Study of the influence of fluvial dynamics on the distribution and transport of microplastics

University of Minho School of Sciences Rui César da Silva Veloso Study of the influence of fluvial dynamics on the distribution and transport of microplastics. October 2023 Study of the influence of fluvial dynamics on the distribution and transport of microplastics Rui César da Silva Veloso UMinho | 2023 October 2 4 University of Minho School of Sciences Rui César da Silva Veloso Study of the influence of fluvial dynamics on the distribution and transport of microplastics. Master thesis in Geosciences: External Dynamics and Global Changes Work made under supervision of: Professor Doutor Luís Miguel Barros Gonçalves Professor Doutor Renato Filipe Faria Henriques 0 DIREITOS DE AUTOR E CONDIÇÕES DE UTILIZAÇÃO DO TRABALHO POR TERCEIROS Este é um trabalho académico que pode ser utilizado por terceiros desde que respeitadas as regras e boas práticas internacionalmente aceites, no que concerne aos direitos de autor e direitos conexos. Assim, o presente trabalho pode ser utilizado nos termos previstos na licença abaixo indicada. Caso o utilizador necessite de permissão para poder fazer um uso do trabalho em condições não previstas no licenciamento indicado, deverá contactar o autor, através do RepositóriUM da Universidade do Minho. Licença concedida aos utilizadores deste trabalho Atribuição - Não Comercial - Sem Derivações CC BY-NC-ND https://creativecommons.org/licenses/by-nc-nd/4.0/ Acknowledgments First and for most, I would like to thank my tutors Doctor Luís Gonçalves and Doctor Renato Henriques for all the knowledge, guidance, support and talks that we had, for motivating me and giving all the means and tools that in some way or another are a perk for my development. I would also like to thank all the DCT professors, that in some way contributed to this work and its development. Additionally, I would like to thank Doctor Joana Prata for encouraging me and help by clarifying any doubts I had regarding methods as well as Engineer Ana Carvalho for aiding me during the development of my work, by providing me with results and on-going projects on the subject region in study. I want to give a special thank you to my brother, which has been, without a doubt, my idol and inspiration to follow this path. I want to also thank my parents for all the opportunities and hours invested in me and my education as well as my family in general, which somehow contribute to my development in the small moments we go through. A big thank you to all my friends, particularly to Alheiras, Paiva, Guida, Maia, Phineas, Tomé, Maurício, Inês, Sara, Zé, Zacarias, Jorge, Angela and Coelho that somehow contribute for my happiness and helped me by motivating me through the development of this thesis. A special thank you to Professor and friend Joana for “showing me a new world”, for changing my mind set and after all this year’s still motivating me to follow my path as well as for having shown me the beauty and mastery behind the words of Pessoa allowing me to turn them into my maxims: “I do not care. I do not care what? I do not know, I do not care “. You are truly an inspiration! Last but not least and because we save the best for the end, I would like to express my heartfelt gratitude to the two most important people in my life! Thank you, Sofia, for everything you do, time you spend and the care you have for me. Without you, nothing would be the same and I’m truly thankful for having you and for everything you do and go through with me. Thank you for always staying by my side, helping me overcome barriers and challenges as well as supporting me in my darkest hours. Thank you for being you, XO Ly. Finally, to the second person, who’s river stopped running eternally, and I can no longer share all these experiences with, a huge thank you for who you were, for the grandfather, pilar, idol and hero you were and still are to me, even in my darkest moments you smiled and showed me love – you guided me and still do! Thank you for everything, Pa, I will never forget you, because in the end of the day, you never left as part of you is still present in me. Thank you. “ A maioria pensa com a sensibilidade, eu sinto com o pensamento. Para o homem vulgar, sentir é viver e pensar é saber viver. Para mim, pensar é viver e sentir não é mais que o alimento de pensar .” – Bernardo Soares (Fernando Pessoa) Statement of Integrity I hereby declare having conducted this academic work with integrity. I confirm that I have not used plagiarism or any form of undue use of information or falsification of results along the process leading to its elaboration. I further declare that I have fully acknowledged the Code of Ethical Conduct of the University of Minho. Título: Estudo da influência da dinâmica fluvial na distribuição e transporte de microplásticos. Resumo: A dependência global da água, juntamente com o crescimento exponencial da produção de plástico nas últimas décadas, deu origem a uma preocupação ambiental premente - a poluição da água por microplásticos. A pandemia de COVID-19 e as consequências das crises financeiras agravaram ainda mais esta questão, com o aumento do consumo de plástico a conduzir a uma maior poluição dos ecossistemas aquáticos. Embora os processos de fragmentação dos plásticos gerem microplásticos, partículas de polímero com menos de 5 mm, a extensão total dos seus efeitos em diversos organismos, nomeadamente o ser humano, continua a ser objeto de investigação. Esta dissertação procura compreender a relação entre a dinâmica fluvial, o transporte de microplásticos e a sua distribuição em ambientes aquáticos. Os rios, considerados como os principais agentes responsáveis pelo transporte de partículas para os oceanos e zonas costeiras, desempenham um papel fundamental neste fenómeno. O comportamento dos microplásticos nos sistemas fluviais é uma interação complexa de processos físicos, químicos e biológicos, que exige uma análise meticulosa. Fundamentalmente, esta investigação tem como objetivo dar um passo no sentido de promover uma compreensão mais abrangente e clara desta questão e das suas consequências. O estudo foi efetuado no rio Cávado, desde a Ponte do Porto até à foz, abrangendo diversos ambientes e condições ambientais. Foram selecionados 17 locais de amostragem estrategicamente marcados e foi amostrado o sedimento em cada um deles. As amostras foram submetidas a um processo meticuloso, incluindo a secagem numa estufa e a separação da densidade utilizando uma solução de CaCl2. A amostra sobrenadante resultante foi então recolhida e submetida a uma inspeção visual ao microscópio. Esta análise rigorosa levou à identificação visual de um total de 571 microplásticos. Os locais MP012B, MP009, MP005 e MP003 apresentaram as contagens mais elevadas e o estudo revelou um aumento distinto da prevalência de microplásticos de montante para jusante. Estatisticamente, os valores exibiram normalidade e indicaram diferenças estatisticamente significativas entre os grupos. Como resultado, a hipótese de que a dinâmica fluvial influencia o comportamento dos microplásticos foi conclusivamente corroborada. O estudo também explorou potenciais correlações entre os fatores de pressão fluvial e a abundância de microplásticos em vários locais de amostragem, considerando a presença de urbanizações, ETARs, terrenos agrícolas, áreas industriais e outras infraestruturas. No entanto, é essencial reconhecer potenciais fontes de contaminação cruzada, tais como partículas transportadas pelo ar ou fibras de vestuário, bem como a ausência de digestão da matéria orgânica e subsequente filtragem ou peneiração, o que pode ter induzido erros humanos na identificação das partículas. Por conseguinte, recomenda-se uma reavaliação e re-execução dos procedimentos laboratoriais. Palavras-chave: Microplásticos, Granulometria, Bacia Hidrográfica do Rio Cávado, Amostragem, Técnica de Extração, Efeitos, Transporte, Distribuição e Fatores de Pressão. Title: Study of the influence of fluvial dynamics on the distribution and transport of microplastics. Abstract: The global reliance on water, coupled with the exponential growth of plastic production over the past decades, has given rise to a pressing environmental concern — microplastics water pollution. The COVID-19 pandemic and the aftermath of financial crises have further exacerbated this issue, with increased plastic consumption leading to the heightened pollution of aquatic ecosystems. While the fragmentation processes of plastic waste generate microplastics, polymer particles smaller than 5mm, the full extent of their effects on diverse organisms remains the subject of extensive research. Remarkably, the effects of microplastics on human health remain inadequately understood, underscoring the urgency of further investigation. This thesis embarks on a comprehensive exploration of the intricate relationship between fluvial dynamics, microplastic transportation, and their distribution in aquatic environments. Rivers, regarded as the primary agents responsible for the transportation of microplastic particles to oceans and coastal areas, play a pivotal role in this phenomenon. The behaviour of microplastics within river systems is a complex interplay of physical, chemical, and biological processes, requiring a meticulous examination. Understanding the specifics of how rivers impact the transport and dispersion of these particles is crucial for developing effective strategies to mitigate their adverse environmental and ecological effects. Fundamentally this investigation aims to be a step towards fostering a more comprehensive understanding of the broader issue of plastic pollution and its far-reaching consequences. The study was conducted in the Cávado River, spanning from the Porto Bridge to the river mouth, encompassing a diverse range of environmental conditions. A total of 17 strategically marked sampling sites were selected and the riverbed sediment of each was sampled. The samples underwent a meticulous process, including drying in a laboratory oven and density separation using a CaCl2 solution. The resulting supernatant sample was then collected and subjected to visual analysis under a microscope. This rigorous analysis led to the visual identification of a total of 571 microplastic particles. Notably, microplastics at sites MP012B, MP009, MP005, and MP003 displayed the highest counts, and the study revealed a distinct increase in microplastic prevalence from upstream to downstream locations. Statistically, the values exhibited normality and indicated statistically significant differences among groups. As a result, the hypothesis that fluvial dynamics influence microplastic behaviour was conclusively substantiated. The study also explored potential correlations between fluvial pressure factors and microplastic abundance at various sampling sites, considering the presence of urbanizations, wastewater treatment plants, agricultural land, industrial areas, and other infrastructures. However, it is essential to acknowledge potential sources of cross-contamination, such as airborne particles or clothing fibers, as well as the absence of organic matter digestion and subsequent filtering or sieving, which could lead to human error in particle identification. Therefore, a careful and thorough reassessment of the laboratory procedures is recommended. Keywords: Microplastics, Particle size, Cávado River watershed, Sampling, Extraction technique, Effects, Transportation, Distribution, and Pressure factors. 4 and incentives, as well as concerns among business owners about the potential loss of customers and profits. Moreover, there is an increasing dependence on single-use plastics, like straws, food packaging, films, and others, by individuals with disabilities or those with motor-restricting diseases/conditions such as Parkinson's (Vimal et al. , 2020). It is vital to acknowledge that environmentalism, while well-intentioned, can have negative impacts and risks, affecting marginalized and vulnerable communities. Therefore, it is crucial to adopt an environmental justice perspective to ensure that measures, policies, and laws do not adversely affect society beyond their economic implications (Jenks & Obringer, 2020). As mentioned earlier, the use and production of plastics have witnessed astronomical growth. Since 1950, a staggering 7800 million tonnes (Mt) of plastic resin and fibers have been manufactured, with half of this production occurring between 2004 and 2017 (Geyer et al. , 2017). In 1950, the annual plastic production stood at approximately 2Mt, and by 2015, it had already surged to 380 Mt (Figure 3). In the years leading up to 2019, coinciding with the onset of the pandemic, there was a slight dip in global plastic production, with output reaching 365.5Mt (Plastics Europe, 2023; OWD, 2019). However, after the pandemic, as depicted in Figure 4, we witnessed a return to the upward trend, peaking in 2021, at 390.7Mt (Plastics Europe, 2023). Figure 3 - Global primary plastics production (in million metric tons) according to industrial use sector from 1950 to 2015. – Data obtained from Geyer et al., 2017 and OECD, 2019. Graph retrieved from OWD, 2023. 