Found 2670 publications. Showing page 28 of 267:
Rising carbon inequality and its driving factors from 2005 to 2015
Carbon inequality is the gap in carbon footprints between the rich and the poor, reflecting an uneven distribution of wealth and mitigation responsibility. Whilst much is known about the level of inequality surrounding responsibility for greenhouse gas (GHG) emissions, little is known about the evolution in carbon inequality and how the carbon footprints of socio-economic groups have developed over time. Inequality can be reduced either by improving the living standards of the poor or by reducing the overconsumption of the rich, but the choice has very different implications for climate change mitigation. Here, we investigate the carbon footprints of income quintile groups for major 43 economies from 2005 to 2015. We find that most developed economies had declining carbon footprints but expanding carbon inequality, whereas most developing economies had rising footprints but divergent trends in carbon inequality. The top income group in developing economies grew fastest, with its carbon footprint surpassing the top group in developed economies in 2014. Developments are driven by a reduction in GHG intensity in all regions, which is partly offset by income growth in developed countries but more than offset by the rapid growth in selected emerging economies. The top income group in developed economies has achieved the least progress in climate change mitigation, in terms of decline rate, showing resistance of the rich. It shows mitigation efforts could raise carbon inequality. We highlight the necessity of raising the living standard of the poor and consistent mitigation effort is the core of achieving two targets.
2023
Plastic pollution has long been identified as one of the biggest challenges of the 21st century. To tackle this problem, governments are setting stringent recycling targets to keep plastics in a closed loop. Yet, knowledge of the stocks and flows of plastic has not been well integrated into policies. This study presents a dynamic probabilistic economy-wide material flow analysis (MFA) of seven plastic polymers (HDPE, LDPE, PP, PS, PVC, EPS, and PET) in Norway from 2000 to 2050. A total of 40 individual product categories aggregated into nine industrial sectors were examined. An estimated 620 ± 23 kt or 114 kg/capita of these seven plastic polymers was put on the Norwegian market in 2020. Packaging products contributed to the largest share of plastic put on the market (∼40%). The accumulated in-use stock in 2020 was about 3400 ± 56 kt with ∼60% remaining in buildings and construction sector. In 2020, about 460 ± 22 kt of plastic waste was generated in Norway, with half originating from packaging. Although ∼50% of all plastic waste is collected separately from the waste stream, only around 25% is sorted for recycling. Overall, ∼50% of plastic waste is incinerated, ∼15% exported, and ∼10% landfilled. Under a business-as-usual scenario, the plastic put on the market, in-use stock, and waste generation will increase by 65%, 140%, and 90%, respectively by 2050. The outcomes of this work can be used as a guideline for other countries to establish the stocks and flows of plastic polymers from various industrial sectors which is needed for the implementation of necessary regulatory actions and circular strategies. The systematic classification of products suitable for recycling or be made of recyclate will facilitate the safe and sustainable recycling of plastic waste into new products, cap production, lower consumption, and prevent waste generation.
2023
Poland continues to rely heavily on coal and fossil fuels for household heating, despite efforts to reduce Particulate Matter (PM) levels. The availability of reliable air quality data is essential for policymakers, environmentalists, and citizens to advocate for cleaner energy sources. However, Polish air quality monitoring is challenging due to the limited coverage of reference stations and outdated equipment. Here, we report the results of a study on the spatio-temporal variability of Particulate Matter in Legionowo, Poland, using residents’ network of low-cost sensors. Along with identifying the hotspots of household-emitted PM, (1) we propose a data quality assurance scheme for PM sensors, (2) suggest an approach for estimating the Relative Humidity-induced uncertainty in the sensors without co-location with reference instruments, and (3) develop an interpretable Machine Learning (ML) model, a Generalized Additive Model (RMSE = 6.16 μg m−3, and R2 = 0.88), for unveiling the underlying relations between PM2.5 levels and other environmental parameters. The results in Legionowo suggest that as air temperature and wind speed increase by 1 °C and 1 km h−1, PM2.5 would respectively decrease by 0.26 μg m−3 and 0.14 μg m−3 while PM2.5 increases by 0.03 μg m−3 as RH increases by 1%.
