Search

Electronic waste recycling companies have proliferated in many countries due to valuable materials present in end-of-life electronic and electrical equipment. This article examined the business characteristics and management performance of Electronic Products Recycling Association (EPRA), a Canadian nationwide electronic product stewardship organization. The organization's annual performance reports, from 2012 to 2020, for nine Canadian provinces in which it currently operates were aggregated and analyzed. Temporal analysis using regression and Mann-Kendall tests were employed, and five characteristics of EPRA's business were analyzed, including e-waste products collected, number of drop-off locations, efforts to build public awareness, operating expenses, and growth of e-waste stewardship. Results show a decline in the amount of e-waste collected across the provinces, except in New Brunswick, which started its program in 2017. The Mann-Kendall test revealed declining temporal trends in most provinces. Although the collection/drop off sites and stewardship organizations increased astronomically over the study period in Canada, the amounts of e-waste collected decreased. We found that public awareness generally did not increase the amount of e-waste collected, and these campaigns only appeared to be effective in jurisdictions with good accessibility of e-waste recycling. Processing cost accounted for the majority of the e-waste management budget in Canada, and different factors affected the financial success of the stewards differently., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The Canadian wildfires in June 2023 significantly impacted the northeastern United States, particularly in terms of worsened air pollution and environmental justice concerns. While advancements have been made in low-cost sensor deployments and satellite observations of atmospheric composition, integrating dynamic human mobility with wildfire PM 2.5 exposure to fully understand the environmental justice implications remains underinvestigated. This study aims to enhance the accuracy of estimating ground-level fine particulate matter (PM 2.5 ) concentrations by fusing chemical transport model outputs with empirical observations, estimating exposures using human mobility data, and evaluating the impact of environmental justice. Employing a novel data fusion technique, the study combines the Weather Research and Forecasting model with Chemistry (WRF-Chem) outputs and surface PM 2.5 measurements, providing a more accurate estimation of PM 2.5 distribution. The study addresses the gap in traditional exposure assessments by incorporating human mobility data and further investigates the spatial correlation of PM 2.5 levels with various environmental and demographic factors from the US Environmental Protection Agency (EPA) Environmental Justice Screening and Mapping Tool (EJScreen). Results reveal that despite reduced mobility during high PM 2.5 levels from wildfire smoke, exposure for both residents and individuals on the move remains high. Regions already burdened with high environmental pollution levels face amplified PM 2.5 effects from wildfire smoke. Furthermore, we observed mixed correlations between PM 2.5 concentrations and various demographic and socioeconomic factors, indicating complex exposure patterns across communities. Urban areas, in particular, experience persistent high exposure, while significant correlations in rural areas with EJScreen factors highlight the unique vulnerabilities of these populations to smoke exposure. These results advocate for a comprehensive approach to environmental health that leverages advanced models, integrates human mobility data, and addresses socio-demographic disparities, contributing to the development of equitable strategies against the growing threat of wildfires., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

This paper investigates the relationships among the important process parameters that impact Post-combustion Carbon Capture (PCC) carbon dioxide (C O 2) separation. A better understanding of the complex relationships among those parameters can support optimization and performance enhancement of the separation process. Being able to precisely predict the process parameters will enable the operator to determine the current state of the process, forecast any potential changes or events, and adjust process parameters to enhance the plant's performance. With the objective of studying the process parameters' correlations in the amine-based PCC process, we modeled the multi-year historical production data of the Clean Energy Technologies Research Institute (CETRi) (formerly known as the International Test Center for PCC or ITC) in Regina, Saskatchewan, Canada, using a Decision Forest approach. The model validation process revealed that the Decision Forest model produced higher predictive accuracy than previous efforts. The Decision Forest models we developed also represent knowledge about the importance of parameters involved in the capture process, and such knowledge is useful for further optimization of the capture process in the future. • Modeling the parameters of the Carbon Capture process with machine learning (ML). • The ML models used Decision Forest with Gradient Boosting and Oblique Split. • The ML models achieved superior predictive accuracy compared to past efforts. • The ML models support interpretability by visualizing weights and prediction paths. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Small Business & Entrepreneurship is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Small Business & Entrepreneurship is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The monitoring of forest ecosystems is significantly affected by the lack of consistent historical data of low-severity (forest partially disturbed) or gradual disturbance (e.g. eastern spruce budworm epidemic). The goal of this paper is to explore the use of a subset of Landsat time series and deep learning models to identify both the type and the year of disturbances, including low-severity and gradual disturbances, in the boreal forest of eastern Canada at the pixel level. Remote sensing data such as the spectral information from Landsat time series are the best available option for large scale observations of disturbances that go back decades. Traditional modeling approaches, like LandTrendr, require substantial handcrafted pre-processing to remove noise and to extract temporal features from the image sequences before using them as input to a classical machine-learning model. Deep-learning models can autonomously discern which features are relevant within the coarse temporal and spectral information from the Landsat annual dense time series. We evaluated the performance of TempCNN and Transformer model in detecting and classifying the type and the year of the forest disturbance using Landsat time series subsequences. Our findings resulted in the generation of four disturbance maps outlining the forest history from 1986 to 2021 within the eastern Canadian boreal forest. Our experimental outcomes demonstrate several significant benefits of employing deep learning models. Firstly, using noisy Landsat time series they achieve comparable accuracy for classifying fire and total harvesting than existing publicly available disturbance maps. Secondly, the use of shorter time series subsequence with deep learning models enables to map adequately different overlapping disturbances occurring in the complete time series. Finally, they increase the number of distinguishable disturbance classes by adding partial harvesting, gradual disturbances, and forest recovery from older events, making them useful approaches for obtaining the first remote sensing-based map for areas affected by the eastern spruce budworm. • TempCNN, Transformer tested on Landsat time series for disturbance classification. • The type and the year of disturbance events were classified with good accuracy. • Deep learning effective for identifying partial and progressive disturbances. • Landsat subsequences extract overlapping disturbances. [ABSTRACT FROM AUTHOR]

Persistent organic pollutants (POPs) are organic chemical substances that threaten human health and the planet's ecosystems due to their toxicity and their ability to remain intact for a long time, wide distribution throughout the environment, and accumulation and magnification in living organisms through the food chain. Discarded products from landfills and dumpsites are potential sources of POPs due to their persistence for several decades and constant release to surrounding environment. POPs in aquatic systems signal input predominantly from landfills, wastewater treatment plants, sewage, and urban runoff, suggesting a research gap to guide policies to address these unabated releases. This scoping review aims to rapidly identify the key concepts underpinning the containment, translation, and migration of POPs in Canadian and US landfill leachate. The review targeted multidisciplinary perspectives on the topic and spanned forensic biology, environmental sciences, chemistry, and geology. Contaminated municipal solid waste (MSW) landfill characteristics, as reported by government agencies in Canada and the US, were synthesized and harmonized to illustrate the geographical scope of MSW landfills releasing POPs into the surrounding environment. The knowledge and data gaps summarized in this study highlight the need to address the inadvertent release of POPs from Canadian and US landfills, particularly in consideration of dated and degrading landfill infrastructure, the proximity of marginalized people, and the implications of climate change on the countries' more vulnerable landscapes. This review is applicable to the development of future studies that aim to guide environmental protective policies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Dioxins, furans, and dioxin-like polychlorinated biphenyls (PCBs) are a group of persistent and toxic chemicals that are known to have human health effects at low levels. These chemicals have been produced for commercial use (PCBs) or