5 Although these numbers are the most cited by authors, we see discrepancies between the different statistic sources, with a variation of the number of total global plastics produced between 350 - 450Mt, for the year of 2018 (Figures 3, 4 and 5). This could be justified by a multitude of factors, including differences in data sources, the considerations of statistical teams, means and methods of analysis, and the willingness of governments, industries, and enterprises to disclose accurate values. However, there is a common denominator — the overall upward trend. By 2050, we should anticipate plastic production reaching approximately 1100-1400Mt, as illustrated in Figures 3, 4, and 5. Europe also followed this growth trend, however, in the last 2 - 3 years it has made gradual reductions in the production and consumption of fossilbased plastics, and has been investing more in recycled and bio-based plastics (Figure 4), nevertheless we are still far from reaching the desired sustainability. Figure 4 - Global Plastic Production from 2018 to 2021. Red Bar - Fossil-based plastics; Green bar - post-consumer recycled plastics; Orange bar - Bio-based plastics. Retrieved from Plastics Europe, 2022. One could argue that the plastic problem relies on many distinct factors, its existence for example, but truthfully the problem lies in its End of Life (EOL) solution, which until now as proven to be inefficient (Williams & Buitrago, 2022). 6 Figure 5 - Global Plastic Production, since 1950, in corelation with population growth and law introduction. Retrieved from Hazlegreaves, 2021. But how can we target such problem? Well, Ammendolia et al. (2021) suggested that we should start by defining a clear line between the terms we use, specifically “litter” and “pollution”. According to their proposal, 'litter' should be linked to individual actions, such as improper garbage disposal. On the other hand, 'pollution' should be associated with companies engaged in the extraction, production, and disposal of plastics. Furthermore, when such pollution poses risks to humans or animals, it should be named “hazardous pollution.” The authors also emphasized the notion of “culpability.” They highlight a prevalent Western narrative that predominantly addresses the end stages of the plastic life cycle, particularly consumption and disposal. However, this perspective overlooks the various key agents in the process, commencing with the extraction 7 of crude materials and extending through transportation, refining, production, and distribution, as depicted in Figure 6. Figure 6 - Plastic Life Cycle. Obtained from Life Cycle Initiative by UN environment programme in October 2023. Retrieve from Life Cycle Initiative, 2023. This individual focused narrative does not address our current predicament. This approach often results in measures and policies adopted by governments that primarily target the end consumer, overlooking the critical production process. One commonly employed strategy is the imposition of additional charges on plastic items. For instance, in Portugal, consumers are charged an extra €0.10 for each plastic bag they use, which once again impacts only the end consumer. Another example is the fines for littering, specifically related to cigarettes and improper disposal of plastic waste. While not particularly stringent, these fines can still carry significant financial penalties or societal consequences for individuals. Nonetheless, it is not to be misinterpreted, as nobody is trying to exonerate the individual responsibility but rather point that focusing on them as proven not to be the best solution for the problem (Williams & Buitrago, 2022). As the entire production and usage of plastic is anthropogenic, human solutions for plastics are both mandatory and feasible. Hence, various societal actors/sectors are necessary: consumers, producers, policy makers, industries, law makers and state agents (Heidbreder et al. , 2019). To gain a deeper insight into addressing this issue, it is highly recommended to read the previously mentioned article, which elucidates each phase of the process comprehensively and offers statistics and practical, real-life examples. 8 Furthermore, it is also worth exploring the Life Cycle Approach (LCA) documented by UNEP. Some globally appliable measures presented by the UN (United Nations), which follow the whole plastic pollution process from extraction to disposal, respect a thorough system consisting of 5 complex steps (UNEP, 2017): 1. Follow a scientific basis, respecting the scientific method and conduct quantitative analysis. 2. Structure Action plans according to geographic and demographic factors. 3. Target hotspots accordingly respecting the social scientific studies. 4. Elaborate Guides, Training opportunities, and multiple financial studies which present Finance Sustainable Solutions. 5. Build from Existing Initiatives, take advantage of already successful measures and ideas strengthening them and scale them up globally. As an introduction to potential solutions, UNEP created Figure 7, which offers some ideas regarding the Government, Investors, Material Producers and Products/Services Producers. In Table 1 and 2, in attachments, Sharma et al. (2023), compiled Plans of Action, policies/laws, as well as challenges that different polluting countries throughout the world have been trying to fight. As of right now, the production and utilization of plastics haver reached such heights that they have become, a mandatory asset in the global marketplace. It is clear that they pose a significant hazard to not only humans but also the multitude of organisms on which we depend, but it also ends up impacting tourism and recreation, just as shown in Figure 8, it threatens rivers, coasts, the ocean life and in the end of the day, serve as a sobering reflection of human selfishness, actions, attitudes, and behaviour (Williams & Buitrago, 2022). 9 Figure 7 - Hotspots, Solutions and Actors. Obtained from Life Cycle Initiative by UN environment programme in October 2023. Retrieved from Life Cycle Initiative, 2023. Figure 8 - Pictures taken in Azurara Beach showing piles of plastic debris scattered around the beach and groyne, Portugal on the 5th of April 2023. 10 There are numerous documents and records of plastic litter pollution in diverse environments. These range from high-altitude mountains like the Everest (Napper et al. , 2020), deep ocean structures and floors like the Mariana trench, and bays like the Great Australian Bight (Jamieson et al. , 2017; Barrett et al. , 2020), to rivers (Williams & Simmons, 1997; Kunz et al. 2023) and even the atmosphere, through the “atmospheric rivers” (Brahney et al. , 2021; Zhang et al. , 2020). Additionally, there are abundant records and studies of plastic pollution in common and anthropogenically affected environments such as coastal and fluvial beaches, sub-tropical gyres, water columns, dunes, mangroves, and many others (Williams & Buitrago, 2022). We can easily understand the direct impacts of plastic pollution on multiple organisms. For instance, there are multiple examples shared across social media platforms, like straws stuck in turtle’s noses, the substantial number of plastics found in the gastrointestinal tracts of birds and fishes, or the entanglement of seals in plastic nets. These are just a few examples of this alarming issue. We have all witnessed the distressing images and videos of children and adults scavenging plastic bottles from colossal 'mountains of plastic' in exchange for a meagre compensation, barely enough for their survival, while this might not directly affect their health, it is the socio-economic condition that leads to such exploitation. In addition, plastics have substantial economic impacts on consumers and society as a whole. The entire lifecycle of plastics, from extraction to disposal, is governed by the interests of various companies and actors. A notable example is the recent COVID-19 pandemic, which highlighted humanity's remarkable ability to adapt and mass-produce affordable single-use plastic products that were crucial for our survival. However, this was often done at the expense of the environment and proper waste management (Adyel, 2020; Benson et al. , 2021; Wang et al. , 2023). Here are some journalistic articles related to the subject, which may provide additional insights into the impact of plastic pollution: https://www.nytimes.com/2021/09/18/world/covid-trash-recycling.html, https://newseu.cgtn.com/news/2020-05-22/Is-the-pandemic-triggering-a-spike-in-plastic-pollution-- QBobeagfok/index.html https://www.reuters.com/world/asia-pacific/hong-kong-zero-covid-policies-create-mountains-plastic-waste2022-04-19/ This pandemic led to a temporary decrease in gas emissions during quarantine periods However, as we started lifting the restrictions, the exploration, extraction, and production of products came back in full force, reaching pollution levels never seen before. Notably, plastics were one of the primary contributors to these increased pollution levels, as illustrated in Figures 3, 4, and 5. 11 This has been a concise general introduction to the issue of plastic pollution. While it provides a valuable overview, the subject is profoundly complex. Therefore, I highly recommend diving into the articles and documents mentioned and explore each aspect of the topic comprehensively. 3. Microplastics 3.1. Formation As it is evident, plastic pollution is a significant issue, and its gravity becomes more apparent when we delve into finer particle sizes (Ukaogo, 2020). It is also common knowledge that plastics, when exposed to the elements, will be broken down into microplastics by an array of physical, chemical, and biological processes. Thermal degradation, physical degradation, photodegradation, thermo-oxidative degradation, and hydrolysis are all examples of non-biodegradation originating what we call of Micro - and Nanoplastics (Van Cauwenberghe et al. , 2013; Yee et al. , 2021). Physical deterioration through weathering causes bigger polymers to break down into smaller pieces naturally, but thermal degradation, or heat degradation, is an artificial, industrial process. Contrarily, two naturally occurring chemical processes — hydrolysis and photodegradation — use water molecules and UV-Visible light, respectively, to dissolve the chemical bonds in plastics and transform them into monomeric forms. Plastic structures are broken down by nonbiodegradation processes, changing their mechanical characteristics and surface area, which enhances physical-chemical reactions and interactions with microbes as we will be able to further understand in this document (Lucas et al. , 2008). Figure 9 summarizes and explains graphically the basic plastic particle formation and transportation system. Microplastics (MP) are defined as polymer particles with a length under 5mm (Betts, 2008), sourcing from 2 different origins: - Primary microplastics, voluntarily created microand nanoplastics for commercial purposes, mainly consumer and industrial uses (e.g.: clothes or rags, cosmetics, cleansers, drug delivery particles or even industrial air blasting). - Secondary microplastics, are particles resulting from the fragmentation of larger pre-existing plastic items such as bottles, plastic bags, basins, single-use utilities, and others (Prata et al. , 2019; Besley, 2016). Most plastics are extremely durable and can persist for decades, or even centuries, in their original form (Hopewell et al. 2009). Due to their physical properties, plastics can contaminate the environment on a global scale (Doyen et al. , 2019) and thus, will bring consequences when consumed by various living beings (Besley et al. , 2016), gaining the title of one of the most growing problems of the 21st century (Thompson et al. , 2004). To get around this problem, attempts have been made to reach a consensus and establish bases in the analysis of microplastics, starting with their origin, that is, whether they are primary or 12 secondary; their shape, if they present as fragments, pellets (spheres, discs, cylinders), filaments/fibers, irregular shapes, thin films, plasticized foams, or granules. And one of the parameters that brought more disagreement among authors, dimension: Macroplastics > 2.5cm, Mesoplastics 0.5 - ≤ 2.5cm, Large microplastics 1 - ≤ 5mm, Small microplastics 1μm - ≤ 1000μm and Nanoplastics 1nm – ≤ 1μm (Van Cauwenberghe et al. , 2015; Gigault et al. , 2018). Figure 9 - Microand nanoplastics formation and transportation system. Retrieved from Yee et al ., 2021. 13 3.2. Detection and Quantification Methods As mentioned, it is not easy to achieve a consensus in the characterisation of these particles, so to fight it, the scientific community has been making the effort to create a “standardized methodology” regarding different physical and chemical aspect to ease the identification and characterisation. 3.2.1. Density Plastics present very diversified densities, Table 3, in attachments, ranging from less dense ones such as XPS (0.028 – 0.045 g/cm3) until the denser ones such as PVC (1.35 – 1.39 g/cm3) e o PET (1.38 – 1.41 g/cm3). Considering this property, it is a good option to perform density separation, for example, using a saline solution. Some of the recommended solutions would be concentrated NaCl solutions (density of 1.2 g/cm3), NaI (1.6 – 1.8 g/cm3), ZnCl2 (1.5 – 1.7 g/cm3) and CaCl2 (1.345 – 2.16 g/cm3; OXY, 2021; Rodríguez-Seijo & Pereira, 2017; Schröder et al. , 2021). 