2023
The present study examined how climate changes may impact the concentrations of lipophilic organochlorines (OCs) in the blood of fasting High Arctic common eiders (Somateria mollissima) during incubation. Polychlorinated biphenyls (PCBs), 1-dichloro-2,2-bis (p-chlorophenyl) ethylene (p,p′-DDE), hexachlorobenzene (HCB) and four chlordane compounds (oxychlordane, trans-chlordane and trans- and cis-nonachlor) were measured in females at chick hatching (n = 223) over 11 years (2007–2017). Firstly, median HCB and p,p′-DDE concentrations increased ~75 % over the study period, whereas median chlordane concentrations doubled (except for oxychlordane). PCB concentrations, in contrast, remained stable over the study period. Secondly, both body mass and clutch size were negatively associated with OC levels, suggesting that females with high lipid metabolism redistributed more OCs from adipose tissue, and that egg production is an important elimination route for OCs. Thirdly, the direct climate effects were assessed using the mean effective temperature (ET: air temperature and wind speed) during incubation, and we hypothesized that a low ET would increase redistribution of OCs. Contrary to expectation, the ET was positively correlated to most OCs, suggesting that a warmer climate may lead to higher OCs levels, and that the impact of ET may not be direct. Finally, potential indirect impacts were examined using the Arctic Oscillation (AO) in the three preceding winters (AOwinter 1–3) as a proxy for potential long-range transport of OCs, and for local spring climate conditions. In addition, we used chlorophyll a (Chla) as a measure of spring primary production. There were negative associations between AOwinter 1 and HCB, trans-chlordane and trans-nonachlor, whereas oxychlordane and cis-chlordane were negatively associated with Chla. This suggests that potential indirect climate effects on eiders were manifested through the food chain and not through increased long-range transport, although these relationships were relatively weak.
2023
Cross-modal representation learning aims to learn a shared representation space where data from multiple modalities can be effectively compared, fused, and understood. This paper investigates the role of increased diversity in the similarity score matrix in enhancing the performance of the CLIP (Contrastive Language-Image Pretraining), a multi-modal learning model that establishes a connection between images and text within a joint embedding space. Two transforming approaches, sine and sigmoid (including two versions), are incorporated into the CLIP model to amplify larger values and diminish smaller values within the similarity matrix (logits). Hardware limitations are addressed using a more compact text encoder (DistilBERT) and a pre-trained ResNet50 image encoder. The proposed adaptations are evaluated on various benchmarks, including image classification and image/text retrieval tasks, using 10 benchmark datasets such as Food101, Flickr30k, and COCO. The performance of the adapted models is compared to the base CLIP model using Accuracy, mean per class, and Recall@k metrics. The results demonstrate improvements in Accuracy (up to 5.32% enhancement for the PatchCamelyon dataset), mean per class (up to 14.48% enhancement for the FGVCAircraft dataset), and retrieval precision (with an increase of up to 45.20% in Recall@1 for the COCO dataset), compared to the baseline algorithm (CLIP).
2023
Genotoxic effects of occupational exposure to glass fibres - A human biomonitoring study.
As part of a large human biomonitoring study, we conducted occupational monitoring in a glass fibre factory in Slovakia. Shopfloor workers (n = 80), with a matched group of administrators in the same factory (n = 36), were monitored for exposure to glass fibres and to polycyclic aromatic hydrocarbons (PAHs). The impact of occupational exposure on chromosomal aberrations, DNA damage and DNA repair, immunomodulatory markers, and the role of nutritional and lifestyle factors, as well as the effect of polymorphisms in metabolic and DNA repair genes on genetic stability, were investigated.
The (enzyme-modified) comet assay was employed to measure DNA strand breaks (SBs) and apurinic sites, oxidised and alkylated bases. Antioxidant status was estimated by resistance to H2O2-induced DNA damage. Base excision repair capacity was measured with an in vitro assay (based on the comet assay).
Exposure of workers to fibres was low, but still was associated with higher levels of SBs, and SBs plus oxidised bases, and higher sensitivity to H2O2. Multivariate analysis showed that exposure increased the risk of high levels of SBs by 20%. DNA damage was influenced by antioxidant enzymes catalase and glutathione S-transferase (measured in blood). DNA repair capacity was inversely correlated with DNA damage and positively with antioxidant status. An inverse correlation was found between DNA base oxidation and the percentage of eosinophils (involved in the inflammatory response) in peripheral blood of both exposed and reference groups. Genotypes of XRCC1 variants rs3213245 and rs25487 significantly decreased the risk of high levels of base oxidation, to 0.50 (p = 0.001) and 0.59 (p = 0.001), respectively.
Increases in DNA damage owing to glass fibre exposure were significant but modest, and no increases were seen in chromosome aberrations or micronuclei. However, it is of concern that even low levels of exposure to these fibres can cause significant genetic damage.
2023
Flue gas recirculation (FGR) is a method used in several industries to control emissions and process conditions, such as NOx reduction and temperature levels, and increase the CO2 concentration in the off-gas, to be better suited for methods of carbon capture. In this study, the influence of FGR, varying levels of flue gas flow and oxygen concentration on the emissions of polycyclic aromatic hydrocarbons (PAHs) was investigated during Si alloy production. In addition, computational fluid dynamics (CFD) modeling was performed using OpenFOAM for combustion of C2H2 and H2 with varying O2 levels to simulate FGR and to gain better insight into the impact of furnace operations on the PAH evolution. Experimental results show that increasing FGR (0–82.5%) and decreasing levels of oxygen (20.7–13.3 vol %) increase the PAH-42 concentration from 14.1 to 559.7 μg/Nm3. This is supported by the simulations, where increased formation of all PAHs species was observed at high levels of FGR, especially for the lighter aromatic species (like benzene and naphthalene), due to the lower availability of oxygen and the reduction in temperature. Residence time was identified as another key parameter to promote complete combustion of PAHs. Benzene oxidation can be prevented with temperatures lower than 1000 K and residence times smaller than 1 s, while complete oxidation is found at temperatures of around 1500 K.
