Divya Nimma, Okram Ricky Devi, Bibek Laishram
et al.
Global warming is a phenomenon whereby the planet's exposure to the sun's radiation worsens from the high emission of gasses believed to trap heat within the atmosphere. Carbon dioxide (CO2) is the leading greenhouse gas majorly responsible for global warming and other related issues and is a danger to global society. This one has a particular role in portraying the key importance of the shifting climate that invariably influences water supply and agricultural production. Global warming presents complex challenges to aquatic organisms and stocks and other natural aquatic life resources. This study examines how freshwater and marine species are affected by climate change in aquatic habitats. Aquatic species' metabolism, growth, reproduction, and dispersal are all impacted by rising temperatures and altered water chemistry brought on by increased greenhouse gas emissions, especially CO2. The goal is to pinpoint the ecosystems and vulnerable species that are most impacted by these changes and suggest flexible management techniques. The suggested remedies center on creating sustainable conservation strategies that lessen the effects of climate change on aquatic biodiversity and increase these ecosystems' resilience. The socio-economic interdependencies between water and climate change impact agricultural and water resources, and the pressures exerted on water bodies and water supply landscapes. Another area is related to alterations in the physical and chemical properties of the water, such as the temperature, which is a well-known effect of climate change: 'This causes abnormalities in the metabolism and physiology of aquatic species.' These alterations flow through the chain and regime of growth, reproduction, feeding habits and distribution, migration, and mass of fish and other creatures in the water system. However, the long-term effect of climate variation and climate change on freshwater ecosystems requires much scientific investigation to address challenges in aquatic ecosystem conservation and sustainability. This being the case, adaptive management solutions that address the interrelated impacts of climate change have to be applied and implemented to reduce vulnerability in aquatic ecosystems worldwide.
Amanda Sengeløv, Giacomo Capuzzo, Sarah Dalle
et al.
Understanding the spatial distribution of strontium isotopes in plants or other archives within a region is crucial for various fields, including archaeology, environmental studies, food sciences and forensic science. This study aims to create a detailed dynamic strontium isoscape for Belgium through high-density plant sampling, presented in a web application (IsoBel) that serves the mentioned research fields. A total of 540 plant samples (199 locations), representing various species of grass, shrubs, and trees across Belgium were collected and were analysed for their strontium isotope ratios (87Sr/86Sr) to create a first biologically available strontium map. Sampling sites were selected to cover diverse lithological formations and soil types, ensuring representative coverage of the region’s geological heterogeneity, by using a novel high density grid mapping method. Sixty-four previously published plants from 21 locations are also included in this study, bringing the total amount of plant samples used to 604 from 220 locations. The results reveal significant variations in 87Sr/86Sr across Belgium (ranging from 0.7054 to 0.7259), which reflect the underlying lithology and geological processes (tectonics, weathering,…) which shaped the landscape. Although overlapping 87Sr/86Sr is seen across the majority of lithologies, there is a statistically significant difference between the distribution of 87Sr/86Sr values across all different lithological units in Belgium (Kruskal-Wallis test; p < 0.0001). Distinct regional patterns were observed, with higher 87Sr/86Sr in the older geological south-eastern part of Belgium, compared to the younger north-western parts. The high-density plant sampling approach employed in this study allowed for enhanced spatial resolution and improved accuracy in the predictive surfaces for bioavailable 87Sr/86Sr created by Empirical Bayesian Kriging (EBK). These findings provide valuable insights into the geographic distribution of strontium isotopes within Belgium and offer a foundation for future studies in archaeology, ecology, environmental studies, food sciences and forensics. Furthermore, the extensive coverage of various plant species provided a robust representation of the local ecosystems and their strontium sources. Overall, this study contributes to the growing body of knowledge on regional strontium isoscapes, enhancing our understanding of the complex interplay between litho- and biosphere in shaping the strontium isotope compositions of ecosystems.
O. V. Kompaniiets, I. B. Vavilova, O. M. Kukhar
et al.