3.2.2. Visual Identification The most common method for identifying plastics involves visual inspection, using the naked eye for larger microplastics or magnification tools such as a microscope for smaller microplastics. This examination focuses on assessing the physical properties of the microplastics. There is a consensus that visual identification should not be followed as protocol to particles with less than 500 µm since the probability of misidentification is very high (Xu et al. , 2019). Additionally, observational errors are usually vast due to observers’ subjectivity. For example, Fries et al. (2013), reported that three different people produced results differing 1 – 4MP particles in the same sediment sample with the support of a microscope (Xu et al. , 2019). Another particularly important factor is colour, serving as a preliminary indicator of their possible composition, since, for example, transparent materials are described as PP, white plastics as PE and opaque plastics as LDPE (Hidalgo-Ruz et al. , 2012). Not only it gives us an insight of the possible composition, but it also allows us to understand the period of weathering and/or “presence” on the surface of the water, since the darkening/yellowing of these is due to the increase in the carbonyl index, resulting from photooxidation or even from “aging” (Stolte et al. , 2015), whereas pigmented plastics tend to dechlorinate. Some authors such as Stolte et al. (2015), Acosta-Coley & Olívero-Verbel (2015), Martins & Sobral (2011) established and distinguished 2 groups of colours: (1) blue, green, red, yellow, orange, among others; and (2) white, black, aged and translucent, however, Castro et al. (2016) demonstrated, through an artificially controlled study, that the colour influences the identification and quantification, when performed visually, obtaining large percentages of blue and green particles, and only a small percentage of yellow/orange particles (Rodríguez-Seijo & Pereira, 2017), as we will be able to see further in this work, most of the particles identified were different shades of red, blue or green. Nevertheless, visual identification is easily 20 3.2.5.2. Soils Both Zhang et al. (2019) and De Souza Machado et al. (2018) were able to conclude that PE fibers can cause soil degradation in some way or another. De Souza Machado et al. (2018) found that there was a reduction of bulk density due to the PE particles which on normal conditions, a bulk density reduction reflects a negative effect on root growth. However, contrarily to De Souza Machado et al. (2018), Zhang et al. (2019), found no significant alteration in the bulk density, thus having concluded that microfibers cannot affect this soil characteristic. Similarly, to the bulk density, there were no detectable changes in the soil aggregate size distribution and saturated hydraulic conductivity. De Souza Machado et al. (2018) also found a significant decrease in water stable aggregates, which are often regarded as impoverishment of the soil structure and the diversity of microenvironments. Both research teams found that microplastic occurrence and accumulation in soils lead to considerable structural, physical, and biological damages, resulting in the formation of soil clumps/clods, as shown in Figure 12, reduction of pores volume, thus increasing water repellence, difficulted percolation and consequent decrease in water storage. As stated, the degradation of soil integrity also affects the biological properties, namely the microbial activity, due to the decreased soil microbiota diversity. Nevertheless, it is mandatory that we further study the damages and effects different types, sizes and shape particles may have in the soil physical, chemical, and biological characteristics and properties, since there is still a lot of disagreement and lack of knowledge about MPs behaviour in soils. 21 Figure 12 - Clods of polyester microfibers. Obtained and adapted from Zhang et al. , 2019. 3.2.5.3. Plants With soil degradation there is a mandatory underlying problem, plants. Green plants when exposed to MPs and NPs see their physiological and biochemical processes affected such as seed germination, plant growth, photosynthesis and antioxidative systems, and can suffer genotoxicity (Bosker et al. , 2019; Jiang et al. , 2019; Zhou et al. , 2021), as represented in Figure 13. Ullah et al. (2022), reviewed 250 articles and compiled the impacts MPs can have on plants, from their roots to the leaves. Additionally, they pointed that Chen et al. (2022) highlighted that 44 articles were published about the interaction between MPs/NPs and higher plants until June of 2021. It was found MPs brought negative effects on biometric parameters, phytotoxicity and MPs/NPs accumulation in plant tissues in multiple plants including many day-to-day vegetables and cereals we commonly eat such as wheat, rice, barley, spring onion, onion, carrot, lettuce, cucumber (Ullah et al. , 2022). Several studies have reported multiple negative effects namely growth inhibition under PS exposure and root decline (Maity et al. , 2020), while Lian et al. (2020) found an increase wheat root elongation as well as Zhang et al. (2021), which additionally found a reduction in antioxidants enzyme activity, enhanced plant biomass, carbon, and nitrogen, and nitrates content and decline of some micronutrients. 22 Figure 13 - Graphical summary of the effects of MPs/NPs interaction on the environment. Obtained from Chen et al. , 2022. Furthermore, it was found that root tips are capable of NPs uptake and translocating them along the xylem and it was concluded that roots are more affected by plastic particles due to direct contact and higher accumulation with the MPs. It was also observed a decline in photosynthetic parameters and chlorophyll content in response to PS particles, also the combination of these with di-n-butyl phthalate (DBP) have been reported to cause severe oxidative damage by inducing Malon-di-aldehyde (MDA) and H2O2 content (Gao et al. , 2021). It was also reported high concentrations of H2O2 and O2 in plant roots which were responsible for remarkable increase in glutathione reductase, dehydroascorbate reductase, ADPGlucose pyrophosphorylase, fructokinase, and phosphofructokinase, whereas the activities of cell wall peroxidase, sucrose synthase, vacuolar invertase, phosphoglucoisomerase, and glucose-6-phosphate dehydrogenase suffered a decrease (Chen et al. , 2022). The adsorption capacity of MPs particles allows high concentrations of heavy metals such as AsIII which in this case resulted in an enhancement of PS particles uptake into the cells due to deformation and distortion facilitating the circulation of these particles along the plant to stems and leaves. There are multiple reports of negative impacts not only in plant growth but also seed germination, since these particles end up blocking seed pores and inhibit shoot and root growth by adhering to root hairs and decreasing water uptake (Bhattacharya et al. , 2010; Jiang et al. , 2019; Prata et al. , 2018; Bosker et al. , 2019). Additionally, on a study realized in Ceratopteris pteridoides , PS NPs shown capable of inducing cytotoxicity, genotoxicity, and oxidative damage and reducing spore size and 23 their adhesion to spore surface, prevented germination from 10 to 88% simply by damaging the spores physically (Yuan et al. , 2019). PS beads of different sizes have demonstrated capable to modify the correlations between the microbial metabolism and photosynthetic activity, which in turn has been proven to affect plant growth. Although there is a lot of remarkable literature regarding MPs and NPs effects on plants there is still a huge gap in knowledge, since it is evident that interaction of MPs and phytotoxic effects on plants are diverse and based on MP type, age, size, shape, surface charge, plant growth media, plant species, and its growth stage, moreover most of these studies were conducted under hydroponic settings, while just a few publications were based on pot tests. Therefore, the results are still debatable, and further research is required to understand clearly how MPs/NPs interact/behave with plants to obtain reliable results for various plant species. 3.2.5.4. Aquatic Organisms As mentioned before, lower trophic organisms, specifically invertebrates, can ingest and accumulate microplastic particles, thus, it is likely that microplastics will be introduced to the food web through different pathways, as shown in Figure 14. Hence, it is not out of line to infer that the microplastics are passed all around through different kinds of organisms and environments. As Wright et al. (2013) documented, the occurrence of MPs in myctophid fish and Hooker’s see lion and fur seals scats suggest there is an actual transference of MPs along the food chain and consequent transference of contaminants. Other studies like (Chouchene et al. , 2023) confirmed this in the marine environment as well as the impacts caused in said organisms due to MPs ingestion. Figure 14 - Potential pathways for the transport of microplastics and its biological interactions. Obtained from Wright et al. , 2013 . 24 Chouchene et al. (2023) were able to collect and summarize relevant information about the effects on marine organisms in different trophic levels, from a collection of 512 papers from the period 2013 – 2022, covering different impact “pathways” or “sources” (“pollutant”, “additives”, “metals”, “pharmaceuticals”, “pesticides”, “toxic”, “ingestion”, “plasticizers”, “bioavailable” and “adsorb”) from these ingestion ones were the focus, for further comprehension of the effects it is suggested the reading of their review. Starting with fish it was found that MPs ingestion led to mortality (Yu et al. , 2019), bio accumulation, liver stress and tumour formation (Miloloža et al. , 2020), toxic effects on feeding, fecundity, and survival (Cássio et al. , 2022), impacts on development, disparities among proand antioxidant metabolic activities, deterioration of liver metabolism, generated oxidative stress and caused the deposition of particles in the liver, gills and gut (Kleinteich et al. , 2018), caused damages to the intestines as well as morphological deformations (Vagi et al,. 2021), neurotoxicity in locomotor activity (Cássio et al. , 2022), accumulation of MPs in the stomach and intestines (Galafassi et al. , 2021). In crustaceans the found uptake, accumulation, and immobilization (Rist et al. , 2019; Arp et al. , 2021; Công & Pham., 2021), gut retention (Kokalj et al. , 2022), significant increase in corticosterone levels, and negative effects in survival and the feeding of offspring (Kokalj et al. , 2022). Finally, in molluscs they found malformation development defects (Fonte et al. , 2016), changes in shell length growth rate (Rist et al. , 2019), increase of the respiration rates as well as changes in benthic assemblage (Jakubowska et al. , 2022; Cássio et al. , 2022). The authors further explore the impacts focusing on the pollutants and their direct effects on specific organisms. 3.2.5.5. Vertebrates From another literature review done by Puskic et al. (2020) out of 290 documents, 82 made significant remarks about MPs ingestion from different types of animals and environments around the world. From these, they were able to conclude the presence of negative effects in birds, mammals, and reptiles. It was shown that the MPs can cause the formation of reproductive cysts and delays in chick growth and sexual maturity (Roman et al. , 2019), they also verified the presence of blockage, obstruction, perforation in the birds GI tracts (Roman et al. , 2019b), the plastics – contaminants (namely POPs) interaction (Herzke et al. , 2016), increased trace elements in 2 different species (Lavers et al. , 2016), punctured stomachs (Carey, 2011; Brandão et al. , 2011), alteration of the blood chemistry and negative impacts on morphometric as well as a general deterioration of birds condition (Lavers et al. , 2014). Mammals presented various significant negative effects from plastic particles ingestion such as lesions, suppurative ulcerative dermatitis, perforation of the digestive tract, abscessation, suppurative peritonitis, septicaemia, physical blockage by plastic, reduced mucin, changed microbiome, hepatic stress, and obstruction of the GI tract (Unger et al. , 2017; Lusher et al. , 2015; De Stephanis et al. , 2013; Liang et al. , 2018; Attademo et al. , 2015). 