2023
Populations of killer whale (Orcinus orca) contain some of the most polluted animals on Earth. Yet, the knowledge on effects of chemical pollutants is limited in this species. Cell cultures and in vitro exposure experiments are pertinent tools to study effects of pollutants in free-ranging marine mammals. To investigate transcriptional responses to pollutants in killer whale cells, we collected skin biopsies of killer whales from the Northern Norwegian fjords and successfully established primary fibroblast cell cultures from the dermis of 4 out of 5 of them. Cells from the individual with the highest cell yield were exposed to three different concentrations of a mixture of persistent organic pollutants (POPs) that reflects the composition of the 10 most abundant POPs found in Norwegian killer whales (p,p’-DDE, trans-nonachlor, PCB52, 99, 101, 118, 138, 153, 180, 187). Transcriptional responses of 13 selected target genes were studied using digital droplet PCR, and whole transcriptome responses were investigated utilizing RNA sequencing. Among the target genes analysed, CYP1A1 was significantly downregulated in the cells exposed to medium (11.6 µM) and high (116 µM) concentrations of the pollutant mixture, while seven genes involved in endocrine functions showed a non-significant tendency to be upregulated at the highest exposure concentration. Bioinformatic analyses of RNA-seq data indicated that 13 and 43 genes were differentially expressed in the cells exposed to low and high concentrations of the mixture, respectively, in comparison to solvent control. Subsequent pathway and functional analyses of the differentially expressed genes indicated that the enriched pathways were mainly related to lipid metabolism, myogenesis and glucocorticoid receptor regulation. The current study results support previous correlative studies and provide cause-effect relationships, which is highly relevant for chemical and environmental management.
2023
The role of SVOCs in the initial film formation and soiling of unvarnished paintings
In recent years increased research efforts and environmental improvements have been directed towards the preventive conservation of the monumental, unvarnished oil paintings on canvas (1909–1916) by Edvard Munch (1863–1944) housed in the University of Oslo Aula. Surface soiling of the paintings has been a documented issue since their display, and the modern-day effect of air-borne particulates and gases on the painting surfaces remains hitherto undocumented. For the first time in the Aula, this study has measured the in-situ time-dependent mass deposit of air pollution onto vertical surfaces over the period of one year (2021–2022). Concomitant measurements of the concentrations of ozone (O3) and nitrogen dioxide (NO2) were also taken, to complement periodic data from 2020. The mass deposit was measured through incremental weight changes of Teflon membrane filters, and quartz filters for analysis of elemental/organic carbon (EC/OC), whilst the gaseous pollutants were measured using passive gas samplers. Indoor-to-outdoor ratios (I/O) for O3 were noted to be higher than those suggested by earlier data, whereas NO2 I/O ratios were found to be lower, indicating a stronger oxidising atmosphere in the Aula. Just over half of the deposited mass on the quartz filters was found to be OC, with no EC detected. Surprisingly, an overall decrease in the mass deposit from three to twelve months was measured on the Teflon membrane filters. It was hypothesised, based on models reported in the literature, that the source of the OC on the filters was mainly gaseous, semi-volatile organic compounds (SVOCs), which were present in an adsorption/desorption equilibrium that was dependent on possible SVOC emission episodes, relative humidity levels, gaseous oxidative reactions and the particulate matter deposit. A simple mathematical model is proposed to rationalise the observed mass deposits on the filters, together with a discussion of uncertainties affecting the measurements. The hypothesis preliminarily indicates the possible and previously unconsidered role of SVOCs on the initial film formation of soiling layers on the Aula paintings, and could bear implications for their monitoring in the preventive care of unvarnished oil paintings on canvas.
2023
Rapid growth in urbanization and industrialization leads to an increase in air pollution and poor air quality. Because of its adverse effects on the natural environment and human health, it’s been declared a “silent public health emergency”. To deal with this global challenge, accurate prediction of air pollution is important for stakeholders to take required actions. In recent years, deep learning-based forecasting models show promise for more effective and efficient forecasting of air quality than other approaches. In this study, we made a comparative analysis of various deep learning-based single-step forecasting models such as long short term memory (LSTM), gated recurrent unit (GRU), and a statistical model to predict five air pollutants namely Nitrogen Dioxide (NO 2 ), Ozone (O 3 ), Sulphur Dioxide (SO 2 ), and Particulate Matter (PM2.5, and PM10). For empirical evaluation, we used a publicly available dataset collected in Northern Ireland, using an air quality monitoring station situated in Belfast city centre. It measures the concentration of air pollutants. The performance of forecasting models is evaluated based on three performance metrics: (a) root mean square error (RMSE), (b) mean absolute error (MAE) and (c) R-squared ( R2 ). The result shows that deep learning models consistently achieved the least RMSE compared to the statistical models with a value of 0.59. In addition, the deep learning model is also found to have the highest R2 score of 0.856.
2023