The environmental density of galaxies within the cosmic web constrains their 3D locations in filaments, voids, groups, and clusters. It traces the distribution of baryons and the influence of dark-matter halos on galaxy evolution, and helps diagnose external processes such as supernova and AGN feedback, tidal interactions, ram-pressure stripping, and large-scale flows. We focus on isolated barred galaxies, the parent population that includes Milky Way analogs. To measure local environmental density and verify isolation (|Delta v| <= 500 km s^-1), we built a Python pipeline that works in two redshift regimes: low (z0 < 0.02) and high (z0 >= 0.02). Densities were estimated with k-nearest neighbors and Voronoi tessellations and classified as void (Sigma < 0.05), filament (0.05 <= Sigma < 0.5), group (0.5 <= Sigma < 2.0), and cluster (Sigma >= 2.0). Our northern-sky sample contains 311 isolated barred galaxies from 2MIG plus Milky Way analog systems (z < 0.07). We find 157 void, 84 filament, 27 group, and 11 cluster galaxies; 30 have no detected neighbors. Sixty-seven lie in extremely low-density regions (Sigma_3D < 0.01 gal Mpc^-3), and 22 have the nearest companion beyond 5 Mpc, indicating residence in extended voids. The Milky Way (Sigma_5NN ~ 0.13 gal Mpc^-3, R ~ 2.1 Mpc) and its close analog NGC 3521 both lie in filamentary environments at the edge of a nearby void. For z > 0.02 we identify three additional Milky Way analog candidates from the density metrics: CGCG 208-043 (3D Voronoi) and NGC 5231 and CGCG 047-026 (5th-nearest neighbor). These results show that local environmental density is an effective, physically motivated criterion for selecting Milky Way analogs.
Designing for sufficiency is one of many approaches that could foster more moderate and sustainable digital practices. Based on the Sustainable Information and Communication Technologies (ICT) and Human-Computer Interaction (HCI) literature, we identify five environmental settings categories. However, our analysis of three mobile OS and nine representative applications shows an overall lack of environmental concerns in settings design, leading us to identify six pervasive anti-patterns. Environmental settings, where they exist, are set on the most intensive option by default. They are not presented as such, are not easily accessible, and offer little explanation of their impact. Instead, they encourage more intensive use. Based on these findings, we create a design workbook that explores design principles for environmental settings: presenting the environmental potential of settings; shifting to environmentally neutral states; previewing effects to encourage moderate use; rethinking defaults; facilitating settings access and; exploring more frugal settings. Building upon this workbook, we discuss how settings can tie individual behaviors to systemic factors.
Riley D Thoen, Andrea Southgate, Gretel Kiefer
et al.
Abstract Anthropogenically fragmented populations may have reduced fitness due to loss of genetic diversity and inbreeding. The extent of such fitness losses due to fragmentation and potential gains from conservation actions are infrequently assessed together empirically. Controlled crosses within and among populations can identify whether populations are at risk of inbreeding depression and whether inter-population crossing alleviates fitness loss. Because fitness depends on the environment and life stage, studies quantifying cumulative fitness over a large portion of the lifecycle in conditions that mimic natural environments are most informative. To assess the fitness consequences of habitat fragmentation, we leveraged controlled within-family, within-population, and between-population crosses to quantify inbreeding depression and heterosis in seven populations of Echinacea angustifolia within a 6,400-ha area. We then assessed cumulative offspring fitness after 14 yr of growth in a natural experimental plot (N = 1,136). The mean fitness of progeny from within-population crosses varied considerably, indicating genetic differentiation among source populations, even though these sites are all less than 9 km apart. The fitness consequences of within-family and between-population crosses varied in magnitude and direction. Only one of the seven populations showed inbreeding depression of high effect, while four populations showed substantial heterosis. Outbreeding depression was rare and slight. Our findings indicate that local crossings between isolated populations yield unpredictable fitness consequences ranging from slight decreases to substantial increases. Interestingly, inbreeding depression and heterosis did not relate closely to population size, suggesting that all fragmented populations could contribute to conservation goals as either pollen recipients or donors.
Alex T. Ford, Amruthavarshini Shankar, Sarah Reynolds
et al.
Abstract The planet faces a triple crisis from climate change, biodiversity loss, and pollution. Like any country, the UK needs to attract the best available talent to become thought leaders to overcome these global challenges. Several Science, Technology, Engineering and Maths subjects in the UK face challenges with attracting ethnic minority students. As part of a wider project on diversity in UK environmental/marine science, we analysed university applications amongst 180 environmental and 88 marine science degrees in the UK between 2019–2021. We found them to be the least diverse degree subjects for ethnic minority students and Asian students were less likely to be accepted than white students on environmental science degrees. A survey of UK marine science course leaders highlights the belief that these issues impact the pipeline of diversity from higher education institutions to marine/environmental science careers. In this paper, we discuss the impacts of these findings and develop a roadmap to change.