25 From the reptile species it was found that the ingestion of these particles resulted in Obstruction and different pathologies, emaciation, and a consequent reduction in the animals’ conditions (Ryan et al. , 2016; Santos et al. , 2015; Campani et al. , 2013) 3.2.5.6. Humans There are already multiple records and sighting of microand nano plastics throughout our whole body such as placenta (Ragusa et al. , 2021), digestive, reproductive, and nervous systems (Yin et al. , 2021; Hua et al. , 2022) and muscles (S. Wang et al. , 2021), thus, representing a worrying subject of research. The presence of microand nanoplastics in the food chain poses a risk to human health as plastic waste grows. It is remarkable that microand nanoplastics are found in numerous food items due to their widespread bioavailability and ubiquity in both aquatic and terrestrial environments, as we seen they are already established in most environments and are affecting many organisms which serve as food sources. Either through animals which consume other animals or plants, thus becoming contaminated with the plastic particles, or during food production processes and/or leaching/fragmentation of plastic food packaging, the sources of plastic ingestion for humans are countless (Santillo et al. , 2017; Karami et al. , 2017; Mason et al. , 2018). Just as we seen MPs and NPs have been found multiple foods like rice, wheat, lettuce, cucumbers, carrots, onions, spring onions, barley, honey, beer, salt, sugar, fish, shrimps, bivalves, and even tap and bottled water (Yee et al. , 2021; Ullah et al. , 2022). Yee et al. (2021) compiled some articles which studied the presence/occurrence of microplastics particles in tap and bottled water. From this study it was concluded that the average human is consuming around 39,000 to 52,000 MP particles/year, variating with age and gender. If we consider inhalation the numbers rise to 74,000 to 121,000 MP particles/year. Curiously, an individual who only consumes bottled water consumes an extra 90,000 particles in comparison to those who only drink tap water. So, it is more than clear that MPs are all over the place and are strongly embedded in our food chain. There are 3 main paths for MPs and NPs to enter our system: Inhalation, ingestion, and skin contact, just as Yee et al. (2021) represented in the following graphic presentation, Figure 15. GI Exposure As recent studies present, humans mostly consume plastics through ingestion, and whilst there are no studies pointing microand nanoplastic toxicity in humans, there are still research showing their presence in the food and drinks we consume, as previously stated. There are still no studies point the impact these particles have on our GI tract, so its pertinent we further investigate their route, whether they remain in the gut lumen or if they translocate across the gut epithelia, as Yee et al. 2021, stated, it is unlikely that these particles permeate at a paracellular level due to their size. However, it is possible that they enter through 26 lymphatic tissue, and particularly by phagocytosis or endocytosis and further infiltrate the microfold (M) cells in Peyer’s patches. Figure 15 - MPs and NPs entry pathways to the human system. Obtained from Yee et al. , 2021. From a study on mice, it was observed PMMA and PE particles entering the peritoneal macrophages through phagocytosis, however, they only presented an adsorption in intestinal tracts of 0.04 – 0.3%. So, there is a significant probability that MPs can enter, circulate, and remain in our system by permeating the gut epithelium. Like MPs, NPs do not present an actual direct threat independently of their adsorption, size, and structure. Researching the rates of nanoplastic absorption represents a challenge to the lumen of the GI tract. Nanoparticles change after being ingested, which affects absorption capacity and rates. Nanoparticles may interact with a variety of substances in the GI tract, including proteins, lipids, carbohydrates, nucleic acids, ions, and water, leading to the encompassing of these particles by a collection 27 of proteins known as “corona” permeabilizing the nanoparticles translocation, and aggravating their accumulation and deposition. Pulmonary Exposure Inhalation takes the second place in key pathways. Alongside PM2.5 particles, microplastic circulate through air, primarily from synthetic textiles, aerosols, airborne fertilizer particles, industrial emissions, and even particles from dried wastewater treatments. The lungs' alveolar surface area is substantial – about 150m2 – and their tissue barrier is very thin – less than 1μm. Because this barrier is permeable to nanoparticles and allows them to enter the capillary blood stream, they can disseminate freely throughout the whole human system. Knowing they can circulate easily and these particles toxicity, chemical toxicity, and capacity to introduce pathogens and parasites, it is important that we further study this subject. Given these particles size range, they can easily aggregate and deposit deep in the lung and remain on the alveolar surface or even translocate to other parts of the body. Along their size, certain factors as hydrophobicity, surface charge, surface functionalization, and surrounding protein coronas may affect adsorption and expelling of these particles from the lungs. Additionally, from the studies on animals, we can positively correlate occupational exposures with higher rates of pulmonary inflammation and cancer. Synthetic fiber particles constitute as the principal microplastic of atmospheric fallout both in urban and suburban areas of Paris, 29% being of petrochemical origin. Considering the average atmospheric flux of fibers, fiber dimensions and densities, it is estimated that 3 – 10 tons of MPs are deposited every year by atmospheric fallout. Urban areas duplicate this number in relation to suburban, with rainfall as an aggravating factor (Dris et al. , 2016). From a study of Dris et al. (2017) we can observe that indoor environments present a significantly larger number of particles per m3 than outdoor environments, where in this last one, most of the particles found are of natural origin. Dermal Exposure As pointed out before cosmetics constitute one of the main sources of microand nanoplastics, particularly in cleanser and exfoliating products, nanocarriers for drug delivery also present as a very important exposure route, although there is no evidence of direct impacts from this last route, small particle size and stressed skin conditions are critical factors to skin penetration. Our skin is protected by the stratum corneum, the outer layer of epidermis, which forms a barrier against injuries, chemicals, and microbial agents. Even if MPs or NPs contact with our skin through multiple cosmetics or medicines, or plastic contaminated products, it is unlikely that they we will be able to penetrate it or even be absorbed by it, however, plastic particle could see their way in through sweat glands, skin wounds or even hair follicles. In a study published, they found that 20nm – 200nm particles aggregated around the hair follicles of a pig’s skin, nevertheless, there were no records of them being capable of penetrating deeper skin tissue, having concluded that 28 particles with a diameter around 20nm – 200nm can only infiltrate de top skin layers down to a depth of 2 – 3μm. In other studies, a different outcome was verified, the authors observed a deeper reach by the plastic nanoparticles. Knowing that exposure to UV radiation causes skin damage, the use of “invasive” or “destructive” cosmetics and medicines can be weakening the skin even more, since many contain chemicals that permeate the skin barrier such as short chainand long chain-alcohols, cyclic amides, esters, fatty acids, glycols, pyrrolidones, sulphoxides, surfactants and terpenes, that are used to enhance the chemical permeation of drugs and others as urea, glycerol and α–hydroxyl acids, which are very common in body lotions. Nonetheless, it is not all bad news since through the analysis of various compositions of lipid lamellae in stratum corneum samples taken from human and porcine sources, it was presented a three-layer “sandwich model”, which prevent the infiltration of the plastic particles in undamaged tissue. (Jatana et al. , 2016; Lane, 2013; Bouwstra et al. , 2001; Campbell et al. , 2012; Som et al. , 2011; Schneider et al. , 2009; Hernandez et al. , 2017). On the cellular level, it was found that there are several cellular absorption pathways and intracellular localization plastic nanoparticles that depend on their physicochemical characteristics. The interaction of plastic particles with human cells is also influenced by their size. The interaction between nanoparticles and cells is significantly different from that of bigger particles because of their high specific surface areas. Additionally, the particle's charge may have an impact on how it interacts with the cell and its structure. In terms of direct health impacts and toxicity to the human body, there is still little to no information, however in some in vitro studies, many research teams were able to make worrying discoveries, it was stated that both microand nanoplastics can cause serious negative impacts e.g.: physical stress and damage, apoptosis, necrosis, inflammation, oxidative stress, and immune responses, Table 4, in attachments (Yee et al. , 2021). As mentioned along this document, plastics tend to carry contaminants with them, chemical, heavy metals, and even POPs as well as additives used to produce them. Naturally, open to the different weathering agents, these particles are subject to leaching, resulting in increasing probability of a leakage of these chemicals out of the polymer and into the surrounding environment. For instance, polycyclic aromatic hydrocarbons (PAHs) are commonly absorbed by MPs and are known to have great consequences when consumed (K. Sun et al. , 2021). As a result, there is a chance that these chemicals will leak out of the polymer and into the environment. For instance, it has been demonstrated that polycyclic aromatic hydrocarbons (PAHs) are absorbed by microplastics and have a variety of harmful consequences when consumed by diverse animals (K. Sun et al. , 2021). Even though these chemicals are easily degraded by our system, these plastic particles serve as very resistant and durable reservoirs for the constant chemical leaching into tissues and body fluids (Engler, 2012). Some usual additives and chemical present in plastics 29 known to affect human health are bisphenol A (BPA), phthalates, triclosan, bisphenone, organotins and brominated flame retardants (Galloway, 2015). But what are these negative effects that are so worrying? Well, as graphically represented by Yee et al. (2021) in Figure 16, many studies have shown that BPA commonly found in food and drink packing can cause a series of diseases such as obesity, cardiovascular diseases and can act as a hormonal disruptor, imitating or blocking the production, action, and function of hormones in the human body. Additionally, BPA is vastly known for affecting brain development in the womb, causing direct damage to the foetus. Also, the human exposure to phthalate esters, very usual in PVC products, such as butyl benzyl phthalate (BBP) and di-2-ethylhexyl phthalate (DEHP) can significantly increase tumour incidence in human, representing a carcinogenic threat. Figure 16 - Overview of the toxic effects of chemicals leaching from plastics. Obtained from Yee et al. , 2021. Although the effects of microplastics and nanoplastics on the marine environment have received extensive study, we have only lately become aware of the possible routes for human exposure. After exposure, absorption by ingestion or inhalation is conceivable. Thus, is needed further study of this inevitable problem we may be facing. Unfortunately, assessing human exposure to both microand nanoplastic is far from being granted as the lack of scientific knowledge, validated methods, certified reference materials and standardization across the analytical procedures represent a challenge to advancements. 36 4.1.2. Sediment As stated previously, MPs distribution is widely affected by vast range of factors, making it uneven and dependent on their properties and the environmental conditions, thus the results will depend on the specific area where we are sampling (e.g.: high tide line, intertidal regions, and others) as well as depth. Having this into account it is important to choose the right sampling site and instrument. For sediments we have two main sources, inland or in river/seabed. Inland it is very direct and intuitive, we can either follow methods like Schröder et al. (2021), where it is drawn a 50x50cm square on the ground and removed the first 1-2cm to assure more trustworthy results, as the top layer is more affected by dynamics, and we might risk compromising representativeness. Then, it is not only important to remove a good depth of sediment since the 10cm present a higher concentration of MPs compared with deeper layers but also grant a good number of replicates, where Besley et al. (2016), suggest that 11 is the perfect number, having shown a confidence level of 90%. In addition, NOAA recommends the use of 400g/replicate. For this process we can use either a metal shovel or similar instrument, or a forceps device with a defined extraction volume. River and Sea wise, we can either collect with the assistance of a boat or from inland depending on our desired region of the substrate. Either way we can collect the sample with a grab sampler, a box corer or for example a metal bucket tied to a rope. 4.2. Separation 4.2.1. Filtration or Sieving Once we have our samples ready, we need to find a way of obtaining the MPs to further quantify and characterize, for that we need to separate them from the rest of the sample. For this process we have 2 steps: - Reduction of sample volume - Density separation. Both sediments and water samples can and should be passed through sieves. The first ones are ought to be larger and followed by the separation and filtration of the supernatant with the help of filters, whereas the water samples can