest. The case study was carried out in the municipality of Paragominas (state of Para). The monitoring used the series of a newly defined spectral index, called Biomass Composite Index (BCI), and the Enhanced Vegetation Index (EVI), both from Landsat images between 1986 and 2017. The analysis was complemented by interpretation of false-color images and by in situ photographs. The method was applied for periods before mining, during exploitation, and after decommissioning, when the traditional planting technique was implemented. BCI demonstrated greater sensitivity to forest disturbance in areas affected by forest degradation and less influence of canopy homogeneity where the forest was substituted by more open formations. The height homogeneity of recovered areas also affected the EVI data more than the BCI data, since these areas presented higher values of EVI, and some areas had index values close to those detected before mine operation. The analysis could have benefited from sampling intensification, with more images analyzed per year, to overcome the presence of clouds, which block the acquisition of surface data by the sensor. Nevertheless, the method proved to be very promising and can improve the evaluation of forest recomposition even in remote areas, besides facilitating large-scale monitoring of recovered forests.

Cross-country ability of tracked vehicles

Research aims to determine conditions and parameters under which the tracked vehicle overcomes stone fields and separate blocks (boulders). Research methodology included the methods of analytical mechanics and mathematical analysis. Results. Mining and geological conditions of deposits gradually get more complicated, while mining moves to remote northern regions, which is a characteristic feature of the Holocene epoch. Road, weather, and natural conditions in arctic and northern territories differ markedly from other regions. Ridges, mounds, lake plains, and marshland are the predominant landscape. Stone fields, marshes, permafrost, marshy hollows, and deep ravines impede the traffic. Due to these factors it is particularly difficult to access and explore in arctic and northern territories. There are particular technical specifications for the exploration equipment, namely, increased cross-country ability for weak soil (snow and swamp), ability to overcome stone fields, increased haulage and towing capacity with the account of maximum possible environmental regulatory compliance, etc. The conditions of ascent and overturning are derived from geometry, while the sliding condition is derived from statics. Summary. A mathematical model has been created, which makes it possible to describe the tracked vehicle’s travel across the uneven ground and, under known design values of the vehicle, determine the limitary obstacle clearance.

Novel metric for managing the protection of humanity and the environment against pollution and its adverse effects

Pollution prevention and control are very significant for protecting humanity and the environment against pollution and its adverse effects worldwide. The primary resistance of every country to the occurrence of any of the adverse effects of pollution is a function of the country's pollution prevention & control. Strengthening pollution prevention & control in a country is tantamount to preventing the occurrence of any of the adverse effects of pollution (including any of the pollution-related communicable diseases). Knowing the status of the pollution prevention & control in a country will enable its Government to plan and improve on it. This research work conducted a survey on the extent of availability of pollution prevention & control infrastructure, availability of environmental regulatory agencies and compliance of operating companies to environmental regulations in the Niger Delta. Based on the outcome of the survey, this work invented a novel composite metric titled “Pollution Prevention & Control Index” (PPCI) for measuring the status of pollution prevention & control in a country or region. It is a measure of the protection of the population and the environment against pollution and its adverse effects. Results revealed that the higher the pollution prevention & control index of a country, the smaller the work left undone (or the work to be done) to protect the environment and the population of the country against pollution, its adverse effects and vice versa. Results also showed that the generic pollution prevention & control index of a developed country is higher than that of a developing country.

Sustainable Approach in the Assessment of Safety and Environmental Regulatory Compliance During Mining Activities

ABSTRACT Optimal resource extraction involves balancing economic, environmental and social aspects. Even though there are regulatory mechanisms, safety anomalies and environmental pollution have persisted during mining activities in Nigeria. The study aims at developing an approach for evaluating safety and environmental regulatory compliance during mining activities, based on effects of noncompliance and having compliance issues. Crosssectional survey design was used in collecting data from miners operating within active mining sites in Ebonyi State, Nigeria. Results indicate that prevalence of noncompliance effects had a four-component structure, while factorial prediction was a good-fit for having compliance issues. The proposed approach integrates dimensions of noncompliance effects with factors predicted having compliance issues during mining activities. The approach can help mining companies, governments and mining communities in Africa improve safety and environmental regulatory compliance

The Setup of Packaging Development Targeted at Source Reduction and Environmental Regulatory Compliance

Permanent growth of packaging waste has a negative environmental effect. Therefore, volume and content of packaging are being regulated by relevant legislation. In 1994, the European Union (EU) adopted the Directive on Packaging and Packaging Waste (94/62/EC) (subsequently – the Directive), which set the environmental requirements for packaging but did not precisely specify the methods of their implementation. The related harmonised standards EN 13427-13432 partly filled in the gap, but a number of questions have been still left without due explanations. The EU countries were supposed to develop their own legislation, which should have been complemented with the elements that have not been elaborated on the EU level. This task appeared to be complicated for many countries for various reasons, including economic. The cost of implementation of the Directive can be high for a country, especially if it is not done carefully. As a result, the state of implementation of the Directive by the EU countries remains non-uniform. Only a few countries have fully implemented it, while others have just transferred the requirements into their own legislation, but have not implemented the obligatory enforcement measures. A big variety of packaging source reduction policies exist in the EU, which have been developed by the Member States trying to fit them to the country’s situation in terms of legislation, institutional infrastructure, conduct of the industry, etc. For this reason, their transfer from one country to another is problematic. Therefore, this study aims to develop a cost-efficient structure of the packaging development process to be applied by both the industry and state enforcement institutions and to fit into the context typical for Lithuania.DOI: http://dx.doi.org/10.5755/j01.erem.72.2.16101

Development of linear and threshold no significant risk levels for inhalation exposure to titanium dioxide using systematic review and mode of action considerations

Titanium dioxide (TiO2) has been characterized as a poorly soluble particulate (PSP) with low toxicity. It is well accepted that low toxicity PSPs such as TiO2 induce lung tumors in rats when deposition overwhelms particle clearance mechanisms. Despite the sensitivity of rats to PSPs and questionable relevance of PSP-induced tumors to humans, TiO2 is listed as a possible human carcinogen by some agencies and regulators. Thus, environmental toxicity criteria for TiO2 are needed for stakeholders to evaluate potential risks from environmental exposure and regulatory compliance. A systematic review of the literature was conducted to characterize the available data and identify candidate datasets upon which toxicity values could be derived. Key to this assessment, a survey of mechanistic data relevant for lung cancer was used to support quantitative inhalation risk assessment approaches. A total of 473 human studies were identified, 7 of which were epidemiological studies that met inclusion criteria to quantitatively characterize carcinogenic endpoints in humans. None of these studies supported derivation of toxicity criteria; therefore, animal data were used to derived safety values for TiO2 using different dose-metrics (regional deposited dose ratios, TiO2 particle surface area lung burden, and volumetric overload of alveolar macrophages), benchmark dose modeling, and different low-dose extrapolation approaches. Based on empirical evidence and mechanistic support for nonlinear mode of action involving particle overload, chronic inflammation and cell proliferation, a no significant risk level (NSRL) of 300 μg/day was derived. By comparison, low-dose linear extrapolation from tumor incidence in the rat lung resulted in an NSRL value of 44 μg/day. These toxicity values should be useful for stakeholders interested in assessing risks from environmental exposure to respirable TiO2.