Tesfaye Bayu Zeleke, Tri Retnaningsih Soeprobowati, Solomon Adissu
et al.
The trends of temperature and rainfall are critical indicators of climate change within a certain area. However, the existence of climate change is not locally understood in most parts of the world. This research aims to analyze the trend of temperature and rainfall in the Lake Tana Sub-basin as a means to understand the current and future status of climate change. The trends of temperature and rainfall were analyzed using the modified Mann-Kendall trend test, while the autoregressive integrated moving average model (ARIMA) was used to predict future temperature and rainfall. The findings reveal that monthly temperatures show a significant increasing trend for March, April, May, June, and December with Z-values of 3.96, 3.32, 2.64, 3.21, and 4.6, respectively. Seasonal and annual temperatures also show a significant increasing trend with Z-values of 4, 5.35, 5.08, and 4.41 for spring, autumn, winter, and annual, respectively. The Mann-Kendall trend analysis results show that monthly, seasonal and annual rainfall exhibit significant increasing trends for some months and seasons. The results of the ARIMA model suggest that the predicted values of temperature and rainfall will continue to increase over the next 10 years in the study area. Based on these findings, it can be concluded that there is a significant and increasing trend in temperature and rainfall, which will likely continue over the next decade, indicating the presence of climate change in the study area. The research findings suggest that temperature and rainfall have been increasing over time, leading to climate change in the study area, so sustainable lake management and urban development should be practiced to mitigate and adopt climate change.
Srinadh Kodali, Chris Flores-Lopez, Isabelle Lobdell
et al.
Global herbicide-resistant weed populations continue rising due to selection pressures exerted by herbicides. Despite this, herbicides continue to be farmers’ preferred weed-control method due to cost and efficiency relative to physical or biological methods. However, weeds developing resistance to herbicides not only challenges crop production but also threatens ecosystem services by disrupting biodiversity, reducing soil health, and impacting water quality. Our objective was to develop a simulation model that captures the feedback between weed population dynamics, agricultural management, profitability, and farmer decision-making processes that interact in unique ways to reinforce herbicide resistance in weeds. After calibration to observed data and evaluation by subject matter experts, we tested alternative agronomic, mechanical, or intensive management strategies to evaluate their impact on weed population dynamics. Results indicated that standalone practices enhanced farm profitability in the short term but lead to substantial adverse ecological outcomes in the long term, indicated by elevated herbicide resistance (e.g., harm to non-target species, disrupting natural ecosystem functions). The most management-intensive test yielded the greatest weed control and farm profit, albeit with elevated residual resistant seed bank levels. We discuss these findings in both developed and developing-nation contexts. Future work requires greater connectivity of farm management and genetic-resistance models that currently remain disconnected mechanistically.
Nynke van Uffelen, Lode Lauwaert, Mark Coeckelbergh
et al.
In recent years, much research has been dedicated to uncovering the environmental impact of Artificial Intelligence (AI), showing that training and deploying AI systems require large amounts of energy and resources, and the outcomes of AI may lead to decisions and actions that may negatively impact the environment. This new knowledge raises new ethical questions, such as: When is it (un)justifiable to develop an AI system, and how to make design choices, considering its environmental impact? However, so far, the environmental impact of AI has largely escaped ethical scrutiny, as AI ethics tends to focus strongly on themes such as transparency, privacy, safety, responsibility, and bias. Considering the environmental impact of AI from an ethical perspective expands the scope of AI ethics beyond an anthropocentric focus towards including more-than-human actors such as animals and ecosystems. This paper explores the ethical implications of the environmental impact of AI for designing AI systems by drawing on environmental justice literature, in which three categories of justice are distinguished, referring to three elements that can be unjust: the distribution of benefits and burdens (distributive justice), decision-making procedures (procedural justice), and institutionalized social norms (justice as recognition). Based on these tenets of justice, we outline criteria for developing environmentally just AI systems, given their ecological impact.