unintentionally as by-products of industry or natural processes (PCBs, dioxins, and furans). Additionally, dioxin-like PCBs were formerly used in electrical applications before being banned internationally (2004). These chemicals are widely dispersed in the environment as they can contaminate air and travel hundreds to thousands of kilometers before depositing on land or water, thereafter, potentially entering food chains. Community concerns surrounding the safety of traditional foods prompted a human biomonitoring project in Old Crow, Yukon Territory (YT), Canada (2019). Through collaborative community engagement, dioxins and like compounds were identified as a priority for exposure assessment from biobanked samples. In 2022, biobanked plasma samples (n = 54) collected in Old Crow were used to measure exposures to seven dioxins, ten furans, and four dioxin-like PCBs. 1,2,3,6,7,8-HxCDD, 1,2,3,7,8,9-HxCDD, 1,2,3,4,6,7,8-HpCDD, OCDD, 2,3,4,7,8-PeCDF, 1,2,3,6,7,8-HxCDF, PCB 126, and PCB 169 were detected in at least 50 % of samples. Among these analytes, the only congener at elevated levels was PCB 169, which was approximately ∼2-fold higher than the general population of Canada. No significant sex-based or body mass index (BMI) differences in biomarker concentrations were observed. Generally, the concentrations of the detected congeners increased with age, except for 1,2,3,4,6,7,8-HpCDD. For the first time, this research measures dioxin and like-compound exposures in Old Crow, advancing the information available on chemical exposures in the Arctic. Further research could be directed towards the investigation of PCB 169 exposure sources and temporal monitoring of exposures and determinants., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

To evaluate effects of tertiary treated wastewater treatment plant effluent (MWWE) on transcriptomic responses in longnose dace (Rhinichthys cataractae; LND) we conducted a semi-controlled study in experimental raceways (Advancing Canadian Water Assets facility) imbedded in the Pine Creek treatment plant (Calgary, AB). LND collected from a reference site in the Bow River (REF) were caged in raceways containing either 5 % Pine Creek effluent (PC) or Bow River water (BR; control) over 28 d. Liver transcriptomes were analyzed in males and females sampled on days 7, 14 and 28 from BR and PC, and compared to REF fish on day 0. Concurrent with the caging, selected environmental substances of concern were analyzed in the BR and PC. Significantly different unigenes (SDUs) in females (vs males) within both BR and PC raceways increased over time and compared to REF fish. Moreover, SDUs in females and males within the same treatment (i.e., BR, PC) showed a temporal increase as well as compared to REF fish. Time was the dominant factor affecting SDUs, whereas sex and treatment had less of an impact on the transcriptome profiling. Gene Set Enrichment Analysis of BR vs PC over time revealed effects on genes involved in growth, metabolism of carbohydrates and lipids, and immune system on day 7; however, by day 28, 80-100 % of the transcripts localized to enriched biomarkers were associated with tissue immune responses in both sexes. Exposure to 5 % effluent had significant effects on female liver somatic index but no effects were observed on other phenotypic health indices in either sex. BR was used as the source of reference water, but analyses showed trace amounts of ESOCs. Analyses did not point towards definitive response patterns that could be used in field-based ecotoxicogenomic studies on the impacts of well-treated MWWE but suggested compromised adaptive immune responses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Reactive skin decontamination lotion (RSDL) is a Health Canada approved product used by the Canadian Armed Forces for removal and inactivation of toxic chemicals on skin. Although it is considered very safe when used as directed, questions have been raised regarding whether topical RSDL in the medical setting will react exothermically with antiseptic compounds on the casualty's epidermis that could result in thermal burns. Benchtop experiments were conducted to investigate reactivity of RSDL with various antiseptic compounds or hemostatic agents. Temperature changes were closely monitored in three different volume ratios, 1:10, 1:1, and 10:1 over a time course of 16 minutes. Chlorine based bleaches versus RSDL were included as a positive control and were the only combination that exhibited a significant exothermic reaction capable of causing minor thermal burns. RSDL was also evaluated with antiseptic solution applied to swine epidermal tissue without observation of visual irritation; then in lacerated skeletal muscle tissue which resulted in no measured temperature change. The conclusion of this study is that antiseptics and hemostatic agents can be used as required on a patient decontaminated with RSDL as no exothermic reaction will occur., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, (Crown Copyright © 2024. Published by Elsevier B.V. All rights reserved.)