use a smaller mesh size – 0.45 to 55500μm – and reduce the sample directly in situ through, for example, nets, followed by filtration or sieving. Additionally, for river and ocean samples there are other not so common separation techniques such as magnetic separation and the use of biotic organisms (Nabi et al. , 2022) 37 4.2.2. Density Separation Notably, compared to sediment, which possesses a density within the range of 2.7 g/cm3, microplastics have a significantly smaller density range (0.8-1.6 g/cm3). The fundamental idea behind successful separation is this differential density property. The process consists of carefully combining the sediment with a salt solution. The residual solution is then given time to settle, during which a supernatant containing the microplastics is removed from it. It is crucial to remember that the density of microplastics may be affected by several variables, including the additive concentration, the kind of polymer, and chemicals or organisms adsorbed onto them. This highlights the complex nature of density-based separation, making careful evaluation of these factors necessary. Is important to note that the selection of the salt solution is an essential aspect of microplastics research and should be considered in addition to the previously described approach (Tirkey & Upadhyay, 2021). For this purpose, sodium chloride (NaCl) solution, which has a density of 1.2 g/cm3, has been used in several research since it is both affordable and recommended by reputable organizations like the MSFD Technical Subgroup of Marine Litter and NOAA. It is important to keep in mind that high-density polymers like polyvinyl chloride and polyethylene terephthalate may not be efficiently separated by NaCl because of its comparatively low density (Frias et al. , 2018). On the other hand, NaCl can easily separate lower-density polymers like polypropylene or polyamide (Imhof et al. , 2012). Researchers have looked at the usage of other high-density salts, such as sodium iodide (NaI), which has a density of 1.8 g/cm3, to solve the constraints of NaCl while being more costly (Stock et al. , 2019). This novel two-step density separation method has been developed where the sample is initially fluidized in NaCl solution to reduce the sample size by 80%, and then it is floated in NaI solution, demanding less NaI due to the smaller sample size (Nuelle et al. , 2014). The study conducted by Quinn et al. (2017) revealed that both NaCl (1.2 g/cm³) and NaBr (1.4 g/cm³) exhibited low recovery rates (<90%) and relatively larger error margins. In contrast, NaI (1.6 g/cm³) and ZnBr2 (1.7 g/cm³) demonstrated the ability to effectively separate heavier polymers with impressive recovery rates of 99% and minimal error variations. Notably, the separation process using NaI and ZnBr2 is advantageous as it necessitates only a single washing step for sediment, as opposed to the three required when using NaCl. However, it is essential to consider some caveats. NaI can react with cellulose filters, leading to discoloration, which can complicate visual identification. On the other hand, ZnBr2 is considered hazardous to the environment and is relatively expensive. These issues can be mitigated by adopting sustainable practices, including careful filtration and density adjustment for ZnBr2, rendering it more environmentally friendly and cost-effective. 38 Furthermore, NaI has demonstrated a remarkable ability to recover oleophobic fibers (93.3%) compared to other substances like CaCl2 (69%). When combined with MeOH, NaI can effectively recover the majority of microplastics from marine snow (90-98%). Additionally, following the protocol established by Kedzierski et al. (2017), NaI can be recycled for up to 10 cycles through processes involving rising and evaporation steps. This recycling approach results in costs like those associated with NaCl. Therefore, the utilization of NaI is recommended, primarily due to its environmentally safe attributes and the potential for multiple cycles of recycling, with the caveat that cellulose filters should be avoided in the process. Table 5, in attachments, adapted from Frias et al. (2018), provides a summarized overview of the characteristics of different salts employed in density separation methodologies, aiding in the selection of the most suitable salt solution for specific microplastics research objectives. Tirkey & Upadhyay (2020), also compilated the different advantages and disadvantage of the saline solutions. The Sediment-Microplastic Isolation unit, also known as the MPs isolation unit, is an apparatus consisting of two interconnected tubes with a valve that enables the separation of supernatant and sediment. It is regarded as a dependable method for the safe removal of plastic particles, custom-built to extract microplastics from sediments in a single phase, with an average efficacy of 95.8%. This method employs ZnCl2 solution with a density of 1.5 g/cm³, enabling the removal of plastics across a range of sizes, from large to small particles. It is worth noting that this unit can also be used with other salt-saturated solutions like NaI. It allows sediments to settle while simultaneously facilitating the flotation of dense microplastics. Remarkably, it achieved a 100% recovery rate for large plastic particles, with a slightly lower removal rate of 95.5% for smaller plastics (Imhof et al. , 2012). While this system is efficient and reliable, it is worth noting that it can be relatively expensive to construct, making it a valuable tool for the identification and quantification of plastics in environmental samples. There are other explored methods such as, elutriation which is a separation method that involves injecting a liquid, typically water, into a column to isolate buoyant microplastics from settling organic matter and sediment. Microplastics are then collected in a mesh within the column and subsequently separated using dense solutions like NaI. Elutriation offers cost-effective and efficient microplastic separation from large sediment volumes, enhancing environmental representation and reducing the sample volume for density-based separation. However, this method is time-intensive, taking at least an hour per sample, and necessitates prior sieving by size range. The Munich Plastic Sediment Separator (MPSS) employs a similar approach, using a dense solution of ZnCl2 injected at the column's base, allowing microplastics to ascend and be collected in the supernatant. Nevertheless, this method is more time-consuming, with settling phases taking up to 1-2 hours (Imhof et al. , 2012). 39 Another technique involves the use of oil as a separation method due to the hydrophobic properties of plastics. Various oils like pine oil and canola oil have been tested, but they exhibit recovery rates that vary. Canola oil, for example, has shown a shorter sampling time (~2 hours) and good recovery rates (96.1%), making it more efficient than salt-saturated solutions. Olive oil has been added to such solutions to enhance recovery rates from 64% to 82%. While oil-based methods have some limitations and require a cleaning step, they can be combined with saturated solutions to improve recovery rates, providing an alternative approach in microplastics separation (Prata et al. , 2019) To further complement the background of separation techniques Table 6, in attachments, gives a general framing of the mentioned above and further presents some other uncommon techniques such as JAMSTEC and Heat Assisted density separation (Nabi et al. , 2022). It also includes the digestion of organic matter which will be discussed further. 4.3. Sample Processing Biomaterial can be found in environmental samples. For example, according to Crichton et al. (2017), silt from beaches contains between 0.5 and 7.0% of biological material. Biological material is frequently mistaken for plastics (such as darker algal pieces), which causes environmental concentrations to be overestimated and increases the number of particles undergoing further analysis. In order to properly identify and characterize the microplastic components of the water sample, it is important to perform a preprocessing procedure to get rid of other interfering organic debris. Check Tables 6 and 7, in attachments, for reading aid. They summarize the digestion techniques, the undergone treatment, the recovery rates, and effects both on organic matter and MPs, as well as a supplement for the density separation methods. 4.3.1. Acid Digestion Acid digestion is a method used to degrade organic matter in environmental samples. However, it is important to note that some polymers, like nylon, PET (polyethylene terephthalate), and others, are susceptible to degradation in the presence of acids, particularly at high concentrations and elevated temperatures. Achieving an optimal balance of acid concentration and temperature is crucial for effectively removing biological material within a reasonable timeframe. For instance, Naidoo et al. (2017) demonstrated that heating nitric acid (HNO3, 55%) to 80°C significantly accelerates the digestion of fish tissues, making it 26 times faster. Hydrochloric acid (HCl) appears to be the least effective treatment for dealing with significant amounts of biological material. However, some studies, like that of Karami et al. (2017) have reported digestion efficiency exceeding 95% with HCl (37%) at 25°C, although it led to the melting of PET. 40 Additionally, research by (Desforges et al. , 2014) revealed that treating a sample with HNO3 for one hour resulted in the complete dissolution of zooplankton tissues, while a mixture of HNO3 and HCl led to the fragmentation of zooplankton bodies into smaller pieces. These findings underscore the superiority of HNO3 over HCl for effective acid digestion in microplastic analysis experiments, given its ability to dissolve biogenic compounds and maintain sample integrity. It is also known that HNO3 can leave oily residues, tissue debris, cause the loss of nylon, and melting of various plastic types, including PS, LDPE, PET, HDPE, PVC, and others. Resistance to digestion varies among polymers and depends on factors such as the presence of organic matter in the sample, which can mitigate the degradation of polymers, and the temperature of the solution. Given these complexities, the use of acid digestion should be approached with caution in microplastics research, as it may lead to the underestimation of microplastics in environmental samples due to potential alterations and degradation of plastic materials. 4.3.2. Alkali Digestion The utilization of alkali digestion as an alternative to acid digestion in microplastic analysis holds substantial promise. However, it is essential to acknowledge that alkali digestion may introduce certain challenges. Alkali digestion has been observed to potentially damage or discolour plastics, leave oily residues, and cause the redeposition of tissue residues on plastic surfaces. These effects can complicate the subsequent characterization of plastics using vibrational spectroscopy. KOH (potassium hydroxide) has emerged as a particularly effective alkali for digesting organic matter and recovering plastics. Protocols employing KOH and NaOH (sodium hydroxide), such as a 10% KOH solution at 60°C overnight or a 60°C treatment for 24 hours, have proven to be among the most effective digestive treatments (Maes et al. , 2017; Dehaut et al. , 2016; Cole et al. , 2014). However, it is important to note that both KOH and NaOH may lead to discoloration or degradation of various plastic types, including nylon, PE, uPVC, polyester, PC, PET, and PVC (Dehaut et al. , 2016). In terms of digestion efficiency, certain hard parts, and fats, such as fish otoliths, squid beaks, paraffin, and palm fat, have been found to withstand the digestion process when exposed to KOH (1 M) for 2 days at room temperature. A noteworthy approach involves the sequential use of both acid and alkali digestion, such as a combination of NaOH and HNO3, which has demonstrated good digestion of biologic material and recovery rates. This method allows for comprehensive digestion while addressing the potential limitations associated with each technique. Overall, the choice between alkali and acid digestion methods should be carefully considered to ensure accurate microplastic analysis while considering the specific 41 characteristics and potential effects on plastic materials and organic matter (Prata et al. , 2019; Nabi et al. , 2022). 