Abstract Background Streptococcus iniae is an important fish pathogen that cause significant economic losses to the global aquaculture industry every year. Although there have some reports on the genotype of S.iniae and its relationship with virulence, no genome-scale comparative analysis has been performed so far. In our previous work, we characterized 17 isolates of S.iniae from Trachinotus ovatus and divided them into two genotypes using RAPD and rep-PCR methods. Among them, BH15-2 was classified as designated genotype A (in RAPD) and genotype 1 (in rep-PCR), while BH16-24 was classified as genotype B and genotype 2. Herein, we compared the differences in growth, drug resistance, virulence, and genome between BH15-2 and BH16-24. Results The results showed that the growth ability of BH16-24 was significantly faster than that of BH15-2 at the exponential stage. Antimicrobial tests revealed that BH15-2 was susceptible to most of the tested antibiotics except neomycin and gentamycin. In contrast, BH16-24 was resistant to 7 antibiotics including penicillin, sulfasomizole, compound sulfamethoxazole tablets, polymyxin B, spectinomycin, rifampin and ceftazidime. Intraperitoneal challenge of T.ovatus, showed that the LD50 value of BH15-2 was 4.0 × 102 CFU/g, while that of BH16-24 was 1.2 × 105 CFU/g. The genome of S.iniae BH15-2 was 2,175,659 bp with a GC content of 36.80%. Meanwhile, the genome of BH16-24 was 2,153,918 bp with a GC content of 36.83%. Comparative genome analysis indicated that compared with BH15-2, BH16-24 genome had a large-scale genomic inversion fragment, at the location from 502,513 bp to 1,788,813 bp, resulting in many of virulence and resistance genes differentially expression. In addition, there was a 46 kb length, intact phage sequence in BH15-2 genome, which was absent in BH16-24. Conclusion Comparative genomic studies of BH15-2 and BH16-24 showed that the main difference is a 1.28 Mbp inversion fragment. The inversion fragment may lead to abnormal expression of drug resistant and virulence genes, which is believed to be the main reason for the multiple resistance and weakened virulence of BH16-24. Our study revealed the potential mechanisms in underlying the differences of multidrug resistance and virulence among different genotypes of S.iniae.
Nils R. B. Olsen, Subhojit Kadia, Elena Pummer
et al.
A new OpenFOAM solver has been developed for computing the spatial variation of particle concentrations in flowing water. The new solver was programmed in C ++ using OpenFOAM libraries, and the source code has been made openly available. The current article describes the coding of how the water flow and particle movements are computed. The solver is based on a Eulearian approach, where the particles are computed as concentrations in cells of a grid that resolves the computational domain. The Reynolds-averaged Navier–Stokes equations are solved by simpleFoam, using the k-ε turbulence model. The new solver uses a drift-flux approach to take the fall or rise velocity of the particles into account in a convection-diffusion equation. The model is therefore called sediDriftFoam. The results from the solver were tested on two cases with different types of particles. The first case was a sand trap with sand particles. The geometry was three-dimensional with a recirculation zone. The computed sediment concentrations in three vertical profiles compared well with earlier numerical studies and laboratory measurements. The second case was a straight channel flume with plastic particles that had a positive rise velocity. In this case, the results also compared well with the laboratory measurements.
HIGHLIGHTS
Open source 3D sediment model.;
Based on OpenFOAM.;
Simple and easy to learn.;
Tested on computing trap efficiency of a sand trap.;
Tested on computing suspended plastic particles in a channel.;
Information technology, Environmental technology. Sanitary engineering
<p>African and South American (ASA) wildfires account for more than 70 % of
global burned areas and have strong connection to local climate for
sub-seasonal to seasonal wildfire dynamics. However, representation of the
wildfire–climate relationship remains challenging due to spatiotemporally
heterogenous responses of wildfires to climate variability and human
influences. Here, we developed an interpretable machine learning (ML) fire
model (AttentionFire_v1.0) to resolve the complex controls of
climate and human activities on burned areas and to better predict burned
areas over ASA regions. Our ML fire model substantially improved
predictability of burned areas for both spatial and temporal dynamics
compared with five commonly used machine learning models. More importantly,
the model revealed strong time-lagged control from climate wetness on the
burned areas. The model also predicted that, under a high-emission future climate scenario, the recently observed declines in burned area will reverse
in South America in the near future due to climate changes. Our study
provides a reliable and interpretable fire model and highlights the importance
of lagged wildfire–climate relationships in historical and future
predictions.</p>
Abstract Background Early life in-utero can have long-term influence on the mental health status of individuals in adulthood, such as depression. Age, gender, socio-economic status, education, and geography are demographic factors shown to be particularly vulnerable towards the development of depressive symptoms. In addition, climate risks on depression include sunlight, rain, and temperature. However, whether climate factors in early life have a long-term influence on depression related to demographic vulnerability remains unknown. Here, the present study explored the association between birth seasonality and adulthood depressive symptoms. Methods We employed data from the project of Chinese Labour-forces Dynamic Survey (CLDS) 2016, containing the epidemiological data of depressive symptoms with a probability proportional to size cluster and random cluster sampling method in 29 provinces of China. A final sample size of 16,185 participants was included. Birth seasonality included spring (March, April, and May), summer (June, July, and August), autumn (September, October, and November), and winter (December, January, and February). Results We found that born in Autumn peaked lowest rate of having depressive symptoms (16.8%) and born in Summer (vs. Autumn) had a significant higher ratio (OR = 1.14, 95%CI = 1.02, 1.29) when controlling for demographic variables. In addition, demographic odds ratio of having depressive symptoms differed between people born in different seasons, particular for age and geography. Conclusion Our findings suggest that birth seasonality influences the sensitive link of depressive symptoms with age and geography. It implicates early life climate environment may play a role in the development of adulthood depressive symptoms.
Accounting for 41.7% of China’s total land area, grasslands are linked to the livelihoods of over 20 million people. Although grassland fires cause severe damage in China every year, their spatiotemporal patterns and climate drivers are not well understood. In this study, we used grassland fire record forms provided by the National Forestry and Grassland Administration and grassland fire location data from the Wildfire Atlas of China to examine the spatiotemporal patterns and and seasonality of fires in China for the period from 2008 to 2020. We found that most grassland fires occurred in Inner Mongolia in northern China, specifically in the Hulun Buir and Xilingol grasslands. We found distinct differences in fire seasonality in northern China, which has a major fire season in April, versus southwestern China, where the major fire season occurs in February, March and April. April grassland fires in northern China are the result of strong winds, typically from the west, and spring drought. A secondary fire season in northern China occurs in October and is also driven by strong winds. The fire season in southwestern China seems to be less shaped by climatic factors such as wind speed, precipitation, and drought. This study provides support for decision-making by fire prevention and fire management authorities in China.
Sweat contains a wealth of health-related biomarkers, which has been a promising resource for personalized real-time monitoring at molecular level. Emergence of non-enzymatic electrochemical sensor that simulates the enzyme catalysis utilizing the functional material further promotes the development of wearable sweat sensor, successfully addressing the limitations of enzyme sensing in sensitivity and stability. Thus, there is an urgent need for centering on the regulation of the nanostructure, combination and preparation method of functional materials to enhance the catalytic activity for enzyme-free detection of sweat biomarkers. This review aims to present the superiors of enzyme-free sensing on wearable sweat sensor, and provides guidance for material innovation, sensor design and system integration. Firstly, we primarily focus on the recent advances of novel functional nanomaterials in wearable non-enzymatic electrochemical sensor, and briefly describe the sensing principles for detecting biomarkers in sweat. Subsequently, the correlation between the electrochemical strategy and functional material is elaborately interpreted by coupling with the diverse molecular structures of the biomarkers and the pH changes of test environments. Finally, challenges and opportunities for wearable non-enzymatic electrochemical sensor in sweat sensing are delineated in the development of future personalized healthcare.
Matthew Scott Luskin, Lindsey Arnold, Adia Sovie
et al.
Abstract Fragments and edges account for most remaining forest habitats globally. Apex predators and megaherbivores often decline in these degraded habitats while smaller generalist omnivores can persist or thrive in forest edges, especially if they can utilize nonnative resources (“cross‐boundary food subsidies”). Outcomes for small‐medium carnivores (mesopredators) remain unclear or idiosyncratic. We tested responses of a widespread and common forest mesopredator to edges and the composition of the adjacent nonforested areas using 91 camera trapping surveys in Southeast Asia. Leopard cats (Prionailurus bengalensis and Prionailurus javanensis) showed a hump‐shaped relationship with forest cover and a positive association with oil palm plantations, but they did not increase near other types of nonnative land cover. Leopard cats' success in edges appears due to their hunting abundant rodent prey inside oil palm plantations, providing natural pest management for farmers. Abundant leopard cats also hunt and suppress native small vertebrates, which may trigger negative ecological cascades and suppress biodiversity in forest edges.
Environmental sciences, Human ecology. Anthropogeography
Leigh N. Fletcher, Thibault Cavalié, Davide Grassi
et al.