4.3.3. Oxidizing Agents In comparison to NaOH and HCl, hydrogen peroxide (H2O2), which is normally present in concentrations of 30–35%, is a potent oxidizing agent that may be used to break down organic waste. Notably, it often has little to no negative effects on the integrity of polymers. Numerous plastic polymers, including PVC, PET, nylon, ABS, PC, PUR, PP, LDPE, LLDPE, and HDPE, exhibit resistance to H2O2 treatment (Nuelle et al. , 2014). The polymers normally remain intact, notwithstanding the possibility of some mild discoloration. It is important to note, nevertheless, that Karami et al. (2017), found that nylon degraded, and PET changed colour after being treated with H2O2 (35%) at 50°C for 96 hours. The efficiency of H2O2 digestion is strongly influenced by the incubation temperature, Cole et al. (2014) proves it by discovering that a seven-day incubation at ambient temperature with H2O2 (35%) only resulted in a 25% breakdown of organic materials. On the other hand, employing H2O2 (15%) at 50°C overnight, found effective organic matter removal (Avio et al. , 2015). In addition, efforts have been made to mitigate the impact of H2O2 on the characteristic properties of microplastic contents in samples, Zhao et al. (2017), pointed out that a 15% concentration of H2O2 is preferred to a 20% concentration, and both treatments are more effective than HCl. Also, it is recommend using a reduced concentration of 10% H2O2 with an exposure time of 18 hours to effectively remove organic materials while maintaining the integrity of microplastics, H2O2 treatments have demonstrated potential. NOOA recommends the use of H2O2 (30%) with Fe(II) solution (0.05 M)(sulphate (Fenton's reagent) heated at 75ºC to glass beaker containing the microplastics fraction for both water and sediment samples. This technique offers a trustworthy way for analysing microplastics, especially when working with intricate organic materials (Frias et al. , 2018). 4.3.4. Enzymatic Digestion Enzymatic digestion has emerged as an alternative method for microplastic analysis. Since they do not distort or degrade the plastic polymers, unlike chemical digestion, enzymes have been used in many studies to degrade or hydrolyse biological tissues. However, enzymatic digestion is also a time-consuming process, and each enzyme operates at its optimal pH and temperature condition, which must be monitored and maintained throughout the experiment. Enzyme efficiency, however, depends on the type of organic material present in the sample (Maes et al. , 2017; Courtene‐Jones et al. , 2017). 42 Enzyme protocols vary and may include pre-digestion of sediments with an industrial enzyme blend, followed by the removal of debris using H2O2. For fish tissues, proteinase K has been used, followed by treatment with calcium chloride and subsequent hydrogen peroxide treatment. While these methods yield high recovery rates, calcium deposition on particles may complicate further characterization (Karlsson et al. , 2017). Other enzymes like Tripsin, Collagenase, and Papain have been tested, with digestion efficiencies ranging from 72% to 88% and no observed effects on polymers (Courtene‐Jones et al. , 2017). A more comprehensive enzymatic purification protocol has been proposed, achieving 98.3% efficiency through a multi-step process involving enzymes and hydrogen peroxide treatments over 13 days. Despite their effectiveness, enzyme use is limited by cost considerations. Industrial Corolase 7089, presented as a more cost-effective enzyme, has shown promise in microplastic sampling, outperforming chemical treatments in some cases. However, enzyme-based protocols may require additional treatment with hydrogen peroxide to remove undigested debris. Enzymatic digestion remains a valuable approach in microplastic analysis, especially when handling complex samples, but its widespread use may be constrained by cost factors (Prata et al. , 2019). 4.4. Identification and Characterization There is not a perfect method for MP for chemical analysis of MPs. However, the combination of some or the aim of the study can lead to the choice of the ideal method(s). The most common method is visual identification as most of the times is enough to identify and determine the presence and certain characteristics of MPs, such as type, colour, size, and shape. Nevertheless, it is chemical characterization is advised when we intend to identify its composition, adsorbed elements, and other properties. Some of the most common techniques are FTIR and Raman Spectroscopy, followed by SEM/EDS, and Py-GC/MS, each of them with a particular purpose: determination of chemical composition of sample particles; identify MPs morphology and detect their surface characteristics; identify the compound types of MPs as well as measure absorbed organic compounds, respectively (Wang et al. , 2022). Given the deep analysis on visual identification and characterization methods conducted in the sections 3.2 and 3.3 of this work, it will not be explored in this one. However, in case of doubts or seek of better comprehension, the reading of Prata et al. (2019) and Tirkey & Upadhyay. (2021) reviews are recommended. Huang et al. (2022) also summarizes the typical methods for analysis and highlights advantages and limitations. 4.5. Cross – Contamination 43 As we have seen, along this process we can easy influence the results by small action and given the widespread contamination of the environment with microplastics, including air, it is crucial to implement measures during sampling to minimize the introduction of these particles and fibers. To reduce crosscontamination of microplastic samples, the following five rules are recommended: - Use glass and metal equipment instead of plastics, which can introduce contamination. - Avoid the use of synthetic textiles during sampling or sample handling and prefer 100% cotton lab coats. - Clean surfaces with 70% ethanol and paper towels, wash equipment with acid followed by ultrapure water, use consumables directly from their packaging, and filter all working solutions. - Utilize open petri dishes, procedural blanks, and replicates to control for airborne contamination. - Keep samples covered as much as possible and handle them in clean rooms with controlled air circulation, limited access (e.g., doors and windows closed), and restricted circulation. Preferably, work within a fume hood or an algae-culturing unit, or cover equipment during handling. Implementing these measures can significantly reduce the risk of contamination during microplastic sampling and analysis. For instance, the use of a fume hood alone can reduce contamination by up to 50%, while covering samples during filtration, digestion, and visual identification can reduce contamination by more than 90%. These precautions are essential for ensuring the accuracy and reliability of microplastic research (Prata et al. , 2019). 4.6. The Implications of Fluvial Dynamics Marine environments are greatly affected by plastic pollution, and thus by MPs, having been widely studied and documented all around the world. Freshwaters however have not had the same level of attention. In this section it will be documented and discussed the matter of freshwater MPs pollution, paying special attention to the methods presented in the previous sections. Posteriorly, a deeper analysis of two articles published by Eo et al. (2018) and Schell et al. (2021) was made, since they fit the best with my thesis theme and purpose. Rivers have a major role in particle transportation to the oceans, and it has been noted that the further we move away from the river mouths the less microplastic debris we find (Lechner et al. , 2014; Lebreton et al. , 2017; Lee et al. , 2013; Eo et al. , 2018). We also know that MPs vary a lot both vertically and horizontally in the beach profiles, and it becomes even clearer once we put seasons into account. (Erkes-Medrano et al. , 2015) However, river wise we do not have clear answers, since the research on spatiotemporal distribution of abundance, size, and polymer composition as well as fluxes of riverine MPs has only been studied by Eerkes-Medrano et al. (2015) and Rochman, (2018), until 2019. 44 There are already multiple records of MPs in freshwater systems worldwide, in Asia, Zhao et al. , 2022 – reviewed and documented multiple freshwater studies in China until 2022, Europe, North America, South America, Oceania and Africa (Eo et al. , 2018; Li et al. , 2020; Li et al. , 2018; Z. Wang et al. , 2021; Erkes et al. , 2015). However, just as Eo et al. (2018) pointed out, it is important to note that most studies only sampled once or twice during the wet and dry seasons, hence there is still a major gap in knowledge regarding seasonal effects on the occurrence and distribution of MPs. Although, there is a considerable number of studies, these reflected mostly of the top and mid layers of the water collum, lacking information on the transport of MP particles in deeper layers including the sediment which plays a big role in material transport (Morritt et al. , 2014). Lima et al. (2014) pointed out that the abundance differences between bottom and top layers are negligible as the results of their study shown no major discrepancies, however, Mani et al. (2015) documented not having found a single particle at a 5m depth spot in Rhine River whereas in NW England, Hurley at al., found that a flooding event brought up 70% of the total MPs stored in the river bed, showing that the sediment serves as a reservoir for these particles (Kapp & Yeatman, 2018). More researching is needed to confirm the role played by both the sediment and seasonal effects on MP abundance, as it is noticeable that climatic, environmental, and physical characteristics widely affect the retention and resuspension of the particles. A study by Lebreton et al. (2017), shown trough a modelling study, in Asia, that there is a potentially astronomic daily input of plastic to oceans from rivers – 1.15 to 2.41 million macroand microplastic particles – nevertheless, the lack of information about the effects previously mentioned brings a great uncertainty referring to particle numbers. As highlighted initially, some authors have made reviews about the study of MPs in freshwater environments and to summarize them, here follow some of the conclusions: Most studies were conducted in rivers, some having been based on samples collected from lakes, WWTPs and tap water. Geographically most sample sites had urbanizations near them. As of today, most freshwater studies preferred a two-method sampling, a large flow collection with buckets, pumps and glass bottles and collection with biological nets with different apertures, where the most common ones were, by order, manta (330μm mesh size), neuston and plankton nets (Eo et al. , 2018; Z. Wang et al. , 2021). In general, surface water was more sampled than sediment, assuring a sample depth between 0.1 – 1m. A lot of studies preferred not to do digestion or purification, due to low presence/abundance of OM, but the preferred method was 30% H2O2, followed by 30% H202 + Fe, Enzyme + H2O2 and HCL treatment. 45 For the density separation, NaCl was the preferred solution for water samples, whereas ZnCl2 and lithium metatungstate were the preferred ones for sediment. Other options adopted include sodium polytungstate (SPT), CaCl2 and NaI solutions. Concluded the separation by densities, the supernatant was retrieved and filtered, most used glass filters of 0.45, 0.7, 1.6μm glass filters and others opted for 1.2μm cellulose and, 5μm and 100μm polycarbonate filters. Some other studies preferred to run the samples through metal sieves. Posteriorly, for the identification and characterization of MPs the most adopted method was visual inspection with the aid of microscopes and cameras, followed by FTIR, Raman, SEM/EDS, and the combination between them. Finally, from the studies it were identified abundancies of 0.1 – 53,250 particles/m3 (Zhao et al. , 2022); 817 particles – 44,435 particles/km2 (Erkes-Medrano et al. , 2015); 0.00297 g/L – 2.5803 g/L and 2.5 particles/m3 – 3.5*10^8 particles/m3 (Li et al. , 2020); 0.19 particles/m3 – 5.66*10^5 particles/m3 and 4.44*10^4 – 1.39*10^7 particles/km2 (Li et al. , 2018); 0.1 – 3,622,00 particles/m3 (Z. Wang et al. , 2021). In addition, the most common compounds found were PE (including, PP, PS, PA, PET,PU, and PVC present in (n = articles): n = 45, 45, 34, 16, 19, 4, and 11, respectively (Z. Wang et al. , 2021) and PE, PP, PS, PET, PA, PU, and PVC present in: n = 44, 50, 28, 21, 13, 3, and 11, respectively (Zhao et al. , 2022). Li et al. (2020), represented the results graphically in a 100 scale, following: PE = 24%, PP = 24%, PS = 13%, PET = 11%, PA = 6%, PVC = 1%, PU = 1%, Other = 20%. The main purpose of this work is to describe the spatial distribution of microplastics and how does fluvial dynamics affect they occurrence and transport them. Regarding this theme 2 studies were found regarding freshwater systems: Eo et al. (2018) and Schell et al. (2021). In Table 9, in attachments, are the summary made about both articles focusing on the sampling site, sampling methods, methods used for filtering/sieving and chemical characterization, particle abundance, size and type, as well as chemical compounds constituting the MPs. The studies were conducted in South Korea (Eo et al. , 2018) and Spain (Schell et al. , 2021), both were conducted in rivers, the first on was Nakdong River and the second on Tagus River. Every chosen sample site was affected by Urban areas (UAs), Agricultural sites (Agro) and Wastewater Treatment Plants (WWTPs). Eo et al. , collected Upstream (US), Midstream (MS) and Downstream (DS). For US and MS, the samples were collected, 3m away from the shoreline, two from the western riverbank and only one from the eastern one. DS samples were collected at three stations along the axis of the river separated by 0.5m. The top layer (20cm of the water surface + surface microlayer) was 52 agricultural regions and less industrial development in the upstream portion of the Cávado River basin (Oliveira et al. , 2021; Vieira et al. , 1998). The watershed's centre has a larger population