ESA's Jupiter Icy Moons Explorer (JUICE) will provide a detailed investigation of the Jovian system in the 2030s, combining a suite of state-of-the-art instruments with an orbital tour tailored to maximise observing opportunities. We review the Jupiter science enabled by the JUICE mission, building on the legacy of discoveries from the Galileo, Cassini, and Juno missions, alongside ground- and space-based observatories. We focus on remote sensing of the climate, meteorology, and chemistry of the atmosphere and auroras from the cloud-forming weather layer, through the upper troposphere, into the stratosphere and ionosphere. The Jupiter orbital tour provides a wealth of opportunities for atmospheric and auroral science: global perspectives with its near-equatorial and inclined phases, sampling all phase angles from dayside to nightside, and investigating phenomena evolving on timescales from minutes to months. The remote sensing payload spans far-UV spectroscopy (50-210 nm), visible imaging (340-1080 nm), visible/near-infrared spectroscopy (0.49-5.56 $μ$m), and sub-millimetre sounding (near 530-625\,GHz and 1067-1275\,GHz). This is coupled to radio, stellar, and solar occultation opportunities to explore the atmosphere at high vertical resolution; and radio and plasma wave measurements of electric discharges in the Jovian atmosphere and auroras. Cross-disciplinary scientific investigations enable JUICE to explore coupling processes in giant planet atmospheres, to show how the atmosphere is connected to (i) the deep circulation and composition of the hydrogen-dominated interior; and (ii) to the currents and charged particle environments of the external magnetosphere. JUICE will provide a comprehensive characterisation of the atmosphere and auroras of this archetypal giant planet.
Thisari K. Mahanama, Abootaleb Shirvani, Svetlozar Rachev
et al.
This paper introduces the concept of a global financial market for environmental indices, addressing sustainability concerns and aiming to attract institutional investors. Risk mitigation measures are implemented to manage inherent risks associated with investments in this new financial market. We monetize the environmental indices using quantitative measures and construct country-specific environmental indices, enabling them to be viewed as dollar-denominated assets. Our primary goal is to encourage the active engagement of institutional investors in portfolio analysis and trading within this emerging financial market. To evaluate and manage investment risks, our approach incorporates financial econometric theory and dynamic asset pricing tools. We provide an econometric analysis that reveals the relationships between environmental and economic indicators in this market. Additionally, we derive financial put options as insurance instruments that can be employed to manage investment risks. Our factor analysis identifies key drivers in the global financial market for environmental indices. To further evaluate the market's performance, we employ pricing options, efficient frontier analysis, and regression analysis. These tools help us assess the efficiency and effectiveness of the market. Overall, our research contributes to the understanding and development of the global financial market for environmental indices.
Shabana Siddique, Imen Farhat, Cariton Kubwabo
et al.
Exposure to organophosphate esters (OPEs) is extensive, yet few studies have investigated their association with hormone levels or semen quality. Here, we studied the association between urinary concentrations of OPEs and their metabolites with hormone levels and semen parameters in men (n = 117) predominantly in the 20–29 years age range who were recruited from the greater Montreal area between 2009 and 2012. Urine, serum, and semen samples were analyzed for OPEs, hormones, and semen quality, respectively. Bis(2-ethylhexyl) phosphate (BEHP), bis(2,4-di-tert-butylphenyl) hydrogen phosphate (B2,4DtBPP), tris(2-chloroisopropyl) phosphate (TCIPP), diphenyl phosphate (DPHP), bis (2-butoxyethyl) phosphate (BBOEP) and di-cresyl phosphate (DCPs) were detected in urine at a frequency ≥ 95%. The highest geometric mean concentration was observed for DPHP (18.54 ng/mL) and the second highest was B2,4DtBPP (6.23 ng/mL). Associations between a doubling in analyte concentrations in urine and hormone levels and semen quality parameters were estimated using multivariable linear regression. B2,4DtBPP levels were positively associated with total T3 (β = 0.09; 95% CI: 0.01, 0.17). DPHP was inversely associated with estradiol (β = -2.56; 95% CI: −5.00, −0.17), and TCIPP was inversely associated with testosterone (β = -0.78; 95% CI: −1.40, −0.17). Concentrations of BCIPP were inversely associated with sperm concentrations (β = -7.76; 95% CI: −14.40, −0.61), progressive motility (β = − 4.98; 95% CI: −8.71, −1.09), and the sperm motility index (β = -9.72; 95% CI: −17.71, −0.96). In contrast, urinary DPHP concentrations were positively associated with the sperm motility (β = 4.37; 95% CI: 0.76, 8.12) and fertility indices (β = 6.64; 95% CI: 1.96, 11.53). Thus, OPE detection rates were high and exposure to several OPEs was associated with altered hormone levels and semen parameters. The possibility that OPEs affect male reproduction warrants further investigation.