density and more industrial activity, particularly textile, around Braga and Barcelos municipalities, which are the highest populated. It is worth noting that there are two industrial parks in Braga, relatively near the Cávado River. There are also two WWTPs, Vila Verde (Cávado-Homem WWTP and Braga (Frossos WWTP). Although all 6 municipalities are equipped with WTPs and WWTPs, the WWTP of Amares has been deactivated since 2015 due to the incapacity of the regional requirements and associated discharges to Cávado River, naturally, the deactivation of the WWTP resulted in an impact in river’s water quality. Figure 19 - (a) Hypsometry and (b) Land occupation in the Cávado River's area. Thus, Amares and Braga WWTPs effluents are responsible for most of the wastewater inputs, whereas Barcelos is responsible for most of the untreated domestic and industrial discharges (Oliveira et al. , 2021; Vieira et al. , 1998). To facilitate the methodology and system modelling, this work considered the begging of the river study area downstream of the Caniçada dam (right after Porto Bridge) and the end near the river mouth, in Cávado River’s estuary. As represented in Figure 20. The climate in all sites is temperate, with dry and comfortable summers and cold, wet, and partly cloudy winters. The “summer” season occurs between June and September with an average high temperature of 26ºC and the cold season occurs between November and March with an average high temperature below 15ºC; all info available in (WeatherSpark, 2023). The sampling sites have approximately the same climatic conditions. In this work all samples were collected from the riverbed sediment, from 14 points along the Cávado River as represented in Figures 20 and Map 1, last one is in Attachments and has the situational framing of each sampling site. The sampling sites were in 5 out of 6 ICM municipalities: 53 Figure 20 - Sampling sites with satellite framing. Retrieved from Google Earth, 2023 Figures 21, 22 and 23 depict the general method for sampling, storing of the respective and resulting trail of the sampling. Photos of each sampling site are available in the Attachments with the sampling site name, designated study ID, and coordinates. MP002 – Praia de Navarra, Braga (41°36'48.38"N, 8°23'5.76"W). Figure 21 - Sampling in MP002 with the stainless-steel bucket. 54 Figure 22 - Storing of the sample inside aluminium lunch boxes. Figure 203 - Trail resulting from the sampling. 55 5.2. Methods Sampling was carried out on May 26th, 2023, with near optimal weather conditions, maximum temperature of 21°C, light winds and little to no precipitation (WeatherSpark, 2023). Sampling started from Amares to Esposende. The first sample (MP001) was collected on Ombra fluvial beach at 09:46, followed by: MP002, on Navarra fluvial beach at 10:15; MP003, on Autocarro Bar fluvial beach at 10:37; MP004 and MP004B, near Mirante bar fluvial beach at 10:53; MP005, on the backwater area near Codracheira at 11:25; MP006, on a floating craft to the east of Areias de Vilar WTP at 11:57; MP007, on Manhente fluvial beach at 12:30; MP008, on the floating craft north of Barcelinhos fluvial beach, at 12:56; MP009, on the Mariz picnic area at 14:55; MP010, on the Perelhal parking to the north of Areal da Agra fluvial beach, at 15:13; MP011, on the meander near the Cávado greenway, at 17:13; MP012, MP012B and MP012C, on the fluvial beach near Fão’s Sailing Club, at 15:40; MP013, on the estuarine “beach” near the ElementFish Kite & Surf Camp, at 15:57; MP014, around the middle of the riprap of Esposendes’ Beach, at 16:22. Sampling was carried out based on the model mentioned by Rocha-Santos & Duarte (2017), with slight adaptations to the methodology used by (Besley et al. , 2016; Eo et al. , 2018 and Schell et al. , 2021). To collect the samples, it was used a personalized metallic bucket with a black rope attached to it (Figure 24). The sampler was launched around 3-5m into the water, in the attempt to reach the 1m depth waters, the sampler was then dragged slowly along the sediment, removing around the top 10cm layer of substrate. Following Carson et al. (2011), samples MP012B, MP012C, and MP013, which were collected by directly rather than by launching, as they were located inland, consisted in retrieving the first 5 to 6cm of sediment, 56 as most MPs are in the first layers of sand. The samples were then stored in ~1L aluminium lunch boxes with dense paper tops and taken to the lab. Figure 24 - Sampler: a stainless-steel bucket ~ (15cm diameter x 30cm height). Already on campus, all the samples were stored inside the laboratory oven at 45ºC for 4 days and left to dry (Figure 25). On the 1st of June, samples were still wet, so they were left there until the 9th to assure that they were all dried. Organic matter digestion was not conducted due to lack of material to do so. Figure 25 - Samples stored and let drying in the laboratory oven. Meanwhile, the density separation CaCl2 solutions were prepared. The solution consists of adding CaCl2 and CaCl2 * 2 H2O (in the absence of CaCl2) to distilled water at 20°C while stirring with a glass rod. Since we still had a lot of untouched solution left from previous research, it was only necessary to dilute the 57 precipitate (Figure 26). Afterwards, the CaCl2 solution had to be filtered with paper filters and poured into Erlenmeyer’s flasks, due to the presence of a lot of impurities (Figure 27). Figure 26 – Dilution of the precipitated CaCl2 solution. Figure 27 - Filtering of the CaCl2 solution. 58 After drying, the sediment samples were prepared with the aid of a small metal shovel and a metal spoon spatula. About 500g of sample, as shown in Figure 28 was separated, and stored in a ceramic bowl (tare weight), to avoid samples contamination. The process was repeated to every sample (Figure 29). Figure 28 - Weighting 500g of sample. Figure 29 - Repeated the process for each sample. Additionally, following the methods documented and explained by Alakangas (2015), an extra 100g of each sample was collected through quartering, to assure statistical representation. 59 With the sediment samples properly stored and with CaCl2 solutions filtered, density separation followed. In aid of the process of identification and counting of microplastics, a pre-treatment of the samples must be carried out mandatorily, by separation of densities. In this case, as previously stated, it was used a saline solution of CaCl2 with a density >1.4g/cm3 (figure 30). Figure 30 – Saline solution with density >1.4g/cm3 Subsequently, the samples were added to the solutions at a ratio of ½:1, that is, 500g of sample to 1000mL of solution. Following the same model as (Schröder et al. , 2021): (1) stirred during and after sample addition; (2) the flasks were rotated 4 times, every 10 minutes and left to settle (Figure 31) (3) the sample 60 was allowed to settle for 15 – 18 hours, before visual identification under the optical microscope (Figure 32), allowing the microplastics from accumulating on the surface. Figure 31 - Stirred solutions left to settle. Figure 32 - Settled solutions with the supernatant separated. After the 18 hours, suspended particles were removed with a metal spoon spatula and a micropipette (Figure 33 and 34a), to avoid contaminating the sample. It was collected about 500μL of sample and then transferred to Petri dishes and marked with about 300μL of Nile Red to better highlight the MPs (Figure 34b). Sample preparation for visual inspection consisted of collecting 50μL, preparing a blade and proceed with the visualisation. This process was repeated 3 times for each sample. Visual identification was then performed with a Nikon ECLIPSE E400 POL optical microscope (Figure 35a) and a Leica MZ12.5 Stereo Microscope (Figure 35b), with x5, x10, x25 zoom lenses. Visual identification allowed a general 61 count of microplastics, by default, identifying microplastics with a size of less than 1 mm (small microplastics), microplastics with a size between 1 – 5 mm (large microplastics) and some macroplastics. Figure 33 - Micropipette used for collection. b) a) Figure 34 – (a) Spoon spatula used for collection and (b) Nile Red marker. 68 (1) A Square value of 0.72478 is relatively high, suggesting that the model accounts for a significant proportion of the variability in the dependent variable. (2) A CV of 0.26476 suggests that the relative variation in data (standard deviation as a proportion of the mean) is relatively small, thus, there is less relative variability around the mean. (3) A Root MSE value of 2.99018 suggests that, on average, the model's predictions are approximately 2.99018 units away from the actual data points. Given the error sources and the dimensions of both the samples and system in study, the value is considered relatively small, indicating being a good fit. While ANOVA establishes that there are significant differences, it does not clarify the direction of those differences. Further analysis, such as post-hoc tests, will help identify which specific groups or conditions differ from each other. Since the one-way ANOVA has been proven statistically significant, a follow up post-hoc test was conducted (e.g., Tukey's HSD or Bonferroni) to identify which specific sites differ from each other. In this situation, there are 17 sampling sites, and it is needed multiple pairwise comparisons to identify which sites have significantly different means, both Tukey's HSD and the Bonferroni correction are suitable options to solve this problem, but since it is sought to find a good balance between controlling Type I errors and having reasonable power to detect true differences, Tukey’s HSD was chosen. Adjusting the alpha level for multiple comparisons to control the familywise error rate, especially when conducting posthoc tests, is very important. For tests such as Tukey’s HSD, it should align with the desired balance between controlling Type I errors (false positives) and having adequate power to detect true differences. In this logic, an α Level of 0.05 (5%) was chosen. It was possible to conclude that there are 13 pairs which present significance levels equal to 1 suggesting that there are significant differences between the means of the sampling sites being compared. However, in all 13 pairs, it was verified that the “q”-value, also known as adjusted p-value, was higher than 0.05, meaning that after adjusting for multiple comparisons, the statistical significance will become less clear. In other words, while there are apparent significant differences between the means in the individual comparisons, these differences are less clear when considering the risk of making false discoveries due to multiple comparisons. Beyond statistical significance, it is crucial to assess whether the observed differences are practically meaningful for the research. Since this study intends to comprehend whether there is an influence from the fluvial dynamics and not exactly what are they and where they occur, a q-value > 0.05 is not so meaningful. Although, the statistical analysis reveals significant differences in microplastic abundance among different sampling sites and thus can be concluded that there are statistically significant variations in microplastic levels between these sites, it should be considered that there are more affecting factors that 69 should be taken into account, however, in this study specifically they do not matter from a practical standpoint. From the data analysis it is possible to comprehend that certain sampling sites are more susceptible to microplastic accumulation and that even the land use practices may have a certain impact on the behaviour of MPs in the environment. Also, as literature shows, the existence of multiple textile industries, high levels of urbanization, river beaches, (W)WTPs and other industries near the river before sampling sites like MP009 may justify its higher number of particles (Eo et al. , 2018; Schell et al. , 2021). 6.3. Granulometry Cumulative frequencies are all displayed in a range of (0.01 – 100). As we can see, the samples present relatively the same curve behaviour, which indicates a certain homogeneity in the constitution and characteristics of the sediment (Figure 40). The average values of grain size do not show anomalies, MP008 was shown to have the highest mean grain size followed by MP004B, MP004 and MP003. MP013 had the lowest mean with a value of 0.73. Most of the standard deviations are negative, except for MP005 and MP006 (Table 11). Given the negative nature of most of the standard deviations we can conclude that the data points for grain size are primarily clustered around the mean and show limited variability or dispersion. Figure 40 - Granulometric curves with the cumulative percentages. X axis represents particle sizes in mm and Y value presents the phi values. 70 As we can see in Figure 40 and as previously mentioned, the samples present relatively similar behaviours. According to the terminology established by (Folk, 1954), samples MP002, MP010, MP012, MP012B and MP014 are classified as “Gravelly sand”, MP001, MP003, MP004B, MP007, MP009 and MP012C as “Sandy gravel”, MP005, MP006, MP011 and MP013 as “Slightly gravelly muddy sand”, and MP004 and MP008 as “Gravel”. From the conducted Pearson’s Test, it was inferable that there is a positive correlation between all the variables (Pearson Correlation Coefficient [r] = 1), however, due to the limitations such as lack of data and small number of samples, it is not possible to reject the null hypothesis, thus there is not sufficient evidence to conclude a statistically significant linear correlation between the variables. Kruskal-Wallis ANOVA (Prob>Chi-Square = 0.45) and Dunn’s tests resulted in a p-value > 0.05, proving no significant differences between the populations, meaning that based on these tests we cannot effectively conclude that sediment grain size has a statistically significant effect on microplastic abundance and retention. 6.4. Correlations: sources and affecting factors As we can observe from the results, particle amount increases from upstream to downstream, being affected by some ecological and environmental factors. MP0012B, 009, 005 and 003 shown the highest particle count. As we can see in Map 2b, MP003 sampling site is highlighted as a highly human-altered area, with heavy daily human presence during the warmer seasons, it is also near a road which contributes with a lot of tyre fragments, it also contains a great number of urbanizations around it and it is right after a WTP, all these factors may justify its high count (Schell et al. , 2021). Although MP005 does not have as much emission sources as 003, the sample was collected in an area right after an isolated urbanization containing multiple types of industries, including textile, painting, and others. It is also a backwater region, “mangrove” like, with lower water levels, higher amounts of organic matter and finer sediment grain, which promotes a higher accumulation of the MPs (De Souza Machado et al. , 2017) MP009 in Map 2g appears right after a region full of emissions sources from the industry complex, with multiple textile industries, and the Barcelos’ WWTP, this alone may be enough to justify the high count of MPs. 71 MP012B was one of the samples collected in Fão’s region, in the wrack line, where we usually find the greatest number of particles, specifically on the top 10cm of sediment, Map 2j. The dissipative behaviour in this region plus the previous point, can very well explain the particle count in this area. It is also important to note that we have a lot of urbanization, roads, agricultural fields and a WWTP near this site. (Schröder et al. , 2021). Additionally, the 3.º Cycle (2022-2027): PGRH Project (Hydrographic Region Management Plans) of Cávado, Ave and Leça (RH2), which is a open project being conducted, already shows multiple pressure points along the Cávado River such as water collection points for urban and agricultural water supply, water collection points for human consumption, hydroelectric stations, large riverside agricultural fields as well as manufacturing industries close to the river. For example, MP005 has two manufacturing industries (Pressure ID: QUAN_CAPTACOES_000076179 and QUAN_CAPTACOES_000072438, respectively) relatively close to it, with discharge volumes of 1,600000 and 0,085800 hm3, which might play a role in the MPs count. The lower microplastic counts need to be deeply look at since the methodology still has room for improvement. Apart from MP014 which is located very close to the river mouth with deeper waters, higher energy levels and deeper sediment, making the accumulation of MPs harder. Statistical tests regarding the interaction of sediment grain size, distance to pollution and microplastics abundance, show that there is a possible positive correlation, however from these preliminary results we cannot firmly affirm that there is a linear correlation. Given the lack of information about pollution sources, current velocity, discharge volumes, and the inclusion of other factors such as runoff and direct input of litter, it is not feasible to label these results as conclusive. Additionally, from the Kruskal-Wallis’ test, it was shown that we cannot affirm the existence of a direct comparison between sediment grain size and microplastics abundance. Nevertheless, given the small number of samples, and sampling sites along the river, as well as further detailed inspection of the sediment, is not correct to affirm that there is not a direct connection between these two variables, as literature as shown that there is a certain trend for higher retention of MPs in finer grained sediment and surfaced layers (Marques Mendes et al ., 2021). 72 7. Conclusion and Future Perspectives In conclusion, we can clearly notice an increasing tendency of MP count downstream which may be directly related with the increase of pollution sources. From the statistical analysis it was concluded that the samples presented similar behaviours, and that the river dynamics do in fact affect the transport and prevalence of MPs. MP012B, MP009, MP005 and MP003 present the higher values, probably due to all the existing pollution factors near them such as WWTPs, agricultural fields, highly concentrated urbanizations, industrial complexes, and other riverine pressure factors. The MP014 low count of microplastics could be justified thanks to the high hydrodynamic scenario and characteristics of this region, namely the depth and length of the stream, estuarine characteristics, and the interaction with both fluvial and ocean dynamics. MP001 and 002 as they presented some abnormality when submitted to stricter tests, for example when we lower the α-level or the Bonferroni test in the ANOVA model, which were not considered do to their increase of the risk of Type II errors (false negative). Additionally, since the digestion of organic matter was not done and the samples were not filtered or sieved, there might have been identification errors during the visual inspection. During the whole process, efforts were made to reduce cross-contamination, however, there are always sources like atmospheric particles, fibers from clothes and pre-existing particles in the aluminium lunch boxes and remaining materials used, that might have altered the results. In this line of thought, the laboratorial procedure should be redone, making sure to reduce all the remaining contamination factors as much as possible. It was also found that collecting more samples and improving the density separation method can generate better quality results. Following the NOAA recommendation, digestion treatment, sieving and/or filtering of the samples should also be done, to reduce the misidentification of MPs. To further complete the work/study, chemical analysis should also be conducted through FTIR and/or Raman spectroscopy to identify the compounds present in the samples, measurement and identification of sample size, type and shape are also important to document as they might help identifying potential pollution sources. An additional interesting addition to the work, would be conducting SEM analysis, to identify if there are heavy metals present in the microplastics. Regarding the sampling, methods should be further explored and developed, such as reducing cross-contamination risks, use smaller portions of samples, increase the number of sampling sites and samples, for example, a 5-point sampling model across the river (1 sample on each margin, 1 on each intermedial zone and 1 on the central axis of the river), identify every possible pollution source of MPs, conduct a study about the discharge volume from each WWTP and WTP, sludge production and use, measurement of biotic and abiotic factors, evaluate water parameters as well as a more comprehensive evaluation of organic matter abundance, overall characteristics and conditions of the sampling sites. With this study, my objective has been fulfilled as it was to further comprehend the behaviour and develop the knowledge of these particles in the fluvial environment, particularly in the Cávado River, which 73 has never been studied in this sense. 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DOI: 10.1016/j.marenvres.2017.07.009 V 100 MP005 – Codracheira, Barcelos (41°33'58.69"N, 8°30'34.26"W) 101 MP006 – Areias de Vilar, Barcelos (41°32'47.32"N, 8°33'4.26"W) 102 MP007 – Manhente, Barcelos (41°32'16.53"N, 8°34'43.71"W) 103 MP008 – North Riverside of Praia de Barcelinhos, Barcelos (41°31'42.15"N, 8°37'5.70"W) 104 MP009 – Parque de Merendas de Mariz, Barcelos (41°31'23.48"N, 8°40'14.66"W) 105 MP010 – Perelhal, Barcelos (41°31'18.88"N, 8°41'16.43"W) 106 MP011 – Ecovia do Cávado, Barcelos (41°30'58.86"N, 8°44'35.38"W) 107 MP012, MP012B & MP012C – Clube Náutico de Fão Beach, Esposende (41°30'53.27"N, 8°46'27.31"W) 108 MP013 – Restinga de Ofir, Esposende (41°31'29.45"N, 8°47'16.00"W) 109 MP014 – Esposende’s Beach Rip-Rap – Esposende (41°32'27.09"N, 8°47'25.12"W) 116 Table 6 - Advantages and limitations of MPs separation methods. Retrieved from Nabi et al. , 2022. 117 Table 7 - Multiple Digestion methods for organic matter removal, highlighting particle and OM degradation. Retrieved from Prata et al. , 2019. 118 Table 8 - Various advantages and disadvantages of sample preparation methods. Retrieved from Stock et al. , 2019. 119 Country Location Sample SMethod Digestion Methods Density Abundace South Korea Nakdong River Water surface (20cm); Mid area (1m) and Sediment Stainless steel beaker; Submersible pump, 20μm mesh net and 1L amber glass bottle Van Veen grab, Stainless steel spon and 1L amber glass bottle 20 mL 35% H2O2 + Fe (II) solution (75º C, 180 rpm) 30 min 20μm sieve + drying 60º FTIR LMT n1 = 293 - 4760 particles/m3 n2 = 1971 particles/kg; 37311 particle/m2 (top 2cm) Spain Tagus River Water surface, Sediment, Raw and Processed Sludge, Untreated influent and Treated effluent WWTPs = Nylon nets (55, 150, 300 μm) and glass flasks; River water = Submersible pump and nets Core sampler and glass flasks Fenton's reagent Vaccum filtered (paper filters); 38 μm stainless steel sieve Visual inpection >300μm = ATR - FTIR 55 - 300μm = μFTIR NaI n1 = 1.30 - 147 particles/m3; 0.54 - 14.6 mg/m3 n2 = 0 - 2910 particles/kg; 0 - 44.3 mg/kg UWW = 850 - 11,550 particles/m3; 1.86 - 194 mg/m3 TWW = 45 - 535 particles/m3; 0.28 - 48.5 mg/m3 PSLG = 2432 - 24,828 particles/kg; 5.05 - 1525 mg/kg RSLG = 7161 - 66,260 particles/kg; 12.7 - 553 mg/kg Table 9 – Methodology and Results summary of Eo et al. and Schell et al. studies. UA’s = Urban Areas or Urbanizations, Agro = Agricultural fields. 120 Country Location Type ChemComp Size UAs Agro WWTPs South Korea Nakdong River n1 = Fragments 69%, Fibers 30%, and Spheres and films <1% n2 = Fragments 84%, Fibers 15%, and Spheres 1% n = 7466 n1 = 41.8% PP, 23.1% PES, 9.4% PE, 5.8% PA, PS 2.1, 4.2% Alkyd, 3.2% Acrylic, 2.6% PEVC, 1.4% PU, 1.1% PVC, 1% PAS n2 = 24.8% PP, 24.5% PE, 5.5% PES, 5.4% PVC, 5.3% PS, 4.6% Acrylic, 4.5% PDS, 3.9% PU, 3.7% PAS and 3.6% PLA Swater = 26% PP, 30% PES, 7% PE, 10% PA, and 6% alkyd Mwater = 34% PP, 23% PES, 8% PE, 8% PA, and 5% alkyd n1: range = 50 - 150μm mean = 265 μm median = 154μm <300μm = 74% n2: range = 100 - 150μm mean = 248μm median = 155μm <300μm = 81% ✓ ✓ ✓ Spain Tagus River Average values UWW = 42% Fragments, 41% Fibers 12% Granules, foams, beads, films, and glitter TWW = 69% Fragments, 19% Fibers 11% Granules, foams, beads, films, and glitter PSLG = 56% Fragments, 44% Fibers 1.6% Granules, foams, beads, films, and glitter RSLG = 52% Fragments, 47% Fibers >1% Granules, foams, beads, films, and glitter n1 = 81% Fragments, 10% Fibers 9% Granules, foams, beads, films, and glitter n2 = 87% Fragments, 13% Fibers >1% Granules, foams, beads, films, and glitter Most common UWW = PS, PE, PP, and Tyre TWW = Paint, PP, PE, Acrylic, and PS PSLG = PP, PES, PE, PS, and Acrylic RSLG = PP, PES, PE, and Acrylic n1 = PP, PES, PE, Acrylic, and Tyre n2 = PP, PES, PE, PS, EPR, PVC and Acrylic UWW = 55 - 5000μm TWW = 55 - 5000μm PSLG = 55 - 5000μm RSLG = 55 - 5000μm n1 = 55 - 5000μm; >300μm less frequent n2 = 55 - 5000μm; most were <300μm ✓ ✓ ✓ Continuation of Table 9. 121 Table 11 - Granulometric results. Mz - mean grain size, σi - standard deviation, p/150μm - particles per volume, Distance(km) - distance from the closest known pollution source and classification - grain size class. Sample Mz σi p/150μL Distance (km) Classification MP001 2.256667 -2.41364 11 0.82 Sandy gravel MP002 1.766667 -1.43939 17 0.49 Gravelly sand MP003 5.853333 -3.30439 39 0.45 Sandy gravel MP004 6.166667 -2.68583 20 1.2 Gravel MP004B 6.866667 -4.92197 37 1.3 Sandy gravel MP005 3.42 1.66 45 1.74 Slightly gravelly muddy sand MP006 2.62 1.67 35 1.8 Slightly gravelly muddy sand MP007 3.423333 -1.8697 31 0.4 Sandy gravel MP008 9.69 -5.38742 33 1.82 Gravel MP009 4.373333 -2.60348 53 0.61 Sandy gravel MP010 1.6 -1.28492 30 0.26 Gravelly sand MP011 0.92 -1.82136 37 0.3 Slightly gravelly muddy sand MP012 2.06 -1.84818 37 1.47 Gravelly sand MP012B 2.123333 -2.10682 58 1.47 Gravelly sand MP012C 3.033333 -2.50152 35 1.47 Sandy gravel MP013 0.726667 -0.52561 37 0.1 Slightly gravelly muddy sand MP014 1.396667 -0.7528 16 1 Gravelly sand 122 Figure 36 - Some of the visualised particles. Particles a) and b) are fibers, d), c) e), and f) are fragments. a) b) c) d) e) f) 1mm 1mm 1mm 80μm m 1mm m 80μm m 123 Figure 38 - Normal Distribution plots for each sampling site. 124 Map 1 - Graphic representation of the study area, sampling sites and riverine stress factors. 125 a) b) d) c) e) f) g) i) h) k) l) j) Map 2 - Sampling sites zoomed in with the possible affecting factors.